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      Data/tables/20240730/.ipynb
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Data/tables/move/*
Intermediates/histid/*
Intermediates/movement/*
Analysis/*
!Analysis/0712_revise_code/
!Analysis/0709_fetch_tables/
test_0721/data/tables/move/*

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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['.ipynb',\n",
" 'TC_IF_TOD_DAY_PLAN.csv',\n",
" 'TC_IF_TOD_HOLIDAY_PLAN.csv',\n",
" 'TC_IF_TOD_RED_YELLO.csv',\n",
" 'TC_IF_TOD_WEEK_PLAN.csv',\n",
" 'TL_IF_SIGL.csv',\n",
" 'TL_IF_SIGL_CYCL.csv',\n",
" 'TM_FA_CRSRD.csv',\n",
" 'TN_IF_SIGL_FLOW.csv']"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"os.listdir()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"pd.read_csv()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "siggen_env",
"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": "3.12.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}

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analysis/0725_main_test/5_go_through_gs.ipynb View File

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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import os, sys, json, argparse\n",
"import sumolib, traci\n",
"from tqdm import tqdm\n",
"from datetime import datetime\n",
"path_root = os.path.dirname(os.path.dirname(os.path.abspath('.')))"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"class SignalGenerator:\n",
" pass\n",
"self = SignalGenerator()\n",
"self.config_name = 'test_0729'\n",
"self.file_net = 'new_sungnam_network_internal_target_0721.net.xml'\n",
"self.month = 7\n",
"self.day = 29\n",
"self.hour = 9\n",
"self.minute = 25"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"# 루트폴더 지정\n",
"self.path_root = path_root\n",
"with open(os.path.join(self.path_root, 'configs', f'config_{self.config_name}.json'), 'r') as config_file:\n",
" config = json.load(config_file)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"# 주요 폴더 경로 지정\n",
"self.paths = config['paths']\n",
"self.path_data = os.path.join(self.path_root, *self.paths['data'])\n",
"self.path_intermediates = os.path.join(self.path_root, *self.paths['intermediates'])\n",
"self.path_results = os.path.join(self.path_root, *self.paths['results'])\n",
"self.path_tables = os.path.join(self.path_root, *self.paths['tables'])\n",
"self.path_networks = os.path.join(self.path_root, *self.paths['networks'])\n",
"self.path_scripts = os.path.join(self.path_root, *self.paths['scripts'])\n",
"\n",
"# 이슈사항 목록\n",
"self.issues = []"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"c:\\github\\siggen\\test_0729\\data\\tables\n"
]
}
],
"source": [
"print(self.path_tables)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"self.midnight = int(datetime(2024, self.month, self.day, 0, 0, 0).timestamp())\n",
"self.next_day = int(datetime(2024, self.month, self.day+1, 0, 0, 0).timestamp())\n",
"self.fsecs = range(self.midnight, self.next_day, 5) # fsecs : unix time by Five SECondS\n",
"self.fmins = range(self.midnight, self.next_day, 300) # fmins : unix time by Five MINuteS\n",
"\n",
"self.present_time = int(datetime(2024, self.month, self.day, self.hour, self.minute).timestamp())\n",
"self.present_time = max([fmin for fmin in list(self.fmins) if fmin <= self.present_time])\n",
"\n",
"self.sim_timespan = 300\n",
"self.adder = 600 # 10분 : '현재시점 + 10분'에 가상신호를 생성하기 위함.\n",
"self.subtractor = 1800 # 30분 : '현재시점 - 30분'의 신호이력을 가져온다."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"# 1-1. 네트워크 불러오기\n",
"self.net = sumolib.net.readNet(os.path.join(self.path_networks, self.file_net))"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"# cnames = []\n",
"# cnames.extend(list(self.inter_info))\n",
"# cnames.extend(list(self.plan))\n",
"# cnames.extend(list(self.history))\n",
"# cnames.extend(list(self.inter_node))\n",
"# cnames.extend(list(self.matching))\n",
"# cnames.extend(list(self.match1))\n",
"# cnames.extend(list(self.match6))\n",
"# sorted(set(cnames))"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"# 1-2. 테이블 불러오기\n",
"# 모든 컬럼에 대하여 데이터타입 지정\n",
"loading_dtype_1 = {\n",
" 'CRSRD_ID':int, 'FRST_REG_DT':str, 'LAST_MDFCN_DT':str,\n",
" 'OCRN_DT':str, 'cycle':int, 'group_no':str,\n",
" 'hh':int, 'inc_edge_id':str, 'inter_lat':float,\n",
" 'inter_lon':float, 'inter_name':str, 'inter_no':int,\n",
" 'inter_type':str, 'main_phase_no':str,'mm':int,\n",
" 'move_A':int, 'move_B':int, 'move_no':int,\n",
" 'node_id':str, 'offset':int, 'out_edge_id':str,\n",
" 'phas_A':int, 'phas_B':int, 'phase_no':int,\n",
" 'plan_no':int, 'ring_type':str, 'state':str,\n",
" 'turn_type':str\n",
" }\n",
"loading_dtype_2 = dict()\n",
"for alph in ['A', 'B']:\n",
" for j in range(1,9):\n",
" loading_dtype_2[f'RING{alph}_PHASE{j}'] = int\n",
" loading_dtype_2[f'dura_{alph}{j}'] = int\n",
" loading_dtype_2[f'red_{alph}{j}'] = int\n",
" loading_dtype_2[f'yellow_{alph}{j}'] = int\n",
"loading_dtype = {**loading_dtype_1, **loading_dtype_2}\n",
"\n",
"# 테이블 불러오기\n",
"self.inter_info = pd.read_csv(os.path.join(self.path_tables, 'inter_info.csv'), dtype=loading_dtype)\n",
"self.plan = pd.read_csv(os.path.join(self.path_tables, 'plan.csv'), dtype=loading_dtype)\n",
"self.history = pd.read_csv(os.path.join(self.path_tables, 'TL_IF_SIGL_CYCL.csv'), dtype=loading_dtype)\n",
"self.inter_node = pd.read_csv(os.path.join(self.path_tables, 'inter_node.csv'), dtype=loading_dtype)\n",
"self.matching = pd.read_csv(os.path.join(self.path_intermediates, 'matching.csv'), dtype=loading_dtype)\n",
"self.match1 = pd.read_csv(os.path.join(self.path_intermediates, 'match1.csv'), dtype=loading_dtype)\n",
"self.match6 = pd.read_csv(os.path.join(self.path_intermediates, 'match6.csv'), dtype=loading_dtype)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"# 컬럼명 변경 적용\n",
"self.history = self.history.rename(columns={'OCRN_DT':'end_unix', 'CRSRD_ID':'inter_no'})\n",
"self.history = self.history.rename(columns={f'RING{alph}_PHASE{i}':f'dura_{alph}{i}' for alph in ['A', 'B'] for i in range(1,9)})\n",
"self.history = self.history.drop(columns='FRST_REG_DT')\n",
"self.history['end_unix'] = pd.to_datetime(self.history['end_unix'])\n",
"self.history['end_unix'] = self.history['end_unix'].astype(int) // 10**9\n",
"self.plan = self.plan.rename(columns={'hh':'start_hour', 'mm':'start_minute'})"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"# 1-5. 보조 딕셔너리, 데이터프레임, 리스트 등 만들기\n",
"\n",
"# inter2node : a dictionary that maps inter_no to the node_id\n",
"inter_node_p = self.inter_node[self.inter_node.inter_type=='parent']\n",
"self.inter2node = dict(zip(inter_node_p['inter_no'], inter_node_p['node_id']))\n",
"self.node2inter = dict(zip(self.inter_node['node_id'], self.inter_node['inter_no']))\n",
"\n",
"# 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",
"\n",
" dura_A = np.array(row[[f'dura_A{j}' for j in range(1, 9)]])\n",
" dura_B = np.array(row[[f'dura_B{j}' for j in range(1, 9)]])\n",
"\n",
" cums_A = dura_A.cumsum()\n",
" cums_B = dura_B.cumsum()\n",
" combined_row = np.unique(np.concatenate((cums_A,cums_B)))\n",
" detailed_durations = np.concatenate(([combined_row[0]], np.diff(combined_row)))\n",
"\n",
" self.splits[(inter_no, start_hour, start_minute)] = {} # split maps (phas_A, phas_B) to k\n",
" ja = 0\n",
" jb = 0\n",
" for k in range(len(detailed_durations)):\n",
" dura_A[ja] -= detailed_durations[k]\n",
" dura_B[jb] -= detailed_durations[k]\n",
" self.splits[(inter_no, start_hour, start_minute)][(ja+1, jb+1)] = k+1\n",
" if dura_A[ja] == 0:\n",
" ja += 1\n",
" if dura_B[jb] == 0:\n",
" jb += 1\n",
"\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",
"\n",
"# timetable : 교차로별 프로그램 시작시각\n",
"self.timetable = self.plan[['start_hour', 'start_minute']].drop_duplicates()\n",
"self.timetable['start_seconds'] = self.midnight + self.timetable['start_hour'] * 3600 + self.timetable['start_minute'] * 60\n",
"\n",
"with open(os.path.join(self.path_intermediates, 'ids.json'), 'r') as file:\n",
" ids = json.load(file)\n",
"self.inter_nos = ids['inter_nos']\n",
"self.node_ids = ids['node_ids']\n",
"self.parent_ids = ids['parent_ids']\n",
"self.child_ids = ids['child_ids']\n",
"self.uturn_ids = ids['uturn_ids']\n",
"self.coord_ids = ids['coord_ids']\n",
"\n",
"# A dictionary that maps parent_id to a list of child_ids\n",
"self.pa2ch = {}\n",
"for parent_id in self.parent_ids:\n",
" inter_no = self.node2inter[parent_id]\n",
" self.pa2ch[parent_id] = list(self.inter_node[(self.inter_node.inter_no==inter_no) & (self.inter_node.inter_type=='child')].node_id)\n",
"\n",
"# node2num_cycles : A dictionary that maps a node_id to the number of cycles\n",
"with open(os.path.join(self.path_intermediates, 'node2num_cycles.json'), 'r') as file:\n",
" # json.load() 함수를 사용해 파일 내용을 Python 딕셔너리로 불러옵니다.\n",
" self.node2num_cycles = json.load(file)\n",
"\n",
"# 초기화신호 불러오기\n",
"with open(os.path.join(self.path_intermediates, 'node2init.json'), 'r') as file:\n",
" self.node2init = json.load(file) \n",
"\n",
"self.plan_set = self.plan.set_index(['inter_no','start_hour','start_minute'])"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"def load_prow(inter_no, time):\n",
" '''\n",
" load the planned row\n",
" '''\n",
" # 프로그램 시작시각\n",
" program_starts = np.array(self.timetable.start_seconds)\n",
" idx = (program_starts <= time).sum() - 1\n",
" program_start = program_starts[idx]\n",
"\n",
" # 최근 프로그램 시작시각에 대한 신호계획\n",
" start_hour = self.timetable.iloc[idx].start_hour\n",
" start_minute = self.timetable.iloc[idx].start_minute\n",
" # prow = self.plan[(self.plan.inter_no==inter_no) & (self.plan.start_hour==start_hour) & (self.plan.start_minute==start_minute)] # planned row\n",
" prow = self.plan_set.loc[(inter_no, start_hour, start_minute)]\n",
" prow = pd.DataFrame([prow],index=[0])\n",
" prow['inter_no'] = inter_no\n",
"\n",
" return program_start, prow\n"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"ename": "KeyError",
"evalue": "(np.int64(456), np.int64(6), np.int64(0))",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mKeyError\u001b[0m Traceback (most recent call last)",
"File \u001b[1;32mc:\\github\\siggen\\siggen_env\\Lib\\site-packages\\pandas\\core\\indexes\\multi.py:3220\u001b[0m, in \u001b[0;36mMultiIndex._get_loc_level\u001b[1;34m(self, key, level)\u001b[0m\n\u001b[0;32m 3219\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m-> 3220\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m (\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_engine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[0;32m 3221\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n",
"File \u001b[1;32mindex.pyx:776\u001b[0m, in \u001b[0;36mpandas._libs.index.BaseMultiIndexCodesEngine.get_loc\u001b[1;34m()\u001b[0m\n",
"File \u001b[1;32mindex.pyx:167\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[1;34m()\u001b[0m\n",
"File \u001b[1;32mindex.pyx:196\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[1;34m()\u001b[0m\n",
"File \u001b[1;32mpandas\\\\_libs\\\\hashtable_class_helper.pxi:2152\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.UInt64HashTable.get_item\u001b[1;34m()\u001b[0m\n",
"File \u001b[1;32mpandas\\\\_libs\\\\hashtable_class_helper.pxi:2176\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.UInt64HashTable.get_item\u001b[1;34m()\u001b[0m\n",
"\u001b[1;31mKeyError\u001b[0m: 594",
"\nThe above exception was the direct cause of the following exception:\n",
"\u001b[1;31mKeyError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[1;32mIn[16], line 24\u001b[0m\n\u001b[0;32m 22\u001b[0m \u001b[38;5;66;03m# present_time + adder 의 시각에 한 주기의 신호 추가\u001b[39;00m\n\u001b[0;32m 23\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m inter_no \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mset\u001b[39m(whole_inter_nos):\n\u001b[1;32m---> 24\u001b[0m program_start, prow \u001b[38;5;241m=\u001b[39m \u001b[43mload_prow\u001b[49m\u001b[43m(\u001b[49m\u001b[43minter_no\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpresent_time\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 25\u001b[0m cycle \u001b[38;5;241m=\u001b[39m prow\u001b[38;5;241m.\u001b[39mcycle\u001b[38;5;241m.\u001b[39miloc[\u001b[38;5;241m0\u001b[39m]\n\u001b[0;32m 26\u001b[0m row3 \u001b[38;5;241m=\u001b[39m prow\u001b[38;5;241m.\u001b[39mcopy()\n",
"Cell \u001b[1;32mIn[15], line 14\u001b[0m, in \u001b[0;36mload_prow\u001b[1;34m(inter_no, time)\u001b[0m\n\u001b[0;32m 12\u001b[0m start_minute \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtimetable\u001b[38;5;241m.\u001b[39miloc[idx]\u001b[38;5;241m.\u001b[39mstart_minute\n\u001b[0;32m 13\u001b[0m \u001b[38;5;66;03m# prow = self.plan[(self.plan.inter_no==inter_no) & (self.plan.start_hour==start_hour) & (self.plan.start_minute==start_minute)] # planned row\u001b[39;00m\n\u001b[1;32m---> 14\u001b[0m prow \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mplan_set\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mloc\u001b[49m\u001b[43m[\u001b[49m\u001b[43m(\u001b[49m\u001b[43minter_no\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstart_hour\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstart_minute\u001b[49m\u001b[43m)\u001b[49m\u001b[43m]\u001b[49m\n\u001b[0;32m 15\u001b[0m prow \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mDataFrame([prow],index\u001b[38;5;241m=\u001b[39m[\u001b[38;5;241m0\u001b[39m])\n\u001b[0;32m 16\u001b[0m prow[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124minter_no\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m inter_no\n",
"File \u001b[1;32mc:\\github\\siggen\\siggen_env\\Lib\\site-packages\\pandas\\core\\indexing.py:1184\u001b[0m, in \u001b[0;36m_LocationIndexer.__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m 1182\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_is_scalar_access(key):\n\u001b[0;32m 1183\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\u001b[38;5;241m.\u001b[39m_get_value(\u001b[38;5;241m*\u001b[39mkey, takeable\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_takeable)\n\u001b[1;32m-> 1184\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_tuple\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 1185\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m 1186\u001b[0m \u001b[38;5;66;03m# we by definition only have the 0th axis\u001b[39;00m\n\u001b[0;32m 1187\u001b[0m axis \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maxis \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;241m0\u001b[39m\n",
"File \u001b[1;32mc:\\github\\siggen\\siggen_env\\Lib\\site-packages\\pandas\\core\\indexing.py:1368\u001b[0m, in \u001b[0;36m_LocIndexer._getitem_tuple\u001b[1;34m(self, tup)\u001b[0m\n\u001b[0;32m 1366\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m suppress(IndexingError):\n\u001b[0;32m 1367\u001b[0m tup \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_expand_ellipsis(tup)\n\u001b[1;32m-> 1368\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_lowerdim\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtup\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 1370\u001b[0m \u001b[38;5;66;03m# no multi-index, so validate all of the indexers\u001b[39;00m\n\u001b[0;32m 1371\u001b[0m tup \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_validate_tuple_indexer(tup)\n",
"File \u001b[1;32mc:\\github\\siggen\\siggen_env\\Lib\\site-packages\\pandas\\core\\indexing.py:1057\u001b[0m, in \u001b[0;36m_LocationIndexer._getitem_lowerdim\u001b[1;34m(self, tup)\u001b[0m\n\u001b[0;32m 1047\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m (\n\u001b[0;32m 1048\u001b[0m \u001b[38;5;28misinstance\u001b[39m(ax0, MultiIndex)\n\u001b[0;32m 1049\u001b[0m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mname \u001b[38;5;241m!=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124miloc\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 1054\u001b[0m \u001b[38;5;66;03m# is equivalent.\u001b[39;00m\n\u001b[0;32m 1055\u001b[0m \u001b[38;5;66;03m# (see the other place where we call _handle_lowerdim_multi_index_axis0)\u001b[39;00m\n\u001b[0;32m 1056\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m suppress(IndexingError):\n\u001b[1;32m-> 1057\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mcast\u001b[49m\u001b[43m(\u001b[49m\u001b[43m_LocIndexer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_handle_lowerdim_multi_index_axis0\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtup\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 1059\u001b[0m tup \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_validate_key_length(tup)\n\u001b[0;32m 1061\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i, key \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(tup):\n",
"File \u001b[1;32mc:\\github\\siggen\\siggen_env\\Lib\\site-packages\\pandas\\core\\indexing.py:1394\u001b[0m, in \u001b[0;36m_LocIndexer._handle_lowerdim_multi_index_axis0\u001b[1;34m(self, tup)\u001b[0m\n\u001b[0;32m 1390\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m ek:\n\u001b[0;32m 1391\u001b[0m \u001b[38;5;66;03m# raise KeyError if number of indexers match\u001b[39;00m\n\u001b[0;32m 1392\u001b[0m \u001b[38;5;66;03m# else IndexingError will be raised\u001b[39;00m\n\u001b[0;32m 1393\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mndim \u001b[38;5;241m<\u001b[39m \u001b[38;5;28mlen\u001b[39m(tup) \u001b[38;5;241m<\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\u001b[38;5;241m.\u001b[39mindex\u001b[38;5;241m.\u001b[39mnlevels:\n\u001b[1;32m-> 1394\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m ek\n\u001b[0;32m 1395\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m IndexingError(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mNo label returned\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mek\u001b[39;00m\n",
"File \u001b[1;32mc:\\github\\siggen\\siggen_env\\Lib\\site-packages\\pandas\\core\\indexing.py:1388\u001b[0m, in \u001b[0;36m_LocIndexer._handle_lowerdim_multi_index_axis0\u001b[1;34m(self, tup)\u001b[0m\n\u001b[0;32m 1385\u001b[0m axis \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maxis \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;241m0\u001b[39m\n\u001b[0;32m 1386\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m 1387\u001b[0m \u001b[38;5;66;03m# fast path for series or for tup devoid of slices\u001b[39;00m\n\u001b[1;32m-> 1388\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_label\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtup\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maxis\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 1390\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m ek:\n\u001b[0;32m 1391\u001b[0m \u001b[38;5;66;03m# raise KeyError if number of indexers match\u001b[39;00m\n\u001b[0;32m 1392\u001b[0m \u001b[38;5;66;03m# else IndexingError will be raised\u001b[39;00m\n\u001b[0;32m 1393\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mndim \u001b[38;5;241m<\u001b[39m \u001b[38;5;28mlen\u001b[39m(tup) \u001b[38;5;241m<\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\u001b[38;5;241m.\u001b[39mindex\u001b[38;5;241m.\u001b[39mnlevels:\n",
"File \u001b[1;32mc:\\github\\siggen\\siggen_env\\Lib\\site-packages\\pandas\\core\\indexing.py:1381\u001b[0m, in \u001b[0;36m_LocIndexer._get_label\u001b[1;34m(self, label, axis)\u001b[0m\n\u001b[0;32m 1379\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_get_label\u001b[39m(\u001b[38;5;28mself\u001b[39m, label, axis: AxisInt):\n\u001b[0;32m 1380\u001b[0m \u001b[38;5;66;03m# GH#5567 this will fail if the label is not present in the axis.\u001b[39;00m\n\u001b[1;32m-> 1381\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mobj\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mxs\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlabel\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maxis\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[1;32mc:\\github\\siggen\\siggen_env\\Lib\\site-packages\\pandas\\core\\generic.py:4293\u001b[0m, in \u001b[0;36mNDFrame.xs\u001b[1;34m(self, key, axis, level, drop_level)\u001b[0m\n\u001b[0;32m 4290\u001b[0m index \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mindex\n\u001b[0;32m 4292\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(index, MultiIndex):\n\u001b[1;32m-> 4293\u001b[0m loc, new_index \u001b[38;5;241m=\u001b[39m \u001b[43mindex\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_loc_level\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlevel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[0;32m 4294\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m drop_level:\n\u001b[0;32m 4295\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m lib\u001b[38;5;241m.\u001b[39mis_integer(loc):\n\u001b[0;32m 4296\u001b[0m \u001b[38;5;66;03m# Slice index must be an integer or None\u001b[39;00m\n",
"File \u001b[1;32mc:\\github\\siggen\\siggen_env\\Lib\\site-packages\\pandas\\core\\indexes\\multi.py:3222\u001b[0m, in \u001b[0;36mMultiIndex._get_loc_level\u001b[1;34m(self, key, level)\u001b[0m\n\u001b[0;32m 3220\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_engine\u001b[38;5;241m.\u001b[39mget_loc(key), \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[0;32m 3221\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n\u001b[1;32m-> 3222\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(key) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01merr\u001b[39;00m\n\u001b[0;32m 3223\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m:\n\u001b[0;32m 3224\u001b[0m \u001b[38;5;66;03m# e.g. partial string indexing\u001b[39;00m\n\u001b[0;32m 3225\u001b[0m \u001b[38;5;66;03m# test_partial_string_timestamp_multiindex\u001b[39;00m\n\u001b[0;32m 3226\u001b[0m \u001b[38;5;28;01mpass\u001b[39;00m\n",
"\u001b[1;31mKeyError\u001b[0m: (np.int64(456), np.int64(6), np.int64(0))"
]
}
],
"source": [
"# 2. 신호이력 전처리\n",
"# 2-1. rhistory\n",
"\n",
"# 1. 조회시점의 유닉스 타임 이전의 신호이력 수집\n",
"self.rhistory = self.history.copy() # recent history\n",
"self.rhistory = self.rhistory[(self.rhistory.end_unix <= self.present_time) & (self.rhistory.end_unix > self.present_time - self.subtractor)]\n",
"\n",
"# rhistory에 모든 교차로번호가 존재하지 않으면 해당 교차로번호에 대한 신호이력을 추가함 (at 최근 프로그램 시작시각)\n",
"whole_inter_nos = set(self.history.inter_no.unique())\n",
"recent_inter_nos = set(self.rhistory.inter_no.unique())\n",
"if not whole_inter_nos==recent_inter_nos:\n",
" for inter_no in whole_inter_nos - recent_inter_nos:\n",
" program_start, prow = load_prow(inter_no, self.present_time - self.subtractor)\n",
" cycle = prow.cycle.iloc[0]\n",
" row1 = prow.copy()\n",
" row2 = prow.copy()\n",
" # prow에서 필요한 부분을 rhistory에 추가\n",
" row1['end_unix'] = program_start\n",
" row2['end_unix'] = program_start + cycle\n",
" self.rhistory = pd.concat([self.rhistory, row1, row2])#.reset_index(drop=True)\n",
"\n",
"# present_time + adder 의 시각에 한 주기의 신호 추가\n",
"for inter_no in set(whole_inter_nos):\n",
" program_start, prow = load_prow(inter_no, self.present_time)\n",
" cycle = prow.cycle.iloc[0]\n",
" row3 = prow.copy()\n",
" # prow에서 필요한 부분을 rhistory에 추가\n",
" row3['end_unix'] = self.present_time + self.adder\n",
" self.rhistory = pd.concat([self.rhistory, row3])#.reset_index(drop=True)\n",
"\n",
"# 2. 시작 유닉스 타임컬럼 생성 후 종류 유닉스 타임에서 현시별 현시기간 컬럼의 합을 뺀 값으로 입력\n",
"# - 현시시간의 합을 뺀 시간의 +- 10초 이내에 이전 주기정보가 존재하면 그 유닉스 시간을 시작 유닉스시간 값으로 하고, 존재하지 않으면 현시시간의 합을 뺀 유닉스 시간을 시작 유닉스 시간으로 지정\n",
"for i, row in self.rhistory.iterrows():\n",
" inter_no = row.inter_no\n",
" end_unix = row.end_unix\n",
" elapsed_time = row[[f'dura_{alph}{j}' for alph in ['A', 'B'] for j in range(1,9)]].sum() // 2 # 현시시간 합\n",
" # 이전 유닉스 존재하지 않음 : 현시시간 합의 차\n",
" start_unix = end_unix - elapsed_time\n",
" pre_rows = self.history[:i] # previous rows\n",
" if inter_no in pre_rows.inter_no.unique(): # 이전 유닉스 존재\n",
" pre_unix = pre_rows[pre_rows.inter_no == inter_no]['end_unix'].iloc[-1] # previous unix time\n",
" # 이전 유닉스 존재, abs < 10 : 이전 유닉스\n",
" if abs(pre_unix - start_unix) < 10:\n",
" start_unix = pre_unix\n",
" # 이전 유닉스 존재, abs >=10 : 현시시간 합의 차\n",
" else:\n",
" pass\n",
" self.rhistory.loc[i, 'start_unix'] = start_unix\n",
"self.rhistory[self.rhistory.isna()] = 0\n",
"self.rhistory['start_unix'] = self.rhistory['start_unix'].astype(int)\n",
"self.rhistory = self.rhistory[['inter_no', 'start_unix'] + [f'dura_{alph}{j}' for alph in ['A', 'B'] for j in range(1,9)] + ['cycle']]"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "siggen_env",
"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": "3.12.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}

+ 3700
- 0
analysis/0725_main_test/6_use_class_gs.ipynb
File diff suppressed because it is too large
View File


+ 144
- 0
analysis/0730_make_history/0730_make_history.ipynb View File

@ -0,0 +1,144 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import os, random, sumolib\n",
"import sumolib\n",
"import pandas as pd\n",
"import numpy as np\n",
"from datetime import datetime"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"path_root = os.path.dirname(os.path.dirname(os.path.abspath('.')))\n",
"path_dayplan = os.path.join(path_root, 'data', 'tables', '20240729', 'TC_IF_TOD_DAY_PLAN.csv')\n",
"path_sigl_cycl = os.path.join(path_root, 'test_0729', 'data', 'tables', 'TL_IF_SIGL_CYCL.csv')\n",
"dayplan = pd.read_csv(path_dayplan)\n",
"CRSRD_IDs = [436, 437, 438, 442, 443, 455, 456, 457, 458]\n",
"dayplan = dayplan[dayplan.CRSRD_ID.isin(CRSRD_IDs)]\n",
"\n",
"dayplan = dayplan.drop(columns=['LAST_MDFCN_DT'])"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"midnight = int(datetime(2024, 7, 29).timestamp())\n",
"next_day = int(datetime(2024, 7, 30).timestamp())\n",
"\n",
"histories = []\n",
"\n",
"for CRSRD_ID in CRSRD_IDs:\n",
" dplan = dayplan[dayplan.CRSRD_ID==CRSRD_ID]\n",
" if ((dplan.HOUR==0) & (dplan.MIN==0)).any():\n",
" pass\n",
" else:\n",
" dplan_temp = dplan[-1:]\n",
" dplan_temp['HOUR'] = 0\n",
" dplan_temp['MIN'] = 0\n",
" dplan = pd.concat([dplan, dplan_temp])\n",
" dplan = dplan.sort_values(by=['HOUR', 'MIN']).reset_index(drop=True)\n",
" dplan.loc[:, 'end_unix'] = dplan['HOUR'].astype(int) * 3600 + dplan['MIN'].astype(int) * 60 + midnight\n",
" history = []\n",
" current_time = midnight\n",
" for i in range(len(dplan)):\n",
" row = dplan.iloc[i]\n",
" cycle = row.CYCL\n",
" offset = row.OFFSET\n",
" unix_end = dplan.iloc[i+1]['end_unix'] if i < len(dplan) - 1 else next_day\n",
" r = 0\n",
" while current_time <= unix_end:\n",
" remainder = current_time % 10\n",
" if remainder != 0: # 현재시각의 일의자리가 0이 아니면 다음 현재시각의 일의자리가 0이 되도록 맞춰준다.\n",
" r = (5 - remainder) % 10 - 5 # 1>-1, 2>-2, 3>-3, 4>-4, 5>-5, 6>4, 7>3, 8>2, 9>1\n",
" else:\n",
" r = random.choices([0, -1, 1], weights=[10, 1, 1])[0] # 측정오차\n",
" # 0.001의 확률로 결측 발생\n",
" if random.random() < 0.001: # 주기의 배수만큼 결측\n",
" n = random.randint(0,100)\n",
" current_time += n * cycle + r\n",
" # 0.01의 확률로 이상치 발생\n",
" elif random.random() > 0.99: # 카이제곱분포값 * 주기만큼의 이상치 발생. 카이제곱분포값은 항상 양수이고 평균이 1\n",
" current_time += int(np.random.chisquare(df=1) * cycle) + r\n",
" else:\n",
" current_time += cycle + r # 결측/이상 없음\n",
" new_row = row.copy()\n",
" new_row['PHASE_DT'] = current_time\n",
" new_row['CYCL'] = cycle\n",
" new_row['OFFSET'] = offset\n",
" history.append(new_row)\n",
" history = pd.concat(history, axis=1).transpose()\n",
" history = history[['PHASE_DT', 'CRSRD_ID']\n",
" + [f'RING{alph}_PHASE{i}' for alph in ['A', 'B'] for i in range(1,9)]]\n",
" history = history[history.PHASE_DT <= next_day]\n",
" history = history.rename(columns={'PHASE_DT':'OCRN_DT'})\n",
" histories.append(history)\n",
"histories = pd.concat(histories)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"histories = histories.sort_values(by=['OCRN_DT', 'CRSRD_ID'])\n",
"histories = histories.reset_index(drop=True)\n",
"histories['FRST_REG_DT'] = ''\n",
"histories['OCRN_DT'] = pd.to_datetime(histories['OCRN_DT'], unit='s')\n",
"histories['OCRN_DT'] = histories['OCRN_DT'].dt.strftime('%Y-%m-%d %H:%M:%S.%f').str[:-3]\n",
"histories.to_csv(path_sigl_cycl, index=False)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"c:\\github\\siggen\\test_0729\\data\\tables\\TL_IF_SIGL_CYCL.csv\n"
]
}
],
"source": [
"print(path_sigl_cycl)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "siggen_env",
"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": "3.12.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}

+ 581
- 0
test_0729/data/tables/TL_IF_SIGL.csv View File

@ -0,0 +1,581 @@
PHASE_DT,CRSRD_ID,RINGA_PHASE,RINGA_FLOW,RINGB_PHASE,RINGB_FLOW,MAP_MODE,FRST_REG_DT
2024-07-29 9:36:32,436,3,7,3,4,0,36:32.8
2024-07-29 9:36:32,437,4,7,4,4,0,36:32.8
2024-07-29 9:36:32,438,3,8,3,3,0,36:32.8
2024-07-29 9:36:32,442,4,7,4,4,0,36:32.8
2024-07-29 9:36:32,443,1,6,1,2,0,36:32.8
2024-07-29 9:36:32,444,3,6,3,1,0,36:32.8
2024-07-29 9:36:32,455,1,6,1,2,0,36:32.8
2024-07-29 9:36:32,456,4,17,4,1,0,36:32.8
2024-07-29 9:36:32,457,5,7,5,4,0,36:32.8
2024-07-29 9:36:32,458,1,8,1,4,0,36:32.8
2024-07-29 9:36:33,436,3,7,3,4,0,36:32.8
2024-07-29 9:36:33,437,4,7,4,4,0,36:32.8
2024-07-29 9:36:33,438,3,8,3,3,0,36:32.8
2024-07-29 9:36:33,442,4,7,4,4,0,36:32.8
2024-07-29 9:36:33,443,1,6,1,2,0,36:32.8
2024-07-29 9:36:33,444,3,6,3,1,0,36:32.8
2024-07-29 9:36:33,455,1,6,1,2,0,36:32.8
2024-07-29 9:36:33,456,4,17,4,1,0,36:32.8
2024-07-29 9:36:33,457,5,7,5,4,0,36:32.8
2024-07-29 9:36:33,458,1,8,1,4,0,36:32.8
2024-07-29 9:36:34,436,3,7,3,4,0,36:33.7
2024-07-29 9:36:34,437,4,7,4,4,0,36:33.7
2024-07-29 9:36:34,438,3,8,3,3,0,36:33.7
2024-07-29 9:36:34,442,4,7,4,4,0,36:33.7
2024-07-29 9:36:34,443,1,6,1,2,0,36:33.7
2024-07-29 9:36:34,444,3,6,3,1,0,36:33.7
2024-07-29 9:36:34,455,1,6,1,2,0,36:33.7
2024-07-29 9:36:34,456,4,17,4,1,0,36:33.7
2024-07-29 9:36:34,457,5,7,5,4,0,36:33.7
2024-07-29 9:36:34,458,1,8,1,4,0,36:33.7
2024-07-29 9:36:36,436,3,7,3,4,0,36:35.7
2024-07-29 9:36:36,437,4,7,4,4,0,36:35.7
2024-07-29 9:36:36,438,3,8,3,3,0,36:35.7
2024-07-29 9:36:36,442,4,7,4,4,0,36:35.7
2024-07-29 9:36:36,443,1,6,1,2,0,36:35.7
2024-07-29 9:36:36,444,3,6,3,1,0,36:35.7
2024-07-29 9:36:36,455,1,6,1,2,0,36:35.7
2024-07-29 9:36:36,456,4,17,4,1,0,36:35.7
2024-07-29 9:36:36,457,5,7,5,4,0,36:35.7
2024-07-29 9:36:36,458,1,8,1,4,0,36:35.7
2024-07-29 9:36:37,436,3,7,3,4,0,36:36.7
2024-07-29 9:36:37,437,4,7,4,4,0,36:36.7
2024-07-29 9:36:37,438,3,8,3,3,0,36:36.7
2024-07-29 9:36:37,442,4,7,4,4,0,36:36.7
2024-07-29 9:36:37,443,1,6,1,2,0,36:36.7
2024-07-29 9:36:37,444,3,6,3,1,0,36:36.7
2024-07-29 9:36:37,455,2,1,2,1,0,36:36.7
2024-07-29 9:36:37,456,4,17,4,1,0,36:36.7
2024-07-29 9:36:37,457,5,7,5,4,0,36:36.7
2024-07-29 9:36:37,458,1,8,1,4,0,36:36.7
2024-07-29 9:36:35,436,3,7,3,4,0,36:34.7
2024-07-29 9:36:35,437,4,7,4,4,0,36:34.7
2024-07-29 9:36:35,438,3,8,3,3,0,36:34.7
2024-07-29 9:36:35,442,4,7,4,4,0,36:34.7
2024-07-29 9:36:35,443,1,6,1,2,0,36:34.7
2024-07-29 9:36:35,444,3,6,3,1,0,36:34.7
2024-07-29 9:36:35,455,1,6,1,2,0,36:34.7
2024-07-29 9:36:35,456,4,17,4,1,0,36:34.7
2024-07-29 9:36:35,457,5,7,5,4,0,36:34.7
2024-07-29 9:36:35,458,1,8,1,4,0,36:34.7
2024-07-29 9:36:38,436,3,7,3,4,0,36:37.7
2024-07-29 9:36:38,437,4,7,4,4,0,36:37.7
2024-07-29 9:36:38,438,3,8,3,3,0,36:37.7
2024-07-29 9:36:38,442,4,7,4,4,0,36:37.7
2024-07-29 9:36:38,443,1,6,1,2,0,36:37.7
2024-07-29 9:36:38,444,3,6,3,1,0,36:37.7
2024-07-29 9:36:38,455,2,1,2,1,0,36:37.7
2024-07-29 9:36:38,456,4,17,4,1,0,36:37.7
2024-07-29 9:36:38,457,5,7,5,4,0,36:37.7
2024-07-29 9:36:38,458,1,8,1,4,0,36:37.7
2024-07-29 9:36:39,436,3,7,3,4,0,36:38.7
2024-07-29 9:36:39,437,4,7,4,4,0,36:38.7
2024-07-29 9:36:39,438,3,8,3,3,0,36:38.7
2024-07-29 9:36:39,442,4,7,4,4,0,36:38.7
2024-07-29 9:36:39,443,1,6,1,2,0,36:38.7
2024-07-29 9:36:39,444,3,6,3,1,0,36:38.7
2024-07-29 9:36:39,455,2,1,2,1,0,36:38.7
2024-07-29 9:36:39,456,4,17,4,1,0,36:38.7
2024-07-29 9:36:39,457,5,7,5,4,0,36:38.7
2024-07-29 9:36:39,458,1,8,1,4,0,36:38.7
2024-07-29 9:36:42,436,3,7,3,4,0,36:41.7
2024-07-29 9:36:42,437,4,7,4,4,0,36:41.7
2024-07-29 9:36:42,438,3,8,3,3,0,36:41.7
2024-07-29 9:36:42,442,4,7,4,4,0,36:41.7
2024-07-29 9:36:42,443,1,6,1,2,0,36:41.7
2024-07-29 9:36:42,444,3,6,3,1,0,36:41.7
2024-07-29 9:36:42,455,2,1,2,1,0,36:41.7
2024-07-29 9:36:42,456,4,17,4,1,0,36:41.7
2024-07-29 9:36:42,457,5,7,5,4,0,36:41.7
2024-07-29 9:36:42,458,1,8,1,4,0,36:41.7
2024-07-29 9:36:40,436,3,7,3,4,0,36:39.8
2024-07-29 9:36:40,437,4,7,4,4,0,36:39.8
2024-07-29 9:36:40,438,3,8,3,3,0,36:39.8
2024-07-29 9:36:40,442,4,7,4,4,0,36:39.8
2024-07-29 9:36:40,443,1,6,1,2,0,36:39.8
2024-07-29 9:36:40,444,3,6,3,1,0,36:39.8
2024-07-29 9:36:40,455,2,1,2,1,0,36:39.8
2024-07-29 9:36:40,456,4,17,4,1,0,36:39.8
2024-07-29 9:36:40,457,5,7,5,4,0,36:39.8
2024-07-29 9:36:40,458,1,8,1,4,0,36:39.8
2024-07-29 9:36:41,436,3,7,3,4,0,36:40.7
2024-07-29 9:36:41,437,4,7,4,4,0,36:40.7
2024-07-29 9:36:41,438,3,8,3,3,0,36:40.7
2024-07-29 9:36:41,442,4,7,4,4,0,36:40.7
2024-07-29 9:36:41,443,1,6,1,2,0,36:40.7
2024-07-29 9:36:41,444,3,6,3,1,0,36:40.7
2024-07-29 9:36:41,455,2,1,2,1,0,36:40.7
2024-07-29 9:36:41,456,4,17,4,1,0,36:40.7
2024-07-29 9:36:41,457,5,7,5,4,0,36:40.7
2024-07-29 9:36:41,458,1,8,1,4,0,36:40.7
2024-07-29 9:36:43,436,3,7,3,4,0,36:42.8
2024-07-29 9:36:43,437,4,7,4,4,0,36:42.8
2024-07-29 9:36:43,438,1,6,1,2,0,36:42.8
2024-07-29 9:36:43,442,4,7,4,4,0,36:42.8
2024-07-29 9:36:43,443,1,6,1,2,0,36:42.8
2024-07-29 9:36:43,444,3,6,3,1,0,36:42.8
2024-07-29 9:36:43,455,2,1,2,1,0,36:42.8
2024-07-29 9:36:43,456,4,17,4,1,0,36:42.8
2024-07-29 9:36:43,457,5,7,5,4,0,36:42.8
2024-07-29 9:36:43,458,1,8,1,4,0,36:42.8
2024-07-29 9:36:45,436,3,7,3,4,0,36:44.8
2024-07-29 9:36:45,437,4,7,4,4,0,36:44.8
2024-07-29 9:36:45,438,1,6,1,2,0,36:44.8
2024-07-29 9:36:45,442,4,7,4,4,0,36:44.8
2024-07-29 9:36:45,443,1,6,1,2,0,36:44.8
2024-07-29 9:36:45,444,3,6,3,1,0,36:44.8
2024-07-29 9:36:45,455,2,1,2,1,0,36:44.8
2024-07-29 9:36:45,456,4,17,4,1,0,36:44.8
2024-07-29 9:36:45,457,5,7,5,4,0,36:44.8
2024-07-29 9:36:45,458,1,8,1,4,0,36:44.8
2024-07-29 9:36:44,436,3,7,3,4,0,36:43.8
2024-07-29 9:36:44,437,4,7,4,4,0,36:43.8
2024-07-29 9:36:44,438,1,6,1,2,0,36:43.8
2024-07-29 9:36:44,442,4,7,4,4,0,36:43.8
2024-07-29 9:36:44,443,1,6,1,2,0,36:43.8
2024-07-29 9:36:44,444,3,6,3,1,0,36:43.8
2024-07-29 9:36:44,455,2,1,2,1,0,36:43.8
2024-07-29 9:36:44,456,4,17,4,1,0,36:43.8
2024-07-29 9:36:44,457,5,7,5,4,0,36:43.8
2024-07-29 9:36:44,458,1,8,1,4,0,36:43.8
2024-07-29 9:36:47,436,4,6,4,1,0,36:46.8
2024-07-29 9:36:47,437,1,6,1,2,0,36:46.8
2024-07-29 9:36:47,438,1,6,1,2,0,36:46.8
2024-07-29 9:36:47,442,4,7,4,4,0,36:46.8
2024-07-29 9:36:47,443,1,6,1,2,0,36:46.8
2024-07-29 9:36:47,444,3,6,3,1,0,36:46.8
2024-07-29 9:36:47,455,2,1,2,1,0,36:46.8
2024-07-29 9:36:47,456,4,17,4,1,0,36:46.8
2024-07-29 9:36:47,457,5,7,5,4,0,36:46.8
2024-07-29 9:36:47,458,1,8,1,4,0,36:46.8
2024-07-29 9:36:48,436,4,6,4,1,0,36:47.8
2024-07-29 9:36:48,437,1,6,1,2,0,36:47.8
2024-07-29 9:36:48,438,1,6,1,2,0,36:47.8
2024-07-29 9:36:48,442,4,7,4,4,0,36:47.8
2024-07-29 9:36:48,443,1,6,1,2,0,36:47.8
2024-07-29 9:36:48,444,3,6,3,1,0,36:47.8
2024-07-29 9:36:48,455,2,1,2,1,0,36:47.8
2024-07-29 9:36:48,456,4,17,4,1,0,36:47.8
2024-07-29 9:36:48,457,5,7,5,4,0,36:47.8
2024-07-29 9:36:48,458,1,8,1,4,0,36:47.8
2024-07-29 9:36:46,436,4,6,4,1,0,36:45.8
2024-07-29 9:36:46,437,4,7,4,4,0,36:45.8
2024-07-29 9:36:46,438,1,6,1,2,0,36:45.8
2024-07-29 9:36:46,442,4,7,4,4,0,36:45.8
2024-07-29 9:36:46,443,1,6,1,2,0,36:45.8
2024-07-29 9:36:46,444,3,6,3,1,0,36:45.8
2024-07-29 9:36:46,455,2,1,2,1,0,36:45.8
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2024-07-29 9:37:14,458,1,8,1,4,0,37:13.9
2024-07-29 9:37:15,436,4,6,4,1,0,37:14.8
2024-07-29 9:37:15,437,1,6,1,2,0,37:14.8
2024-07-29 9:37:15,438,1,6,1,2,0,37:14.8
2024-07-29 9:37:15,442,5,8,5,3,0,37:14.8
2024-07-29 9:37:15,443,2,5,2,2,0,37:14.8
2024-07-29 9:37:15,444,4,7,4,4,0,37:14.8
2024-07-29 9:37:15,455,1,6,1,2,0,37:14.8
2024-07-29 9:37:15,456,2,6,2,2,0,37:14.8
2024-07-29 9:37:15,457,1,6,1,2,0,37:14.8
2024-07-29 9:37:15,458,1,8,1,4,0,37:14.8
2024-07-29 9:37:16,436,4,6,4,1,0,37:15.8
2024-07-29 9:37:16,437,1,6,1,2,0,37:15.8
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2024-07-29 9:37:16,442,5,8,5,3,0,37:15.8
2024-07-29 9:37:16,443,2,5,2,2,0,37:15.8
2024-07-29 9:37:16,444,4,7,4,4,0,37:15.8
2024-07-29 9:37:16,455,1,6,1,2,0,37:15.8
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2024-07-29 9:37:16,457,1,6,1,2,0,37:15.8
2024-07-29 9:37:16,458,1,8,1,4,0,37:15.8
2024-07-29 9:37:17,436,1,5,1,2,0,37:16.8
2024-07-29 9:37:17,437,1,6,1,2,0,37:16.8
2024-07-29 9:37:17,438,1,6,1,2,0,37:16.8
2024-07-29 9:37:17,442,5,8,5,3,0,37:16.8
2024-07-29 9:37:17,443,2,5,2,2,0,37:16.8
2024-07-29 9:37:17,444,4,7,4,4,0,37:16.8
2024-07-29 9:37:17,455,1,6,1,2,0,37:16.8
2024-07-29 9:37:17,456,2,6,2,2,0,37:16.8
2024-07-29 9:37:17,457,1,6,1,2,0,37:16.8
2024-07-29 9:37:17,458,1,8,1,4,0,37:16.8
2024-07-29 9:37:21,436,1,5,1,2,0,37:19.8
2024-07-29 9:37:21,437,1,6,1,2,0,37:19.8
2024-07-29 9:37:21,438,1,6,1,2,0,37:19.8
2024-07-29 9:37:21,442,5,8,5,3,0,37:19.8
2024-07-29 9:37:21,443,2,5,2,2,0,37:19.8
2024-07-29 9:37:21,444,4,7,4,4,0,37:19.8
2024-07-29 9:37:21,455,1,6,1,2,0,37:19.8
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2024-07-29 9:37:21,457,1,6,1,2,0,37:19.8
2024-07-29 9:37:21,458,1,8,1,4,0,37:19.8
2024-07-29 9:37:22,436,1,5,1,2,0,37:20.8
2024-07-29 9:37:22,437,1,6,1,2,0,37:20.8
2024-07-29 9:37:22,438,1,6,1,2,0,37:20.8
2024-07-29 9:37:22,442,5,8,5,3,0,37:20.8
2024-07-29 9:37:22,443,2,5,2,2,0,37:20.8
2024-07-29 9:37:22,444,4,7,4,4,0,37:20.8
2024-07-29 9:37:22,455,1,6,1,2,0,37:20.8
2024-07-29 9:37:22,456,2,6,2,2,0,37:20.8
2024-07-29 9:37:22,457,1,6,1,2,0,37:20.8
2024-07-29 9:37:22,458,1,8,1,4,0,37:20.8
2024-07-29 9:37:23,436,1,5,1,2,0,37:21.8
2024-07-29 9:37:23,437,1,6,1,2,0,37:21.8
2024-07-29 9:37:23,438,1,6,1,2,0,37:21.8
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2024-07-29 9:37:23,444,4,7,4,4,0,37:21.8
2024-07-29 9:37:23,455,1,6,1,2,0,37:21.8
2024-07-29 9:37:23,456,2,6,2,2,0,37:21.8
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2024-07-29 9:37:23,458,1,8,1,4,0,37:21.8
2024-07-29 9:37:24,436,1,5,1,2,0,37:22.9
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2024-07-29 9:37:24,438,1,6,1,2,0,37:22.9
2024-07-29 9:37:24,442,5,8,5,3,0,37:22.9
2024-07-29 9:37:24,443,2,5,2,2,0,37:22.9
2024-07-29 9:37:24,444,4,7,4,4,0,37:22.9
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2024-07-29 9:37:24,456,2,6,2,2,0,37:22.9
2024-07-29 9:37:24,457,1,6,1,2,0,37:22.9
2024-07-29 9:37:24,458,1,8,1,4,0,37:22.9
2024-07-29 9:37:25,436,1,5,1,2,0,37:23.9
2024-07-29 9:37:25,437,1,6,1,2,0,37:23.9
2024-07-29 9:37:25,438,1,6,1,2,0,37:23.9
2024-07-29 9:37:25,442,5,8,5,3,0,37:23.9
2024-07-29 9:37:25,443,2,5,2,2,0,37:23.9
2024-07-29 9:37:25,444,4,7,4,4,0,37:23.9
2024-07-29 9:37:25,455,1,6,1,2,0,37:23.9
2024-07-29 9:37:25,456,2,6,2,2,0,37:23.9
2024-07-29 9:37:25,457,1,6,1,2,0,37:23.9
2024-07-29 9:37:25,458,1,8,1,4,0,37:23.9
2024-07-29 9:37:26,436,1,5,1,2,0,37:24.8
2024-07-29 9:37:26,437,1,6,1,2,0,37:24.8
2024-07-29 9:37:26,438,1,6,1,2,0,37:24.8
2024-07-29 9:37:26,442,5,8,5,3,0,37:24.8
2024-07-29 9:37:26,443,2,5,2,2,0,37:24.8
2024-07-29 9:37:26,444,4,7,4,4,0,37:24.8
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2024-07-29 9:37:26,456,2,6,2,2,0,37:24.8
2024-07-29 9:37:26,457,1,6,1,2,0,37:24.8
2024-07-29 9:37:26,458,1,8,1,4,0,37:24.8
2024-07-29 9:37:27,436,1,5,1,2,0,37:25.8
2024-07-29 9:37:27,437,1,6,1,2,0,37:25.8
2024-07-29 9:37:27,438,1,6,1,2,0,37:25.8
2024-07-29 9:37:27,442,5,8,5,3,0,37:25.8
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2024-07-29 9:37:27,444,4,7,4,4,0,37:25.8
2024-07-29 9:37:27,455,1,6,1,2,0,37:25.8
2024-07-29 9:37:27,456,2,6,2,2,0,37:25.8
2024-07-29 9:37:27,457,1,6,1,2,0,37:25.8
2024-07-29 9:37:27,458,1,8,1,4,0,37:25.8
2024-07-29 9:37:28,436,1,5,1,2,0,37:26.9
2024-07-29 9:37:28,437,1,6,1,2,0,37:26.9
2024-07-29 9:37:28,438,1,6,1,2,0,37:26.9
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2024-07-29 9:37:28,443,2,5,2,2,0,37:26.9
2024-07-29 9:37:28,444,4,7,4,4,0,37:26.9
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2024-07-29 9:37:28,457,1,6,1,2,0,37:26.9
2024-07-29 9:37:28,458,1,8,1,4,0,37:26.9
2024-07-29 9:37:29,436,1,5,1,2,0,37:27.9
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2024-07-29 9:37:29,438,1,6,1,2,0,37:27.9
2024-07-29 9:37:29,442,5,8,5,3,0,37:27.9
2024-07-29 9:37:29,443,2,5,2,2,0,37:27.9
2024-07-29 9:37:29,444,4,7,4,4,0,37:27.9
2024-07-29 9:37:29,455,1,6,1,2,0,37:27.9
2024-07-29 9:37:29,456,2,6,2,2,0,37:27.9
2024-07-29 9:37:29,457,1,6,1,2,0,37:27.9
2024-07-29 9:37:29,458,1,8,1,4,0,37:27.9
2024-07-29 9:37:18,436,1,5,1,2,0,37:17.8
2024-07-29 9:37:18,437,1,6,1,2,0,37:17.8
2024-07-29 9:37:18,438,1,6,1,2,0,37:17.8
2024-07-29 9:37:18,442,5,8,5,3,0,37:17.8
2024-07-29 9:37:18,443,2,5,2,2,0,37:17.8
2024-07-29 9:37:18,444,4,7,4,4,0,37:17.8
2024-07-29 9:37:18,455,1,6,1,2,0,37:17.8
2024-07-29 9:37:18,456,2,6,2,2,0,37:17.8
2024-07-29 9:37:18,457,1,6,1,2,0,37:17.8
2024-07-29 9:37:18,458,1,8,1,4,0,37:17.8
2024-07-29 9:37:19,436,1,5,1,2,0,37:18.9
2024-07-29 9:37:19,437,1,6,1,2,0,37:18.9
2024-07-29 9:37:19,438,1,6,1,2,0,37:18.9
2024-07-29 9:37:19,442,5,8,5,3,0,37:18.9
2024-07-29 9:37:19,443,2,5,2,2,0,37:18.9
2024-07-29 9:37:19,444,4,7,4,4,0,37:18.9
2024-07-29 9:37:19,455,1,6,1,2,0,37:18.9
2024-07-29 9:37:19,456,2,6,2,2,0,37:18.9
2024-07-29 9:37:19,457,1,6,1,2,0,37:18.9
2024-07-29 9:37:19,458,1,8,1,4,0,37:18.9
2024-07-29 9:37:30,436,1,5,1,2,0,37:28.9
2024-07-29 9:37:30,437,1,6,1,2,0,37:28.9
2024-07-29 9:37:30,438,1,6,1,2,0,37:28.9
2024-07-29 9:37:30,442,5,8,5,3,0,37:28.9
2024-07-29 9:37:30,443,2,5,2,2,0,37:28.9
2024-07-29 9:37:30,444,4,7,4,4,0,37:28.9
2024-07-29 9:37:30,455,1,6,1,2,0,37:28.9
2024-07-29 9:37:30,456,2,6,2,2,0,37:28.9
2024-07-29 9:37:30,457,1,6,1,2,0,37:28.9
2024-07-29 9:37:30,458,1,8,1,4,0,37:28.9

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{"A": {

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