{
"cells": [
{
"cell_type": "code",
"execution_count": 104,
"id": "1ef760fd",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The autoreload extension is already loaded. To reload it, use:\n",
" %reload_ext autoreload\n"
]
}
],
"source": [
"%load_ext autoreload\n",
"%autoreload 2"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "17919476",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import dual_loops as dual_loops"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "4ed3fcaa",
"metadata": {},
"outputs": [],
"source": [
"## Loading and preparing data\n",
"dataset_name = 'nasa'\n",
"with_blocking = True\n",
"\n",
"if with_blocking:\n",
" all_dataset_df = pd.read_csv(dataset_name + '_blocked.csv')\n",
"else:\n",
" all_dataset_df = pd.read_csv(dataset_name + '.csv')\n",
"\n",
"import pickle\n",
"source_ontology = pickle.load( open(dataset_name + \"_source_ontology.pk\", \"rb\" ) )\n",
"target_ontology = pickle.load( open(dataset_name + \"_target_ontology.pk\", \"rb\" ) )\n",
"\n",
"dual_loops.source_ontology = source_ontology\n",
"dual_loops.target_ontology = target_ontology\n"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "3784f2ae",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['LF_aml', 'LF_logmap', 'LF_yam', 'LF_class_name_equal',\n",
" 'LF_class_name_stemmed_equal', 'LF_acronyms', 'LF_class_name_synonyms',\n",
" 'LF_label_equal', 'LF_root_nouns_equal', 'LF_class_name_spacy_distance',\n",
" 'LF_class_name_distance', 'LF_name_segment_overlap',\n",
" 'LF_label_words_overlap', 'LF_subclasses_overlap',\n",
" 'LF_superclasses_overlap', 'LF_properties_overlap', 'label', 'x', 'y',\n",
" 'shared_word', 'levenshtein_distance', 'hamming_distance', 'text_pair',\n",
" 'class_name_embedding_distance', 'num_common_words',\n",
" 'class_long_name_distance_a', 'class_long_name_distance_b',\n",
" 'label_long_distance_a', 'label_long_distance_b', 'comment_distance_a',\n",
" 'comment_distance_b', 'num_common_words_blocked',\n",
" 'class_long_name_distance_a_blocked', 'label_long_distance_a_blocked',\n",
" 'comment_distance_a_blocked', 'class_long_name_distance_b_blocked',\n",
" 'label_long_distance_b_blocked', 'comment_distance_b_blocked',\n",
" 'selected_after_blocking'],\n",
" dtype='object')"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"my_dataset_df = all_dataset_df[all_dataset_df['selected_after_blocking'] == 1].reset_index(drop=True)\n",
"my_dataset_df.columns"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "dd7c45a5",
"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>LF_aml</th>\n",
" <th>LF_logmap</th>\n",
" <th>LF_yam</th>\n",
" <th>LF_class_name_equal</th>\n",
" <th>LF_class_name_stemmed_equal</th>\n",
" <th>LF_acronyms</th>\n",
" <th>LF_class_name_synonyms</th>\n",
" <th>LF_label_equal</th>\n",
" <th>LF_root_nouns_equal</th>\n",
" <th>LF_class_name_spacy_distance</th>\n",
" <th>...</th>\n",
" <th>comment_distance_a</th>\n",
" <th>comment_distance_b</th>\n",
" <th>num_common_words_blocked</th>\n",
" <th>class_long_name_distance_a_blocked</th>\n",
" <th>label_long_distance_a_blocked</th>\n",
" <th>comment_distance_a_blocked</th>\n",
" <th>class_long_name_distance_b_blocked</th>\n",
" <th>label_long_distance_b_blocked</th>\n",
" <th>comment_distance_b_blocked</th>\n",
" <th>selected_after_blocking</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>147</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>...</td>\n",
" <td>0.791844</td>\n",
" <td>0.627131</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>328</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>...</td>\n",
" <td>0.594224</td>\n",
" <td>0.417973</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>334</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>...</td>\n",
" <td>0.731980</td>\n",
" <td>0.597956</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>474</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>...</td>\n",
" <td>0.781320</td>\n",
" <td>0.619332</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>564</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>...</td>\n",
" <td>0.788297</td>\n",
" <td>0.560064</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>666</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>...</td>\n",
" <td>0.800338</td>\n",
" <td>0.654230</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>841</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>...</td>\n",
" <td>0.908957</td>\n",
" <td>0.776825</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>934</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>...</td>\n",
" <td>0.834274</td>\n",
" <td>0.651881</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1375</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>...</td>\n",
" <td>0.864641</td>\n",
" <td>0.611613</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2059</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>...</td>\n",
" <td>0.722928</td>\n",
" <td>0.366583</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2475</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>-1</td>\n",
" <td>1</td>\n",
" <td>-1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>...</td>\n",
" <td>0.506345</td>\n",
" <td>0.407206</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2584</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>...</td>\n",
" <td>0.479343</td>\n",
" <td>0.672563</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2875</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>...</td>\n",
" <td>0.874169</td>\n",
" <td>0.742459</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2987</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>...</td>\n",
" <td>0.733293</td>\n",
" <td>0.549064</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3045</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>...</td>\n",
" <td>0.690793</td>\n",
" <td>0.671258</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3242</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>...</td>\n",
" <td>0.845631</td>\n",
" <td>0.653763</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3406</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>-1</td>\n",
" <td>1</td>\n",
" <td>-1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>...</td>\n",
" <td>0.744407</td>\n",
" <td>0.535358</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3542</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>...</td>\n",
" <td>0.907686</td>\n",
" <td>0.700407</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3805</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>...</td>\n",
" <td>0.763579</td>\n",
" <td>0.614950</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3887</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>...</td>\n",
" <td>0.796497</td>\n",
" <td>0.568144</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4155</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>...</td>\n",
" <td>0.735750</td>\n",
" <td>0.496517</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4757</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>...</td>\n",
" <td>0.655484</td>\n",
" <td>0.490966</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4813</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>-1</td>\n",
" <td>1</td>\n",
" <td>-1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>...</td>\n",
" <td>0.849309</td>\n",
" <td>0.717462</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5285</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>0</td>\n",
" <td>...</td>\n",
" <td>0.794718</td>\n",
" <td>0.516438</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5412</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>-1</td>\n",
" <td>1</td>\n",
" <td>-1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>...</td>\n",
" <td>0.798994</td>\n",
" <td>0.650058</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5762</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>...</td>\n",
" <td>0.879676</td>\n",
" <td>0.615668</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5813</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>...</td>\n",
" <td>0.892128</td>\n",
" <td>0.773428</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5832</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>-1</td>\n",
" <td>1</td>\n",
" <td>-1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>...</td>\n",
" <td>0.577903</td>\n",
" <td>0.391842</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6199</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>...</td>\n",
" <td>0.507038</td>\n",
" <td>0.251494</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6523</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>...</td>\n",
" <td>0.644747</td>\n",
" <td>0.338784</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7264</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>...</td>\n",
" <td>0.865944</td>\n",
" <td>0.859074</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7435</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>-1</td>\n",
" <td>...</td>\n",
" <td>0.410549</td>\n",
" <td>0.148055</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>32 rows × 39 columns</p>\n",
"</div>"
],
"text/plain": [
" LF_aml LF_logmap LF_yam LF_class_name_equal \\\n",
"147 1 1 1 1 \n",
"328 0 0 0 -1 \n",
"334 0 0 0 -1 \n",
"474 0 0 0 -1 \n",
"564 0 0 0 -1 \n",
"666 0 0 0 -1 \n",
"841 0 0 0 -1 \n",
"934 0 0 0 -1 \n",
"1375 0 0 0 -1 \n",
"2059 0 0 0 -1 \n",
"2475 1 1 1 1 \n",
"2584 1 1 1 1 \n",
"2875 0 0 0 -1 \n",
"2987 0 0 0 -1 \n",
"3045 0 0 0 -1 \n",
"3242 0 0 0 -1 \n",
"3406 1 1 1 1 \n",
"3542 0 0 0 -1 \n",
"3805 1 1 1 1 \n",
"3887 0 0 0 -1 \n",
"4155 0 0 0 -1 \n",
"4757 0 0 0 -1 \n",
"4813 1 1 1 1 \n",
"5285 1 1 1 -1 \n",
"5412 1 1 1 1 \n",
"5762 0 0 0 -1 \n",
"5813 1 1 1 1 \n",
"5832 1 1 1 1 \n",
"6199 0 0 0 -1 \n",
"6523 0 0 0 -1 \n",
"7264 0 0 0 -1 \n",
"7435 0 0 0 -1 \n",
"\n",
" LF_class_name_stemmed_equal LF_acronyms LF_class_name_synonyms \\\n",
"147 1 -1 -1 \n",
"328 -1 -1 -1 \n",
"334 -1 -1 1 \n",
"474 -1 -1 -1 \n",
"564 -1 -1 -1 \n",
"666 -1 -1 -1 \n",
"841 -1 -1 -1 \n",
"934 -1 -1 -1 \n",
"1375 -1 -1 -1 \n",
"2059 -1 -1 -1 \n",
"2475 1 -1 1 \n",
"2584 1 -1 -1 \n",
"2875 -1 -1 -1 \n",
"2987 -1 -1 -1 \n",
"3045 -1 -1 -1 \n",
"3242 -1 -1 -1 \n",
"3406 1 -1 1 \n",
"3542 -1 -1 -1 \n",
"3805 1 -1 -1 \n",
"3887 -1 -1 -1 \n",
"4155 -1 -1 -1 \n",
"4757 -1 -1 -1 \n",
"4813 1 -1 1 \n",
"5285 -1 1 -1 \n",
"5412 1 -1 1 \n",
"5762 -1 -1 -1 \n",
"5813 1 -1 -1 \n",
"5832 1 -1 1 \n",
"6199 -1 -1 -1 \n",
"6523 -1 -1 -1 \n",
"7264 -1 -1 -1 \n",
"7435 -1 -1 -1 \n",
"\n",
" LF_label_equal LF_root_nouns_equal LF_class_name_spacy_distance ... \\\n",
"147 -1 1 1 ... \n",
"328 -1 -1 -1 ... \n",
"334 -1 -1 -1 ... \n",
"474 -1 -1 -1 ... \n",
"564 -1 -1 -1 ... \n",
"666 -1 -1 -1 ... \n",
"841 -1 -1 -1 ... \n",
"934 -1 -1 -1 ... \n",
"1375 -1 -1 -1 ... \n",
"2059 -1 -1 -1 ... \n",
"2475 -1 1 1 ... \n",
"2584 -1 1 1 ... \n",
"2875 -1 -1 -1 ... \n",
"2987 -1 -1 -1 ... \n",
"3045 -1 -1 -1 ... \n",
"3242 -1 -1 -1 ... \n",
"3406 -1 1 1 ... \n",
"3542 -1 -1 -1 ... \n",
"3805 -1 1 1 ... \n",
"3887 -1 -1 -1 ... \n",
"4155 -1 -1 -1 ... \n",
"4757 -1 -1 -1 ... \n",
"4813 -1 1 1 ... \n",
"5285 -1 -1 0 ... \n",
"5412 -1 1 1 ... \n",
"5762 -1 -1 -1 ... \n",
"5813 -1 1 1 ... \n",
"5832 -1 1 1 ... \n",
"6199 -1 -1 -1 ... \n",
"6523 -1 -1 -1 ... \n",
"7264 -1 -1 -1 ... \n",
"7435 -1 -1 -1 ... \n",
"\n",
" comment_distance_a comment_distance_b num_common_words_blocked \\\n",
"147 0.791844 0.627131 0 \n",
"328 0.594224 0.417973 0 \n",
"334 0.731980 0.597956 1 \n",
"474 0.781320 0.619332 0 \n",
"564 0.788297 0.560064 1 \n",
"666 0.800338 0.654230 0 \n",
"841 0.908957 0.776825 0 \n",
"934 0.834274 0.651881 0 \n",
"1375 0.864641 0.611613 1 \n",
"2059 0.722928 0.366583 0 \n",
"2475 0.506345 0.407206 0 \n",
"2584 0.479343 0.672563 0 \n",
"2875 0.874169 0.742459 0 \n",
"2987 0.733293 0.549064 0 \n",
"3045 0.690793 0.671258 0 \n",
"3242 0.845631 0.653763 0 \n",
"3406 0.744407 0.535358 0 \n",
"3542 0.907686 0.700407 1 \n",
"3805 0.763579 0.614950 0 \n",
"3887 0.796497 0.568144 1 \n",
"4155 0.735750 0.496517 0 \n",
"4757 0.655484 0.490966 0 \n",
"4813 0.849309 0.717462 0 \n",
"5285 0.794718 0.516438 1 \n",
"5412 0.798994 0.650058 0 \n",
"5762 0.879676 0.615668 1 \n",
"5813 0.892128 0.773428 0 \n",
"5832 0.577903 0.391842 0 \n",
"6199 0.507038 0.251494 0 \n",
"6523 0.644747 0.338784 0 \n",
"7264 0.865944 0.859074 0 \n",
"7435 0.410549 0.148055 1 \n",
"\n",
" class_long_name_distance_a_blocked label_long_distance_a_blocked \\\n",
"147 0 1 \n",
"328 0 1 \n",
"334 1 1 \n",
"474 0 1 \n",
"564 1 1 \n",
"666 1 1 \n",
"841 0 1 \n",
"934 1 1 \n",
"1375 1 1 \n",
"2059 0 1 \n",
"2475 0 1 \n",
"2584 0 1 \n",
"2875 0 1 \n",
"2987 1 1 \n",
"3045 1 1 \n",
"3242 0 1 \n",
"3406 0 1 \n",
"3542 0 1 \n",
"3805 0 1 \n",
"3887 1 1 \n",
"4155 0 1 \n",
"4757 0 1 \n",
"4813 0 1 \n",
"5285 1 1 \n",
"5412 0 1 \n",
"5762 0 1 \n",
"5813 0 1 \n",
"5832 0 1 \n",
"6199 1 1 \n",
"6523 1 1 \n",
"7264 0 1 \n",
"7435 0 1 \n",
"\n",
" comment_distance_a_blocked class_long_name_distance_b_blocked \\\n",
"147 0 0 \n",
"328 1 0 \n",
"334 1 0 \n",
"474 0 0 \n",
"564 0 1 \n",
"666 0 0 \n",
"841 0 0 \n",
"934 0 1 \n",
"1375 0 1 \n",
"2059 0 0 \n",
"2475 1 0 \n",
"2584 1 0 \n",
"2875 0 0 \n",
"2987 1 1 \n",
"3045 1 0 \n",
"3242 0 0 \n",
"3406 1 0 \n",
"3542 0 0 \n",
"3805 0 0 \n",
"3887 1 1 \n",
"4155 0 0 \n",
"4757 1 0 \n",
"4813 0 0 \n",
"5285 0 1 \n",
"5412 1 0 \n",
"5762 0 1 \n",
"5813 0 0 \n",
"5832 1 0 \n",
"6199 1 0 \n",
"6523 1 0 \n",
"7264 0 0 \n",
"7435 1 0 \n",
"\n",
" label_long_distance_b_blocked comment_distance_b_blocked \\\n",
"147 1 0 \n",
"328 1 0 \n",
"334 1 1 \n",
"474 1 0 \n",
"564 1 1 \n",
"666 1 0 \n",
"841 1 0 \n",
"934 1 0 \n",
"1375 1 0 \n",
"2059 1 0 \n",
"2475 1 1 \n",
"2584 1 0 \n",
"2875 1 0 \n",
"2987 1 0 \n",
"3045 1 0 \n",
"3242 1 0 \n",
"3406 1 1 \n",
"3542 1 0 \n",
"3805 1 0 \n",
"3887 1 0 \n",
"4155 1 1 \n",
"4757 1 1 \n",
"4813 1 0 \n",
"5285 1 0 \n",
"5412 1 0 \n",
"5762 1 1 \n",
"5813 1 0 \n",
"5832 1 1 \n",
"6199 1 1 \n",
"6523 1 1 \n",
"7264 1 0 \n",
"7435 1 1 \n",
"\n",
" selected_after_blocking \n",
"147 1 \n",
"328 1 \n",
"334 1 \n",
"474 1 \n",
"564 1 \n",
"666 1 \n",
"841 1 \n",
"934 1 \n",
"1375 1 \n",
"2059 1 \n",
"2475 1 \n",
"2584 1 \n",
"2875 1 \n",
"2987 1 \n",
"3045 1 \n",
"3242 1 \n",
"3406 1 \n",
"3542 1 \n",
"3805 1 \n",
"3887 1 \n",
"4155 1 \n",
"4757 1 \n",
"4813 1 \n",
"5285 1 \n",
"5412 1 \n",
"5762 1 \n",
"5813 1 \n",
"5832 1 \n",
"6199 1 \n",
"6523 1 \n",
"7264 1 \n",
"7435 1 \n",
"\n",
"[32 rows x 39 columns]"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"my_dataset_df.query('label==1')"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "e86bea9d",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['LF_aml', 'LF_logmap', 'LF_yam', 'LF_class_name_equal',\n",
" 'LF_class_name_stemmed_equal', 'LF_acronyms', 'LF_class_name_synonyms',\n",
" 'LF_label_equal', 'LF_root_nouns_equal', 'LF_class_name_spacy_distance',\n",
" 'LF_class_name_distance', 'LF_name_segment_overlap',\n",
" 'LF_label_words_overlap', 'LF_subclasses_overlap',\n",
" 'LF_superclasses_overlap', 'LF_properties_overlap', 'label', 'x', 'y',\n",
" 'shared_word', 'levenshtein_distance', 'hamming_distance', 'text_pair',\n",
" 'class_name_embedding_distance', 'num_common_words',\n",
" 'class_long_name_distance_a', 'class_long_name_distance_b',\n",
" 'label_long_distance_a', 'label_long_distance_b', 'comment_distance_a',\n",
" 'comment_distance_b', 'num_common_words_blocked',\n",
" 'class_long_name_distance_a_blocked', 'label_long_distance_a_blocked',\n",
" 'comment_distance_a_blocked', 'class_long_name_distance_b_blocked',\n",
" 'label_long_distance_b_blocked', 'comment_distance_b_blocked',\n",
" 'selected_after_blocking'],\n",
" dtype='object')"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"all_dataset_df.columns"
]
},
{
"cell_type": "markdown",
"id": "f30ac78c",
"metadata": {},
"source": [
"# Results to be used in the paper"
]
},
{
"cell_type": "markdown",
"id": "840a6295",
"metadata": {},
"source": [
"## Experiment to show the effectiveness of data query strategy"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "0f4b7420",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r\n",
"\r\n",
"************* KDD19 *************************\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "4130aa319a4e4686b5c59d4c7627ebd6",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/20 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r\n",
"\r\n",
"************* WeSAL *************************\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "8d4003496bca46edacfec1fa26e01ab8",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/20 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r\n",
"\r\n",
"************* ActiveWeaSul *************************\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "7c16213af2da49cab7e8dcf2ee595d89",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/20 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r\n",
"\r\n",
"************* ActiveLearning *************************\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "d7bee20d194a4078afae4af757f46d77",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/20 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r\n",
"\r\n",
"************* DualLoops *************************\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "0dfd0d111c7c49448bc605c623cea0c7",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/20 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"### predefined configuration for different setups\n",
"\n",
"configuration_options = {\n",
" 'KDD19': {\n",
" 'datapoint_grouping': 'disagreement', \n",
" 'group_selection': 'max',\n",
" 'datapoint_selection': 'random',\n",
" \n",
" 'lf_ensemble': 'snorkel',\n",
" \n",
" 'lf_selection': 'all', \n",
" 'with_slow_loop': False \n",
" }, \n",
" 'WeSAL': {\n",
" 'datapoint_grouping': 'disagreement', \n",
" 'group_selection': 'max',\n",
" 'datapoint_selection': 'entropy', # best option for uncertainty sampling\n",
" \n",
" 'lf_ensemble': 'snorkel_with_corrected_votes',\n",
" \n",
" 'lf_selection': 'all', \n",
" 'with_slow_loop': False \n",
" }, \n",
" 'ActiveWeaSul': {\n",
" 'datapoint_grouping': 'uniqueness_votes', \n",
" 'group_selection': 'max_kl',\n",
" 'datapoint_selection': 'random',\n",
" \n",
" 'lf_ensemble': 'snorkel_with_corrected_votes', #'snorkel_with_annotated_labels',\n",
" \n",
" 'lf_selection': 'all', \n",
" 'with_slow_loop': False \n",
" }, \n",
" 'DualLoops': {\n",
" 'datapoint_grouping': 'num_positive_votes', \n",
" 'group_selection': 'max',\n",
" 'datapoint_selection': 'match_confidence', #entropy, least_confidence, margin\n",
" \n",
" 'lf_ensemble': 'snorkel_with_corrected_votes', #snorkel_with_init_precision\n",
" \n",
" 'lf_selection': 'all', \n",
" 'with_slow_loop': False \n",
" }, \n",
" 'ActiveLearning': {\n",
" 'datapoint_grouping': 'none', \n",
" 'group_selection': 'none',\n",
" 'datapoint_selection': 'entropy', #entropy, least_confidence, margin\n",
" 'lf_ensemble': 'normal_active_learning_rf',\n",
" \n",
" 'lf_selection': 'all', \n",
" 'with_slow_loop': False \n",
" } \n",
"}\n",
"\n",
"lfs_set = [\n",
"# 'LF_aml', \n",
"# 'LF_logmap', \n",
"# 'LF_yam',\n",
" \n",
" 'LF_class_name_equal', \n",
" 'LF_class_name_stemmed_equal',\n",
" 'LF_acronyms', \n",
" 'LF_class_name_synonyms',\n",
" 'LF_label_equal', \n",
" 'LF_root_nouns_equal', \n",
" \n",
" 'LF_class_name_spacy_distance', \n",
" 'LF_class_name_distance', \n",
" \n",
" 'LF_name_segment_overlap', \n",
" 'LF_label_words_overlap',\n",
" 'LF_subclasses_overlap',\n",
" 'LF_superclasses_overlap',\n",
" 'LF_properties_overlap',\n",
" ]\n",
"\n",
"feature_set = [\n",
" 'shared_word', \n",
" 'levenshtein_distance', \n",
" 'hamming_distance',\n",
" 'class_name_embedding_distance'\n",
" ]\n",
"\n",
"\n",
"epochs = 100\n",
"balance=[0.9, 0.1]\n",
"\n",
"num_iteration = 20\n",
"interval_slow_loop = 10\n",
"budget = 4000\n",
"\n",
"experiments = [ \n",
" 'KDD19', \n",
" 'WeSAL',\n",
" 'ActiveWeaSul',\n",
" 'ActiveLearning', \n",
" 'DualLoops',\n",
"]\n",
"\n",
"results = {}\n",
"\n",
"for exp in experiments:\n",
" print(\"\\r\\n\\r\\n************* \" + exp + \" *************************\")\n",
" experiment_config = configuration_options[exp]\n",
" result, result_df = dual_loops.run_experiment(experiment_config, my_dataset_df, lfs_set, feature_set, num_iteration, interval_slow_loop, balance, epochs, budget, False)\n",
" \n",
" results[exp] = result \n",
"\n",
"# plot the results generated from all experiments\n",
"dual_loops.plot_result(results, 'f1', 100.0) \n",
"dual_loops.plot_result(results, 'precision', 100.0) \n",
"dual_loops.plot_result(results, 'recall', 100.0) \n",
"\n",
"dual_loops.plot_result(results, 'human_effort', 1.0) \n",
"dual_loops.plot_result(results, 'num_true_matches', 1.0) \n",
"\n",
"dual_loops.plot_result(results, 'a-tp', 1.0) \n",
"dual_loops.plot_result(results, 'p-tp', 1.0) \n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 101,
"id": "1d400f2b",
"metadata": {},
"outputs": [],
"source": [
"import seaborn as sns\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
" \n",
"def plot_comparison_result(results, methods, names): \n",
" \n",
" metrics = ['human_effort', 'num_true_matches', 'a-tp', 'p-tp']\n",
" labels = ['cost', 'gain', '#annoate_matches', '#verified_matches']\n",
" markers = ['o', '*', '+', 'x']\n",
" fsize=20 \n",
"\n",
" num_fig = len(metrics)\n",
" fig, axs = plt.subplots(1, num_fig, figsize=(28, 5)) \n",
" lines = []\n",
" \n",
" for i in range(len(metrics)):\n",
" metric = metrics[i] \n",
" for j in range(len(methods)):\n",
" method = methods[j]\n",
" rdf = pd.DataFrame(results[method]) \n",
" x = rdf.columns\n",
" xticks = np.arange(min(x), max(x)+1, 2)\n",
" y = rdf.loc[metric] \n",
" \n",
" axs[i].set_xticks(xticks)\n",
" line = axs[i].plot(x, y, linestyle = '-', marker=markers[j])\n",
" lines.append(lines)\n",
" \n",
" axs[i].set_ylabel(labels[i], fontsize=fsize)\n",
" axs[i].grid(True)\n",
"\n",
"\n",
" fig.legend(lines, # The line objects\n",
" labels=names, # The labels for each line\n",
" loc=\"upper center\", # Position of legend,\n",
" bbox_to_anchor=(0.45, 1.0), ncol=len(methods)\n",
" ) \n",
" \n",
" plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 105,
"id": "ec46ecf8",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/bcheng/.local/lib/python3.7/site-packages/ipykernel_launcher.py:36: UserWarning: You have mixed positional and keyword arguments, some input may be discarded.\n"
]
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 2016x360 with 4 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_comparison_result(results, ['KDD19', 'ActiveLearning', 'DualLoops'], ['WeSAL, ActiveWeaSul', 'Active Learning', 'DualLoops (with only slowloop)'])"
]
},
{
"cell_type": "code",
"execution_count": 96,
"id": "9dfbc893",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/bcheng/.local/lib/python3.7/site-packages/ipykernel_launcher.py:66: UserWarning: You have mixed positional and keyword arguments, some input may be discarded.\n"
]
}
],
"source": [
"exp_result_df_kdd19 = pd.DataFrame(results['KDD19'])\n",
"exp_result_df_dualloops = pd.DataFrame(results['DualLoops'])\n",
"exp_result_df_active_learning = pd.DataFrame(results['ActiveLearning'])\n",
"\n",
"x = exp_result_df_kdd19.columns\n",
"\n",
"xticks = np.arange(min(x), max(x)+1, 2)\n",
"\n",
"# cost\n",
"y11 = exp_result_df_kdd19.loc['human_effort']\n",
"y12 = exp_result_df_dualloops.loc['human_effort']\n",
"y13 = exp_result_df_active_learning.loc['human_effort']\n",
"\n",
"# gain\n",
"y21 = exp_result_df_kdd19.loc['num_true_matches']\n",
"y22 = exp_result_df_dualloops.loc['num_true_matches']\n",
"y23 = exp_result_df_active_learning.loc['num_true_matches']\n",
"\n",
"# gain\n",
"y31 = exp_result_df_kdd19.loc['a-tp']\n",
"y32 = exp_result_df_dualloops.loc['a-tp']\n",
"y33 = exp_result_df_active_learning.loc['a-tp']\n",
"\n",
"# gain\n",
"y41 = exp_result_df_kdd19.loc['p-tp']\n",
"y42 = exp_result_df_dualloops.loc['p-tp']\n",
"y43 = exp_result_df_active_learning.loc['p-tp']\n",
"\n",
"fig, axs = plt.subplots(1, 4, figsize=(28, 5))\n",
"#fig.suptitle('Horizontally stacked subplots')\n",
"\n",
"axs[0].set_xticks(xticks)\n",
"l1 = axs[0].plot(x, y11, linestyle = '-', marker='o')\n",
"l2 = axs[0].plot(x, y12, linestyle = '-', marker='*')\n",
"l3 = axs[0].plot(x, y13, linestyle = '-', marker='+')\n",
"axs[0].set_ylabel('cost', fontsize=20)\n",
"\n",
"axs[1].set_xticks(xticks)\n",
"axs[1].plot(x, y21, linestyle = '-', marker='o')\n",
"axs[1].plot(x, y22, linestyle = '-', marker='*')\n",
"axs[1].plot(x, y23, linestyle = '-', marker='+')\n",
"axs[1].set_ylabel('gain', fontsize=20)\n",
"\n",
"axs[2].set_xticks(xticks)\n",
"axs[2].plot(x, y31, linestyle = '-', marker='o')\n",
"axs[2].plot(x, y32, linestyle = '-', marker='*')\n",
"axs[2].plot(x, y33, linestyle = '-', marker='+')\n",
"axs[2].set_ylabel('#annoate_matches', fontsize=20)\n",
"\n",
"axs[3].set_xticks(xticks)\n",
"axs[3].plot(x, y41, linestyle = '-', marker='o')\n",
"axs[3].plot(x, y42, linestyle = '-', marker='*')\n",
"axs[3].plot(x, y43, linestyle = '-', marker='+')\n",
"axs[3].set_ylabel('#verified_matches', fontsize=20)\n",
"\n",
"plt.grid(True)\n",
"axs[0].grid(True)\n",
"axs[1].grid(True)\n",
"axs[2].grid(True)\n",
"axs[3].grid(True)\n",
"\n",
"line_labels = [\"WeSAL\", \"DualLoop\", \"Active Learning\"]\n",
"fig.legend([l1, l2, l3], # The line objects\n",
" labels=line_labels, # The labels for each line\n",
" loc=\"upper center\", # Position of legend,\n",
" bbox_to_anchor=(0.45, 1.0), ncol=3\n",
" )\n",
"\n",
"plt.savefig(dataset_name + '_result_without_slowloop.pdf')\n",
"plt.close(fig)"
]
},
{
"cell_type": "code",
"execution_count": 56,
"id": "0bd5127a",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'KDD19': {0: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 0,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7995,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 14,\n",
" 'num_true_matches': 10},\n",
" 1: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 1,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7994,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 15,\n",
" 'num_true_matches': 10},\n",
" 2: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 2,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7993,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 16,\n",
" 'num_true_matches': 10},\n",
" 3: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 3,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7992,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 17,\n",
" 'num_true_matches': 10},\n",
" 4: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 4,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7991,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 18,\n",
" 'num_true_matches': 10},\n",
" 5: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 5,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7990,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 19,\n",
" 'num_true_matches': 10},\n",
" 6: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 6,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7989,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 20,\n",
" 'num_true_matches': 10},\n",
" 7: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 7,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7988,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 21,\n",
" 'num_true_matches': 10},\n",
" 8: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 8,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7987,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 22,\n",
" 'num_true_matches': 10},\n",
" 9: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 9,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7986,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 23,\n",
" 'num_true_matches': 10},\n",
" 10: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 10,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7985,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 24,\n",
" 'num_true_matches': 10},\n",
" 11: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 11,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7984,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 25,\n",
" 'num_true_matches': 10},\n",
" 12: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 12,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7983,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 26,\n",
" 'num_true_matches': 10},\n",
" 13: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 13,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7982,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 27,\n",
" 'num_true_matches': 10},\n",
" 14: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 14,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7981,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 28,\n",
" 'num_true_matches': 10},\n",
" 15: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 15,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7980,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 29,\n",
" 'num_true_matches': 10},\n",
" 16: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 16,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7979,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 30,\n",
" 'num_true_matches': 10},\n",
" 17: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 17,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7978,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 31,\n",
" 'num_true_matches': 10},\n",
" 18: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 18,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7977,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 32,\n",
" 'num_true_matches': 10},\n",
" 19: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 19,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7976,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 33,\n",
" 'num_true_matches': 10},\n",
" 20: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 20,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7975,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 34,\n",
" 'num_true_matches': 10}},\n",
" 'WeSAL': {0: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 0,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7995,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 14,\n",
" 'num_true_matches': 10},\n",
" 1: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 1,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7994,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 15,\n",
" 'num_true_matches': 10},\n",
" 2: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 2,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7993,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 16,\n",
" 'num_true_matches': 10},\n",
" 3: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 3,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7992,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 17,\n",
" 'num_true_matches': 10},\n",
" 4: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 4,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7991,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 18,\n",
" 'num_true_matches': 10},\n",
" 5: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 5,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7990,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 19,\n",
" 'num_true_matches': 10},\n",
" 6: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 6,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7989,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 20,\n",
" 'num_true_matches': 10},\n",
" 7: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 7,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7988,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 21,\n",
" 'num_true_matches': 10},\n",
" 8: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 8,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7987,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 22,\n",
" 'num_true_matches': 10},\n",
" 9: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 9,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7986,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 23,\n",
" 'num_true_matches': 10},\n",
" 10: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 10,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7985,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 24,\n",
" 'num_true_matches': 10},\n",
" 11: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 11,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7984,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 25,\n",
" 'num_true_matches': 10},\n",
" 12: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 12,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7983,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 26,\n",
" 'num_true_matches': 10},\n",
" 13: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 13,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7982,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 27,\n",
" 'num_true_matches': 10},\n",
" 14: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 14,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7981,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 28,\n",
" 'num_true_matches': 10},\n",
" 15: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 15,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7980,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 29,\n",
" 'num_true_matches': 10},\n",
" 16: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 16,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7979,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 30,\n",
" 'num_true_matches': 10},\n",
" 17: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 17,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7978,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 31,\n",
" 'num_true_matches': 10},\n",
" 18: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 18,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7977,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 32,\n",
" 'num_true_matches': 10},\n",
" 19: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 19,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7976,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 33,\n",
" 'num_true_matches': 10},\n",
" 20: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 20,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7975,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 34,\n",
" 'num_true_matches': 10}},\n",
" 'ActiveWeaSul': {0: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 0,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7995,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 14,\n",
" 'num_true_matches': 10},\n",
" 1: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 1,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7994,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 15,\n",
" 'num_true_matches': 10},\n",
" 2: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 2,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7993,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 16,\n",
" 'num_true_matches': 10},\n",
" 3: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 3,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7992,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 17,\n",
" 'num_true_matches': 10},\n",
" 4: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 4,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7991,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 18,\n",
" 'num_true_matches': 10},\n",
" 5: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 5,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7990,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 19,\n",
" 'num_true_matches': 10},\n",
" 6: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 6,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7989,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 20,\n",
" 'num_true_matches': 10},\n",
" 7: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 7,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7988,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 21,\n",
" 'num_true_matches': 10},\n",
" 8: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 8,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7987,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 22,\n",
" 'num_true_matches': 10},\n",
" 9: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 9,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7986,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 23,\n",
" 'num_true_matches': 10},\n",
" 10: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 10,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7985,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 24,\n",
" 'num_true_matches': 10},\n",
" 11: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 11,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7984,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 25,\n",
" 'num_true_matches': 10},\n",
" 12: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 12,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7983,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 26,\n",
" 'num_true_matches': 10},\n",
" 13: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 13,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7982,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 27,\n",
" 'num_true_matches': 10},\n",
" 14: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 14,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7981,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 28,\n",
" 'num_true_matches': 10},\n",
" 15: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 15,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7980,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 29,\n",
" 'num_true_matches': 10},\n",
" 16: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 16,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7979,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 30,\n",
" 'num_true_matches': 10},\n",
" 17: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 17,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7978,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 31,\n",
" 'num_true_matches': 10},\n",
" 18: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 18,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7977,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 32,\n",
" 'num_true_matches': 10},\n",
" 19: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 19,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7976,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 33,\n",
" 'num_true_matches': 10},\n",
" 20: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 20,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7975,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 34,\n",
" 'num_true_matches': 10}},\n",
" 'ActiveLearning': {0: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 32,\n",
" 'tp': 0,\n",
" 'precision': nan,\n",
" 'recall': 0.0,\n",
" 'f1': 0.0,\n",
" 'a-tn': 0,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7999,\n",
" 'p-fp': 0,\n",
" 'p-fn': 32,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 0,\n",
" 'num_true_matches': 0},\n",
" 1: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 32,\n",
" 'tp': 0,\n",
" 'precision': nan,\n",
" 'recall': 0.0,\n",
" 'f1': 0.0,\n",
" 'a-tn': 1,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7998,\n",
" 'p-fp': 0,\n",
" 'p-fn': 32,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 1,\n",
" 'num_true_matches': 0},\n",
" 2: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 32,\n",
" 'tp': 0,\n",
" 'precision': nan,\n",
" 'recall': 0.0,\n",
" 'f1': 0.0,\n",
" 'a-tn': 2,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7997,\n",
" 'p-fp': 0,\n",
" 'p-fn': 32,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 2,\n",
" 'num_true_matches': 0},\n",
" 3: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 32,\n",
" 'tp': 0,\n",
" 'precision': nan,\n",
" 'recall': 0.0,\n",
" 'f1': 0.0,\n",
" 'a-tn': 3,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7996,\n",
" 'p-fp': 0,\n",
" 'p-fn': 32,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 3,\n",
" 'num_true_matches': 0},\n",
" 4: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 32,\n",
" 'tp': 0,\n",
" 'precision': nan,\n",
" 'recall': 0.0,\n",
" 'f1': 0.0,\n",
" 'a-tn': 4,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7995,\n",
" 'p-fp': 0,\n",
" 'p-fn': 32,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 4,\n",
" 'num_true_matches': 0},\n",
" 5: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 32,\n",
" 'tp': 0,\n",
" 'precision': nan,\n",
" 'recall': 0.0,\n",
" 'f1': 0.0,\n",
" 'a-tn': 5,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7994,\n",
" 'p-fp': 0,\n",
" 'p-fn': 32,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 5,\n",
" 'num_true_matches': 0},\n",
" 6: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 32,\n",
" 'tp': 0,\n",
" 'precision': nan,\n",
" 'recall': 0.0,\n",
" 'f1': 0.0,\n",
" 'a-tn': 6,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7993,\n",
" 'p-fp': 0,\n",
" 'p-fn': 32,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 6,\n",
" 'num_true_matches': 0},\n",
" 7: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 32,\n",
" 'tp': 0,\n",
" 'precision': nan,\n",
" 'recall': 0.0,\n",
" 'f1': 0.0,\n",
" 'a-tn': 7,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7992,\n",
" 'p-fp': 0,\n",
" 'p-fn': 32,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 7,\n",
" 'num_true_matches': 0},\n",
" 8: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 32,\n",
" 'tp': 0,\n",
" 'precision': nan,\n",
" 'recall': 0.0,\n",
" 'f1': 0.0,\n",
" 'a-tn': 8,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7991,\n",
" 'p-fp': 0,\n",
" 'p-fn': 32,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 8,\n",
" 'num_true_matches': 0},\n",
" 9: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 32,\n",
" 'tp': 0,\n",
" 'precision': nan,\n",
" 'recall': 0.0,\n",
" 'f1': 0.0,\n",
" 'a-tn': 9,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7990,\n",
" 'p-fp': 0,\n",
" 'p-fn': 32,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 9,\n",
" 'num_true_matches': 0},\n",
" 10: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 32,\n",
" 'tp': 0,\n",
" 'precision': nan,\n",
" 'recall': 0.0,\n",
" 'f1': 0.0,\n",
" 'a-tn': 10,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7989,\n",
" 'p-fp': 0,\n",
" 'p-fn': 32,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 10,\n",
" 'num_true_matches': 0},\n",
" 11: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 32,\n",
" 'tp': 0,\n",
" 'precision': nan,\n",
" 'recall': 0.0,\n",
" 'f1': 0.0,\n",
" 'a-tn': 11,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7988,\n",
" 'p-fp': 0,\n",
" 'p-fn': 32,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 11,\n",
" 'num_true_matches': 0},\n",
" 12: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 32,\n",
" 'tp': 0,\n",
" 'precision': nan,\n",
" 'recall': 0.0,\n",
" 'f1': 0.0,\n",
" 'a-tn': 12,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7987,\n",
" 'p-fp': 0,\n",
" 'p-fn': 32,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 12,\n",
" 'num_true_matches': 0},\n",
" 13: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 32,\n",
" 'tp': 0,\n",
" 'precision': nan,\n",
" 'recall': 0.0,\n",
" 'f1': 0.0,\n",
" 'a-tn': 13,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7986,\n",
" 'p-fp': 0,\n",
" 'p-fn': 32,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 13,\n",
" 'num_true_matches': 0},\n",
" 14: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 32,\n",
" 'tp': 0,\n",
" 'precision': nan,\n",
" 'recall': 0.0,\n",
" 'f1': 0.0,\n",
" 'a-tn': 14,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7985,\n",
" 'p-fp': 0,\n",
" 'p-fn': 32,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 14,\n",
" 'num_true_matches': 0},\n",
" 15: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 32,\n",
" 'tp': 0,\n",
" 'precision': nan,\n",
" 'recall': 0.0,\n",
" 'f1': 0.0,\n",
" 'a-tn': 15,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7984,\n",
" 'p-fp': 0,\n",
" 'p-fn': 32,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 15,\n",
" 'num_true_matches': 0},\n",
" 16: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 32,\n",
" 'tp': 0,\n",
" 'precision': nan,\n",
" 'recall': 0.0,\n",
" 'f1': 0.0,\n",
" 'a-tn': 16,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7983,\n",
" 'p-fp': 0,\n",
" 'p-fn': 32,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 16,\n",
" 'num_true_matches': 0},\n",
" 17: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 32,\n",
" 'tp': 0,\n",
" 'precision': nan,\n",
" 'recall': 0.0,\n",
" 'f1': 0.0,\n",
" 'a-tn': 17,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7982,\n",
" 'p-fp': 0,\n",
" 'p-fn': 32,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 17,\n",
" 'num_true_matches': 0},\n",
" 18: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 32,\n",
" 'tp': 0,\n",
" 'precision': nan,\n",
" 'recall': 0.0,\n",
" 'f1': 0.0,\n",
" 'a-tn': 18,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7981,\n",
" 'p-fp': 0,\n",
" 'p-fn': 32,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 18,\n",
" 'num_true_matches': 0},\n",
" 19: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 32,\n",
" 'tp': 0,\n",
" 'precision': nan,\n",
" 'recall': 0.0,\n",
" 'f1': 0.0,\n",
" 'a-tn': 19,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7980,\n",
" 'p-fp': 0,\n",
" 'p-fn': 32,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 19,\n",
" 'num_true_matches': 0},\n",
" 20: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 32,\n",
" 'tp': 0,\n",
" 'precision': nan,\n",
" 'recall': 0.0,\n",
" 'f1': 0.0,\n",
" 'a-tn': 20,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7979,\n",
" 'p-fp': 0,\n",
" 'p-fn': 32,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 20,\n",
" 'num_true_matches': 0}},\n",
" 'DualLoops': {0: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 0,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 0,\n",
" 'a-precision': nan,\n",
" 'a-recall': nan,\n",
" 'a-f1': nan,\n",
" 'p-tn': 7995,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 10,\n",
" 'p-precision': 0.7142857142857143,\n",
" 'p-recall': 0.3125,\n",
" 'p-f1': 0.43478260869565216,\n",
" 'human_effort': 14,\n",
" 'num_true_matches': 10},\n",
" 1: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 0,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 1,\n",
" 'a-precision': 1.0,\n",
" 'a-recall': 1.0,\n",
" 'a-f1': 1.0,\n",
" 'p-tn': 7995,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 9,\n",
" 'p-precision': 0.6923076923076923,\n",
" 'p-recall': 0.2903225806451613,\n",
" 'p-f1': 0.4090909090909091,\n",
" 'human_effort': 14,\n",
" 'num_true_matches': 10},\n",
" 2: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 0,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 2,\n",
" 'a-precision': 1.0,\n",
" 'a-recall': 1.0,\n",
" 'a-f1': 1.0,\n",
" 'p-tn': 7995,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 8,\n",
" 'p-precision': 0.6666666666666666,\n",
" 'p-recall': 0.26666666666666666,\n",
" 'p-f1': 0.38095238095238093,\n",
" 'human_effort': 14,\n",
" 'num_true_matches': 10},\n",
" 3: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 0,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 3,\n",
" 'a-precision': 1.0,\n",
" 'a-recall': 1.0,\n",
" 'a-f1': 1.0,\n",
" 'p-tn': 7995,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 7,\n",
" 'p-precision': 0.6363636363636364,\n",
" 'p-recall': 0.2413793103448276,\n",
" 'p-f1': 0.35,\n",
" 'human_effort': 14,\n",
" 'num_true_matches': 10},\n",
" 4: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 0,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 4,\n",
" 'a-precision': 1.0,\n",
" 'a-recall': 1.0,\n",
" 'a-f1': 1.0,\n",
" 'p-tn': 7995,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 6,\n",
" 'p-precision': 0.6,\n",
" 'p-recall': 0.21428571428571427,\n",
" 'p-f1': 0.3157894736842105,\n",
" 'human_effort': 14,\n",
" 'num_true_matches': 10},\n",
" 5: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 0,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 5,\n",
" 'a-precision': 1.0,\n",
" 'a-recall': 1.0,\n",
" 'a-f1': 1.0,\n",
" 'p-tn': 7995,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 5,\n",
" 'p-precision': 0.5555555555555556,\n",
" 'p-recall': 0.18518518518518517,\n",
" 'p-f1': 0.2777777777777778,\n",
" 'human_effort': 14,\n",
" 'num_true_matches': 10},\n",
" 6: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 0,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 6,\n",
" 'a-precision': 1.0,\n",
" 'a-recall': 1.0,\n",
" 'a-f1': 1.0,\n",
" 'p-tn': 7995,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 4,\n",
" 'p-precision': 0.5,\n",
" 'p-recall': 0.15384615384615385,\n",
" 'p-f1': 0.23529411764705882,\n",
" 'human_effort': 14,\n",
" 'num_true_matches': 10},\n",
" 7: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 0,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 7,\n",
" 'a-precision': 1.0,\n",
" 'a-recall': 1.0,\n",
" 'a-f1': 1.0,\n",
" 'p-tn': 7995,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 3,\n",
" 'p-precision': 0.42857142857142855,\n",
" 'p-recall': 0.12,\n",
" 'p-f1': 0.1875,\n",
" 'human_effort': 14,\n",
" 'num_true_matches': 10},\n",
" 8: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 0,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 8,\n",
" 'a-precision': 1.0,\n",
" 'a-recall': 1.0,\n",
" 'a-f1': 1.0,\n",
" 'p-tn': 7995,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 2,\n",
" 'p-precision': 0.3333333333333333,\n",
" 'p-recall': 0.08333333333333333,\n",
" 'p-f1': 0.13333333333333333,\n",
" 'human_effort': 14,\n",
" 'num_true_matches': 10},\n",
" 9: {'tn': 7995,\n",
" 'fp': 4,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7142857142857143,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.43478260869565216,\n",
" 'a-tn': 0,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 9,\n",
" 'a-precision': 1.0,\n",
" 'a-recall': 1.0,\n",
" 'a-f1': 1.0,\n",
" 'p-tn': 7995,\n",
" 'p-fp': 4,\n",
" 'p-fn': 22,\n",
" 'p-tp': 1,\n",
" 'p-precision': 0.2,\n",
" 'p-recall': 0.043478260869565216,\n",
" 'p-f1': 0.07142857142857142,\n",
" 'human_effort': 14,\n",
" 'num_true_matches': 10},\n",
" 10: {'tn': 7996,\n",
" 'fp': 3,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.7692307692307693,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.4444444444444444,\n",
" 'a-tn': 1,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 9,\n",
" 'a-precision': 1.0,\n",
" 'a-recall': 1.0,\n",
" 'a-f1': 1.0,\n",
" 'p-tn': 7995,\n",
" 'p-fp': 3,\n",
" 'p-fn': 22,\n",
" 'p-tp': 1,\n",
" 'p-precision': 0.25,\n",
" 'p-recall': 0.043478260869565216,\n",
" 'p-f1': 0.07407407407407407,\n",
" 'human_effort': 14,\n",
" 'num_true_matches': 10},\n",
" 11: {'tn': 7997,\n",
" 'fp': 2,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.8333333333333334,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.45454545454545453,\n",
" 'a-tn': 2,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 9,\n",
" 'a-precision': 1.0,\n",
" 'a-recall': 1.0,\n",
" 'a-f1': 1.0,\n",
" 'p-tn': 7995,\n",
" 'p-fp': 2,\n",
" 'p-fn': 22,\n",
" 'p-tp': 1,\n",
" 'p-precision': 0.3333333333333333,\n",
" 'p-recall': 0.043478260869565216,\n",
" 'p-f1': 0.07692307692307693,\n",
" 'human_effort': 14,\n",
" 'num_true_matches': 10},\n",
" 12: {'tn': 7998,\n",
" 'fp': 1,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 0.9090909090909091,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.46511627906976744,\n",
" 'a-tn': 3,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 9,\n",
" 'a-precision': 1.0,\n",
" 'a-recall': 1.0,\n",
" 'a-f1': 1.0,\n",
" 'p-tn': 7995,\n",
" 'p-fp': 1,\n",
" 'p-fn': 22,\n",
" 'p-tp': 1,\n",
" 'p-precision': 0.5,\n",
" 'p-recall': 0.043478260869565216,\n",
" 'p-f1': 0.08,\n",
" 'human_effort': 14,\n",
" 'num_true_matches': 10},\n",
" 13: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 1.0,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.47619047619047616,\n",
" 'a-tn': 4,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 9,\n",
" 'a-precision': 1.0,\n",
" 'a-recall': 1.0,\n",
" 'a-f1': 1.0,\n",
" 'p-tn': 7995,\n",
" 'p-fp': 0,\n",
" 'p-fn': 22,\n",
" 'p-tp': 1,\n",
" 'p-precision': 1.0,\n",
" 'p-recall': 0.043478260869565216,\n",
" 'p-f1': 0.08333333333333333,\n",
" 'human_effort': 14,\n",
" 'num_true_matches': 10},\n",
" 14: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 1.0,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.47619047619047616,\n",
" 'a-tn': 4,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 10,\n",
" 'a-precision': 1.0,\n",
" 'a-recall': 1.0,\n",
" 'a-f1': 1.0,\n",
" 'p-tn': 7995,\n",
" 'p-fp': 0,\n",
" 'p-fn': 22,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 14,\n",
" 'num_true_matches': 10},\n",
" 15: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 1.0,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.47619047619047616,\n",
" 'a-tn': 5,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 10,\n",
" 'a-precision': 1.0,\n",
" 'a-recall': 1.0,\n",
" 'a-f1': 1.0,\n",
" 'p-tn': 7994,\n",
" 'p-fp': 0,\n",
" 'p-fn': 22,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 15,\n",
" 'num_true_matches': 10},\n",
" 16: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 1.0,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.47619047619047616,\n",
" 'a-tn': 6,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 10,\n",
" 'a-precision': 1.0,\n",
" 'a-recall': 1.0,\n",
" 'a-f1': 1.0,\n",
" 'p-tn': 7993,\n",
" 'p-fp': 0,\n",
" 'p-fn': 22,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 16,\n",
" 'num_true_matches': 10},\n",
" 17: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 1.0,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.47619047619047616,\n",
" 'a-tn': 7,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 10,\n",
" 'a-precision': 1.0,\n",
" 'a-recall': 1.0,\n",
" 'a-f1': 1.0,\n",
" 'p-tn': 7992,\n",
" 'p-fp': 0,\n",
" 'p-fn': 22,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 17,\n",
" 'num_true_matches': 10},\n",
" 18: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 1.0,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.47619047619047616,\n",
" 'a-tn': 8,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 10,\n",
" 'a-precision': 1.0,\n",
" 'a-recall': 1.0,\n",
" 'a-f1': 1.0,\n",
" 'p-tn': 7991,\n",
" 'p-fp': 0,\n",
" 'p-fn': 22,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 18,\n",
" 'num_true_matches': 10},\n",
" 19: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 1.0,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.47619047619047616,\n",
" 'a-tn': 9,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 10,\n",
" 'a-precision': 1.0,\n",
" 'a-recall': 1.0,\n",
" 'a-f1': 1.0,\n",
" 'p-tn': 7990,\n",
" 'p-fp': 0,\n",
" 'p-fn': 22,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 19,\n",
" 'num_true_matches': 10},\n",
" 20: {'tn': 7999,\n",
" 'fp': 0,\n",
" 'fn': 22,\n",
" 'tp': 10,\n",
" 'precision': 1.0,\n",
" 'recall': 0.3125,\n",
" 'f1': 0.47619047619047616,\n",
" 'a-tn': 10,\n",
" 'a-fp': 0,\n",
" 'a-fn': 0,\n",
" 'a-tp': 10,\n",
" 'a-precision': 1.0,\n",
" 'a-recall': 1.0,\n",
" 'a-f1': 1.0,\n",
" 'p-tn': 7989,\n",
" 'p-fp': 0,\n",
" 'p-fn': 22,\n",
" 'p-tp': 0,\n",
" 'p-precision': nan,\n",
" 'p-recall': 0.0,\n",
" 'p-f1': 0.0,\n",
" 'human_effort': 20,\n",
" 'num_true_matches': 10}}}"
]
},
"execution_count": 56,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"\n",
"results"
]
},
{
"cell_type": "code",
"execution_count": 43,
"id": "dcb69ebb",
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAEMCAYAAAArnKpYAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/MnkTPAAAACXBIWXMAAAsTAAALEwEAmpwYAABOVElEQVR4nO3dd3xTZRfA8V9Gd+mClpZNy2qZpYWKgMjeCAiiDMVXRV5FQEVQHCAgCCpDwRdwK4giIqvIEhcoG4SyKaOFtnTTRZsmue8ftYFCW9KRpuN8Px8+NOO559zkJifPHc+jUhRFQQghhADU1k5ACCFE+SFFQQghhIkUBSGEECZSFIQQQphIURBCCGEiRUEIIYSJFAUhhBAmWmsnUBqSktIxGot+uUX16s4kJKRZIKPyGdeasWWdq0bsqhbX2rGLS61W4e7ulO9jlaIoGI1KsYpCbltrsFZca8aWda4asataXGvHLm2y+0gIIYSJFAUhhBAmUhSEEEKYlElRmD9/Pt26daNp06acO3fOdP+lS5cYMWIEvXv3ZsSIEVy+fLks0hFCCFGAMikK3bt3Z/Xq1dSuXTvP/TNmzGDkyJFs376dkSNH8tZbb5VFOkIIC9BoVGSk69BoVMVqa2erLXbb4sa1ZuySxi1u23spk6IQHByMj49PnvsSEhI4deoUAwYMAGDAgAGcOnWKxMTEskhJCFGKNBoVKlT8tPooKlSo1SoURTHrn1qd03bz98eL3bY4ca0ZuzTi5rRVl3phsNopqdHR0dSsWRONRgOARqPBy8uL6OhoPDw8rJWWEKKINBoVKkXF6pUHSIxPZ/WKAwwe2YYN3x4jMT79ruePGt+e6Mgb7A49y9gXOuDgYMuazw8W2Pb259/+t0cNpzzPzW1rVIxEXEy86/l3yq/9yGfaExGeyNZ1YQWu76jx7UmKz8C7lutdsfNb5zvzv1fbgtY3/5z3M+rZEDQaIwZD6ZwWWymuU6he3bnYbT09q5ViJuU/rjVjyzpXztgZ6Tp+Wn3U9GWYGJ/O79vPMfyJIM6Exdz1/Fq13XByssegV/Co7szGNccKbXv782//u1kLb3ZtOX1X24cea4Otrc1dz79Tfu1/Xh/GgEda0aW3rsD1rVXbjRqe1diy9rhZ63xn/vdqW9D6FpTz1nUnGDIqEEcnWzPfscKpynLmtW7durF8+XKaNGlCQkICvXv3Zv/+/Wg0GgwGAyEhIezYsaPIPYWEhLRiXTzi6VmNuLjUIrcrKWvFtWZsWefKGzs5IYMans6mnoJHDSdGPRuCwr1/vebsdlKzesX+Mm1rzdjWXOdcarWqwB/TVjsltXr16vj7+7NlyxYAtmzZgr+/v+w6EqICSUrIYN1XR9i/5xKjng3Br6lnkb6kDAYFBWOZt7VmbGuusznKpKcwZ84cduzYQXx8PO7u7ri5uREaGkp4eDivvvoqKSkpuLi4MH/+fHx9fYu8fOkplP/Yss6VL3a2zsCPXx/hZno2w59si6u7A/Z2tmRm6Yr8JaXRqNBqNOgNhmK1LW5ca8YuadzitoXCewpluvvIUqQolP/Yss6VK7aiKPyy5QznT8YyYERL6jb0KJO4BanMr7UllMvdR0KIiuvk0WjOn4ylXecGpoIgKgcpCkKIIomNTmHvLxeo5+tB0P31rJ2OKGVSFIQQRXJ0XyROTrZ0H9gMlar0r6gV1lUprlMQQlieoiikp+roMdCftNQs7B1srJ2SsADpKQghzHJsfyTff3aQ9DQdru4O1k5HWIj0FIQQZvFr5oXBoFDN1c7aqQgLkp6CEKJQaSmZbFl7HIDgjvXlOEIlJz0FIUSBDAYj2zecIik+A4PBaO10RBmQnoIQokB/775IbFQqXfs1xb26o7XTEWVAioIQIl/nT8Vy4vA1WgXXxq+Zp7XTEWVEioIQ4i5J8en89vNZvGu7cF/Xoo9HJiouKQpCiDyydQa2/3QKrY2GnoMD0Gjka6IqkQPNQhSgpKNY5s7dW9YjYJY0tq2THU1beuPp7YxzNTn9tKqRoiBEPnInM9n8/XH6DGmORqMiPjadmxn5z8il1arx8nEhKSEDFQo1vFz4afVR+gxpTnxsGrosfYHPz9bpTX8bDEa8vKqxed3xPG0Lev6d+djaafHyqsZPq4/Sb1hL0lIyyEjPKvD5t+fjU8cVvU7h503H6TesZamP0y8qBikKQtzh1pzDObNbrfn0IKOeDeFcWAxH/o7Mt42Lmz2jxuc8J7B9fdPMWGs+PZgzp+6mvHP35j7/yF9XiLmWYmrbpl091nx68K62er3hrucf+esK507GmpaZO39vbvvVK/Yz7PG2/L7tLP0faXXX829Xz9edhx4LZO0X+y0296+oGGQ+BRn7vVLHLU5sWxstW9YeJ/xsnOk+v6ae9B3agiuXEvJto9Wq8a7jikal5uf1YXe17T04gMgrSXc9PzEuHV2W/p5to6/duOv5iXHpZKTf+uVft7472zecyqd9cxSVctfzb1e3vgfbN5y8q+3AEa3I0unzbZMf2b4qhsLmU5CeghB3+OvXcLr0bkJSQoZpHtzc3Sl1GrgX3lit0G9Yyzxz6BbW1sPTyay23nVc73q+h6dTnttqjarA9gbD3c/Pk7aGfNvqDYYivHKiMpDTCoS4zZkTMRzcc5lzp2Iq3Py75X3uX1ExSFEQ4l8JsWn8sf08teq50bxtbRSMDBzRqshfjrlfsENGBRa7bXHiWju2qBykKAgBZGXq2f7TKezstfR8yB+1Oud0ziydvlhfjgaDgqOTbbHbFjeutWOLik+KghDAnzvPk5J8k14PBeDoZGvtdISwmmIdaN63bx9qtZr27duXdj5ClDlFUWh7Xz3qNHDHp66rtdMRwqrM6imMHj2aw4cPA7By5UpeeuklXn75ZZYvX27R5ISwtOjIG2z5/gQOTjY0a+lt7XSEsDqzisL58+dp06YNAD/88ANff/01a9eu5bvvvrNkbkJYXEa6jpsZOtRq2ZMqBJi5+8hoNKJSqYiIiEBRFBo1agTAjRs3LJqcEJZiNCqcORFDs5beNGxSA7VaZhMTAswsCkFBQcyaNYu4uDh69uwJQEREBO7u97iQR4hy6sAflzi6LxInZ1vq+1W3djpClBtm9ZnnzZuHi4sLTZs2ZcKECQBcvHiRxx9/3KLJCWEJl87Hc3RfJAFtfKQgCHEHs3oK7u7uvPTSS3nue/DBBy2RjxAWdSPpJru3nKFGTWc69mhk7XSEKHfM6inodDoWLVpE9+7dCQoKAmDPnj2sWrXKoskJUZr02QZ2/HQKlUpF7yEBaLVycFmIO5n1qZg7dy7nzp3j/fffR6XKOSDXuHFj1qxZY9HkhChNf+68QHxsGt0HNMPFzcHa6QhRLpm1+2jXrl3s2LEDR0dH06l7NWvW5Pr16xZNTojSkpWp53pUCm3vr0f9RnIcQYiCmFUUbGxsMNwxhG5iYiJubm6lksSvv/7KkiVLUBQFRVGYMGECvXr1KpVli6pNo1GRknwTUHj48bZoZJeREIUy6xPSp08fpk2bRmRkzqxTsbGxzJo1i/79+5c4AUVRmDp1KgsWLGDjxo0sWLCAadOmYTQaS7xsUbXlTKmpYvPa46hRY2evlesRhLgHs4rCiy++SJ06dRg0aBApKSn07t0bLy8vnn/++dJJQq0mNTVn5qLU1FS8vLzkClNRIrkFYfWKA4SfjWP9qqOoVWo0GikKQhSmyNNxJiYm4u7ubjrgXBr+/vtvJk+ejKOjI+np6axcudI0rIYQxZGRruOn1Ufvml5yyKhAGQVViEKYPUpqamoqly5dIj09Pc/9HTp0KFECer2eFStW8PHHHxMUFMThw4eZPHkyoaGhODnlP3XgnWSO5vIfu6zjxl9Py3dKzcwsHekZWWWSg7zPlT+utWMXV4nnaF6/fj2zZs3C0dERe3t70/0qlYpffvmlRMmdPn2a2NhY0/UPQUFBODg4EB4eTqtWrUq0bFE1padlsWXtcby8qzFqXHu2/hh221zFMnmMEIUxqygsWrSIJUuW0KVLl1JPwNvbm5iYGC5evIivry/h4eEkJCRQr169Uo8lKj+jUWHnxtNk6wyEPOiLolIYMiqQzCydFAQhzGBWUTAYDHTq1MkiCXh6ejJz5kwmTZpkOk4xd+7cUjvdVVQt+3+/SHTkDboPaEZ1TyfT1JRltctIiIrOrKLwzDPP8L///Y/nnnvOImcFDRo0iEGDBpX6ckXVEnExkWP7rxIQ6EOTFjWtnY4QFVKBRaFLly6mX+6KohAfH8+nn3561y/43377zZL5CWE2nzquBHeqT9v7ZNejEMVVYFF47733yjIPIYpNn21g2/qTBN5Xl3adGlg7HSEqtAKLQvv27csyDyGK7WZGNmmpWej1chW8ECVl1gGCCRMmcOjQoTz3HTp0iIkTJ1okKSHMdflCAmqNikf+EywT5ghRCsw60Hzw4EGWLFmS5742bdqU2jAXQhRHXEwqO346ScOmnvQc5G/tdCocg0FPUlIcer2u1JYZG6u2yrhl1opr7dj3otXa4u7uiUZj9nXK5hUFW1tbbt68ibPzrSvgMjIy0GrNDyREacrK1LNjwynsHW3o1MPP2ulUSElJcdjbO+Lk5F1qw9ZotWqr7MazVlxrxy6Moiikp6eQlBRHjRo+Zrcza/dRp06deOutt0hLSwMgLS2NWbNm0blz5+JlK0QJKIrC7i1nSEvJotfgABwcZSyj4tDrdTg5uZTqOGai/FCpVDg5uRS5J2hWUXj11VdJS0ujffv2dOjQgfbt25OWlsZrr71WrGSFKIlj+yO5fCGBDt188a7tau10KjQpCJVbcd5fs/b/uLq6snLlSuLi4oiOjsbHxwdPT88iBxOipK5dSWb/75fwa+ZJy6Da1k5HiErHrJ7C4MGDgZwhKVq1amUqCEOHDrVYYkLk50p4Aq4ejjzYt4n8yhVm69QpmKtXI0tlWcOGDeTgwf2lsqzyyKyicOXKlbvuUxSFq1evlnpCQuTHYDASc/UG93fzY+iYQGzt5CQHkb8JE8axefMGa6dRYRX6yZo6dSoA2dnZpr9zXbt2jUaNGlkuMyHImUFNq9Fw/Mg1dm85w4ingvHwNG+eDSFE0RVaFG4fvvrOoazbtm1Lnz59LJOVEOROqalm8/fH6fdwC+wdbKQgVGLDhg1k6NDhbN++lWvXrtK9ey+effZ53nnnbY4fP0ZAQAtmz34XFxcXwsJOsHTpIi5fvkjNmj689NIrtG7dlhUrlnH8+DFOnQrjww8/oG/fAbz00jQADh3az5QpE0lOTqJnz7689NJUVCoVRqORr7/+nM2bN5CVlUVISAdefHGq6RT8bdtC+eST/3Hz5k1GjBiZJ+dTp8JYuHA+ERER2NnZ0atXH1544aUyf+1KU6FFYcKECQC0bt1aTj8VZSq3IKxesZ/E+HRWrzzAqGdDZKKcSu6333azaNEyDAYDTz45ivPnz/Lqq29Sv35DXnllEuvWfcfAgYOZOnUyb775NiEh93P48AFee+0VVq9ex7PPPs+JE//Qu3c/Bg4cnGfZf/21h08++Zr09HSefno0HTt25r777mfr1s38/PMWPvxwOe7uHsyZM4NFi+bz5puzuXTpIh988C7vvbeEgIAWrFixlLi4WNMylyz5gBEjHqNnz35kZGRw8WJ4Gb9ipc+sYwqdO3dGp9Nx9uxZ9u3bx99//236J4QlaDUatq47QWJ8zvSvifHpbF13Aq1GY+XMhCUNGzYCD4/qeHp60bp1GwICWtCkSTPs7Ox44IEHOX/+LNu3b6VDh/vp0KETarWadu3uw9/fn3379ha67FGjxlKtWjW8vb0JDAzm/PlzAOzcuY0RI0ZRu3YdHB0dGT/+eXbt2oFer+e3337h/vs70aZNW2xtbXn66f/mOcFBq9Vy9WokycnJODo60qJFS4u+PmXBrKN1hw4dYvLkyeh0OtLS0nB2diY9PR1vb+8ST8cpRH6y9Qa692921xzLeoPB2qkJC3J39zD9bWdnf9ftjIybxMTE8Ouvv7B375+mx/R6PW3aBBe67OrVb42NZW9vz82bGQDEx8fh7X3rit+aNX0wGAwkJSUSHx+Hl5e36TEHBwdcXW9dG/Pqq2/y+ecrGDXqYXx8avPkk8/QsWPF3qtiVlGYN28eTz/9NGPHjqVdu3YcOHCApUuX4uDgYOn8RBUVdiSKE4euMXxsELs2n5Y5loVJzZo16d27H9OmvWG67/ahJop6qnKNGp7ExESbbl+/HoNGo8Hd3YPq1Wtw5col02OZmZncuHHDdLtu3XrMnj0PnU7P77/v5s03pxEa+kuF/m40a/fR5cuXefzxx/PcN27cOL788ktL5CSquLiYVPbsPI9TNVs0NmoGjmglBUGY9OrVl717/2T//r8xGAxkZWVx+PAhYmOvA+Dh4UFU1DWzl9ejR2/Wrv2WqKhrZGRksHLlMrp374VWq+XBB7vz1197+OefY2RnZ/Ppp8tRlFvb4fbtW0lKSkKtVuPsXA0AtbpiXz9jVlGoVq2aadwjT09PLly4QEpKChkZGRZNTlQ92dkGtv90CgcnW7oP9EdRFLJ0eikIwqRmTW/mzfuAb775ggEDevLww/1ZvfprjMacbWT48Mf49ddf6NOnK4sX33uysP79B9G7dz8mTBjHI48MwtbWjsmTXwHA19ePl16axttvv85DD/WhWrVqeHp6mdru3/83I0cOo2fPzixZ8gEzZ87Fzs7eMiteRlTK7WWvAO+88w6tWrVi4MCBfPbZZ3z22WdotVo6derE3LlzyyLPQiUkpJk2iKLw9KxGXFyqBTIqn3GtGbsocc8cj8G9hiM1a7mUeezSVN7f55iYK3h71y/VuDJKavmT3/usVquoXt053+ebdUzh9ddfN/391FNP0bp1a9LT0+U0VVGqjvwdgT7bQLvODWQICyGspFhjBQQHF36UX4iiUhSFlOSbZOvk7CIhrMmsohAVFcXSpUs5ffr0XccRtm/fbpHERNWRlppFckIGXfo0wWhUpJcghBWZVRQmTZqEr68vEydOxN6+Yh9EEeWLwWBk58ZTJMalM/q/IdjZ21g7JSGqNLOKwsWLF/n+++9Rq806WUkIs+377SIxV1PoMchfCoIQ5YBZ3/Jdu3blwIEDls5FVDHhZ+I4fvAaLdrWonGA170bCCEszqyewhtvvMGjjz5KvXr18lwqDjlXOwtRVMmJGfy69Sxetapxf3c/a6cjhPiXWUXhtddeQ6PR4Ofnh52dnaVzEpVcti7nAjWNRkXvwQFoNLJbUuQMnb1gwSJ8fRuRmZnJ9OlTqFHDE4NBz5Ejh3Fzc+PmzZu4u3vw0END6dOnPwDR0VE8+ugQGjb0w2g0oNfrad06kCeffAYvr5pAzpXH3377NZcvX2LixJd4+OERprgREZd5//13uXEjGYAJEybTrt19Zb7+5YVZRWHfvn38+eefpvHFhSiJ+OtppN7IpPeQAJxd5MSFiubvkzGs/z2chJQsqrvYMbSLHx2ae9+7oZlSU1OZOnUSzZo1Z+LEl5g7921Gj37C9EV+/vxZ3nrrNZKTk3j00dEAODtX48svvwVyJgX76qvPGD/+P3z99fc4OzvTuHETZs6cy6pVX94Vb+7cWQwe/DB9+vQnMjKCiRPHs2bN+ip7Uo1ZP9GaNm1KcnKyhVMRVcH1qBRq1nZh9H9DqNvQ494NRLny98kYvvr5DAkpWQAkpGTx1c9n+PtkTKksPykpiYkTnyU4OIRJk17O9/Tkxo2bMmnSFFav/pr8BmSwsbHh6afH4+npxfbtWwHw9W1Ew4a++Z4sc+HCOUJC7gdyBrhzcXG55zDclZlZPYX77ruPp556iqFDh951TGHYsGElTiIrK4u5c+fy999/Y2dnR5s2bZg9e3aJlyvKl5TkTDasPkabkLqEPNDQ2umIO+w9Ec2e49GFPic86gb6O8ah0umNfLH1NH8ci0KlgvwGzunUyoeOLX3ufuAOb731KkOGDOepp54t9HkBAS1ISkokOTmpwOf4+zfn0qWL94zZtKk/O3du45FHHuPMmVNERFzJM2pqVWNWUTh8+DBeXl7s2bMnz/0qlapUisJ7772HnZ0d27dvR6VSER8fX+JlivJDo1GRka7DvboDXfs1pZ6v9BAqqjsLwr3uL6r77uvIL7/sYPDgh6lRw7OQZ5oTz7ycpk+fwUcfLWTr1s00aNCQVq3aoNEUa7CHSsGsNf/mm28slkB6ejobNmzg999/N3UVa9SoYbF4omzlTKup4qfVR+k50B//Vt4y4mk51bHlvX/Nv/LxXtOuo9tVd7Fj2qi2JR4cbtSox9m7909eeOFZPvpoRYGF4fTpU7i7e+Du7kF0dFSBz+ndu989Y9auXYd3311ouj169HAaNKi6PVmrn/YRGRmJm5sbS5cuZejQoYwZM4ZDhw5ZOy1RCm7Ns3yA8LNxrP3yMCrUaDQyjEVFNbSLH7bavF8btlo1Q7uU3mnFY8Y8Sd++A3jhhWeJj4+76/ELF87z4YcfMGrU4/m0zjnQ/PnnK4mLi6VXr773jJeUlGg6NrF162ZsbGwIDm5fspWowKzeRzIYDERGRhIQEMC0adP4559/GD9+PDt37jT7bKeChoA1h6dntWK3LQlrxS3L2BnpOn5affSueZaHjArE0cm2THLIJe/z3WJj1Wi1Rftd2Ll1LTQaFT/8Gk7CjUyqu9ozvKsf97e41cMo6jJvp9Hk5PSf/zyNSgUTJ47H29uHVau+YsuWjWRmZuLu7sETT/yHfv0GmNqkpaXy5JMjMRhunZL6ySdf4OaWM/z6jh3b+OijxaSmprBnz++sWvUVH374MQ0b+vLXX3/yzTdfolKpqF27DvPnL8TGpmhzgZdknS1NrVYXaTs0az4FS0pMTKRz586EhYWZdh/169eP+fPn07KleZNgy3wK5TN25s1s1Kj4afUx0zzLo54NKfNZ1OR9zp/Mp1DxY5ujqPMpWL28eXh4EBISwt69OaeAXbp0iYSEBOrXL92NVZQtg8HI1nVhbF57nMeeaY9fU0+rFAQhRNEUuPsoMjLSrAXUrVu3xEm8/fbbTJ8+nfnz56PValmwYAEuLqUz65awjgN/XOL6tRR6DQ5ApVYYMiqQzCydFAQhyrkCi0LPnj1RqVQoSt7x7e+8ffr06RInUbduXYue4STKXrOW3jg42uLXzBODQcHRyZb0jLvPWhFClC8FFoUzZ86Y/v7xxx/566+/eOGFF6hVqxZRUVEsW7aMDh06lEmSouJISsjg793hPNi3KW1CSt6LFEKULbPOPlqyZAk7duwwjQXSoEEDZs2aRe/evRk6dKhFExQVS3JiBolx6cU68C+EsD6zioLRaOTatWv4+d06FzkqKgqjsfwecRdlS1EUws/E4dvUk3q+HjLyqRAVlFlFYezYsTzxxBMMHToUb29vYmJiWL9+PU888YSl8xMVxMmj0fy54zxd+xtp1rL0RswUQpQts37OPf3008ydO5f4+Hh2795NXFwcc+fO5ZlnnrF0fqICuB6Vwt5dF6jn60HTFjWtnY6wMH3UadJ/eB1jRnKev0tq5cqPef/9W5N27d37J506BXPxYrjpvqlTJ7Nly4YCl3HkyCGeeeYJxo4dyahRw5g4cfxdezTeeus1BgzogV6vz3N/p07BZGRklHg9Kjqzr2h+4IEHeOCBByyZi6iAMm9ms2PDKZycbek+sFm+Qx2LykMfdZqb2xaBQU/m7hUYYsPBoEd3ZBP2nfIfdsJcbdsGs2jRAtPtY8eOEBDQgqNHD+Pr64fBYOD48WNMmjQl/9z0el5/fSoffbSCRo0aA3Du3Jk822RKyg0OHtxPvXr12bPndx58sHuJcq6MzCoKOp2OZcuWsWXLFpKTkzl8+DB79uzh8uXLjB492tI5inJKURR2bT5NRrqOIaMDsXewsXZKooQyNuc/va7jwNcAuLlzKeh1ABiizpA7Emn2hX3Yd3qcrDN/knX6jwLbF6Zly1ZER0eRmJiAh0d1jh07zJNPjmPr1s08/PAjnD9/FkdHJ+zs7Hnjjalcvx5DVlYWPXr05j//eZqMjAxu3szAw+PWKLxNmjTLE2PHjp+5//6OtG/fgdDQTVIU8mHW7qO5c+dy7tw53n//fVPVbdy4MWvWrLFocqJ8O7z3CpEXk+jUoxFePtYb40eUHW2DILB1AFTcGppahW3ggBIv287OHn//5hw9epiMjHRu3swkJKQDFy6cA+DIkcMEBgYxZ85bDBv2KJ988jWffbaKffv+Yv/+fbi4uDBo0BAefXQoU6e+yDfffMn163kn/wkN3US/foPo0qUbYWEn8h1wr6ozq6ewa9cuduzYgaOjo2nmopo1a3L9+nWLJifKL4PeSPjZeJo09yKgzb0nTxEVw71+0ds07oA+fB955ipQq1FScr5c7Zp1RtOoY7HjBwYGcfToYRwdnWjVqjUajYY6depy8WI4x44dJiTkfj788IM8M0FmZKRz+fIlgoLa89JL0xgxYhRHjhxi3769rFr1BZ9++g1169bj3LkzpKam0rZtMCqVigcf7MbPP29hzJgni51vZWRWUbCxscFgMOS5LzExETc3N0vkJMq5tNQsVMDQMYEAchyhCsnauwoM/x6g1diAYgSjgexLh7DvXPKzEdu2DeaDD97FycmZNm2CAGjdui2HDx/k+PFjPPvsBFQqFZ9++jVa7a2vr9sHpatduw61a9dh4MDBvPzyRPbu/YNHHx1NaOgm0tJSGT58EADZ2TocHJykKNzBrN1Hffr0Ydq0aabxkGJjY5k1axb9+/e3aHKifPo19Awbv/0HjVaNjW3RhhgWFZtD/1ew8X8Q7Kth33UcNk0fAPtqOPR4rlSW37x5S6Kjo/n99920bZtTFNq0CeTHH9fi7FwNP79GtG4dyKpVX5raXL8eQ0JCPBkZGRw4sM80N0JqairR0dfw8amNTqdj587tfPrpN6xbt5l16zazceN2VCr455+jpZJ7ZWFWT+HFF1/k/fffZ9CgQdy8eZPevXszfPhwnn/+eUvnJ8oZRVHo2KMRqTcyUaulh1DVqB3dsO/0uOlMIxvfdqXSQ8hlZ2dHQEBz4uPjTLOu+fs3Jz4+lq5dewDw1luz+fDDhTz++AgAHB2deOONGXh42LF+/VoWLVqAra0dBoOBXr360qVLV375ZQe1a9ehTp28Q6/06tWX0NBNtG6d0+sdOfJhU8/X3t6eNWvWl9q6VRRFnk8hMTERd3f3crXLQOZTsHxsjUaFXmfkt21n6dDNr8hnGlXEda6occ2NLfMpVPzY5rDIfArt29+ams7Dw8NUEGRAvKpBo1GhGGDnptN06tFYTj0VohIzqyhkZ2fne5+MfVT5aTQqVIqKNZ8eJPxsHOu/OYpWo5F5loWopAo9pjBy5EhUKhU6nY5Ro0bleSwmJobAwECLJiesT6PRsOX743fNszxwRCsMBv09WgshKppCi8Lw4cNRFIUTJ04wbNgw0/0qlYrq1atz3333WTxBYV2n/4miS+8mJCVkmOZZ7jesJfo7TlEWQlQOhRaFIUOGANC6des8w2aLqiEuJpVdm88Q0MaHUc+2Z+u6MPoNaynzLAtRiZl1Sqqfnx/x8fEcP36cpKQkbj9h6fYehKhc3Ko70qpdbdp2qIeCwsARrdAbDFIQhKjEzDrQvGvXLnr27MmHH37IjBkzWLVqFTNmzGDjxo2Wzk9YgdGYM9BdzNUbdOjqh529DQaDQpZOLwVBWFRKSgrdunVk8eL37/ncP/74jVOnwky3z5w5xdtvv1Hs2AcP7mfUqFs/ctPS0ujSJYQff1xruu/bb79h9uw3ix3DnKG981OWw3qbVRQWL17M3Llz2bBhAw4ODmzYsIFZs2bRokULS+cnrCDzZjbx19NIvZFp7VREFbNz5zaaN2/Brl3b8z3r8XZ//vkbp0+fNN1u1iyAGTPmFDt2q1atTaO0Ahw/foymTf05evSw6TnHjuUMylccuUN7T5v2Bl9++S2rV69jwoTJ5eqaLzBz91FUVBR9+/bNc9+QIUPo2LEj06ZNs0hiwjqir97AxdWeYWOD5LRTka9X98wiVZdmul3N1pl3O71VKssODd3Ec89N5JtvvuTPP3+nW7cexMXFsnjxe1y9mjPMTo8evWnSpBl79vzBoUMH2Lx5IyNHjqZGDS+WLVvCZ599w7vvzsbXtxGPPPIYABcvXmDatJdZu3YDGRnpfPTRIsLDz6PT6QgMDOaFF17Ezs6eZs0COHr0MN279+LYscMMGzaCzz//BCDPfA7Z2dmsXPkxx44dJjs7Gz+/Rrz88ms4OjqyY8c2fvhhDXp9TlF7/vnJBAe3v+fQ3p06BbNjxx84Ojrme7usmNVTqF69OvHx8QDUrl2bo0ePEhERIdcpVDKpNzL5eV0Yu0PPotWqy90vGGF5i48s5+/oQ4X+fXtBuP324iPL+evawXzbmuPChfOkpNwgKKgd/fsPJDR0EwCzZr1J8+Yt+eqr7/jqq+8YOHAIISEd6NTpAUaPfoIvv/yWfv3yDt3dt+9Atm3bYrodGrqZfv0GoFKp+OijRbRp05ZPPvmaL774lqSkRFOstm2DTT2Do0eP0LZtO+rWzRml9fz5szg5OVO7dh1Wr/4KJycnPvnka1at+p7q1T355psvAAgJuY+VK7/kiy++5e235/LOOzMBzBrauzwwq6cwfPhwDh8+TO/evRk7diyPP/44arWasWPHWjg9UVYMeiM7NpxCURQ692pk7XREFbRly0b69OmPSqWiS5euLFr0HjEx0YSFHWfRomWm55kzOnPr1m3IyMggPPwC9es3YNeu7axYkfOlvWfPH5w+fZLvvlsNQGZmJl5eOdPIBgYGsXDh/H/nc7hJjRo1aNOmLUePHiYrK8u062jv3j9IT0/nt992o1LlTESWO9vbtWtXmTnzdeLi4tBqtSQmJpCQEE/16jUKHdq7vDCrKIwbN8709+DBg2nfvj03b96U01Qrkb92hxMbnUrvIQG4eZRtd1WUH5Pbjr/n34W1zR0HqKhts7Oz2bVrGzY2tmzbFgrk7IPfunVzUdLPo0+f/mzdupnAwCAaNGiIt3fuvB8Kc+e+T+3ade5q06JFK6Kjo/ntt920bNkayBm6+7vvVqHTZdGlS7ecJSjw8suvEhTU7q6xj2bOfJ0JE17kgQcexGg00qNHJ3Q6nenxgob21mg0KErOcrKysoq93iVl1u6j//73v3lu16pVCz8/PyZMmGCRpETZOnfyOmFHomjdvg6+TT2tnY4o56rZOhd6uzj+/PN36tatz08/bTUNbb1o0VJ27PiZFi1asXbtt6bn5k6w4+TkRFpaWgFLhD59BrBr13a2bNlAv34DTfd37PgAq1Z9ZZojJjk5maioa8CtUVq//voLU6+gWTN/zp49zfHjx2jbNhiATp0e4PvvV5OVlXMyRu5EP5Bz1pKPTy0g5xhJbkEobGhvyCkWp0+fAnIOuFuLWT2F/fv353v/gQMHSjUZUfYS49P5fds5vOu4ENKlobXTERVAaR1Uvl1o6CZ69cp7MkuLFq0wGo385z/jWLv2W8aMeQS1WkPPnr0ZPXosvXv345133ubXX38xHWi+nbe3Nw0a+HL06GFmzpxrun/SpJf5+OMPGTv2MVQqFTY2tkyc+DK1auV8OQcGBvHFF58QGNgWAK1WS+3adbh6NdL0ZT969Fg++2wFTz/9+L+zUar4z3+eoUGDhkyc+BLTp0+hWrVqhITcj6ur67+RlQKH9gZ44YUXee+9uTg5OdOtW49Sf43NVejQ2UuWLAHg008/5emnn87zWGRkJBcuXGDDhg0WTdAcMnR28WMf2nOZsKNRDB8bhFM1uzKLW5bkfc6fDJ1d8WObo6hDZxfaU4iJyTkyriiK6e9cPj4+vPDCCyXJVViRoijEX08juFMDAtrUwtHZ1topCSHKgUKLwrx58wAIDAzkkUceKZOERNk4F3ad3aFnGTyqDT51Xe/dQAhRJZh1TOGRRx7h8uXLbNmyhdjYWLy8vBgwYAANGjSwcHrCEhRFwbeZJ1lZerzruFg7HSFEOWLW2Ue7d+9m6NChXLp0CVdXVy5dusTDDz/ML7/8UqrJLF26lKZNm3Lu3LlSXa7IodGoSEvNZOfG08RFp9IquI5coCaEyMOsnsKiRYv4+OOP88yfsH//fmbPnk337t1LJZGTJ09y7NgxateuXSrLE3nlzqC2cc0/dOndhMxM3b0bCSGqHLN6CjExMQQHB+e5Lygo6K6Dz8Wl0+mYNWsWM2fOLJXlibw0GhUq1KxeeYDws3Fs+PYY1T2rydhGQoi7mNVTaNasGZ9//nmeK5u/+OIL/P39SyWJJUuWMGjQIOrUufsKQ3MUdGqVOTw9qxW7bUmUZdyMdB0/rT5615SaQ0YF4uhUdmcdWeu1tmbs8rzOsbFqtFqzfhcWiSWWWZ7jWjv2vajV6iJth2YVhZkzZ/Lf//6Xr7/+Gh8fH6Kjo3FwcGD5cvMGuirM0aNHCQsLY8qUKcVehlynULibGdk8mM+UmplZOtIzyuZy+vJ+zn5limtubKPRWOzz68NfmoghJQWNiwt+Cz803V/Sc/ZTUlIYPLgvgwYNYfLkwr8T/vjjN2rUqEFAQAu0WjVhYWF8//23JRo++513ZtKsmT8PPzzC7DaldZ3ClCkTefHFqfkOv1ESRqPxrm2h2Ncp5PLz82Pr1q0cO3bMdPZR69atsbGxKXHCBw8eJDw83HRsIiYmhqeeeop58+bRqVOnEi+/qjMaFbb+cAKVCkY+056f18uUmqLkDCkpef4vLbfPp/D885MK/Y7588/faNbMn4CAnHldSjqfgqUZDAY0Gk2Bj7///ocFPlaWzCoKkHOpd3BwcJ7hso1G47+XeBffuHHj8uyW6tatG8uXL6dJkyYlWq7IoVaraBFUG1tbDagVhowKJDNLJwVB5Ctywbw8t106dsK1Y2cSt24hPewEmVcuo2RlgVoNRiOoVJx7eixoNDRZ8Rn65GQiP84Z0dTn2f+idXUjcsE86k59zaz41pxPobAv7IiIyyxZspAbN5LJzs7mkUceo3//QQC89dbrXLlymexsHbVr1+W1197CxcWFI0cOsWTJ+zRt6s+5c2d55pn/smjRAvr06c/Bg/tJSIjnscdGm3olw4YNZMGCRfj6NmLChHH4+zcnLOw48fHxdOvWg//+N+di4UuXLjJ37ttkZt6kceOmXL0ayRNPPEXHjp3Nf6MLYVZROHnyJLNmzeLs2bOm0fsURUGlUnH69OlSSUSUvnMnr5MUn0G7zg1Qq1UYDAqOTrZltstIVD5K7uiduT8Oc0fJ+XdwuZK4fT6FxMQEQkM30a1bD2bNepMOHTryzjvvATkD2Lm5udGp0wOmXT1arTrPWGx9+w5kyZL3TEUhv/kUXn31TYxGI2+//QahoZsYNGhIvnnp9XpmznyDGTPmUL9+AzIy0nnqqTG0aNGK+vUb8NJLU3B2zrkAdOXKj1m9+qs8X+CvvDKdFi1aAbBo0QIyMzNZseILoqOjePzxEfTtOzDfiXSuX49h2bJPyMjIYMSIhxgw4CHq1q3H7NlvMWLESHr37seZM6cYN25siV/725lVFF599VW6du3K3Llzsbe3L9UE7rR7926LLr8qiY1KJT624FEkhbhTQb/oPfoNwKPfANOxBJVWi6LXm/7XuORcBKl1c7trGeb2EsrDfAr5iYyM4MqVS8yYMd10X3Z2NpcvX6J+/QZs3RrKtm1b0euzuXkzM8/cCHXq1DUVhFw9evQCwMenFtWquRAXF0v9+g3uitu1a3fUajXOzs7Ur9+Qa9eu4uHhwaVL4fTs2QfI2WXm51e685+YVRSuXbvGiy++KBc6VRC6LD2x0al06tkIfbYBtVreN1E6cg8qn3t6LACKXk+TT78s8XLLy3wK+VEUBVdXN7788tu7Hvvnn6OsX/8D//vf57i7u7NjxzY2bVpvetzB4e4egK3trTP+1Go1BoM+37i2tnZ3PO9Wb8yS38VmHRDo2bMne/bssVgSovQoisKvW88SuvYEaSmZaG0K3k8qRHHl9gxy/y+p8jKfQn7q1auPvb29qVgBXLlymfT0NFJTU3F2dsbV1RWdTmea1tNSnJycadjQl507twNw9uwZLl4ML9UYZvUUsrKymDBhAkFBQdSoUSPPYwsWLCjVhETJHD90jYtn47mvqy/OLpbd1SeqrttPQy0N5Wk+hU8+Wc6qVV+Znj916nTmz1/Ehx9+wJo132AwGPHw8GDWrHe577772bnzZx57bCiurm60aRPIqVMnS/W1udMbb7zNvHmzWLXqC3x9G+Hr64ezc8knOspV6HwKuZYuXVrgY+Vh9jW5TiFH9NUbbPr2H+r7edB7aPN8u5iVbZ3Lc+zyvs4yn0LFjJ2RkYGDgwMqlYpLly7ywgvP8u23P+JSQK+tVOdTyFUevvhF4TLSdezccApnFzu69m8mx3+EqKTCwo6zbNkSIOeH8LRprxdYEIrD7OsULl68yJkzZ8jIyMhz/7Bhw0otGVE8RqPCrk2nyczUM3RMIHb2Zr+tQogKpn37+2jf/r57P7GYzPr2WL58OcuWLaNZs2Z5TklVqVRSFMqBxLh0rkel8ECvxtSoWXr7FoUQVY9ZReGrr77ihx9+oFmzZpbORxRRYlw6Hp5OjBzX3qJzLAshqgazTkm1t7fH19fX0rmIIsq8mc2G1cfYs+uCFAQhRKkwqyhMmjSJOXPmEBsbi9FozPNPWIeiKNg72NCxRyNatyvdURWFEFWX2cNcAPzwww+m+2TsI+v6Y8d5HBxsaNe5gZxpJCqFYcMGYmtri42NLZmZN2nY0JdRo56gZcvWJVpm7iBzxRkWuyoyqyiU9lzMovg0GhXZWUZiIlOo38hDCoKwimtXktgdepZu/ZtSu757qS13zpz5+PrmjOXz+++7eeWVSXzwwVKaN29RajFE4cwqCjJvcvmg0ahQDLBr82keHhOIjb0WM649FKJUXbuSxNYfwtDrjWz9IYx+w1uUamHI1aVLN06dOsmaNd/g4OCQ51f+7b/6d+zYxrp135GdnTPv+PPPTyY4uL3ZcU6fPsnixe+TmXkTe3sHJk+egr9/cwB+/nkLa9Z8g0qlolatOkydOh13dw+2bt3Mjh0/Y2dn9+9AddV5881ZeHp6ceLEPyxatACjUUGv1/PEE/8xDWBXEZh9Qvsvv/zCwYMHSUpKyvNFJMNclA2NRoVKUfHtpwdIjE8nKSGDUc+GyGQ5olRtXH2swMeatvSmmqsdm747nnvdFHq9kU3fHad6DSfs7LWoVCrT90PTlt40a+XNxtXHeGhUm2LlExDQgr17/zB9SecnJOQ++vbti8GgEBFxmUmTnuOnn7aatfzs7Gxef30q06fPIDi4PQcP7uf116fy/fcbiIy8wvLlS/nss1XUqFGDTz75H4sWvcesWTlzThw//g9ffrkaX19fVq5czpIl7zNnzgJWr/6Kxx4bQ8+efVAUpdDxmcojsw40L126lBkzZmA0Gtm2bRtubm7s2bOnVK+iE4XTaDRs/THsrnmWtYVMDCJEadsdetZUEEwUSE7MyPf5JXfvHzzXrl1l0qTnGT36Ed56azqJiQkkJMSbtfSIiCvY2NiYehbt2oVgY2NDRMQVjhw5RIcOHU3jvT300FAOHbo1Z0OrVq2pV68BAAMHDubw4UMAtG0bzFdffc6XX37KqVMnqVbNevN0F4dZPYUff/yRzz//nCZNmrB+/XqmT5/OgAED+Pjjjy2dn/jXyaPX6JLPPMv6UpjcRIhc9/pFX83VzrTrKJdWqzbtQspvHKDi9hIATp8+RcOGfmg0mjzjm+l0tyaKmjnzdSZNeomOHbtgNBrp0aMTOp2u2DFL6pFHRtKx4wMcPLifxYsX0K7dfYwb95zV8ikqs3oKKSkppukxbWxsyM7OplWrVhw8eNCiyYlbanhX40xYNKOebY9fU0/ZdSSsonZ9d/oNb4FWm/PVcXtBKG1//vkbGzas49FHR1O7dl3OnMkZfTQ+Pp4jRw6bnpeWlmYa4TQ0dFORCkK9evXJzs7myJGcX/mHDx9Er9dTr1592rYN5u+/95p6HZs3b6Bdu1vHKk6c+IfIyAhT3KCgYCCn91G7dh0GD36Y4cMf4/Rpy46aWtrM6inUq1eP8+fP07hxYxo3bsyaNWtwcXHB1dXV0vlVeRnpOvbsvEDH7n60bl8XBYWBI1qhNxikIAiryC0Mljj76I03pplOSW3QoCHvvbeE5s1bUKdOHd54YxqjRw+nbt16BATcOsYwceJLTJ36EtWqVSMk5P5Cv5fyGxb7nXcW5DnQPGfOfGxsbPD1bcT48RN48cXn/z3QXJtXXrk1+1rLlq1ZtmwxV69Gmg40A6xb9x1HjhzGxkaLjY0tL774Sqm9PmXBrKGzf//9dxwdHWnXrh3Hjx/n5ZdfJiMjgxkzZtCrV6+yyLNQlXno7MhLiezadIaBj7YqlXGNKsI6V5bY5X2dZejs4tu6dTN//fUnc+YssOqw3eawyNDZXbp0Mf3dqlUrdu7cWYIUhbkiLiZSp4E7o/8bgo2tHFAWQlieWccURNm7fD6e0LUnOHHoqhQEIcqZfv0GMmdO5TwdX4pCOZSSfJNftpylRk1nmreVCweFEGVHikI5o9cb2f7TKQB6DwkwneUhhCXIFfGVW3He3wK/cebPn2/6+++//y5eRqLI9uy8QPz1NLoPbIaLm4O10xGVmFZrS3p6ihSGSkpRFNLTU9BqbYvUrsADzWvXrmXatGkAPP/88xw5cqRkGYp7OnMihtP/RBPYoS4NGlW3djqiknN39yQpKY60tORSW6ZarbbKkPrWimvt2Pei1dri7u5ZtDYFPdCsWTMmTpyIn58fOp2OJUuW5Pu8SZMmFS1LkS9FUTh5JIpa9dxo37mhtdMRVYBGo6VGDZ9SXaac/lvxFVgUPvzwQ77//nuioqIAiImJKbOkqpqsTD3ZOgODRrZGn21ErZbhsIUQ1lFgUahevTrPPZczXofBYGDevHllllRV8+fO80RdSeaxce1xcLSxdjpCiCrMrIvX5s2bx40bN/j111+5fv06NWvW5MEHH8TNzc3C6VV+iqIQdH996jb0kOsRhBBWZ9b5jkePHqVnz5589913nD17lu+++45evXpx9OhRS+dXqUVFJLNpzXHs7LU0bVHT2ukIIYR5PYW5c+cyY8YM+vfvb7pv69atzJkzhx9//LFECSQlJTF16lQiIiKwtbWlfv36zJo1Cw8PjxItt7zLSNOxc+NpbOw0ci2CEKLcMOvb6PLly/Tt2zfPfb179yYiIqLECahUKp5++mm2b9/O5s2bqVu3Lu+//36Jl1teaTQqMtKz2P/7RXRZenoPDsDWzuwJ8IQQwqLMKgr169cnNDQ0z33btm2jbt26JU7Azc2NkJAQ0+02bdqYzniqbDQaFSrU/LT6GPd3bUSvIc2p7lXykU+FEKK0mPUTdfr06YwfP55vvvmGWrVqce3aNa5cucLy5ctLNRmj0ciaNWvo1q1bqS63PMgtCKtX7Jc5loUQ5ZZZ8ykA3Lhxg99++43Y2Fi8vLzo0qVLqZ999Pbbb3P9+nWWLl2KWl259rNnpOv4afVRws/Gme7za+rJkFGBODoV7TJ0IYSwFLOLgqXNnz+fs2fPsnz5cmxti/YlWREm2dFoVKgUFatXHjDNsWyNnoJccVr541ozdlWLa+3YxVXYJDvl4uf4woULCQsLY9myZUUuCBXFnzsvcC0ymVHPhsgcy0KIcsvqp72cP3+eFStW0KBBAx599FEA6tSpw7Jly6ycWenRZemJvJSERqumVj1XhowKJDNLJwVBCFHuWL0oNG7cmLNnz1o7DYtJjEvH1l7L0McD0WjUGAwKjk62pGdkWTs1IYS4i9m7j65du2bJPCqlrEw9P/8Yxs/rwtBq1TLQnRCi3DO7KAwZMgSAr7/+2mLJVCaKorA79AxpKVl07tUIlUoKghCi/Ct099HQoUNp3rw5/v7+GAwGAJYuXcrjjz9eJslVZMf2R3L5fAIdu/vhXdvV2ukIIYRZCu0pLFmyhI4dOxIVFUVmZiZDhgxBp9Oxb98+UlMr1ilYZSkqIpn9v1/Cr5knLYNrWzsdIYQwW6FFwWg00qdPH6ZMmYKTkxMff/wxiqKwatUqHnroIXr16lVWeVYY6WlZ7Nh4Cld3Bx7s20R2GwkhKpRCdx9NmTKF6Oho/Pz8yMrK4saNG9jZ2bF06VIAkpOTyyLHCuXC6bicWdQebS0D3QkhKpxCv7V++OEH9Ho9586dY+TIkcyePZv09HRmzJhB8+bNCQgIkIl2bpOUkEHrdnVo2LgGLm721k5HCCGK7J5nH2m1WgICArCxsWH16tU4ODgQEhLC5cuXK/UQ10UVcTGR7z45yOXz8VIQhBAVltn7N1577TUgZ/6Dfv360a9fP4slVRHVqutK+84NqNuwck8OJISo3My+TmHo0KEA7Nq1y2LJVETZ2QY2rfmHmGspBHWsj0ZmURNCVGBF/gZzdZVz7nMpisKfO85z7UoyBoPR2ukIIUSJyc/aEjh9PIazJ64T1LE+9f2qWzsdIYQoMSkKxaDRqFCj4uSRa9Rt6E5wx/rWTkkIIUqFnEhfRBqNChQV234K46FHA1FpkIHuhBCVhvQUiiBnnmUV3648QPjZOH5afRQHB9ucQiGEEJWAFIUi0Go0bF0XRmJ8OgCJ8elsXXcCrUZj5cyEEKJ0SFEogqsRSfQY6I9HDScAPGo40W9YS/T/jiArhBAVnRxTKILwM3EcjLvMqHHt2fpjGP2GtZR5loUQlYoUBTMYDEZio1K570FfsjL1KCqFgSNaoTcYpCAIISoV2X1khv2/XWLD6mMkxKVjZ6/FYFDI0umlIAghKh0pCvcQfiaOfw5epUXbWlT3dLJ2OkIIYVFSFAqRnJjBr1vP4uVTjfu7+Vk7HSGEsDgpCgXIzjaw/adTaDQqeg0OkIHuhBBVgnzT5UNRFP7Yfp7EuHS6D/SnmqvMjyCEqBqkKOQj9UYmF8/GEdyxPvV8ZX4EIUTVIaek3iH1RibOLvaMeCoYZxfpIQghqhbpKdwmO9vAxm//YfeWM7i4OchAd0KIKkd6CrexsdHQvnMDXD0crJ2KEEJYhRSFfx35OwKdTk/IAw1RqaSHIISommT3EXD1chIH/rhE6o0sa6cihBBWVeWLQlpqFjs3ncbNw5EH+zSRXoIQokpTKYpi9QF8Ll26xKuvvkpycjJubm7Mnz+fBg0amN0+ISENo9H81bCx0eCADp1iw88bThJ+Np6Hn2iLe417D2NhY6PB3piJIUuHytYOta2G1EzzCsmtttmobG2L1NaasStiXGvGlnWuGHGtGbt04hZvG4Gc2SKrV3fO/7EiLclCZsyYwciRI9m+fTsjR47krbfeslgsGxsNahsdNw1aNv0Qxv3dGtN3aENq1TKvIKDNxJCVybHxz6PoMsnISsLB1ry4t9o+V6S21oxdEeNaM7asc8WIa83YpRe36NuIOax+oDkhIYFTp07xxRdfADBgwABmz55NYmIiHh6lf+GYAzpuZmpZtfIgifHpJCVkMPqZYG5GXuLX1YvxcXHmQFo2DaL0ODvbsS3ISIezmdSKvEmjF1/Cwaka6TduAJAUFYmLkwtp6WfY+uvnNM62IeFCLFqDHXrFFb02EaOXLT4uzjQYOBYXrSOpKTltU65G4FTNlbT0Mxz/cCGOBvixhzst4xWaHEsm2k7L3tb30+VmPKpzJ+n0/CvYOjqTfiM5J3Z0JC6u1cm8cZ4zn3/E+mAHU57xdooph03dnZjX5Ukcbip52lZzdCHz5nn2Lv4StLHovBzxcXHmZMoNfKN0OFSzZ2X7unxw30jsjSpT2/SICBzq1iEj4zoH3/iADJs0LrTwo1NmIgkXYnHUq3A0QLydwv3T3sKpmhupkZEApEZG4FSnDjcTIjk7ezaxdqAYndEYHfi9q9607vF2Ch3emoWzrTPpEZGmuHaurtxURXJm/XJTnrFu/mwP0tP5bBoBV6KJt1Nw1KtoN3kaWm9PkqKumdo71qmF1pjO3tcmm/KMtYMLtfyJrd6FRtc/xzdKx33TZ6ByqUbK1at5YmdnhjP32Mo8eSb6u3Nd1Z1GpzbiYFDTcdKLqB3sSUm9YVpnBxdXjJrrTPv7M/qcvm56j3Jz+K6nF9obzZjxwP2o7e1ISk+5K+5vH33ApVqNaeys4nryBdN7lPu+O12zI2jSfwrcPr/4I5QEVVfuO/EJLnqD6T3Kfd/N2T5X9GpM9WQfHjr4NzdsdST6u9M424bGvcbkiZtyNQKX2nVIjDnP6ffeM+Xpf94er6t69NpEUw41Z0/Hx9ad9KvXTDm7+9Qm9cqtuLfneftn0/elZ/HGmfTYWNPrZe/qSrRDBOvW/0Dnw2dN71F+n80Hpr6Gk4v7XdtnRtI1/przMWhvbc93fjYfmDkLZ61dvtvnp1tOYZv4C02vZeDqrL7rs9np+anYOjqRlHEjT9sMx+ucXf0hcRfiTJ+LOz+bw4ZPxM7NnaTkeNNn2d27Nlp1NjexKfkXJOWgKERHR1OzZk00/05pqdFo8PLyIjo62uyiUFA3KD9pyemE/ph3Ss3Q9acYOLQZqEClVqFS/ftPDahu/bN1cCRs2uumZV2ZNR8A/3mzQJ3TFnKeq+bW3yq1Cgcbe8Km3mp7cc6CW21vi8FtMTUaNWqNCgXQ2ttzYtr0W7Hfzond/N3ZqG5vn9uL/DcHlUqFjd7IidvzNrWdg1qlwnhbnrnLUP17W6vRcuKVaaa25+f+m/fCuaa4KrUqz7rn5mCj0nJs/AumtuHv5LQNeO8d03NUKhVqlSrvugM2eiPHJt5qmxs34L138uSp1qj+fc/uWHc7G46Pn3hX+9aL59+Vp1qtwsZWc+s+Rcm3bYt5c+7KEzVotepb+djZ5NlGcte55cL3c45X3ZFn7t8ajRq1vT1ht73HuXFbzpuds2y1CrUm73t0+9+2Dk4Fbp8qtSrnV+YdcYuyfarUKjQa9a3jbv9u83d+LnLbNl0wO0+eKhU57/VtOTgrWv55blKenK/cEff2PG//bDorWo6/OOWu18t3ybu3tpHb8sxdTu5n00alzn/7XDg/z+civ8+m1qjK0/b27VNroza91/l9Nu/8LOf5TP2bZ+7n4s7PptbenuMvvnLr9Xo75/UKXP4xnj6l8yPa6scUwsLCmDZtGqGhoab7+vXrx3vvvUfz5s3NWkZRjik4a41kGTWmnoJHDSdGj2uHvUZPanbhcy07qfUoukySoiO58vZ86s+YhrtPHdR29qQZCq/SJWlrzdgVsW1FzVvWWV4vS69zrnJ9TMHHx4fr169j+HeeY4PBQGxsLD4+PhaJp9KqQHWD0ePa4dfUk9Hj2mHMvIqq8HoAgNpWQ5ZWh7t3bQDcfeqQoYtHbXPvl7Ekba0ZuyK2rah5yzrL62XJtuayek8BYMyYMQwbNoyHHnqIjRs3sm7dOr755huz2xf17CMHW7BVDOiwQUs2Kg2kZ2vNmknNwRZsDNnos7JR29mgtlEXua0hKxtVEdtaM3ZFjCvrXDXWuSp/poq7jUDhPYVyURTCw8N59dVXSUlJwcXFhfnz5+Pr62t2+6IWhVyentWIi0stcruSslZca8aWda4asataXGvHLq7CioLVDzQD+Pn58cMPP1g7DSGEqPKsfkxBCCFE+SFFQQghhIkUBSGEECbl4phCSZVkMhxrTaRjzQl8ZJ0rf1xrxq5qca0duzgKy7dcnH0khBCifJDdR0IIIUykKAghhDCRoiCEEMJEioIQQggTKQpCCCFMpCgIIYQwkaIghBDCRIqCEEIIEykKQgghTKpkUbh06RIjRoygd+/ejBgxgsuXL5dJ3KSkJJ555hl69+7NwIEDmTBhAomJiWUSO9fSpUtp2rQp586dK5N4WVlZzJgxg169ejFw4EDefPPNMokL8OuvvzJ48GAeeughBg0axI4dOywSZ/78+XTr1u2u17UstrP8YpfFdlbQOuey5HZWUGxLb2sFxS2r7azMKFXQmDFjlA0bNiiKoigbNmxQxowZUyZxk5KSlH379pluv/vuu8prr71WJrEVRVHCwsKUp556Sunataty9uzZMok5e/Zs5Z133lGMRqOiKIoSFxdXJnGNRqMSHBxsWs/Tp08rbdq0UQwGQ6nHOnjwoBIVFXXX61oW21l+sctiOytonRXF8ttZQbEtva3lF7cst7OyUuV6CgkJCZw6dYoBAwYAMGDAAE6dOlUmv9jd3NwICQkx3W7Tpg1RUVEWjwug0+mYNWsWM2fOLJN4AOnp6WzYsIFJkyahUuUMwFWjRo0yi69Wq0lNzZkRKzU1FS8vL9Tq0t/kg4OD75pTvKy2s/xil8V2ll9cKJvtLL/YZbGtFbTOZbWdlZVKMUpqUURHR1OzZk00Gg0AGo0GLy8voqOj8fDwKLM8jEYja9asoVu3bmUSb8mSJQwaNIg6deqUSTyAyMhI3NzcWLp0Kfv378fJyYlJkyYRHBxs8dgqlYrFixfz3HPP4ejoSHp6OitXrrR43FyynZXddgbW29asvZ1ZQsUtZxXc7NmzcXR0ZPTo0RaPdfToUcLCwhg5cqTFY93OYDAQGRlJQEAA69evZ8qUKbzwwgukpaVZPLZer2fFihV8/PHH/Prrr/zvf/9j8uTJpKenWzx2eVIVtjOw3rZWGbezKlcUfHx8uH79OgaDAcjZmGJjY/PtFlrK/PnzuXLlCosXLy6TbubBgwcJDw+ne/fudOvWjZiYGJ566in27Nlj0bg+Pj5otVrTLpTWrVvj7u7OpUuXLBoX4PTp08TGxhIUFARAUFAQDg4OhIeHWzw2yHZWltsZWG9bs/Z2ZglVrihUr14df39/tmzZAsCWLVvw9/cvsy79woULCQsLY9myZdja2pZJzHHjxrFnzx52797N7t278fb25rPPPqNTp04Wjevh4UFISAh79+4Fcs7GSUhIoH79+haNC+Dt7U1MTAwXL14EIDw8nISEBOrVq2fx2CDbWVluZ2C9bc3a25klVMlJdsLDw3n11VdJSUnBxcWF+fPn4+vra/G458+fZ8CAATRo0AB7e3sA6tSpw7Jlyywe+3bdunVj+fLlNGnSxOKxIiMjmT59OsnJyWi1WiZPnkyXLl0sHhdg06ZNfPLJJ6YDjxMnTqRHjx6lHmfOnDns2LGD+Ph43N3dcXNzIzQ0tEy2s/xiL1682OLbWUHrfDtLbWcFxbb0tlZQ3LLazspKlSwKQggh8lfldh8JIYQomBQFIYQQJlIUhBBCmEhREEIIYSJFQQghhIkUBSFu079/f/bv32+1+FFRUQQGBpouehOirElREFXSsGHDuHTpEpGRkQwZMsR0f2hoqGkwuY8++ogpU6ZYNI9u3brx119/mW7XqlWLo0ePmsZMEqKsSVEQVU52djZRUVE0aNCAsLAwAgICLBJHr9dbZLlCWJIUBVHlnD9/Hj8/P1Qq1V1FIfeX+x9//MGKFSv4+eefCQwMZNCgQUDO0MjTp0+nU6dOdO7cmUWLFpl29axfv55HH32UuXPnEhISwkcffURERASPP/44ISEhhISE8PLLL5OSkgLAK6+8QlRUFOPHjycwMJBPPvmEq1ev0rRpU1NBuX79OuPHj6d9+/b07NmTtWvXmnL96KOPmDRpElOnTiUwMJD+/ftz4sSJsnoZRWVl3ekchCg769atU4KCgpRWrVopLVq0UIKCghR/f3+lTZs2SlBQkBIREaF07dpV2bt3r6IoivLhhx8qL7/8cp5lPPfcc8qbb76ppKenK/Hx8crDDz+srFmzRlEURfnxxx8Vf39/5euvv1ays7OVmzdvKpcvX1b27NmjZGVlKQkJCcrIkSOVOXPmmJZ3ezxFUZTIyEilSZMmSnZ2tqIoijJy5EhlxowZSmZmpnLq1CklJCRE+euvv0z5tWjRQvntt98UvV6vvP/++8rw4cMt+hqKyk96CqLKePjhhzl06BDNmzdn7dq1bNq0icaNG3PkyBEOHTpE3bp1C20fHx/P77//zvTp03F0dKR69eqMHTs2z5g/Xl5ejBkzBq1Wi729PfXr16djx47Y2tri4eHBk08+ycGDB83KNzo6miNHjjBlyhTs7Ozw9/dn+PDhbNy40fScoKAgunTpgkaj4aGHHuLMmTPFe3GE+FeVm2RHVE3Jycn06NEDRVHIyMhgzJgx6HQ6ANq1a8eECRMYO3ZsocuIiopCr9fnGfXTaDTmGQ7b29s7T5v4+HjeeecdDh06RHp6Ooqi4OLiYlbOsbGxuLq64uzsbLqvVq1ahIWFmW7fPruYvb09WVlZ6PV6tFr5aIvikS1HVAlubm4cOnSI0NBQ9u/fz6xZs3j++ecZNWoU999/f75tcke9zOXt7Y2trS379u0r8Ev3zjYLFy5EpVKxefNm3Nzc2LVrF7NmzTIrZy8vL27cuEFaWpqpMOTO6CaEpcjuI1Gl3H5g+fTp0zRv3rzA51avXp1r165hNBqBnC/pjh078u6775KWlobRaCQiIoIDBw4UuIz09HQcHR2pVq0a169f59NPP83zeI0aNYiMjMy3rY+PD4GBgSxcuJCsrCzOnDnDunXrTAe9hbAEKQqiSjl58iQBAQEkJSWhVqtxdXUt8Ll9+vQBICQkxHQtw4IFC8jOzqZfv360a9eOiRMnEhcXV+AyJkyYwKlTpwgODmbcuHH06tUrz+Pjxo3jf//7H8HBwXz22Wd3tV+4cCHXrl2jc+fOTJgwgRdeeKHAno0QpUHmUxBCCGEiPQUhhBAmUhSEEEKYSFEQQghhIkVBCCGEiRQFIYQQJlIUhBBCmEhREEIIYSJFQQghhIkUBSGEECb/B2XP7+Fqf7AjAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_result(results, 'human_effort', 'cost', 1.0) \n",
"plot_result(results, 'num_true_matches', 'gain', 1.0) \n",
"\n",
"plot_result(results, 'a-tp', '# of annotated matches', 1.0) \n",
"plot_result(results, 'p-tp', '# of predicted matches', 1.0) "
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "7c199827",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r\n",
"\r\n",
"************* KDD19 *************************\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "2ee83ff16f5a4c708bd79dce79eb4b07",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/2000 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r\n",
"\r\n",
"************* WeSAL *************************\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "1ff093413f284beba8b3ed52eb49d19e",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/2000 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r\n",
"\r\n",
"************* ActiveWeaSul *************************\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "dda3e7ff2c854822bddb472a281ba2a3",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/2000 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r\n",
"\r\n",
"************* ActiveLearning *************************\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "3abb6c2d2c68447287c000e0b2e66567",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/2000 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r\n",
"\r\n",
"************* DualLoops *************************\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "2694d7c1ee39455fba0ef6e4b4f48f15",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/2000 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAmQAAAFCCAYAAABfDMEKAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/MnkTPAAAACXBIWXMAAAsTAAALEwEAmpwYAABhsElEQVR4nO3dd3hUVfrA8e+dmk5IgYQiCAqEXoKooCiCIkXdFQVRWKxYKIqICCwIAkqRIiBg+Ykrim1dFAICigVZRTCwShURqQHSID1T7v39ETIQSJtkaub9PA8PmXbmPTNzJ2/OOfc9iqZpGkIIIYQQwmt03g5ACCGEECLQSUImhBBCCOFlkpAJIYQQQniZJGRCCCGEEF4mCZkQQgghhJdJQiaEEEII4WWSkAkhhBBCeJnB2wG4QmZmLqrqvnJq0dFhpKfnuK19XxbIfYfA7n8g9x0Cu/+B3HcI7P5L393bd51OoXbt0FJvqxEJmapqbk3Iip8jUAVy3yGw+x/IfYfA7n8g9x0Cu//Sd++QKUshhBBCCC+ThEwIIYQQwstqxJTlpex2G5mZqdhsFpe0d+aMDlVVXdKWv/HVvhsMJmrXjkWvr5EfYSGEEAGmRv42y8xMJSgohNDQOBRFqXZ7BoMOm833khJP8MW+a5pGbm4WmZmpxMTEezscIYQQotpq5JSlzWYhNDTCJcmY8D2KohAaGuGyEVAhhBDC22pkQgZIMlbDyfsrhBCiJqmRU5ZCCCGEtwQHGwgyVrF8gqZBZf7g1DSw28BgdPycmVdjx1gCgrx7fq5bt0SOHz/mkrYGDOjP9u3bXNKWEEIEouBgA2adDc1ud/6fzYqmqpW7X0EuuXt+QNE0x88RQYFbP6wmkITMj4wY8Rhr1qz2dhhCCCHKEKRYUDR7Ff+plb5f3u8/k/H9hxQe30/KB9PI2rUJPXZvd19Ug0xZCiGEEC6SmaejdpiuUrOOpdJUUCoeKwlr0x1jVDynPpoJQP1H5pJPEGCr4hMLb5MRMg8YMKA/H3zwL/7xj0H07NmNl1+eRkZGOs8+O4pevW5k9OgnycrKAmD37t94/PGH6N37Jv7xj/tITt4BwPLlS/j1113Mnz+bXr1uYN68WY72d+zYxqBBf6N375t49dVZaFrRsLWqqqxY8RZ3392Pfv168dJLk8nJubBP15dfJnH33f3o0+cW3n337RIx7927m4cfHkKPHjfQv/+tLFo0z90vkxBC+L3gYAOapqKqVfhnt6FqVO5+hfmkbXzH8bzZ//sGE1Yv9lxUlyRkHvLtt5uZP38Jq1Z9xtatWxg7dhTDhz/J2rWb0DSVTz/9kNTUM4wb9zT/+MdDrFu3mREjRjNp0vNkZmYyfPhTtG3bnmeeGcemTVsYM+Z5R9v//e8PvPnmv1ix4kO++WYT27b9CMC6dWtYv34tr722jI8//pz8/Hzmzy9K5A4f/pNXX32Ff/5zGqtXrycr6xypqWccbS5c+Cr33DOIzZu38NFHq7n55l6efcGEEMIPeXLKUjEYqP/wXCI696Xg+H6ZsvRzkpB5yIABA4mKiiY2tg7t2rWnZcvWNGvWArPZzI033sTBgwfYsGEd1113Pddd1w2dTkfnztfSokUCP/20tdy2779/GOHh4cTFxdGhQyIHD/4OwKZNXzJw4P3Ur9+AkJAQHn/8Kb76aiM2m41vv/2a66/vRvv2HTGZTDzyyBMlSkkYDAZOnDjO2bOZhISE0Lp1G7e+PkIIURNk5umKNqjWcP4fSqXvF9qyG/GDp6CPrEvk9X8n7t4XyNPMnuuocDlZQ+YhtWtHOX42m4Muu5yXl8+pU6f45puv2bp1i+M2m81Ghw6J5bYdHR3t+DkoKIj8/DwA0tJSiYu7UMm+bt147HY7mZkZpKWlUqdOnOO24OBgatWq5bg8fvw/eeutZQwceDfx8fV48MFH6dr1hir0XAghAsu5Ak/+arUD+ot+Fv5KEjIfUrduXW67rQ/PPz+p1NudLYYaExPLqVMpjsunT59Cr9dTu3YU0dExHDly2HFbQUEB586dc1xu2PAKpk6diU4HX3/9Ff/85/MkJX1NcHCwk70SQojAouZnYT+xF329FuhCIr0djvATMmXpQ2699Xa2bt3Ctm0/YrfbKSwsJDl5B2fOnAYgKiqKkydPVLq9nj1v4+OPP+DkyRPk5eXxxhtLuOWWWzEYDNx00y38978/8L//7cJqtfLWW8scJwMAbNiwjszMTHQ6HWFh4QDodFIdXwghKqKeTaFg8zLUzJPeDkX4EUnIfEjdunG8/PKrvPfeO/Tr14u77+7LqlXvFa1HAO655z6++eZreve+mQUL5lTYXt++d3DbbX0YMeIx7r33DkwmM08//RwATZo0ZcyY55k6dSJ33tmb8PBwYmPrOB67bduPDBlyLzff3JWFC1/lxRdnYjYHuafjQgghRIBTtIuHRfxUenqOI2kBOHXqCHFxjVzWvsGgw2ZTXdaeP/Hlvrv6fS5NbGw4qanZbn0OXxXIfYfA7n8g9x2q339bygHy17xMcN9xGOq3dGFk7hfI770n+q7TKURHh5V+m1ufWQghhAg0/j/OIbxAEjIhhBDCHapcrl8EIknIhBBCCBdSgsMxNLkGJSjC26EIPyJlL4QQQggX0teuT3DPJ70dhvAzMkImhBBCuJBmt6LmnUWzy0bfovIkIRNCCCFcyH76D3JXPo399B/eDkX4EUnIhBBCCFeSsyxFFUhCJoQQQriDnGUpnCCL+i/y455TfPbdIdKzComOMPP37k25rlVcxQ+shAED+jN79nyaNLmKgoICJkwYS0xMLHa7jeTkX4iMjCQ/P5/ataO4886/07t3XwBSUk4yaNDfuPLKpqiqHZvNRrt2HXjwwUepU6cuULTN0Qcf/Iu//jrMqFFjuPvugY7nPXr0L+bOfYVz584CMGLE03TufK1L+iSEEEII15CE7Lwf95zi3fX7sZyvSp+eVci76/cDcEO7ei57nuzsbMaNG02LFq0YNWoMM2dO5YEH/uFIog4ePMDkyS9w9mwmgwY9AEBYWBgrVnwAgNVq5d133+bxxx/iX//6iLCwMK6+uhkvvjiTlStXXPZ8M2dO46677qZ3774cO3aUUaMeZ9WqzwgKkm2QhBBCCF8REAnZ1t9S+OHXlHLvc+jkOWz2kvP+FpvKO+v2seV/J8tcEtCtbTxd28RXKo7MzExeemky3bp15+GHh5d6n6uvbs7o0WOZMeNFBg68/7LbjUYjjzzyONu3b2PDhnXcffe9NGlyFQA63eUz0H/88TtdulwPQMOGVxAREcFPP23lpptuqVTMQgghnKTTowRHoOj03o5E+BFZQ3bepclYRddXxeTJ4+na9cYyk7FiLVu2JjMzg7NnM8u8T0JCKw4f/rPC52zePIFNm74EYP/+vRw9eoRTp8pPToUQQlSdIb45YUNeQ1/3Km+HIvxIQIyQdW1T8SjWc69vJT2r8LLroyPMTBia6JINtq+9titff72Ru+66m5iY2HLuWZkksHKJ4oQJU1i0aB7r1q2hceMradu2PXp9QLztQgghhN+QEbLz/t69KSZDyZfDZNDx9+5NXfYc998/lD59+jNy5HDS0lLLvN++fXupXTuK2rWjyr1PkyYVx1a/fgNeeWUeK1Z8wIsvziA9PY3Gja+sUvxCCCEqZj91kNyPxmNP/cvboQg/4pGhkszMTMaNG8fRo0cxmUw0atSIadOmERUVRfPmzWnWrJlj/dPs2bNp3ry5J8IqofhsSnedZVlsyJAH0TSNkSOHs2jR8stu/+OPg7z22qvcf//QUh9vtVp57713SE09w6233l7h82VmZhAZWRtFUVi3bg1Go5HExGuq3Q8h/I3ZrMdoLPrKq0wxgoJ8C+FhZjStqHqBVsnHlcUV7XiqjeK++0Isnmrn4jYq0//y2uGq1tS6aj5UMR5vvi6X9t2Vr211uaKd8trIySqgVrDCuXzv1JHzSEKmKAqPPPIIXbp0AWDWrFnMnTuXmTNnAvDhhx8SGhrqiVDKdV2rOJcnYKUZOvQhR1IWFxfPypU/s2bN5xQUFFC7dm0eeGAYt9/ez3H/nJwchg0bjN1uc5S9WLr0bcLCwgDYtOlLXn/9NbKzs9iy5TtWrnyXefMWc+WVTfjhh+95//13AYX69Rswc+ZcFKmNIwKM2azHoDegnV95UNmvW03TUBTFcVJPVb+mXdGOr7QhsVTczsUNONtWTXtdLm2jqlzRTnltWAptJH36G30HtCE4WCE/3/PbXima5vmSwhs2bGDVqlWsWLGC5s2bk5ycXK2ELD09B1W90I1Tp44QF9fIFaECYDDoXLKGzB/5ct9d/T6XJjY2nNTUbLc+h6+qKX0vTsac5fjlWk2uaMdX2pBYJBZPt+GJWCyFNlYu30ZGWi5RMaE8MLwLISbVLSNlOp1CdHRYqbd5fHW3qqqsWrWKHj16OK4bMmQIdrudG2+8kZEjR2IymZxq89LOnTmjw2Bw7fI4V7fnT3y17zqdjtjYcLc/jyeew1fVhL7nZBVgt1fhjwoNUFzwheyKdnylDYlFYvF0Gx6IJenT38hIywUgIy2XpE9/485B7YiN9Wy9To+PkE2dOpXTp0+zePFidDodKSkpxMfHk5OTw3PPPUezZs145plnnGpTRsjcx5f7LiNk7lVT+i4jZK5rQ2KRWDzdhidi8ZURMo8OfcyaNYsjR46wYMECxyL++PiichRhYWHcc889JCcnezIkIUQNV1hox2Z3fj1I0VqT6n8hu6IdX2lDYpFYPN2GJ2IxmQ08MLwLTZvH8sDwLhhM3lnY77Epy3nz5rF7927eeOMNx5TkuXPnMJvNBAUFYbPZ2LBhAwkJCZ4KSQgRIAoL7Xyz+Xdu7d8SFGfOFlNcdMabK9rxlTYkFomlam1UjyvaKbuNoGADdw5qh0lnq9lnWR48eJDly5fTuHFjBg0aBECDBg145JFHmDx5MoqiYLPZ6NChA6NHj/ZESEKIANO8TRxnTmcTEla5Nao1Zcq2KgK571D9/tszjmPd8xWmdn3RRZRXBNz3ONN3TVU5+NhDRN/5N6L73+nmyNzP2597jyRkV199NQcOHCj1tjVr1ngiBCFEgDuXkQdRIZVOyISoKi0nA+u+bzE2vwH8LCFzhma1AqAYZPcXV5BX0QPeeON1srLOMXbsCwBs3bqF559/hn/96yNHtf1x457mxhtvol+/u0ptIzl5B0uXLsJqtWK1WoiOjmHBgtdLbCg+efILJCdvZ/XqLzFcdIB065bIxo3fExIS4r5OCuHjNq7eS4drryC6u+xUIdzt8imvUMWKvspVxTynMC2diMpOCwYpdHprGZrNhqZYydWMbo2tppOE7CK2k/so3LqS4L7PoZ5NcfxMRNlbGFVGx46JzJ8/23F5165kWrZszc6dv9CkSVPsdju//rqL0aPHlh6XzcbEieNYtGg5V111NQC//76/xBkjWVnn2L59G1dc0YgffviOm266pVoxC1EjSU1k4VEXPnCa1YJa6YXp1a3R78p2ym/Dkp7O7klTaL9sCRgkIasOScjOs53cR/6X88Fuo2DzcuxnDoHdhiX5C0w3DatW223atCUl5SQZGelERUWza9cvPPjgY6xbt4a7776XgwcPEBISitkcxKRJ4zh9+hSFhYX07HkbQ4c+RF5eHvn5eURFXUgMmzVrUeI5Nm5cz/XXd+Waa64jKekLSciEuISmST4mPOVC4uUYGTPWrGRF01TUgkJsOTkAWNPSCIvR0IxmGSmrooBJyPLWvFzq9SH9i6YR8zctBpsFAPvJ/RQfUNY/foKbhmE9sAXr7z+U+fjymM1BJCS0YufOX7juuq7k5xfQpct1vPbaqwAkJ/9Chw6dmD59MsOGPUL79h2xWq2MHv0ECQkt6dz5Wu64428MGvR32rfvSJs27bj11t7UrXthm6ekpC8YMeIZWrVqw4IFc0lLSyUmpuauXRBCCH9Q00fGiu05/7OMlFVdwCRkFTE07oTt8HawFHDhrxsFU4d+5T2s0jp06MTOnb8QEhJK27bt0Ov1NGjQkD//PMSuXb/Qpcv1vPbaq5w9e9bxmLy8XP766y86d76WMWOeZ+DA+0lO3sFPP21l5cp3eOut92jY8Ap+/30/2dnZdOyYiKIo3HRTD9avX8uQIQ+6JHYhagzZx1V4gK52A8zdhqKEx6AYTej8YO2Ys8xxdemweCH5x4+z/5U5tJo+FXNMNJrRVPUNOANcwCRkFY1kGa++DtuhnyjxSdLp0LJSi25vfkPRGTNV1LFjIq+++gqhoWG0b98JgHbtOvLLL9v59dddDB8+AkVReOutf5VYkH+x+vUbUL9+A/r3v4tnnx3F1q3fM2jQAyQlfUFOTjb33HMHAFarheDgUEnIhDivuCCkpGPCE3ThMZhaFm0PmHv+V0pwbgb6Sm8L6B8jZYpejyGsqOq8MSaGHEOoJGPVEDAJWUUKt66E4mreeiNoKqh2rId3wM3VT2xatWpDSkoK3323mXvuKarF1r59B2bMmEpYWDhNm15Fu3YdWLlyBcOGPQLA6dOnMBgMBAeHsHv3r3Tu3AVFUcjOziYl5QTx8fWxWCxs2rSBt956jwYNGjqe7777/s7//reTdu06VDt2IWoMyciEB6i5mdhTDmBo0BolqChh0YWF19iRso7LFsvImAtIQnZecN/nsCR/gfXP7QR1G4r9xF6sh3cQ3PNJl7RvNptp2bJVibVdCQmtSEs7w8039wRg8uSXeO21eQwdOhCAkJBQXnhhMsHBwXz22cfMnz8bk8mM3W7n1ltvp3v3m/n6643Ur9+gRDIGcOutt5OU9IUjIRs8+G7HWZlBQUGsWvWZS/olhL+496FOBIdKDTLhfmraXxRsXkbI315Efz4hSzt0FOvpU0Rc19XL0ZWvSsVRDUgy5gIe31zcHWRzcffx5b7L5uLuVZP6rmkafx5IIyo2lNrRlavHV5P676xA7jtUv/+2v3aSv3FhUUIW2xiAMx9+QNbWLVy1aKmLonSPQH7vPdF3n9lcXAghvEFVNTau3sufB1K9HYoIILXrxBOhWIhQLFx13wDaz5tDhGLxdljCR0lCJoSo8XQ6hXsf6kRCu3hvhyICgHZ+/k61WFEtlvP/Ckl+YgSqRRIyUTpZQyaEqPE0Dc5m5KPT6wiRdWTCzaKvbAXD33BcVi0WClPTAChMTSUsFnQmE1mafBbFBZKQCSFqPNWusnH1Xrp0v5La113h7XBEDadarBdd0kh+YqTj0p7JUwHouHQxGCUhExdIQiaEqPEcpZ6l7IXwAN0l9cY6Ll1MYWoqeyZPpdW0KZhjY4vu4/en1AlXkoRMCFHzyS8+4UHnrKAW5FDLfCExM8fGnP8/lhxjmHwmxWVkUb8QInDIEJnwANux38j51xgUgwGdyXT+n5mOSxdfNnomRDFJyDwkKyuLHj26smDB3Arv+/3337J3727H5f379zJ16qQqP/f27du4//4Bjss5OTl0796Ff//7Y8d1H3zwHi+99M8qP0dy8g4effQfDBs2mPvvH8CoUY+jqhXXL+vWLZG8vLwqP68QlSFbJwnP0tA0+OXRxzm6eQtZWtEC/hxjmCzkF2WSKcuLjP9hGtmWHMflcFMYr3Sb7JK2N236klatWvPVVxt46qnRGI3GMu+7Zcu3tGiRQMuWrQFo0aIlU6ZMr/Jzt23bjpSUk2RkpBMVFc2vv+6iefMEdu78hbvvvheAXbt+4cYbb6pS+zabjYkTx7Fo0XKuuupqAH7/fb9jZwAhhAg45/8eVcr5rhfiYgGTkC1IXkaX+ESui08s8+eLkzHAcfnV7a9zTVzpj3264+OVev6kpC948slRvPfeCrZs+Y4ePXqSmnqGBQvmcPz4MQB69ryNZs1a8MMP37Njx8+sWfM5AwcOpm7dOJYsWcjbb7/HK6+8RJMmV3HvvfcB8Oeff/D888/y8cerycvLZdGi+Rw6dBCLxUKHDomMHPkMZnMQLVq0ZOfOX7jlllvZtesXBgwYyP/935sA2O12fv11F6NHj8VqtfLGG6+za9cvWCxWrr76asaMGU9ISAgbN37JJ5+swmYrOoPoqaeeJjHxGvLy8sjPzyMqKsrR32bNWjh+7tYtkY0bvyckJKTUy0K4W/F+JPI3gm8KVazofWhRVWFaOhHV+aw0aUv0qDdoqKloNhuaYiVXk8RMlC9gEjJv+uOPg2RlnaNTp85kZKSTlPQFPXr0ZNq0f3LddV2ZMWMOAGfPniUyMpJu3W6kRYsE7r67aE/L5OQdjrZuv70/CxfOcSRkSUlr6NOnH4qisGjRfNq378j48f9EVVWmTp1EUtIX3HHH3+jYMdGRkO3cmcy9997Ppk1f8uefh7BYCgkNDaN+/QasWPEWoaGhvPnmvwBYtmwR7733DsOHP0WXLtfSq9dtKIrC0aN/MXr0k/znP+uIiIjgjjv+xqBBf6d9+460adOOW2/tTd26cR5+pYUondGk596HOhESJtNFvkizWlCrtYufRvUnpF3RRsl2LOnp7J40hfbLloBBEjJRvoBJyC4eySrr57I82/lJx36Ozj4WYO3az+nduy+KotC9+83Mnz+HU6dS2L37V+bPX+K4X2RkZIVttWvXnry8PA4d+oNGjRrz1VcbWL78HQB++OF79u3bw4cfvg9AQUEBderUBaBDh07MmzeLvLxc8vPziYmJoX37juzc+QuFhYV06NAJgK1bvyc3N5dvv90MgNVqcUxDnjhxnBdfnEhqaioGg4GMjHTS09OIjo5hzJjnGTjwfpKTd/DTT1tZufId3nrrPRo2lJpPwvs0TeNsRj4Go55gGZj1GY6RsRo2radpKmpBIbacolkWa1oaYTEamtEsI2WiTAGTkFVGuCnssjVk1WW1Wvnqqy8xGk18+WUSULTmat26NVVus3fvvqxbt4YOHTrRuPGVxMUVbwejMXPmXOrXb3DZY1q3bktKSgrffruZNm3aAdCuXUc+/HAlFksh3bv3KGpBg2efHU+nTp2BkpuLv/jiREaMeIYbb7wJVVXp2bMblou2AalfvwH16zegf/+7ePbZUWzd+j2DBj2AXq9H04raKCwsrHK/hagqq8XOxtV76dqzKW0TLz8+hHfU9JGxYnvO/ywjZaI8kpBdxFUL+C+2Zct3NGzYiKVL33Zct3v3r0yfPoXWrdvy8ccfMHjwUODClGVoaCg5OTllNUnv3v0YPnwYJ04co0+f/o7ru3a9kZUr32Xs2PHo9XrOnj1LXl4u9erVx2w207JlK/71r3d46KHHAGjRIoEDB/aRnZ3FM8+MA6Bbtxv56KP3ad26DWZzELm5uaSknKJx4yvJyckhPr4eULQmrjgZy8vLY/fuX+ncuQuKopCdnU1Kygni4+sDRYnavn17SUy8hk2bvnThqytE5ZjMhvNTlmZvhyIuohhN6Hxo7ZirmOPq0mHxQvKPH2f/K3NoNX0q5phoNKMUgxVlk4TMzZKSvuDWW28vcV3r1m1RVZWHHnqMjz/+gCFD7kWn09Or12088MAwbrutDzNmTOWbb752LOq/WFxcHI0bN2Hnzl948cWZjutHj36W119/jWHD7kNRFIxGE6NGPUu9ekWJUYcOnXjnnTfp0KEjAAaDgfr1G3D8+DFHovXAA8N4++3lPPLIUHQ6HYqi8OCDj9K48ZWMGjWGCRPGEh4eTpcu11OrVq3zz6zx2WcfM3/+bEwmM3a7nVtvvZ3u3W8GYOTIZ5gzZyahoWH06NHTHS+zEOXS1IunLGWEwlcUT9+F2HLR1bCRMkWvxxBWNMtijIkhxxAqyZgol6Jp1ToKfEJ6eg6qeqEbp04dIS6ukcvav3jaLtD4ct9d/T6XJjY2nNTUbLc+h6+qSX3Py7Xw7qIfuaHXVbTuVL9Sj6lJ/XeWp/selH8OU0iwx57PU7Tisyz9aO2YfO7d23edTiE6uvTlUDJCJoQIHFL2wif99dGn5O3ZTZM5870dClD9X8zWQz9T8PXrhAyYgT6qvoyMiUqRSv1CiJrP8QtRMjJfpFltKIYaOD4gHzfhhBp4BAghREna+YysOoVhIxRLxXeqIapdGNVJEY89iGqxoFMsNWRrIRkSE86ThEwIUfO54PejaqluQuYrC89dX+ah+m1oJD8xko5LF4OxJiRkxWSITFSeJGRCiBqvOB+rygiZY2TMVJMSBd+hWiwUpqYBUJiaSlgs6Ewmvx4pMzRsS8i9M9GFx3o7FOFHJCETQtR81VhDJiNj7oylaGSs2J7JUwH8fqRMMQWjN9W8s0aFe0lC5iFZWVncddft3HHH33j66bHl3vf7778lJiaGli1bA7B//14++ugDpkyZXuXnnzHjxRL7Y3rS2LGjeOaZcaXuICCEJwSHGrn3oU6EhjtfGFYnI2Nu1XHpYgpTU9kzeSqtpk3BHBtb9Jr78TIs+5k/sR74HlOnu9CFRHo7HOEnJCG7xKExo7BnZaGPiKDpvNdc1u6mTV/SqlVrvvpqA089NRpjOXu3bdnyLS1aJDgSshYtWlYrGXM3u92OXq8v8/a5c133OgpRFer5wrBGk4GgYOfqQWVpJux5udQyqlRvZMhXRrl8b6TMHBsDgDk2lhxjmF8nYwBq1hms+77F1OY2kIRMVJIkZJewZ2WV+N9VkpK+4MknR/HeeyvYsuU7evToSWrqGRYsmMPx48cA6NnzNpo1a8EPP3zPjh0/s2bN545K/UuWLOTtt9/jlVdeokmTq7j33vsA+PPPP3j++Wf5+OPV5OXlsmjRfA4dOojFYqFDh0RGjnym3GTp6NG/WLhwHufOncVqtXLvvffRt+8dAEydOoljx45gsVioX78hL7wwmYiICJKTd7Bw4VyaN0/g998P8OijTzB//mx69+7L9u3bSE9P4777HnCMxg0Y0J/Zs+fTpMlVjBjxGAkJrdi9+1fS0tLo0aMnT5yfsjh8+E9mzpxKQUE+V1/dnOPHj/GPfzxM1643uPS9EIGnIM/KxtV7uen2ZkRExlf8gEtoVhtKsBlFJ5WC3KXj0sV+PzJ2QY3ohPCwgEnIjs1+ucTliK7dqNX1BjLWrSV3928UHPkLrbAQdDpQVVAUfn9kGOj1tHz7HWznzpKyfCkA8cOfwFArkmOzX6bhuBcqfO4//jhIVtY5OnXqTEZGOklJX9CjR0+mTfsn113XlRkz5gAX9rLs1u3GEtOLyck7HG3dfnt/Fi6c40jIkpLW0KdPPxRFYdGi+bRv35Hx4/+JqqpMnTqJpKQvuOOOv5Ual81m48UXJzFlynQaNWpMXl4uDz88hNat29KoUWNGjx5LTEwUNpvKG2+8zvvvv1sieXruuQm0bt0WgPnzZ1NQUMDy5e+QknKSoUMHcvvt/QkJCbnseU+fPsWSJW+Sl5fHwIF30q/fnTRseAUvvTSZgQMHc9ttfdi/fy+PPTaswtdWiMoICTNVecoSQLNZ+eXR0dQd9hC1ut3o4uh8j1eqtdfIfR7lLEtReR5JyDIzMxk3bhxHjx7FZDLRqFEjpk2bRlRUFLt27WLy5MkUFhZSv3595syZQ3R0tCfCKkErLCz6QT2/TVDxjlJ2e7XbXrv2c3r37ouiKHTvfjPz58/h1KkUdu/+lfnzlzjuFxkZWWFb7dq1Jy8vj0OH/qBRo8Z89dUGli9/B4Affvieffv28OGH7wNQUFBAnTp1y2zr2LGjHDlymClTJjius1qt/PXXYRo1asyXX65l06YvsVqt5OcX0LDhFY77NWjQ0JGMFevZ81YA4uPrER4eQWrqGRo1anzZ89588y3odDrCwsJo1OhKTpw4TlRUFIcPH6JXr95A0TRt06ZXVfh6+KqaULPK07Wo3Mmi2jmdmU1UkEZESOV+65fof0wEUW8tK9oGR7H6zTY4wkv8f0dC4QUeScgUReGRRx6hS5cuAMyaNYu5c+cyffp0nnvuOV5++WUSExN5/fXXmTt3Li+//HIFLTqvrJGsqD79iOrTz7F2TDEY0Gw2x//6iAgADLUiL2ujMqNjVquVr776EqPRxJdfJgFFI1Pr1q2pcl969+7LunVr6NChE40bX0lcXPEUjMbMmXMrvXhe0zRq1YpkxYoPLrvtf//byerV/+bNN1cQHl6LjRu/5IsvPnPcHhx8+ciX6aLFzzqdDrvdVurzmkzmS+53IelVqlO504c4d2aer6wL8r21Ra6KJedsIZ//53du792Y1q2c/YOvqA1Lejq7J02h/bIlYJCETFRCzfg6Ex7ikYQsMjLSkYwBtG/fnlWrVrF7927MZjOJiYkADBo0iFtuucUtCVlFihfw//7IMAA0m41mb62odrtbtnxHw4aNWLr0bcd1u3f/yvTpU2jdui0ff/wBgwcPBS5MWYaGhpKTk1Nmm71792P48GGcOHGMPn36O67v2vVGVq58l7Fjx6PX6zl79ix5ebnUq1f6ZspXXNGIoKAgvvwyid69+wJw5MhfxMTEkJ2dTWhoGLVq1aKgwEJS0hfVfi3KExoaxpVXNmHTpg3cemtvDhzYz59/HnLrc7qD1KzyTYqxaORbZzA4fdakpqmoBYXYzh+T1rQ0wmI0v9owWniWvk4TzN2GogSFezsU4UecSsjeeecdrr32WhISEti1axdPP/00Op2OV199lQ4dOlSqDVVVWbVqFT169CAlJYV69eo5bouKikJVVUdiUlmX7px+5owOg6Fqi2/1EbWwZ51DH1GrRBtVbW/dui/o3btPice3b98eTdN49NHH+fDD9xk6dCA6nY5bb72doUOH0adPP156aQrffvs19933AHXrxqEoF2Jo0KAeV17ZhJ07k5k+/WXH9WPGPMfixQt58MHBKIqC0Wjk6afHcsUVDVEUhbfeWsbKle864njhhUnMnbuQBQvmsmrVe6iqSlRUFDNmzKJbt65s2rSee++9i1q1ImnfviN79+7BYNCh1+tKxON47fQlX/eLLxf/rCgKer3iuP7iy1OmvMSMGVN5//0VNG16FU2bXkWtWuFlvvY6nY7YWPd/4TnzHPknU5xo2VdGkmruyFix4hFLzW5zYvSy5MhYsT3nf+70xlJi60a5IFbf5Iljy5dVq/+x4XDV1a4LxsMC+b33Zt8VTav8ZHf37t1Zu3Yt4eHhDBkyhFtuuYXQ0FA+/vhjPvnkk0q1MXXqVE6fPs3ixYvZtGkT//73v3njjTcct7dr147vvvvOqYQsPT0HVb3QjVOnjhAX16jSj6+IwaDDZlNd1p4/8WTf8/LyCA4ORlEUDh/+k5Ejh/PBB/8m4vy08aVc/T6XxtnFzTVh7VhNlJGRz5vLd9Gv/1W0au1c9fTiEbL848fZ/8ocWk2fijkmukaPkHllUb8PqW7/1exU7KcPYbiiHYqfFYgN5PfeE33X6ZTLBpGKOTVClp2dTXh4ODk5ORw4cIAVK1ag1+uZNWtWpR4/a9Ysjhw5wrJly9DpdMTHx3Py5EnH7RkZGeh0OqeSMVFz7N79K0uWLKT4VKvnn59YZjLmq7I0E6rF4mRi5isjSzV3pEy1WIsuOTVCdqENRa/HEFb0JWqMiSHHEFoDzwgUrmJP+Z2Cb98kdNBsv0vIhPc4lZDFx8eTnJzMH3/8QWJiInq9npycnHLrXBWbN28eu3fv5o033nAs/m7dujUFBQXs2LGDxMREPvzwQ3r37l21ngi/d80113LNNdd6O4xqK/jzEJEJTZAVvb5DMRadOFKVNWTFzHF16bhsMVqNLM8ghPA2pxKycePGMWrUKEwmE6+9VrQI/ptvvqFNmzblPu7gwYMsX76cxo0bM2jQIAAaNGjAkiVLmD17NlOmTClR9kIIf6bZbOx4eDgNx08k2M/XkdSUqYscreiM33yMld60utT+G5BkTAjhFk4lZN27d+eHH34ocV3v3r0rHNW6+uqrOXDgQKm3dezYkTVrql4CQghfo9mKfvkrUhrBZ0TUCuLehzoRFhHk7VBEQJCsXTjP6bIXhw4d4ssvvyQ9PZ3Jkydz9OhRrFYrLVq0cEd8Qnjcxeu/qlIcNaJDK+LObwOTJd/LPsFuVzmbkY85yIg5KGA2KBFeJ8sWROU5Vcth/fr13H///Zw+fZrVq1cDRWfGvfLKK+6ITQivUC2WSv4rLPO25CdGVGHxuHCXnKxCNq7ey+mTrt2jVojSKGExGJpcA8aqbdUlApNTfyq+9tprrFixghYtWrB+/XoAWrRowf79+90SnBCe5IqirqrFQmFqKgCFqamExXJ+pEwKxXpTRO1gmbIUHmOo1wJDPZk1Es5xKiHLyMigefPmwIUtbhRFqTHb3QCcOJLJ5qQD9OjbnPqNarus3QED+mMymTAaTRQU5HPllU24//5/0KZNu2q1OXv2fJo0uYoZM14ssSG5cJ6zBUNLk/zECMfPeyZPBaDj0sVFGycLr7Hbzk9ZBsuUpXA/zVaIZslHCYpA0VWtqLgIPE59Ulq1asXnn39e4rqkpCTatm1bxiP8y4kjmaz7ZDc5WYWs+2Q3J45kurT96dNn8e67q/joo9Xcfns/nntuNHv27Hbpc4iq05lMlfxnLvO2jksX02paUSX3VtOm0PH8WjLhXdnnCti4ei9nZMpSeIDtj23krnwaLc+1v0NEzebUn4oTJ07k4Ycf5tNPPyUvL4+HH36Yw4cP83//93/uis9lPn9/V5m3NW8TR3gtM198+Kvj5BibTeWLD38lOiaUoGAjF29o0LxNHC3axvH5+7u48/72VYqne/ce7N27h1Wr3iM4OLjE6NbFo10bN37JJ5+swmYrKmz51FNPk5h4TaWfZ9++PSxYMJeCgnyCgoJ5+umxJCS0AmD9+rWsWvUeiqJQr14Dxo2bQO3aUaxbt4aNG9djNps5ceI4UVHR/POf04iNrcNvv/2P+fNno6oaNpuNf/zjIXr1qhm147I0E9bUVGpHVraQY+kjZebYWMf/OcYwOeHKp9Sc0XwhRM3iVELWtGlT1q9fzzfffMNNN91EfHw8N910E6Ghoe6Kz2M2Jx24/BenBmcz8oirX8stz9myZWu2bv3ekSCVpkuXa+nV6zYUReHo0b8YPfpJ/vOfdZVq32q1MnHiOCZMmEJi4jVs376NiRPH8dFHqzl27AjLli3m7bdXEhMTw5tvLmX+/DlMm1a0sfuvv/6PFSvep0mTJrzxxjIWLpzL9Omzef/9d7nvviH06tUbTdPK3QTdHxljY9G5YPsjx8iYJGM+ofgPqhq0ukL4ME0OfFEFTi+mCA4Opk+fPu6Ixa0qGskKr2Vm3Se7S+zbaDDo6HNPaxo1jS51P8eqjo5dUPFBe+LEcV58cSKpqakYDAYyMtJJT08jOjqmwscePXoEo9HoGFHr3LkLRqORo0ePsHPnDq67risxMUXt3Hnn3xk2bLDjsW3btuOKKxoD0L//XQwdWlTQt2PHRN599/84ceI4nTtfS6tWrZ3ttE+znDrFn9t+pNYN3TFGRVW9OKpUcxdCCOEEpxKyY8eOsWDBAvbt20deXl6J27799ltXxuVx9RvVps89rR1JWXEy5sqF/Zfat28vV17ZFL1eX2JzdIul0PHziy9OZMSIZ7jxxptQVZWePbth8WI5hXvvHUzXrjeyffs2FiyYTefO1/LYY096LR5Xs5xKIWPN54S164AxKsrb4QhXkxEyIYSPciohGzt2LA0bNuT5558nOLjmbZhanJS54yzLS23Z8i2rV3/Kq68uJjl5B/v37wEgLS2N5ORfaNu2PQA5OTnEx9cDICnpC6eSsSuuaITVaiU5eQcdOybyyy/bsdlsXHFFIxQF3ntvhWO0bc2a1XTufGFt2m+//Y9jx45y5ZWNSUr6gk6dEoGiUbcrrmhE/foNCAkJYf36tS55PXxFvQ4tiVu6CJ3JLEVdawizWc+VV8UwZmovbBY7Kip2u7y5wn0UgwklOAIUOcNSVJ5TCdnBgwdZtWoVuhp8Gm/9RrUZ8qR7NrieNOl5R9mLxo2vZM6chbRq1ZoGDRowadLzPPDAPTRseAUtW15YUzZq1BgmTBhLeHg4XbpcT61aZa9ne/PNZaxc+a7j8rhxE5gxY3aJRf3Tp8/CaDTSpMlVPP74CJ555qnzi/rr89xzExyPbdOmHUuWLOD48WOORf0An376IcnJv2A0GjAaTTzzzHNueKW8R7VYSX5ipJSqqCHMZj0GvQFroZ28XAtfJ+2n7z1tQC9JmXAf41XXYbzqOm+HIfyMol18+mAFhg8fzsiRI2nd2rfWDaWn55SY8jt16ghxcY1c1r7BoCt1DVlNtW7dGv773y1Mnz7bp/vuyvc5QrE4irrumTyVVtOmYI6NRWc2kaUGZmLm75uLFydjNqudnOxCPlu5k4y0XKJiQnng8S6oWvlJmb/3vzoCue8Q2P2Xvru37zqdQnR0WKm3VThCtnDhQsfP9evX55FHHqFXr16OxeDFRo8eXc0whfCe4u2OiklRV/+noMNuVzmXmc/3mw6SkZYLQEZaLkmf/Eb/gW2x221ejlLURNZDP2PZ8RnB/V9AF+Kes/RFzVNhQnbq1KkSl2+++WZsNttl14uao0+f/vTp09/bYXhUcVHX0kbI8M0BQlEBDRWD3kCt2sHcfHtzMtPzHCNkfe9pg81u93aIoobSLHmo506BJl8eovIqTMhefvllT8Thcpqm1agtnURJTsy0V0qWZgKjibDYonaLi7rGRodDgA7f+7vCQjs2vUqQ2URYuJkBQzs61pBVNF0pRLW4+PtJBAanVuevXr36so3E9+/fz+rVq10ZU7UZDCZyc7Nc/ktb+AZN08jNzcJgcO1UoqZpKEaTbHdUg2RnFbLxi70YzXrCagVx533tJBkTniODAsIJTp1luXDhwsuSr7i4OJ544gnuuusuF4ZVPbVrx5KZmUpOzlmXtKfT6VDVwBx69tW+GwwmateOdWmbiqKQjRmMZinqWkOodpVfdxwnKjaEhHbx3g5HBAz5AhHOcyohy8nJISys5NkB4eHhZGX51oa9er2BmBjXffnKWSeB0Xe1sJCMpDWEtu9AcJOm3g5HuEDxGcJ6fc0t1SOEqBmc3styw4YNJbZO2rRpE02byi8v4bsiKrs3ZZBCrb/3Q7PZ0BQruZrRvYGJKgkONqDX6ytVdD801MyYF3thKbSBTpOpSuERxqZd0NdrgRIU7u1QhB9xulL/Y489xvr162nYsCFHjx7lxx9/5I033nBXfEJUm1rq7gYape2jY0lPZ/ekKbRftgQMkpD5muBgAzpFj6ZWPCmkaRp2m3qhIOwAKQgrPEMxh6I3h3o7DOFnnBrHT0xMZO3atbRp04b8/Hzatm3L2rVr6dSpk7viE6LKIhQLEYoFnclUyj9zicuK0YBmt2PLyQHAmpZGmC0H67lzXu6FKFacjFVGcTKWk13Ip/9K5tCBVFYu34YOHXq9LLQW7mU7uZ+CLSvQLPneDkX4EadGyN5++20efvhhHnvssRLXv/POOzz44IMuDUyI6qrKyFixPed/7vTGUtDVvH1b/ZGmKtgrWxROo/SCsJ9KQVjhfmrmCaz7vsWU+HcU5PtDVI5TI2RLliwp9fqlS5e6JBghXKkyI2PF/8xxdemweCEtxhftzdlq+lQ6LluMPsjs5V6IYopOQ6/XVeqfTq84CsJGxRRNHUXFhNJ3gBSEFZ4g0+LCeZUaIfvxxx8BUFWVn376qUR9r+PHjxMaKnPlwvdkaSYsp04RVeq+YZePlCl6PYbzZxEbY2LIMYQSW0sKw/qK/HwblsICateu+PtGURT0Bl3JgrAD2qAia8iEEL6pUgnZxIkTASgsLGTChAmO6xVFITY2lkmTJrknOiGqSbNZ0ZmMlDZNWRpzXF06LluMZjTJH7k+qLDAxtG/MmjUJKoS76iCTqcn3BDEHYPaYbXZJBkTniEfM1EFlUrINm/eDMC4ceOYPXu2WwMSwpUUk5l9C18nqt8dla8tZkC+UH1UaLiZkFCN7OwC2RpN+D75jAonOLWGTJIx4W9MdepQf9QzUui1hjj8expvzN1CRmqut0MRokz6ei0wdxuKYpA1qKLynK7Uv2jRIrZv305mZmaJtWTffvutq2MTotrCKUS1FJW+yMa1X45Gow6zuahWWXX+Dta0oj+kSz//03ttFORbCA9z/jVzZ3/aJTagVbt65OdXstivEF6gj2qAPqqBt8MQfsapEbIXX3yRvXv38uSTT3L27FkmTZpEfHw8w4YNc1N4QlSPZrGw88mRaFbX/gI3GnWYjMaiAqUqqFX8Z7draFrRz1Vtx1fa8EQshfk2vvjwf5iMBoKDnfp7UgiPUc+ewvrHT2h2q7dDEX7EqYRs69atvPbaa/Ts2RO9Xk/Pnj1ZsGABn3/+ubviE6JKwhULYdYcCtPSAChMTSPMmkN4ZbdRKkdxMlZdmqZVex2Ur7ThiVgshTZWLt/mKPJqs2iSlAmfZDv+GwWbl4G10NuhCD/i1LeZqqqEhxftzRUSEkJ2djaxsbEcOXLELcEJUVWaxULyEyMcl/dMngpAx6WLwWiqVtt6nR67vZIFSsujAUo1zx7wlTY8EEvSp79dVuT1jkHtqvd8QriDJmcFCec5lZC1aNGC7du3c91115GYmMiLL75IaGgojRs3dlN4QlSNYjLRceliClNT2TN5Kq2mTcEcG4tiqn45C7tqlxEyL8TSd0AbVi7fRkZarqPIq6KTX3zCh8lZlsIJTk1ZTp8+nfr16wNFtcmCgoLIysqSsy+Fz8nWTOQYwzDFRANgjo0lxxhGtla90TEAq1XFYrWWOKmlKhRFqTFteCIWk9nAA8O70LR5LA8M74LBpJCfL1sgCV8kfygI5zk1QtawYUPHz9HR0cyYMcPlAQnhSoqio8OS11wyMnYxq1Xl67W7uf1vbVB01TnLUnHBWYm+0ob7YwkKNnDnoHag0yQZE0LUKE6viN2xYwd79+4lLy+vxPWPP/64y4ISwlX2L16GmpfHFRMnu7ztv/5IZ+2nv3Jzn+Yub9sXxMaGkyrbRgnhNF2tOAxNrgGdnHQiKs+pT8tLL73E+vXrSUxMxGy+UJ+oMutGZs2axYYNGzhx4gRr1qyhWbNmAPTo0QOTyeRob+zYsdxwww3OhCVEmRSDAV1IiFvattuKNrsWQoiLGa5oh+EKOeFEOMephGzNmjWsWbOGunXrOv1Et9xyC0OHDuX++++/7LbXXnvNkaCJwBEcbECv1zs1reXsdFiLF56vVjvlFUd9cvxNqHYVm90ueyQKIRw0ayGaNR8lOAJFkT/aROU49UmJi4vDZKraoujExETi4+Or9FhR8wQHG9ApeqeKh/pS8VJLoZ2ccwWs+ehXdIoOvV7OphJCFLHu+4bclU9LHTLhFKdGyGbMmME///lP+vbtS0xMTInbOnfuXOUgxo4di6ZpdOrUiTFjxhAREVHltoTvK07GnOFLpRlsVjs52YV8tnInGWm5rFy2jQce7wJ6VUbKhBDIWZaiKpxKyPbs2cP333/P9u3bCQoKclyvKEqV97J8//33iY+Px2KxMGPGDKZNm8bcuXOdaiM6OqxKz+2M2Nhwtz+Hr3J133OyCrDjZGFVHypeei4zn+83HSxZpPST3/jb/R0ICa1+WQ1fEsifewjs/gdy36F6/T8bGkQhEBMTjs4c7LqgPCSQ33tv9t2phGz+/PksW7aM66+/3mUBFE9jmkwmBg8ezBNPPOF0G+npOaiq+/4iCeSzzdzR9+BgA3o/HiGrVTuYm29vTmZ63oUipfe0oaDQQm5ezZmiCOTPPQR2/wO571D9/ltyCgBIS8tGMflXeZZAfu890XedTilzEMmpNWTBwcEkJia6JCiAvLw8srOLOq9pGuvWrSMhIcFl7QvflJ9vIy0tx6nH+FLxUoNRT1i4mQFDOxYVKX28C6om05VCiEtIpX7hBKdGyEaNGsXMmTN56qmniI6OLnGbTld+bjd9+nQ2btxIWloaDz74IJGRkSxbtoyRI0dit9tRVZWmTZsyZcoU53sh/M6p4+c48OspuvW8yomzLEsWDC26piqqX7zUZNajNwRx533tsFhtkowJIS4wmFCCI6hOiWUReBTNieGCFi1aFD3ooqy/eApo3759ro+ukmTK0n3c1fc/9p1h0+f7GPhIIlExoS5v31XkvQ/MvkNg9z+Q+w6B3X/pu/emLJ0aIfv6669dEpCoWcxmPUZj0UepvL8Hi0elANp3bkjr9vXRCgswK5YqP7emqWg2G5rRTK5W/Q2/hRBCCG9wag1Z/fr1y/xXrH///i4PUvgus1mPQW9Aq6Cm18W1v1QVCvNtfPHh/1D1JhSDAdViqeS/whKXC0+dJvnxEWjWqid1QgjhSpb935H70Xg0m3wvicpzeQnh48ePu7pJ4aOKk7GKXHpmo6XQxsrl2zh0IJWVy7eRpxrRR4SjM5kq8c+MzmRCMRrQ7HZsOUUnB1jT0giz5RCqWN3WXyGEqAytIBf13CmkHplwhst3PnVFaQLhHxR02O2VqCd2Se2vpE9/K1nD69PfuHNQO/SW8ubuSy6/t6Sns3vShRNA9pz/uf2yJWCQqUshhDdJIiacJ1vRiyrTUKs0QtZ3QBtWLt92oYbXgDaYdDY0J7blMsfVpcPiheQfP87+V+bQavpUzDHRaEaTfBcKIXyEDFCIypOETFRZYaEdzFSYlBXX/ipOykxmAw8M70LSp7/Rd0AbQnRW7Fl5lXzWCyNlil6PIazobBVjTAw5hlBJxoQQPkC+iITzXJ6QuaJ4p/AfhYV2VKOG2Vw0TahQVm0vpcRZlkHBBu4c1K5oZKzAhq6Km9ab4+rScdliGRkTQgjh16qUkKmqSlpaGnXq1LnstmnTplU7KOE/VFXjtZe+ofMNjUns2giAgiN/cfSlF6n31CjCOnQs9/H5AFRz/0cDkowJIXyGqcVNGBp3hEos6RCimFNnWWZlZfHss8/Stm1bbr31VqCoNtn8+fMd95GyF4HFbita1K/XX1Qs2Fp0pqNilMX1QojAowSFoY+sh6K4vJCBqMGcqtT/zDPPEBERwVNPPUXfvn3Zvn07GRkZDBo0iI0bN7ozznJJpf6KhSpW9JUcRlJ0OrSgULTzOdbFU42lsdk1rAU2QnUWNLUoQVMtFnQmE1laNUe/vKwmvPdVFch9h8Duvyv7bjTqCA1SLv8OqeiLpbJc0Y6rY7FZQWcAXdHPeZi9FkpNaMMTsRQUqthVFb1eR5BRR2G+e0oouaxS/48//siWLVswGo2OBdpRUVGkp6dXP0rhVprVglqJ3FvR67EHnV8cr104Q7Ksh9qsdvJyLXydtJ9+A1pjtuei2e0kPzGCjksXg9G/EzIhqksXasff5tTT8zLRuWhHMzuQVYnqODWKAmiWos4rULw4o9KPdVUMNaUNV7VTTht2Y1ECZgesOhPm4CC3JWVlcSohCw8PJzMzs8TasZMnTxIbG+vywIRrOEbGKjF9qOh02MwhFH9qLy1XcSmb1U5OdiGfrdxJRlou7y3/mSHDr0HJOAZAYWoqYbHUiJEyIarKYpdq7UL4utHrLtS1XNhnKnaryeNFS5ya4L7nnnsYNWoUP/30E6qqsnPnTp5//nkGDRrkrvhENWnWym5JZMGiM2G3a9jtKna7inrRz6X9O5eZzzfrD5Qo8rr2090UFNgB2DN5KslPjEC1yC8kIYQQ/sOuen5Y16kRskcffRSz2cy0adOw2WxMmDCBgQMH8o9//MNd8YlqUowmdJWcLtGrFmzGyo+Q1aodzM23NyczPc9R5LXfgNYop4tGyFpNm4I5NraopIV/zdgIIYQIYHqdDux2jz6nU4v6fZUs6q9YUHY6hqCKF5Yqej224HB0ej1QuWnLEmvIrCXXkOUYS1+86C9qwntfVYHcd3Bd//1xDZkQgcZiv7BezKQ3YVTds4bMpYv6y3Ldddc5F5XwKH1ERKVHygrPZmGOjMBg1HNpQddLmcx69IYg7rqvLUZrAZpej6LX03HpYhkZEwJQc/XeDsFprkzGw8waBp0aYJsIaWAMAmshoGE1hmK1VW4KzF/OSvRkG56IxW41Y1c19HoFo+K+syzL41RCNnHixBKXMzMzsVqt1K1bl6+//tqlgQnXSj98AntOFqGt21Z43zwVUo+fo3Z0CHXrRjjxxXzRx0kq5wvh8Mnvn9MgrB7X1evs7VA8LqdQIW/9ArSCHEL/NqXiB1TDvzYc4JcDZ1g46oZqteOShDTfBpxPxvMLq9eWBwXqyLgCxJ/ve6HNs1OVxZxKyDZv3lzist1uZ+nSpYSGuuj8aOE2Zzd/Rd7+vTSZPa/C+x747RQ/fXuYR8Z080BkQtR8h88dxaQP4DON7TYUvfsLRdtsKkaDFGMV/qnaa8hsNhvdu3dn69atrorJaTVtDVllirheWry1LFUZ5lW1ogr8dlUlMjIkIP9aKhaofy2C//X9sgKk1ZzjUDi/N68/zLd4sg1n21FVUO2gN4JW9HMeZpeHomlQaLlQ3NNsULAU2KrUpr999l1J+u7evrtsDVlptm7dWu6ib+G8oiKuKmVVsbu0eGuZ7VRQ1LWsx1gtdpI+/Y2+A9o4FbcQZdEF2UHv3jlsXy1AqmkaVrUoMVBQCNIbCcXJdWWaCtXdhscVbTjbjmoDm4W833cQ1qY7amEueb/vwJhwA/la9fd5tKsaep2CXdXIyrHy8oqfOZOZT53awbww7Bpia5mrnJQJ4WlOHRHdu3cvkXzl5+djsViYMsW96wICRWWKuF5avLUsFZ0dWdZjrBY7K5dvIyMtl5XLt/HA8C6YzXoKC70zpy5qBqtmRbMH5qLCjPyzTP3mwn6/i/tMI8zZvEir4K8vT7XhZDuaaifv9+1kfP8Rxqg40ja+g2IwEJdwPTm26idkqgaoRf8XJ2MAZzLzeXnFz7z8ZLcAO5lA+DOnjog5c+aUuBwcHMyVV15JWJh/lzbwFRWNjAHYQyLO/2Kr4AtRAxQnv3w1SPr0txKFXpM+/Y07BrWjaPxBCFFtClVbT+WHo2SK3khoy64Yo+I59dFMAOo/MpdsNQi76prvFPv5KYDiZKzYmcx87Kpa/WkgITyk0p9Vu93OokWLePvttzGZAnhxqhtVpojrpcVby1LVEbK+A9o4RsiiYkLpO6ANGj44DySEv9JAdbYKeHECpFXjWHRFG862o9rAaiFt4zuOq7L/9w0h1w7ApnPFCJmGTlFQNY06tYNLJGV1agd7pbinEFVV6SNCr9dz/Phx579IRKXlakV/NQfnZqA3GSkr6dJZrdiCwtEZyl6HUrR2zLmkTFEUjCY9Dwzv4lhDFhkV2Iv6hWsYFaPb15D5qrqhMSzsMxUoWkNm1htRNCeTBH+esjy4HcVgoP7Dc8n+9RsKju+nlmJHb3DB2JUKel3R/y8Mu+ayNWRmo4JF8jHhJ5w6y/LTTz9lx44djBw5kri4uBK/7HU6751qXNPOsjRnp2OOCKO8UbDknWe4qk0DwmuVX32/KmcyaefPslRRiYgI7IRMzjhyXd8Pnf2Lg2cPcVujHm45ESgwC5D6C63oLEu7DdAo1Idis6tuOsuyqLinnGVZNdJ3PznLctKkSQB8/vnnjuuKR2H27dtXjRDFxdIPHydzfRLxjz+FoVat0u9zzspXc7/j8ee7ezg6IaqmUUQDGkc0dNtZ2TmFCvkbX0fNOk3ogOnVbs/ffzE9OvsbbrvmCgbc1NTpx7qn7xqOQqm4p1CqwvlfajawyMmVws84lZBJNX7PCGvbjrC27cq9j92uopcCiMKP/OePJLadSmbujVPd9hxKSCQ6KcODqmnYVQ2DXl4LIfyFU1OWb7/9Ng8//PBl17/zzjs8+OCDLg3MGf42ZRmhWCq8j6LToQaHFp0sWcrtxcVbg4MUKGs9ir8WkpRY/LONCtr57cwBjmWdos9VFYzqVjWW4gKkBiOoKppqJ5/yp/Qr4q9vs9WmYbOrqCoYDQo6VcNur/z6X38fHayuQO6/9N17U5ZOJWQdO3YkOTn5suuvueYafv7556pHWE3+lpCFWXPKvV0fZMZmLruUyKXFW0NDufxMIj88RV5icV42djQ/2TTUYr+wWa9JbyKitOKoVX1NyihAamp5A3lq1RaPFxcdrS5XtONMG7n5Ns5mF7Lww52OBe4TH7yGyGBjpZOyQP6lDIHdf+m7j68h+/HHH4GiU7V/+uknLs7hjh8/LntZVpJjZKycsiFFhV/Lfj3LKt4aFqKDi37h+etZWRKLcwrVikdbfcXodRcKSC/sMxVFV8pxUMXXpLwCpPYqFiAtLjpaXa5ox5k2zmTksfTfv5YokjrjnZ95+cmucsKDED6sUt9UEydOBKCwsJAJEyY4rlcUhdjYWMdif1E+1VLRL08NW2htKO+v2DKKt945qB3Bl/5+q2GjQRJLKfwoIbtUmcVRq/CauKsAqb3yEwhub6eybQSZDGUUSdWkSKoQPqxSx+fmzZsBGDduHLNnzy73vqdOnSIuLq76kdVAukoU1DXbCyocISuteKvZrKJenMj5ayFJiSVglFrTsKqvSVkFSK+regHS4qKj1eWKdpxpo8BiK6NIqgIBun2VEP7AqTVklVHWOjN3qmlryHRBZuxOrCELC9FKTlcW3ckvFnpLLNVrJ0vxlxVkl68hq1Va4FV8TTS7jbz9P5G16yvq3DHaUYC07j0vkKVVbWG/rCELzHVEENj9l777yaL+yujQoQM7d+50ZZMV8reErKKzLAsL7ZxJL6D+1UUjjaV9DRcXbw0y2i9PxkRA+e7YLxzJOsnQVv29HYoPuLwAqb0au4v4UO5dhbMsNVRNw6iXsyydFcj9l777+KJ+Z7ir6GNNsvOZsYR16EjdIcNKvf1sTh6r3v2VW/pZaNa6bpnt2E7u48zaWQT3ex5DvYRKPfcvB86w5D+7efHBzlxRN7zC+wfywQn+0f+2MdfQNgYuWTZUbf7Q99K5pgCp//a/iO78P00F2T1ICN/nkcqis2bNokePHjRv3pzff//dcf3hw4cZOHAgt912GwMHDuSvv/7yRDjeV8FgXnitIB54oguNr44u/462opGxMhdHl8JqK/or2ShFZWuMD/Z/yuJdb3k7DCGEENXgkZNubrnlFoYOHcr9999f4vopU6YwePBg7rzzTj7//HMmT57Mv/71L0+EVCnBwUaCTFCQbyE8rPLrUCqaWmj35nKgvJ0qITTEjE6xYzaVc68WraHVe0UN2azkXVIEs7Q4urStT2LrePQ6HWaTjsJ8me70d/VC4wk3VTzaKYQQwne5PCErbUlaYmLiZdelp6ezd+9e3nmn6Kyofv368dJLL5GRkUFUVJSrw3JacLAR1WDDYq34zMiLFe/tWZmVeWXdxVJocyzY18wahbYy1pwpgFp44WfyL7/9EvqgC5M5VkBXQQm59LzMCu9Tk/lD/7td3REAG/mYdCbUvFIKrgohhPBpLk/I1q1bV6n7paSkULduXfT6ol8eer2eOnXqkJKS4hMJmVlnw2qvWjJWHZZC22VFXw3BBvJsLl4gJGoEVVN5Zv2FvSEX9pmKgWAvRiSEEKIqnErI9u/fz8yZM9m/fz95eXnAhSRk9+7dAMTHx7s+ygqUdcZCdWRnFeB0eW0NUKp3tmdpRV/vGNQOFEnIROXExrpu+tKVbfmjQO5/IPcdArv/0nfvcCohGzNmDLfeeiuTJk0iKCioWk8cHx/P6dOnsdvt6PV67HY7Z86cqVJC546yF0Eh5tJ22iuXK0bISiv6qhqtYKtWsyKAuOrMQH8/y7C6Arn/gdx3COz+S9/9pOxFWloao0ePdklpi+joaBISEli7di133nkna9euJSEhwSemKwGCyCdfr8fgxLRl0dqx6iVlJrOBB4Z3cawhM4RpFNpsmJw4k1IEloV9LkxZmnQmV2y/KIQQwsOcKgw7c+ZMWrduzR133OHUk0yfPp2NGzeSlpZG7dq1iYyMJCkpiUOHDjF+/HiysrKIiIhg1qxZNGnSxOlOuKswbHiwhkGnw6Y4u5as/LMsNco/wxLAZlUJMqlQ1oL+4paMQWAtBDSsxlBHWYuy4igoVIuqfusVgowVn2UZyH8tQWD3P5D7DoHd/0DuOwR2/6XvflKpPy0tjYEDBxIUFER0dMkaWd4sV+Fvlfr9SSD3HQK7/4Hcdwjs/gdy3yGw+y9995Mpy1GjRtGgQQN69eqF2Vy1/eEEnPngPYKaXk1El2u9HYoQQgghfIBTCdm+ffvYtm0bJpNzU3iipKwf/ws6nSRkQgghhACc3DopMTGRQ4cOuSuWwKFVZhWZEEIIIQKFUyNkDRo04KGHHqJXr16XrSEbPXq0SwOryYryMUnIhBBCCFHEqYSsoKCAm266CavVyqlTp9wVU41nqB2JPiTE22EIIYQQwkc4lZC9/PLL7oojoFw5/RVvhyCEEEIIH+JUQnbs2LEyb2vYsGG1gwkU+QcPYoiMxBgb6+1QhBBCCOEDnErIevXq5ahGX6y4Kv2+fftcG1kNdnz+HCJv7kHsPYO8HYoQQgghfIDTm4tfLDU1lcWLF5OYmOjSoAKDLOoXQgghRBGnErJLxcbGMnHiRG677Tb69+/vqphqvKsWL/N2CEIIIYTwIU7VISvNn3/+SX5+vitiCRi2s5moBfKaCSGEEKKIUyNkgwcPdqwZA8jPz+ePP/7gySefdHlgNdlfE54nstdtxN59j7dDEUIIIYQPcCohu+eekglEcHAwLVq0oHHjxq6MqcZzYj93IYQQQgQApxKyvn378p///Id9+/aRl5cHwObNmwGYPXu266OrwRSp1C+EEEKI85xKyMaPH8/+/fu5+eabiYmJcVdMNZ+MkAkhhBDiIk4lZFu2bOHrr78mIiLCXfEEhLpDh2FuIIV0hRBCCFHEqYQsPj4ei8XirlgCRq1uN3o7BCGEEEL4EKcSsrvuuosnn3ySoUOHEh0dXeK26667zqWB1WTHX51NeJfrqNXtBm+HIoQQQggf4FRCtnLlSgDmzZtX4npFUfj6669dF1UNl7dvL0FNr/J2GEIIIYTwEU4lZMVnVIrqierXn5DmLbwdhhBCCCF8RLW2ThJVE3PX3d4OQQghhBA+pNpbJwnnaJrGqRVvk7Nrp7dDEUIIIYSPkITM0zSNrB+2UHj0iLcjEUIIIYSPkITMW6RSvxBCCCHOk4TM06RKvxBCCCEuIQmZFxhqR6ELDvZ2GEIIIYTwEXKWpYcpej1N5syr+I5CCCGECBgyQuZhmqqS9/sBrBnp3g5FCCGEED5CEjIP0+x2js9+meyffvR2KEIIIYTwEZKQCSGEEEJ4mawh8zDFYODqN/7P22EIIYQQwofICJmnaRq2s5mohYXejkQIIYQQPkISMg/TrFYOj3uWc99+4+1QhBBCCOEjJCETQgghhPAyScg8rbhSv+ycJIQQQojzJCHzuOKETDIyIYQQQhTxibMse/Togclkwmw2AzB27FhuuOEGL0flHorBSN1/PEjQlU28HYoQQgghfIRPJGQAr732Gs2aNfN2GG6nGAzUuqG7t8MQQgghhA+RKUsPUwsLOTZ3Ftk7tns7FCGEEEL4CEXTileZe0+PHj0ICwtD0zQ6derEmDFjiIiI8HZYbmHLyWXb/UNp/NAw6t/Z39vhCCGEEMIH+ERClpKSQnx8PBaLhRkzZpCbm8vcuXMr/fj09BxU1X3diI0NJzU12yVtqRYLGevWENq6LcFXXe2SNt3JlX33R4Hc/0DuOwR2/wO57xDY/Ze+u7fvOp1CdHRY6be59ZkrKT4+HgCTycTgwYNJTk72ckTuozOZiLnrbr9IxoQQQgjhGV5PyPLy8sjOLspINU1j3bp1JCQkeDkq91ELCji14m3y9u31dihCCCGE8BFeP8syPT2dkSNHYrfbUVWVpk2bMmXKFG+H5Taa1UrWD1swN7yCkISW3g5HCCGEED7A6wlZw4YNWb16tbfD8DwpDCuEEEKI87w+ZRloNLx+DoUQQgghfIwkZB6mKDoMtaPQnd+VQAghhBDC61OWgUYfFkaTOfO8HYYQQgghfIiMkHmYZrOR9/sBbGfPejsUIYQQQvgIScg8zJ6Tw/HZL5Ozq+bWWhNCCCGEcyQh8xY5y1IIIYQQ58kaMg/T16rF1W/8n7fDEEIIIYQPkREyT1NVbGcz0SwWb0cihBBCCB8hCZkHhSpWQu15mDNOkfXzT94ORwghhBA+QhIyD9KsFnY9ORJDWOk7vQshhBAiMMkaMg8IVaxoVguW1DQAbDk5xHdsg06xkqsZvRydEEIIIbxNEjIP0KwWdj3+lOPy/lfmANB+2RIwSEImhBBCBDpJyDxAMZpov2wJBX/9xf5X5pAw5Z+Y68SiGE3I1pZCCCGEkITMA3I1IxiMmKOiADDHx5FnCJVkTAghhBCALOr3LIORNnNnYTl9htzdv3o7GiGEEEL4CBkh86Dj6zeRuWkDAHUffNjL0QghhBDCV8gImQcVJ2NR/fpjbniFl6MRQgghhK+QETIPSpgyidArrkDTVDSbDU3KXgghhBACGSHzKGNkJKrFQuGp0yQ/PgLNKtsnCSGEEEISMo8IVaxEKBaM4WFodju2nBwArGlphNlyCFWsXo5QCCGEEN4kU5YeoFktqJqGJT2d3ZOmOK7fc/5nKRArhBBCBDZJyDxAMZrQoWGOq0uHxQvJP36c/a/ModX0qZhjotGkQKwQQggR0CQh84DihfumtBOYatVybC5ujIkhRwrECiGEEAFP1pB5kD03D53JhDmuLh2XLS7aOkkIIYQQAU9GyDzo0P+9S9AVjYh7+NGiV15GxoQQQgiBJGQe1XjqdG+HIIQQQggfJAmZG4QqVvSlDn9pqBYrislEtibTlUIIIYQoImvI3ECzWlAtl/+zFxSQ/MQINIsUhBVCCCHEBTJC5kKOkTHjpTXFNFSLBUtaOgCFqamExSIjZUIIIYQAJCFzqeICsJddr9rZ+dRox+U9k6cC0HHpYpAzLYUQQoiAJwmZCxUXgL2cRseliyg8k8qeKdNoNW0K5thYFJMUhBVCCCGEJGQuVVwANqQwC53u0uV5CqaYaADMsbHkGMMkGRNCCCEEIAmZW1izsgiuU6eUWzQ6Ll0sI2NCCCGEKEESMjc4tuZL8vbvo8nsVy+/0WiWZEwIIYQQJUhC5gZxDz2CZrd7OwwhhBBC+AmfSMgOHz7M+PHjOXv2LJGRkcyaNYvGjRt7OywAwhULhWnpRCjOPEpDVa0oBilrIYQQQoiK+URh2ClTpjB48GA2bNjA4MGDmTx5srdDctBKKfBa0T8pACuEEEIIZ3g9IUtPT2fv3r3069cPgH79+rF3714yMjK8Gle4YiFCsaAzmZz4ZwS0kgVgrTmEK5KYCSGEEKJsXp+yTElJoW7duuj1egD0ej116tQhJSWFqKioSrURHR3m8rjyT6Y4vfa+vAKwsfWiXRidZ8XGhns7BK8K5P4Hct8hsPsfyH2HwO6/9N07vJ6QuUJ6eg6q6tpTF8NNJpxaNgaUVwA2NTXbpfF5SmxsuN/G7gqB3P9A7jsEdv8Due8Q2P2Xvru37zqdUuYgktcTsvj4eE6fPo3dbkev12O32zlz5gzx8fFejat4MX6YNcfJR0oBWCGEEEI4x+tryKKjo0lISGDt2rUArF27loSEhEpPV7qb4tQasqJ/+qCgCwVghRBCCCEq4PURMoAXX3yR8ePH8/rrrxMREcGsWbO8HZJDtmaq2jCmFIAVQgghRCX5RELWtGlTPvnkE2+HIYQQQgjhFV6fshRCCCGECHSSkAkhhBBCeJkkZEIIIYQQXiYJmRBCCCGEl0lCJoQQQgjhZT5xlmV16XTO19T3xefwVYHcdwjs/gdy3yGw+x/IfYfA7r/03TvtK5qmSbUsIYQQQggvkilLIYQQQggvk4RMCCGEEMLLJCETQgghhPAySciEEEIIIbxMEjIhhBBCCC+ThEwIIYQQwsskIRNCCCGE8DJJyIQQQgghvEwSMiGEEEIIL6sRWye5y+HDhxk/fjxnz54lMjKSWbNm0bhxY2+H5TKZmZmMGzeOo0ePYjKZaNSoEdOmTSMqKormzZvTrFkzdLqinH327Nk0b94cgM2bNzN79mzsdjutWrXi5ZdfJjg42JtdqZIePXpgMpkwm80AjB07lhtuuIFdu3YxefJkCgsLqV+/PnPmzCE6Ohqg3Nv8yfHjx3nqqaccl7Ozs8nJyeHnn38u83UB/+3/rFmz2LBhAydOnGDNmjU0a9YMKP8Yr+ptvqa0vpd37AM16vgv672v6ufcn46B0vpe3rEPVX9dfE15n/Gqvr9u778myjRkyBBt9erVmqZp2urVq7UhQ4Z4OSLXyszM1H766SfH5VdeeUV74YUXNE3TtGbNmmk5OTmXPSYnJ0e7/vrrtcOHD2uapmkTJkzQFi1a5JF4Xe3mm2/WDhw4UOI6u92u9ezZU9u+fbumaZq2ZMkSbfz48RXe5u+mT5+uTZ06VdO00l8XTfPv/m/fvl07efLkZX0r7xiv6m2+prS+l3fsa1rNOv7Leu+r8jn3t2OgrL5f7OJjX9NqzvFf1me8qu+vJ/ovU5ZlSE9PZ+/evfTr1w+Afv36sXfvXjIyMrwcmetERkbSpUsXx+X27dtz8uTJch/z/fff07p1a8dowKBBg1i/fr07w/So3bt3YzabSUxMBIr69+WXX1Z4mz+zWCysWbOGu+++u9z7+XP/ExMTiY+PL3Fdecd4VW/zRaX1vSrHPvjn8V9a/8tTk74DKup7ZY998L++l/UZr+r764n+y5RlGVJSUqhbty56vR4AvV5PnTp1SElJcQzr1ySqqrJq1Sp69OjhuG7IkCHY7XZuvPFGRo4ciclkIiUlhXr16jnuU69ePVJSUrwRskuMHTsWTdPo1KkTY8aMuax/UVFRqKrK2bNny70tMjLSC9G7xubNm6lbty6tWrVyXHfp6xIREVHj+l/eMa5pWpVu88fvhtKOfQjM47+iz3lNOwZKO/ah5h3/F3/Gq/r+eqL/MkImAHjppZcICQnhgQceAODbb7/ls88+4/333+ePP/5gyZIlXo7Q9d5//32++OIL/v3vf6NpGtOmTfN2SF7x73//u8RfyPK6BJZLj32Q4z9QXHrsQ818XUr7jPsiScjKEB8fz+nTp7Hb7QDY7XbOnDnj1NC3v5g1axZHjhxhwYIFjkW8xf0MCwvjnnvuITk52XH9xVMbJ0+e9NvXpDhuk8nE4MGDSU5Ovqx/GRkZ6HQ6IiMjy73NX50+fZrt27fTv39/x3WlvS7F19ek/pd3jFf1Nn9T2rEPgXv8F18fCN8BpR37UPOO/0s/41V9fz3Rf0nIyhAdHU1CQgJr164FYO3atSQkJPjllER55s2bx+7du1myZAkmkwmAc+fOUVBQAIDNZmPDhg0kJCQAcMMNN/Dbb7/x119/AfDhhx9y++23eyX26sjLyyM7OxsATdNYt24dCQkJtG7dmoKCAnbs2AEU9a93794A5d7mr/7zn//QvXt3ateuDZT9ukDN6395x3hVb/MnpR37ENjHP5T/Oa9Jx8Clxz7UvOO/tM94Vd9fT/Rf0TRNc2mLNcihQ4cYP348WVlZREREMGvWLJo0aeLtsFzm4MGD9OvXj8aNGxMUFARAgwYNeOSRR5g8eTKKomCz2ejQoQMTJkwgNDQUgK+++oo5c+agqioJCQm88sorhISEeLMrTjt27BgjR47EbrejqipNmzZl0qRJ1KlTh+TkZKZMmVLi1OaYmBiAcm/zR7fddhsTJ07kxhtvBMp/XcB/+z99+nQ2btxIWloatWvXJjIykqSkpHKP8are5mtK6/uCBQtKPfaXLFnCzp07a9TxX1r/ly1bVuXPuT8dA2V97uHyYx9q1vFf1u+3JUuWVPn9dXf/JSETQgghhPAymbIUQgghhPAySciEEEIIIbxMEjIhhBBCCC+ThEwIIYQQwsskIRNCCCGE8DJJyIQQNULfvn3Ztm2b157/5MmTdOjQwVEwVgghnCEJmRDCrwwYMIDDhw9z7Ngx/va3vzmuT0pKcmwmvGjRIsaOHevWOHr06MF///tfx+V69eqxc+dOxx6XQgjhDEnIhBB+w2q1cvLkSRo3bszu3btp2bKlW57HZrO5pV0hhCiLJGRCCL9x8OBBmjZtiqIolyVkxSNW33//PcuXL2f9+vV06NCBO+64A4Ds7GwmTJhAt27duOGGG5g/f75jevGzzz5j0KBBzJw5ky5durBo0SKOHj3K0KFD6dKlC126dOHZZ58lKysLgOeee46TJ0/y+OOP06FDB958802OHz9O8+bNHcnc6dOnefzxx7nmmmvo1asXH3/8sSPWRYsWMXr0aMaNG0eHDh3o27cvv/32m6deRiGED5KETAjh8/7973+TmJjIfffdx65du0hMTOSdd95h7ty5JCYmcuzYMcd9b7zxRoYPH87tt9/Ozp07+eKLLwAYP348BoOBjRs3snr1arZu3conn3zieNyvv/5Kw4YN2bp1K0888QSapjF8+HC2bNnC+vXrOXXqFIsWLQJgzpw51KtXj2XLlrFz504effTRy2IeM2YMcXFxbNmyhddee4158+bx448/Om7fvHkzffv2ZceOHfTo0YOXXnrJXS+fEMIPSEImhPB5d999Nzt27KBVq1Z8/PHHfPHFF1x99dUkJyezY8cOGjZsWO7j09LS+O6775gwYQIhISFER0czbNgwx75+AHXq1GHIkCEYDAaCgoJo1KgRXbt2xWQyERUVxYMPPsj27dsrFW9KSgrJycmMHTsWs9lMQkIC99xzD59//rnjPp06daJ79+7o9XruvPNO9u/fX7UXRwhRIxi8HYAQQpTn7Nmz9OzZE03TyMvLY8iQIVgsFgA6d+7MiBEjGDZsWLltnDx5EpvNRrdu3RzXqapKfHy843JcXFyJx6SlpTFjxgx27NhBbm4umqYRERFRqZjPnDlDrVq1CAsLc1xXr149du/e7bh88abEQUFBFBYWYrPZMBjka1mIQCRHvhDCp0VGRrJjxw6SkpLYtm0b06ZN46mnnuL+++/n+uuvL/UxiqKUuBwXF4fJZOKnn34qM+G59DHz5s1DURTWrFlDZGQkX331FdOmTatUzHXq1OHcuXPk5OQ4krKUlBTq1q1bqccLIQKPTFkKIfzCxYv49+3bR6tWrcq8b3R0NCdOnEBVVaAoQeratSuvvPIKOTk5qKrK0aNH+fnnn8tsIzc3l5CQEMLDwzl9+jRvvfVWidtjYmJKrF27WHx8PB06dGDevHkUFhayf/9+Pv30U8cJBkIIcSlJyIQQfmHPnj20bNmSzMxMdDodtWrVKvO+vXv3BqBLly6OWmWzZ8/GarXSp08fOnfuzKhRo0hNTS2zjREjRrB3714SExN57LHHuPXWW0vc/thjj7F06VISExN5++23L3v8vHnzOHHiBDfccAMjRoxg5MiRZY7oCSGEomma5u0ghBBCCCECmYyQCSGEEEJ4mSRkQgghhBBeJgmZEEIIIYSXSUImhBBCCOFlkpAJIYQQQniZJGRCCCGEEF4mCZkQQgghhJdJQiaEEEII4WWSkAkhhBBCeNn/A4eSXh3JUkTEAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"### predefined configuration for different setups\n",
"\n",
"configuration_options = {\n",
" 'KDD19': {\n",
" 'datapoint_grouping': 'disagreement', \n",
" 'group_selection': 'max',\n",
" 'datapoint_selection': 'random',\n",
" \n",
" 'lf_ensemble': 'snorkel',\n",
" \n",
" 'lf_selection': 'all', \n",
" 'with_slow_loop': False \n",
" }, \n",
" 'WeSAL': {\n",
" 'datapoint_grouping': 'disagreement', \n",
" 'group_selection': 'max',\n",
" 'datapoint_selection': 'entropy', # best option for uncertainty sampling\n",
" \n",
" 'lf_ensemble': 'snorkel_with_corrected_votes',\n",
" \n",
" 'lf_selection': 'all', \n",
" 'with_slow_loop': False \n",
" }, \n",
" 'ActiveWeaSul': {\n",
" 'datapoint_grouping': 'uniqueness_votes', \n",
" 'group_selection': 'max_kl',\n",
" 'datapoint_selection': 'random',\n",
" \n",
" 'lf_ensemble': 'snorkel_with_corrected_votes', #'snorkel_with_annotated_labels',\n",
" \n",
" 'lf_selection': 'all', \n",
" 'with_slow_loop': False \n",
" }, \n",
" 'DualLoops': {\n",
" 'datapoint_grouping': 'num_positive_votes', \n",
" 'group_selection': 'max',\n",
" 'datapoint_selection': 'match_confidence', #entropy, least_confidence, margin\n",
" \n",
" 'lf_ensemble': 'snorkel_with_corrected_votes', #snorkel_with_init_precision\n",
" \n",
" 'lf_selection': 'all', \n",
" 'with_slow_loop': False \n",
" }, \n",
" 'ActiveLearning': {\n",
" 'datapoint_grouping': 'none', \n",
" 'group_selection': 'none',\n",
" 'datapoint_selection': 'entropy', #entropy, least_confidence, margin\n",
" 'lf_ensemble': 'normal_active_learning_rf',\n",
" \n",
" 'lf_selection': 'all', \n",
" 'with_slow_loop': False \n",
" } \n",
"}\n",
"\n",
"lfs_set = [\n",
"# 'LF_aml', \n",
"# 'LF_logmap', \n",
"# 'LF_yam',\n",
" \n",
" 'LF_class_name_equal', \n",
" 'LF_class_name_stemmed_equal',\n",
" 'LF_acronyms', \n",
" 'LF_class_name_synonyms',\n",
" 'LF_label_equal', \n",
" 'LF_root_nouns_equal', \n",
" \n",
" 'LF_class_name_spacy_distance', \n",
" 'LF_class_name_distance', \n",
" \n",
" 'LF_name_segment_overlap', \n",
" 'LF_label_words_overlap',\n",
" 'LF_subclasses_overlap',\n",
" 'LF_superclasses_overlap',\n",
" 'LF_properties_overlap',\n",
" ]\n",
"\n",
"feature_set = [\n",
" 'shared_word', \n",
" 'levenshtein_distance', \n",
" 'hamming_distance',\n",
" 'class_name_embedding_distance'\n",
" ]\n",
"\n",
"\n",
"epochs = 100\n",
"balance=[0.9, 0.1]\n",
"\n",
"num_iteration = 50\n",
"interval_slow_loop = 10\n",
"budget = 4000\n",
"\n",
"experiments = [ \n",
" 'KDD19', \n",
" 'WeSAL',\n",
" 'ActiveWeaSul',\n",
" 'ActiveLearning', \n",
" 'DualLoops',\n",
"]\n",
"\n",
"results = {}\n",
"\n",
"for exp in experiments:\n",
" print(\"\\r\\n\\r\\n************* \" + exp + \" *************************\")\n",
" experiment_config = configuration_options[exp]\n",
" result, result_df = dual_loops.run_experiment(experiment_config, my_dataset_df, lfs_set, feature_set, num_iteration, interval_slow_loop, balance, epochs, budget, False)\n",
" \n",
" results[exp] = result \n",
"\n",
"# plot the results generated from all experiments\n",
"dual_loops.plot_result(results, 'f1', 100.0) \n",
"dual_loops.plot_result(results, 'precision', 100.0) \n",
"dual_loops.plot_result(results, 'recall', 100.0) \n",
"\n",
"dual_loops.plot_result(results, 'human_effort', 1.0) \n",
"dual_loops.plot_result(results, 'num_true_matches', 1.0) \n",
"\n",
"dual_loops.plot_result(results, 'a-tp', 1.0) \n",
"dual_loops.plot_result(results, 'p-tp', 1.0) \n"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "91d236dc",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"KDD19\n",
"13 2014 3 10\n",
"ActiveWeaSul\n",
"13 2014 3 10\n",
"ActiveLearning\n",
"25 2000 25 0\n",
"DualLoops\n",
"25 2328 23 2\n"
]
}
],
"source": [
"experiments = [ \n",
" 'KDD19', \n",
"# 'WeSAL',\n",
" 'ActiveWeaSul',\n",
" 'ActiveLearning', \n",
" 'DualLoops',\n",
"]\n",
"for exp in experiments:\n",
" print(exp)\n",
" final = results[exp][num_iteration]\n",
" print(final['num_true_matches'], final['human_effort'], final['a-tp'], final['p-tp'])"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "b86d1767",
"metadata": {},
"outputs": [],
"source": [
"# figure to show how adaptive blocking works"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "40e477f9",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.9"
}
},
"nbformat": 4,
"nbformat_minor": 5
}