diff --git a/.gitignore b/.gitignore index bcf002e92..18420ac9e 100644 --- a/.gitignore +++ b/.gitignore @@ -1,7 +1,4 @@ Data/tables/move/* Intermediates/histid/* Intermediates/movement/* -Analysis/* -!Analysis/0712_revise_code/ -!Analysis/0709_fetch_tables/ test_0721/data/tables/move/* \ No newline at end of file diff --git a/Data/tables/20240730/.ipynb b/Data/tables/20240730/.ipynb new file mode 100644 index 000000000..473aa81e1 --- /dev/null +++ b/Data/tables/20240730/.ipynb @@ -0,0 +1,72 @@ +{ + "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 +} diff --git a/analysis/0725_main_test/5_go_through_gs.ipynb b/analysis/0725_main_test/5_go_through_gs.ipynb new file mode 100644 index 000000000..be811ef5a --- /dev/null +++ b/analysis/0725_main_test/5_go_through_gs.ipynb @@ -0,0 +1,396 @@ +{ + "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 +} diff --git a/analysis/0725_main_test/6_use_class_gs.ipynb b/analysis/0725_main_test/6_use_class_gs.ipynb new file mode 100644 index 000000000..b7ddea3b5 --- /dev/null +++ b/analysis/0725_main_test/6_use_class_gs.ipynb @@ -0,0 +1,3700 @@ +{ + "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, pickle\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('.')))\n", + "path_scr = os.path.join(path_root, 'scripts')\n", + "sys.path.append(path_scr)\n", + "from generate_signals import SignalGenerator" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "self = SignalGenerator(config_name='test_0729',\n", + " file_net='new_sungnam_network_internal_target_0721.net.xml',\n", + " month=7,\n", + " day=29,\n", + " hour=9,\n", + " minute=40)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1-1. 네트워크가 로드되었습니다.\n" + ] + } + ], + "source": [ + "self.load_networks()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1-2. 테이블들이 로드되었습니다.\n" + ] + } + ], + "source": [ + "self.load_tables()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'c:\\\\github\\\\siggen\\\\test_0729\\\\data\\\\tables'" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "self.path_tables\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "# dura_As = [f'dura_A{i}' for i in range(1,9)]\n", + "# dura_Bs = [f'dura_B{i}' for i in range(1,9)]\n", + "# for i, row in self.plan.iterrows():\n", + "# is_zero_A = (row[dura_As]==0).all()\n", + "# is_zero_B = (row[dura_Bs]==0).all()\n", + "# assert not (is_zero_A & is_zero_B)\n", + "# if is_zero_B:\n", + "# for j in range(1, 9):\n", + "# self.plan.at[i, f'dura_B{j}'] = row[f'dura_A{j}']\n", + "# if is_zero_A:\n", + "# for j in range(1, 9):\n", + "# self.plan.at[i, f'dura_A{j}'] = row[f'dura_B{j}']" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1-5. 필요한 보조 객체들이 모두 준비되었습니다.\n" + ] + } + ], + "source": [ + "self.prepare_auxiliaries()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2. 신호이력 테이블을 변환합니다.\n" + ] + } + ], + "source": [ + "self.process_history()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "c:\\github\\siggen\\test_0729\\data\\tables\\TL_IF_SIGL.csv\n" + ] + } + ], + "source": [ + "print(os.path.join(self.path_tables, 'TL_IF_SIGL.csv'))" + ] + }, + { + "cell_type": "code", + "execution_count": 98, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2024-07-29 09:36:32\n" + ] + } + ], + "source": [ + "time_str = '2024-07-29 9:36:32'\n", + "time_dt = datetime.strptime(time_str, '%Y-%m-%d %H:%M:%S')\n", + "print(time_dt)\n", + "time_unix = int(time_dt.timestamp())" + ] + }, + { + "cell_type": "code", + "execution_count": 103, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " start_unix inter_no phas_A phas_B STOS_NO move_A move_B\n", + "0 1722213392 436 3 3 0 7 4\n", + "1 1722213392 437 4 4 0 7 4\n", + "2 1722213392 438 3 3 0 8 3\n", + "3 1722213392 442 4 4 0 7 4\n", + "4 1722213392 443 1 1 0 6 2\n", + ".. ... ... ... ... ... ... ...\n", + "575 1722213450 444 4 4 0 -1 -1\n", + "576 1722213450 455 1 1 0 6 2\n", + "577 1722213450 456 2 2 0 6 2\n", + "578 1722213450 457 1 1 0 6 2\n", + "579 1722213450 458 1 1 0 8 4\n", + "\n", + "[580 rows x 7 columns]" + ] + }, + "execution_count": 103, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "phases = pd.read_csv(os.path.join(self.path_tables, 'TL_IF_SIGL.csv'))\n", + "phases = phases.drop(columns=['FRST_REG_DT', 'RINGA_FLOW', 'RINGB_FLOW'])\n", + "phases = phases.rename(columns={\n", + " 'PHASE_DT':'start_unix','CRSRD_ID':'inter_no',\n", + " 'RINGA_PHASE':'phas_A', 'RINGB_PHASE':'phas_B',\n", + " 'MAP_MODE':'STOS_NO'\n", + " })\n", + "isp2move_A = self.isp2move['A']\n", + "isp2move_B = self.isp2move['B']\n", + "phases['move_A'] = phases.apply(\n", + " lambda row: int(isp2move_A.get((row.inter_no, row.STOS_NO, row.phas_A), -1)), axis=1)\n", + "phases['move_B'] = phases.apply(\n", + " lambda row: int(isp2move_B.get((row.inter_no, row.STOS_NO, row.phas_B), -1)), axis=1)\n", + "phases['start_unix'] = phases['start_unix'].apply(lambda time_str:int(datetime.strptime(time_str, '%Y-%m-%d %H:%M:%S').timestamp()))" + ] + }, + { + "cell_type": "code", + "execution_count": 109, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1722213392\n", + "1722213450\n", + "1722213600\n" + ] + } + ], + "source": [ + "print(phases.start_unix.min())\n", + "print(phases.start_unix.max())\n", + "print(self.present_time)" + ] + }, + { + "cell_type": "code", + "execution_count": 117, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " start_unix inter_no phas_A phas_B STOS_NO move_A move_B \\\n", + "0 1722213392 436 3 3 0 7 4 \n", + "1 1722213392 437 4 4 0 7 4 \n", + "2 1722213392 438 3 3 0 8 3 \n", + "3 1722213392 442 4 4 0 7 4 \n", + "4 1722213392 443 1 1 0 6 2 \n", + "5 1722213392 444 3 3 0 -1 -1 \n", + "6 1722213392 455 1 1 0 6 2 \n", + "7 1722213392 456 4 4 0 17 -1 \n", + "8 1722213392 457 5 5 0 7 4 \n", + "9 1722213392 458 1 1 0 8 4 \n", + "10 1722213393 436 3 3 0 7 4 \n", + "11 1722213393 437 4 4 0 7 4 \n", + "12 1722213393 438 3 3 0 8 3 \n", + "13 1722213393 442 4 4 0 7 4 \n", + "14 1722213393 443 1 1 0 6 2 \n", + "15 1722213393 444 3 3 0 -1 -1 \n", + "16 1722213393 455 1 1 0 6 2 \n", + "17 1722213393 456 4 4 0 17 -1 \n", + "18 1722213393 457 5 5 0 7 4 \n", + "19 1722213393 458 1 1 0 8 4 \n", + "20 1722213394 436 3 3 0 7 4 \n", + "21 1722213394 437 4 4 0 7 4 \n", + "22 1722213394 438 3 3 0 8 3 \n", + "23 1722213394 442 4 4 0 7 4 \n", + "24 1722213394 443 1 1 0 6 2 \n", + "25 1722213394 444 3 3 0 -1 -1 \n", + "26 1722213394 455 1 1 0 6 2 \n", + "27 1722213394 456 4 4 0 17 -1 \n", + "28 1722213394 457 5 5 0 7 4 \n", + "29 1722213394 458 1 1 0 8 4 \n", + "30 1722213395 436 3 3 0 7 4 \n", + "31 1722213395 437 4 4 0 7 4 \n", + "32 1722213395 438 3 3 0 8 3 \n", + "33 1722213395 442 4 4 0 7 4 \n", + "34 1722213395 443 1 1 0 6 2 \n", + "35 1722213395 444 3 3 0 -1 -1 \n", + "36 1722213395 455 1 1 0 6 2 \n", + "37 1722213395 456 4 4 0 17 -1 \n", + "38 1722213395 457 5 5 0 7 4 \n", + "39 1722213395 458 1 1 0 8 4 \n", + "\n", + " start_unix \n", + "0 1.722213e+09 \n", + "1 1.722213e+09 \n", + "2 1.722213e+09 \n", + "3 1.722213e+09 \n", + "4 1.722213e+09 \n", + "5 NaN \n", + "6 1.722213e+09 \n", + "7 1.722213e+09 \n", + "8 1.722213e+09 \n", + "9 1.722213e+09 \n", + "10 1.722213e+09 \n", + "11 1.722213e+09 \n", + "12 1.722213e+09 \n", + "13 1.722213e+09 \n", + "14 1.722213e+09 \n", + "15 NaN \n", + "16 1.722213e+09 \n", + "17 1.722213e+09 \n", + "18 1.722213e+09 \n", + 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movement\u001b[38;5;241m.\u001b[39mdrop_duplicates([\u001b[38;5;124m'\u001b[39m\u001b[38;5;124minter_no\u001b[39m\u001b[38;5;124m'\u001b[39m,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mphas_A\u001b[39m\u001b[38;5;124m'\u001b[39m,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mphas_B\u001b[39m\u001b[38;5;124m'\u001b[39m,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mstart_unix\u001b[39m\u001b[38;5;124m'\u001b[39m])\n\u001b[0;32m 19\u001b[0m display(movement)\n\u001b[1;32m---> 20\u001b[0m movement \u001b[38;5;241m=\u001b[39m \u001b[43mmovement\u001b[49m\u001b[43m[\u001b[49m\u001b[43mmovement\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstart_unix\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m>\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mfsec\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msubtractor\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m]\u001b[49m\n", + "File \u001b[1;32mc:\\github\\siggen\\siggen_env\\Lib\\site-packages\\pandas\\core\\frame.py:4089\u001b[0m, in \u001b[0;36mDataFrame.__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m 4087\u001b[0m \u001b[38;5;66;03m# Do we have a (boolean) DataFrame?\u001b[39;00m\n\u001b[0;32m 4088\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(key, DataFrame):\n\u001b[1;32m-> 4089\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[43mwhere\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 4091\u001b[0m \u001b[38;5;66;03m# Do we have a (boolean) 1d indexer?\u001b[39;00m\n\u001b[0;32m 4092\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m com\u001b[38;5;241m.\u001b[39mis_bool_indexer(key):\n", + "File \u001b[1;32mc:\\github\\siggen\\siggen_env\\Lib\\site-packages\\pandas\\core\\generic.py:10984\u001b[0m, in \u001b[0;36mNDFrame.where\u001b[1;34m(self, cond, other, inplace, axis, level)\u001b[0m\n\u001b[0;32m 10977\u001b[0m warnings\u001b[38;5;241m.\u001b[39mwarn(\n\u001b[0;32m 10978\u001b[0m _chained_assignment_warning_method_msg,\n\u001b[0;32m 10979\u001b[0m \u001b[38;5;167;01mFutureWarning\u001b[39;00m,\n\u001b[0;32m 10980\u001b[0m stacklevel\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2\u001b[39m,\n\u001b[0;32m 10981\u001b[0m )\n\u001b[0;32m 10983\u001b[0m other \u001b[38;5;241m=\u001b[39m common\u001b[38;5;241m.\u001b[39mapply_if_callable(other, \u001b[38;5;28mself\u001b[39m)\n\u001b[1;32m> 10984\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_where\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcond\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mother\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minplace\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlevel\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[1;32mc:\\github\\siggen\\siggen_env\\Lib\\site-packages\\pandas\\core\\generic.py:10685\u001b[0m, in \u001b[0;36mNDFrame._where\u001b[1;34m(self, cond, other, inplace, axis, level, warn)\u001b[0m\n\u001b[0;32m 10682\u001b[0m cond \u001b[38;5;241m=\u001b[39m cond\u001b[38;5;241m.\u001b[39mastype(\u001b[38;5;28mbool\u001b[39m)\n\u001b[0;32m 10684\u001b[0m cond \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m-\u001b[39mcond \u001b[38;5;28;01mif\u001b[39;00m inplace \u001b[38;5;28;01melse\u001b[39;00m cond\n\u001b[1;32m> 10685\u001b[0m cond \u001b[38;5;241m=\u001b[39m \u001b[43mcond\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mreindex\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_info_axis\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_info_axis_number\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcopy\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[0;32m 10687\u001b[0m \u001b[38;5;66;03m# try to align with other\u001b[39;00m\n\u001b[0;32m 10688\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(other, NDFrame):\n\u001b[0;32m 10689\u001b[0m \u001b[38;5;66;03m# align with me\u001b[39;00m\n", + "File \u001b[1;32mc:\\github\\siggen\\siggen_env\\Lib\\site-packages\\pandas\\core\\frame.py:5378\u001b[0m, in \u001b[0;36mDataFrame.reindex\u001b[1;34m(self, labels, index, columns, axis, method, copy, level, fill_value, limit, tolerance)\u001b[0m\n\u001b[0;32m 5359\u001b[0m \u001b[38;5;129m@doc\u001b[39m(\n\u001b[0;32m 5360\u001b[0m NDFrame\u001b[38;5;241m.\u001b[39mreindex,\n\u001b[0;32m 5361\u001b[0m klass\u001b[38;5;241m=\u001b[39m_shared_doc_kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mklass\u001b[39m\u001b[38;5;124m\"\u001b[39m],\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 5376\u001b[0m tolerance\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[0;32m 5377\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m DataFrame:\n\u001b[1;32m-> 5378\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mreindex\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 5379\u001b[0m \u001b[43m \u001b[49m\u001b[43mlabels\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlabels\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 5380\u001b[0m \u001b[43m \u001b[49m\u001b[43mindex\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mindex\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 5381\u001b[0m \u001b[43m \u001b[49m\u001b[43mcolumns\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcolumns\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 5382\u001b[0m \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 5383\u001b[0m \u001b[43m \u001b[49m\u001b[43mmethod\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 5384\u001b[0m \u001b[43m \u001b[49m\u001b[43mcopy\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcopy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 5385\u001b[0m \u001b[43m \u001b[49m\u001b[43mlevel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlevel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 5386\u001b[0m \u001b[43m \u001b[49m\u001b[43mfill_value\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfill_value\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 5387\u001b[0m \u001b[43m \u001b[49m\u001b[43mlimit\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlimit\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 5388\u001b[0m \u001b[43m \u001b[49m\u001b[43mtolerance\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtolerance\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 5389\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[1;32mc:\\github\\siggen\\siggen_env\\Lib\\site-packages\\pandas\\core\\generic.py:5610\u001b[0m, in \u001b[0;36mNDFrame.reindex\u001b[1;34m(self, labels, index, columns, axis, method, copy, level, fill_value, limit, tolerance)\u001b[0m\n\u001b[0;32m 5607\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_reindex_multi(axes, copy, fill_value)\n\u001b[0;32m 5609\u001b[0m \u001b[38;5;66;03m# perform the reindex on the axes\u001b[39;00m\n\u001b[1;32m-> 5610\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_reindex_axes\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 5611\u001b[0m \u001b[43m \u001b[49m\u001b[43maxes\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlevel\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlimit\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtolerance\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfill_value\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcopy\u001b[49m\n\u001b[0;32m 5612\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39m__finalize__(\u001b[38;5;28mself\u001b[39m, method\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mreindex\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "File \u001b[1;32mc:\\github\\siggen\\siggen_env\\Lib\\site-packages\\pandas\\core\\generic.py:5633\u001b[0m, in \u001b[0;36mNDFrame._reindex_axes\u001b[1;34m(self, axes, level, limit, tolerance, method, fill_value, copy)\u001b[0m\n\u001b[0;32m 5630\u001b[0m \u001b[38;5;28;01mcontinue\u001b[39;00m\n\u001b[0;32m 5632\u001b[0m ax \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_get_axis(a)\n\u001b[1;32m-> 5633\u001b[0m new_index, indexer \u001b[38;5;241m=\u001b[39m \u001b[43max\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mreindex\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 5634\u001b[0m \u001b[43m \u001b[49m\u001b[43mlabels\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlevel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlevel\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlimit\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlimit\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtolerance\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtolerance\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmethod\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmethod\u001b[49m\n\u001b[0;32m 5635\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 5637\u001b[0m axis \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_get_axis_number(a)\n\u001b[0;32m 5638\u001b[0m obj \u001b[38;5;241m=\u001b[39m obj\u001b[38;5;241m.\u001b[39m_reindex_with_indexers(\n\u001b[0;32m 5639\u001b[0m {axis: [new_index, indexer]},\n\u001b[0;32m 5640\u001b[0m fill_value\u001b[38;5;241m=\u001b[39mfill_value,\n\u001b[0;32m 5641\u001b[0m copy\u001b[38;5;241m=\u001b[39mcopy,\n\u001b[0;32m 5642\u001b[0m allow_dups\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[0;32m 5643\u001b[0m )\n", + "File \u001b[1;32mc:\\github\\siggen\\siggen_env\\Lib\\site-packages\\pandas\\core\\indexes\\base.py:4429\u001b[0m, in \u001b[0;36mIndex.reindex\u001b[1;34m(self, target, method, level, limit, tolerance)\u001b[0m\n\u001b[0;32m 4426\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcannot handle a non-unique multi-index!\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m 4427\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mis_unique:\n\u001b[0;32m 4428\u001b[0m \u001b[38;5;66;03m# GH#42568\u001b[39;00m\n\u001b[1;32m-> 4429\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcannot reindex on an axis with duplicate labels\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m 4430\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m 4431\u001b[0m indexer, _ \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mget_indexer_non_unique(target)\n", + "\u001b[1;31mValueError\u001b[0m: cannot reindex on an axis with duplicate labels" + ] + } + ], + "source": [ + "for fsec in range(self.present_time - self.sim_timespan, self.present_time + 1, 5):\n", + " move = phases[phases.start_unix <= fsec]\n", + " if not len(move):\n", + " continue\n", + " recent_histories = [group.iloc[-1:] for _, group in self.history[self.history['end_unix'] < fsec].groupby('inter_no')] # 교차로별로 유닉스시간이 최대인 행들\n", + " if not recent_histories:\n", + " rhistory = pd.DataFrame({'inter_no':[], 'end_unix':[]}) # recent history\n", + " else:\n", + " rhistory = pd.concat(recent_histories)\n", + " recent_unix = rhistory[['inter_no', 'end_unix']]\n", + " move = pd.merge(move, recent_unix, how='left', on='inter_no')\n", + " move = move.rename(columns={'end_unix':'start_unix'})\n", + " try:\n", + " movement\n", + " except NameError:\n", + " movement = pd.DataFrame()\n", + " movement = pd.concat([movement, move])\n", + " movement = movement.drop_duplicates(['inter_no','phas_A','phas_B','start_unix'])\n", + " display(movement)\n", + " movement = movement[movement.start_unix > fsec - self.subtractor // 2]" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'movement' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[16], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[43mmovement\u001b[49m\n", + "\u001b[1;31mNameError\u001b[0m: name 'movement' is not defined" + ] + } + ], + "source": [ + "movement" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "3. 이동류정보 테이블을 변환합니다.\n" + ] + } + ], + "source": [ + "self.process_movement()" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[436, 437, 438, 442, 443, 455, 456, 457, 458]" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "self.inter_nos" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'heathcliff' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[41], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[43mheathcliff\u001b[49m \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n", + "\u001b[1;31mNameError\u001b[0m: name 'heathcliff' is not defined" + ] + } + ], + "source": [ + "if heathcliff is None:\n", + " print('heathcliff')" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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inter_nostart_unixphas_Aphas_Bmove_Amove_Bduration
04551.722212e+09116263
14551.722212e+09116263
24551.722212e+09116263
34551.722212e+09116263
44551.722213e+09116262
54551.722213e+09116263
64551.722213e+09116263
74551.722213e+09116263
84551.722213e+09116263
94551.722213e+09116264
104551.722213e+09116263
114551.722213e+09116263
124551.722213e+09116263
134551.722213e+09116263
144551.722213e+09116263
154551.722213e+09116263
164551.722213e+09116263
174551.722213e+09116263
184551.722213e+09116263
194551.722214e+09116263
204551.722214e+09116263
214561.722212e+09115215
224561.722212e+09226228
234561.722212e+09337712
244561.722212e+0944171735
254561.722213e+09115215
264561.722213e+09226228
274561.722213e+09337712
284561.722213e+0944171735
294561.722213e+09115215
304561.722213e+09226228
314561.722213e+09337712
324561.722213e+0944171735
334561.722213e+09115215
344561.722213e+09226228
354561.722213e+09337712
364561.722213e+0944171735
374561.722213e+09115215
384561.722213e+09226228
394561.722213e+09337712
404561.722213e+0944171735
414561.722213e+09115215
424561.722213e+09226228
434561.722213e+09337712
444561.722213e+0944171735
454561.722213e+09115215
464561.722213e+09226228
474561.722213e+09337712
484561.722213e+0944171735
494561.722213e+09115215
504561.722213e+09226228
514561.722213e+09337712
524561.722213e+0944171735
534561.722213e+09115215
544561.722213e+09226228
554561.722213e+09337712
564561.722213e+0944171735
574561.722213e+09115215
584561.722213e+09226228
594561.722213e+09337712
\n", + "
" + ], + "text/plain": [ + " inter_no start_unix phas_A phas_B move_A move_B duration\n", + "0 455 1.722212e+09 1 1 6 2 63\n", + "1 455 1.722212e+09 1 1 6 2 63\n", + "2 455 1.722212e+09 1 1 6 2 63\n", + "3 455 1.722212e+09 1 1 6 2 63\n", + "4 455 1.722213e+09 1 1 6 2 62\n", + "5 455 1.722213e+09 1 1 6 2 63\n", + "6 455 1.722213e+09 1 1 6 2 63\n", + "7 455 1.722213e+09 1 1 6 2 63\n", + "8 455 1.722213e+09 1 1 6 2 63\n", + "9 455 1.722213e+09 1 1 6 2 64\n", + "10 455 1.722213e+09 1 1 6 2 63\n", + "11 455 1.722213e+09 1 1 6 2 63\n", + "12 455 1.722213e+09 1 1 6 2 63\n", + "13 455 1.722213e+09 1 1 6 2 63\n", + "14 455 1.722213e+09 1 1 6 2 63\n", + "15 455 1.722213e+09 1 1 6 2 63\n", + "16 455 1.722213e+09 1 1 6 2 63\n", + "17 455 1.722213e+09 1 1 6 2 63\n", + "18 455 1.722213e+09 1 1 6 2 63\n", + "19 455 1.722214e+09 1 1 6 2 63\n", + "20 455 1.722214e+09 1 1 6 2 63\n", + "21 456 1.722212e+09 1 1 5 2 15\n", + "22 456 1.722212e+09 2 2 6 2 28\n", + "23 456 1.722212e+09 3 3 7 7 12\n", + "24 456 1.722212e+09 4 4 17 17 35\n", + "25 456 1.722213e+09 1 1 5 2 15\n", + "26 456 1.722213e+09 2 2 6 2 28\n", + "27 456 1.722213e+09 3 3 7 7 12\n", + "28 456 1.722213e+09 4 4 17 17 35\n", + "29 456 1.722213e+09 1 1 5 2 15\n", + "30 456 1.722213e+09 2 2 6 2 28\n", + "31 456 1.722213e+09 3 3 7 7 12\n", + "32 456 1.722213e+09 4 4 17 17 35\n", + "33 456 1.722213e+09 1 1 5 2 15\n", + "34 456 1.722213e+09 2 2 6 2 28\n", + "35 456 1.722213e+09 3 3 7 7 12\n", + "36 456 1.722213e+09 4 4 17 17 35\n", + "37 456 1.722213e+09 1 1 5 2 15\n", + "38 456 1.722213e+09 2 2 6 2 28\n", + "39 456 1.722213e+09 3 3 7 7 12\n", + "40 456 1.722213e+09 4 4 17 17 35\n", + "41 456 1.722213e+09 1 1 5 2 15\n", + "42 456 1.722213e+09 2 2 6 2 28\n", + "43 456 1.722213e+09 3 3 7 7 12\n", + "44 456 1.722213e+09 4 4 17 17 35\n", + "45 456 1.722213e+09 1 1 5 2 15\n", + "46 456 1.722213e+09 2 2 6 2 28\n", + "47 456 1.722213e+09 3 3 7 7 12\n", + "48 456 1.722213e+09 4 4 17 17 35\n", + "49 456 1.722213e+09 1 1 5 2 15\n", + "50 456 1.722213e+09 2 2 6 2 28\n", + "51 456 1.722213e+09 3 3 7 7 12\n", + "52 456 1.722213e+09 4 4 17 17 35\n", + "53 456 1.722213e+09 1 1 5 2 15\n", + "54 456 1.722213e+09 2 2 6 2 28\n", + "55 456 1.722213e+09 3 3 7 7 12\n", + "56 456 1.722213e+09 4 4 17 17 35\n", + "57 456 1.722213e+09 1 1 5 2 15\n", + "58 456 1.722213e+09 2 2 6 2 28\n", + "59 456 1.722213e+09 3 3 7 7 12" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "self.merge_dfs()\n", + "self.movedur[:60]" + ] + } + ], + "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 +} diff --git a/analysis/0730_make_history/0730_make_history.ipynb b/analysis/0730_make_history/0730_make_history.ipynb new file mode 100644 index 000000000..cf64611c1 --- /dev/null +++ b/analysis/0730_make_history/0730_make_history.ipynb @@ -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 +} diff --git a/test_0729/data/tables/TL_IF_SIGL.csv b/test_0729/data/tables/TL_IF_SIGL.csv new file mode 100644 index 000000000..7ca573feb --- /dev/null +++ b/test_0729/data/tables/TL_IF_SIGL.csv @@ -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 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14:59:10.000,455,63,27,0,0,0,0,0,0,0,0,0,0,0,0,0,0, +2024-07-29 14:59:20.000,458,148,32,0,0,0,0,0,0,0,0,0,0,0,0,0,0, +2024-07-29 14:59:30.000,457,45,20,40,40,35,0,0,0,45,20,40,40,35,0,0,0, +2024-07-29 15:00:00.000,438,125,50,25,0,0,0,0,0,125,50,25,0,0,0,0,0, diff --git a/test_0729/intermediates/isa2move.json b/test_0729/intermediates/isa2move.json new file mode 100644 index 000000000..d11380696 --- /dev/null +++ b/test_0729/intermediates/isa2move.json @@ -0,0 +1 @@ +{"A": { \ No newline at end of file diff --git a/test_0729/intermediates/isa2move.pkl b/test_0729/intermediates/isa2move.pkl new file mode 100644 index 000000000..4aad39d50 Binary files /dev/null and b/test_0729/intermediates/isa2move.pkl differ diff --git a/test_0729/intermediates/isp2move.pkl b/test_0729/intermediates/isp2move.pkl new file mode 100644 index 000000000..4aad39d50 Binary files /dev/null and b/test_0729/intermediates/isp2move.pkl differ