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548 lines
21 KiB
548 lines
21 KiB
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 37,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"1. 데이터를 로드합니다.\n",
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"1-1. 네트워크가 로드되었습니다.\n",
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"1-2. 테이블들이 로드되었습니다.\n",
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"1-3. 네트워크의 모든 clean state requirement들을 체크했습니다.\n",
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"1-4. 테이블들의 무결성 검사를 완료했습니다.\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"이동류정보 불러오는 중: 100%|██████████| 17280/17280 [00:13<00:00, 1247.47it/s]\n"
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]
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}
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],
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"source": [
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"import sys\n",
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"from datetime import datetime\n",
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"sys.path.append('../../Scripts')\n",
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"from preprocess_daily import DailyPreprocessor\n",
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"self = DailyPreprocessor()\n",
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"\n",
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"# 1. 데이터 준비\n",
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"self.load_data()\n",
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"\n",
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"self.make_match1()\n",
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"self.make_match2()\n",
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"self.make_match3()\n",
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"self.make_match4()\n",
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"self.make_match5()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 36,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"u00 True\n",
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"u20 False\n",
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"u30 True\n",
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"u31 True\n",
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"u32 True\n",
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"u60 True\n"
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]
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}
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],
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"source": [
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"self.node2inter = dict(zip(self.inter_node['node_id'], self.inter_node['inter_no']))\n",
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"\n",
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"child_ids = self.inter_node[self.inter_node.inter_type=='child'].node_id.unique()\n",
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"ch2pa = {} # child to parent\n",
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"for child_id in child_ids:\n",
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" parent_no = self.inter_node[self.inter_node.node_id==child_id].inter_no.iloc[0]\n",
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" sub_inter_node = self.inter_node[self.inter_node.inter_no==parent_no]\n",
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" ch2pa[child_id] = sub_inter_node[sub_inter_node.inter_type=='parent'].iloc[0].node_id\n",
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"directions = ['북', '북동', '동', '남동', '남', '남서', '서', '북서'] # 정북기준 시계방향으로 8방향\n",
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"\n",
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"# 각 uturn node에 대하여 (inc_edge_id, out_edge_id) 부여\n",
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"cmatches = []\n",
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"for _, row in self.uturn.iterrows():\n",
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" child_id = row.child_id\n",
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" parent_id = row.parent_id\n",
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" direction = row.direction\n",
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" condition = row.condition\n",
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" inc_edge_id = row.inc_edge\n",
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" out_edge_id = row.out_edge\n",
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" # match5에서 parent_id에 해당하는 행들을 가져옴\n",
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" cmatch = self.match5.copy()[self.match5.node_id==parent_id] # match dataframe for a child node\n",
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" cmatch = cmatch.sort_values(by=['phase_no', 'ring_type']).reset_index(drop=True)\n",
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" cmatch['node_id'] = child_id\n",
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" cmatch[['inc_edge', 'out_edge']] = np.nan\n",
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"\n",
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" # condition 별로 inc_dire, out_dire_A, out_dire_B를 정함\n",
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" ind = directions.index(direction)\n",
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" if condition == \"좌회전시\":\n",
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" inc_dire = direction\n",
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" out_dire_A = out_dire_B = directions[(ind + 2) % len(directions)]\n",
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" elif condition == \"보행신호시\":\n",
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" inc_dire = directions[(ind + 2) % len(directions)]\n",
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" out_dire_A = directions[(ind - 2) % len(directions)]\n",
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" out_dire_B = directions[(ind - 2) % len(directions)]\n",
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" print(child_id, ((cmatch.inc_dir==inc_dire) & (cmatch.out_dir==out_dire_A)).any())\n",
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" # (inc_dire, out_dire_A, out_dire_B) 별로 inc_edge_id, out_edge_id를 정함\n",
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" cmatch.loc[(cmatch.inc_dir==inc_dire) & (cmatch.out_dir==out_dire_A), ['inc_edge', 'out_edge']] = [inc_edge_id, out_edge_id]\n",
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" cmatch.loc[(cmatch.inc_dir==inc_dire) & (cmatch.out_dir==out_dire_B), ['inc_edge', 'out_edge']] = [inc_edge_id, out_edge_id]\n",
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" if condition == '보행신호시':\n",
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" # 이동류번호가 17(보행신호)이면서 유턴노드방향으로 가는 신호가 없으면 (inc_edge_id, out_edge_id)를 부여한다.\n",
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" cmatch.loc[(cmatch.move_no==17) & (cmatch.out_dir!=direction), ['inc_edge', 'out_edge']] = [inc_edge_id, out_edge_id]\n",
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" # 유턴신호의 이동류번호를 19로 부여한다.\n",
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" cmatch.loc[(cmatch.inc_dir==inc_dire) & (cmatch.out_dir==out_dire_A), 'move_no'] = 19\n",
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" cmatch.loc[(cmatch.inc_dir==inc_dire) & (cmatch.out_dir==out_dire_B), 'move_no'] = 19\n",
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" cmatches.append(cmatch)\n",
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"\n",
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"# 각 coordination node에 대하여 (inc_edge_id, out_edge_id) 부여\n",
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"self.coord['inter_no'] = self.coord['parent_id'].map(self.node2inter)\n",
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"self.coord = self.coord.rename(columns={'child_id':'node_id'})\n",
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"self.coord[['inc_dir', 'out_dir', 'inc_angle','out_angle']] = np.nan\n",
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"self.coord['move_no'] = 20\n",
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"self.coord = self.coord[['inter_no', 'phase_no', 'ring_type', 'move_no', 'inc_dir', 'out_dir', 'inc_angle','out_angle', 'inc_edge', 'out_edge', 'node_id']]\n",
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"\n",
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"# display(coord)\n",
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"cmatches = pd.concat(cmatches)\n",
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"self.match6 = pd.concat([self.match5, cmatches, self.coord]).drop_duplicates().sort_values(by=['inter_no', 'node_id', 'phase_no', 'ring_type'])\n",
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"# self.match6.to_csv(os.path.join(self.path_intermediates, 'match6.csv'))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 34,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>inter_no</th>\n",
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" <th>phase_no</th>\n",
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" <th>ring_type</th>\n",
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" <th>move_no</th>\n",
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" <th>inc_dir</th>\n",
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" <th>out_dir</th>\n",
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" <th>inc_angle</th>\n",
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" <th>out_angle</th>\n",
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" <th>inc_edge</th>\n",
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" <th>out_edge</th>\n",
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" <th>node_id</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>175</td>\n",
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" <td>1</td>\n",
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" <td>A</td>\n",
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" <td>8</td>\n",
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" <td>남</td>\n",
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" <td>북</td>\n",
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" <td>179</td>\n",
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" <td>004</td>\n",
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" <td>-571542797_02</td>\n",
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" <td>571500487_01</td>\n",
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" <td>i0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>175</td>\n",
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" <td>1</td>\n",
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" <td>B</td>\n",
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" <td>4</td>\n",
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" <td>북</td>\n",
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" <td>남</td>\n",
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" <td>003</td>\n",
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" <td>176</td>\n",
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" <td>-571500487_01</td>\n",
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" <td>571542797_02</td>\n",
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" <td>i0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>175</td>\n",
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" <td>2</td>\n",
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" <td>A</td>\n",
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" <td>7</td>\n",
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" <td>북</td>\n",
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" <td>동</td>\n",
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" <td>001</td>\n",
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" <td>095</td>\n",
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" <td>-571500487_01</td>\n",
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" <td>571545870_01</td>\n",
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" <td>i0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>175</td>\n",
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" <td>2</td>\n",
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" <td>B</td>\n",
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" <td>3</td>\n",
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" <td>남</td>\n",
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" <td>서</td>\n",
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" <td>179</td>\n",
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" <td>270</td>\n",
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" <td>-571542797_02</td>\n",
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" <td>571510153_01</td>\n",
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" <td>i0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>175</td>\n",
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" <td>3</td>\n",
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" <td>A</td>\n",
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" <td>6</td>\n",
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" <td>동</td>\n",
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" <td>서</td>\n",
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" <td>090</td>\n",
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" <td>270</td>\n",
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" <td>571545870_02</td>\n",
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" <td>571510153_01</td>\n",
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" <td>i0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>...</th>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>210</td>\n",
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" <td>2</td>\n",
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" <td>B</td>\n",
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" <td>2</td>\n",
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" <td>서</td>\n",
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" <td>동</td>\n",
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" <td>270</td>\n",
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" <td>090</td>\n",
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <td>u60</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>210</td>\n",
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" <td>3</td>\n",
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" <td>A</td>\n",
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" <td>7</td>\n",
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" <td>북</td>\n",
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" <td>동</td>\n",
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" <td>359</td>\n",
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" <td>090</td>\n",
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <td>u60</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>5</th>\n",
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" <td>210</td>\n",
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" <td>3</td>\n",
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" <td>B</td>\n",
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" <td>4</td>\n",
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" <td>북</td>\n",
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" <td>남</td>\n",
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" <td>000</td>\n",
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" <td>180</td>\n",
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <td>u60</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>6</th>\n",
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" <td>210</td>\n",
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" <td>4</td>\n",
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" <td>A</td>\n",
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" <td>8</td>\n",
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" <td>남</td>\n",
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" <td>북</td>\n",
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" <td>180</td>\n",
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" <td>000</td>\n",
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <td>u60</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>7</th>\n",
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" <td>210</td>\n",
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" <td>4</td>\n",
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" <td>B</td>\n",
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" <td>3</td>\n",
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" <td>남</td>\n",
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" <td>서</td>\n",
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" <td>180</td>\n",
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" <td>270</td>\n",
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <td>u60</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"<p>116 rows × 11 columns</p>\n",
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"</div>"
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],
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"text/plain": [
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" inter_no phase_no ring_type move_no inc_dir out_dir inc_angle out_angle \\\n",
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"0 175 1 A 8 남 북 179 004 \n",
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"1 175 1 B 4 북 남 003 176 \n",
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"2 175 2 A 7 북 동 001 095 \n",
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"3 175 2 B 3 남 서 179 270 \n",
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"4 175 3 A 6 동 서 090 270 \n",
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".. ... ... ... ... ... ... ... ... \n",
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"3 210 2 B 2 서 동 270 090 \n",
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"4 210 3 A 7 북 동 359 090 \n",
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"5 210 3 B 4 북 남 000 180 \n",
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"6 210 4 A 8 남 북 180 000 \n",
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"7 210 4 B 3 남 서 180 270 \n",
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"\n",
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" inc_edge out_edge node_id \n",
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"0 -571542797_02 571500487_01 i0 \n",
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"1 -571500487_01 571542797_02 i0 \n",
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"2 -571500487_01 571545870_01 i0 \n",
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"3 -571542797_02 571510153_01 i0 \n",
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"4 571545870_02 571510153_01 i0 \n",
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".. ... ... ... \n",
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"3 NaN NaN u60 \n",
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"4 NaN NaN u60 \n",
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"5 NaN NaN u60 \n",
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"6 NaN NaN u60 \n",
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"7 NaN NaN u60 \n",
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"\n",
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"[116 rows x 11 columns]"
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]
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},
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"execution_count": 34,
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|
"metadata": {},
|
|
"output_type": "execute_result"
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}
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],
|
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"source": [
|
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"self.match6"
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]
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},
|
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"splits 딕셔너리 다시 만들기"
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]
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},
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{
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"cell_type": "code",
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|
"execution_count": 53,
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"metadata": {},
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"outputs": [
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|
{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"dura_A1 37\n",
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"dura_A2 39\n",
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"dura_A3 55\n",
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"dura_A4 29\n",
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"dura_A5 0\n",
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"dura_A6 0\n",
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"dura_A7 0\n",
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"dura_A8 0\n",
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"Name: 0, dtype: int64\n",
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"dura_B1 37\n",
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"dura_B2 39\n",
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"dura_B3 25\n",
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"dura_B4 59\n",
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"dura_B5 0\n",
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"dura_B6 0\n",
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"dura_B7 0\n",
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"dura_B8 0\n",
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"Name: 0, dtype: int64\n"
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]
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},
|
|
{
|
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"ename": "NameError",
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"evalue": "name 'dura_A' is not defined",
|
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"output_type": "error",
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"traceback": [
|
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"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[1;32mIn[53], line 11\u001b[0m\n\u001b[0;32m 9\u001b[0m duration_dict \u001b[38;5;241m=\u001b[39m {}\n\u001b[0;32m 10\u001b[0m \u001b[38;5;66;03m# 두 시리즈의 길이가 같다고 가정합니다.\u001b[39;00m\n\u001b[1;32m---> 11\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;28mlen\u001b[39m(\u001b[43mdura_A\u001b[49m)):\n\u001b[0;32m 12\u001b[0m \u001b[38;5;66;03m# A와 B의 현시간이 같은 경우\u001b[39;00m\n\u001b[0;32m 13\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m dura_A[i] \u001b[38;5;241m==\u001b[39m dura_B[i]:\n\u001b[0;32m 14\u001b[0m duration_dict[(i\u001b[38;5;241m+\u001b[39m\u001b[38;5;241m1\u001b[39m, i\u001b[38;5;241m+\u001b[39m\u001b[38;5;241m1\u001b[39m)] \u001b[38;5;241m=\u001b[39m dura_A[i]\n",
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"\u001b[1;31mNameError\u001b[0m: name 'dura_A' is not defined"
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]
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}
|
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],
|
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"source": [
|
|
"import numpy as np\n",
|
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"row = self.plan.iloc[0]\n",
|
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"inter_no = row.inter_no\n",
|
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"start_hour = row.start_hour\n",
|
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"start_minute = row.start_minute\n",
|
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"cycle = row.cycle\n",
|
|
"print(row[[f'dura_A{j}' for j in range(1,9)]])\n",
|
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"print(row[[f'dura_B{j}' for j in range(1,9)]])\n",
|
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"\n",
|
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"\n",
|
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"dura_A = row[[f'dura_A{j}' for j in range(1, 9)]]\n",
|
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"dura_B = row[[f'dura_B{j}' for j in range(1, 9)]]\n",
|
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"\n",
|
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"duration_dict = {}\n",
|
|
"# 두 시리즈의 길이가 같다고 가정합니다.\n",
|
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"for i in range(len(dura_A)):\n",
|
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" # A와 B의 현시간이 같은 경우\n",
|
|
" if dura_A[i] == dura_B[i]:\n",
|
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" duration_dict[(i+1, i+1)] = dura_A[i]\n",
|
|
" # A와 B의 현시간이 다른 경우\n",
|
|
" else:\n",
|
|
" duration_dict[(i+1, i+1)] = min(dura_A[i], dura_B[i])\n",
|
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" duration_dict[(i+1, i+2)] = max(dura_A[i], dura_B[i])\n",
|
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"\n",
|
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"print(duration_dict)\n",
|
|
"# cums_A = row[[f'dura_A{j}' for j in range(1,9)]].cumsum()\n",
|
|
"# cums_B = row[[f'dura_B{j}' for j in range(1,9)]].cumsum()\n",
|
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"# print(cums_A)\n",
|
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"# print(cums_B)\n",
|
|
"# detailed_cums = []\n",
|
|
"# combined_row = np.unique(np.concatenate((cums_A,cums_B)))\n",
|
|
"# print(combined_row)\n",
|
|
"# detailed_durations = np.concatenate(([combined_row[0]], np.diff(combined_row)))\n",
|
|
"# print(detailed_durations)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 38,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# split, isplit : A,B 분리 혹은 통합시 사용될 수 있는 딕셔너리 \n",
|
|
"self.splits = {} # splits maps (inter_no, start_hour, start_minute) to split \n",
|
|
"for i, row in self.plan.iterrows():\n",
|
|
" inter_no = row.inter_no\n",
|
|
" start_hour = row.start_hour\n",
|
|
" start_minute = row.start_minute\n",
|
|
" cycle = row.cycle\n",
|
|
" cums_A = row[[f'dura_A{j}' for j in range(1,9)]].cumsum()\n",
|
|
" cums_B = row[[f'dura_B{j}' for j in range(1,9)]].cumsum()\n",
|
|
" self.splits[(inter_no, start_hour, start_minute)] = {} # split maps (phas_A, phas_B) to k\n",
|
|
" k = 0\n",
|
|
" for t in range(cycle):\n",
|
|
" new_phas_A = len(cums_A[cums_A < t]) + 1\n",
|
|
" new_phas_B = len(cums_B[cums_B < t]) + 1\n",
|
|
" if k == 0 or ((new_phas_A, new_phas_B) != (phas_A, phas_B)):\n",
|
|
" k += 1\n",
|
|
" phas_A = new_phas_A\n",
|
|
" phas_B = new_phas_B\n",
|
|
" self.splits[(inter_no, start_hour, start_minute)][(phas_A, phas_B)] = k\n",
|
|
"self.isplits = {} # the inverse of splits\n",
|
|
"for i in self.splits:\n",
|
|
" self.isplits[i] = {self.splits[i][k]:k for k in self.splits[i]} # isplit maps k to (phas_A, phas_B)\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 49,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"{(175, 0, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (3, 4): 4, (4, 4): 5},\n",
|
|
" (175, 7, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (3, 4): 4, (4, 4): 5},\n",
|
|
" (175, 9, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (3, 4): 4, (4, 4): 5},\n",
|
|
" (175, 18, 30): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (3, 4): 4, (4, 4): 5},\n",
|
|
" (176, 0, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3},\n",
|
|
" (176, 7, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3},\n",
|
|
" (176, 9, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3},\n",
|
|
" (176, 18, 30): {(1, 1): 1, (2, 2): 2, (3, 3): 3},\n",
|
|
" (177, 0, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4},\n",
|
|
" (177, 7, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4},\n",
|
|
" (177, 9, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4},\n",
|
|
" (177, 18, 30): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4},\n",
|
|
" (178, 0, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4},\n",
|
|
" (178, 7, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 3): 4, (4, 4): 5},\n",
|
|
" (178, 9, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 3): 4, (4, 4): 5},\n",
|
|
" (178, 18, 30): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 3): 4, (4, 4): 5},\n",
|
|
" (201, 0, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4, (5, 5): 5},\n",
|
|
" (201, 7, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4, (5, 5): 5},\n",
|
|
" (201, 9, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4, (5, 5): 5},\n",
|
|
" (201, 18, 30): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4, (5, 5): 5},\n",
|
|
" (202, 0, 0): {(1, 1): 1, (2, 2): 2},\n",
|
|
" (202, 7, 0): {(1, 1): 1, (2, 2): 2},\n",
|
|
" (202, 9, 0): {(1, 1): 1, (2, 2): 2},\n",
|
|
" (202, 18, 30): {(1, 1): 1, (2, 2): 2},\n",
|
|
" (206, 0, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4},\n",
|
|
" (206, 7, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4},\n",
|
|
" (206, 9, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4},\n",
|
|
" (206, 18, 30): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4},\n",
|
|
" (210, 0, 0): {(1, 1): 1, (1, 2): 2, (2, 2): 3, (3, 3): 4, (4, 4): 5},\n",
|
|
" (210, 7, 0): {(1, 1): 1, (1, 2): 2, (2, 2): 3, (3, 3): 4, (4, 4): 5},\n",
|
|
" (210, 9, 0): {(1, 1): 1, (1, 2): 2, (2, 2): 3, (3, 3): 4, (4, 4): 5},\n",
|
|
" (210, 18, 30): {(1, 1): 1, (1, 2): 2, (2, 2): 3, (3, 3): 4, (4, 4): 5}}"
|
|
]
|
|
},
|
|
"execution_count": 49,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"self.splits"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "rts",
|
|
"language": "python",
|
|
"name": "rts"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.8.10"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
}
|