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250 lines
6.8 KiB
250 lines
6.8 KiB
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 19,
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"import numpy as np\n",
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"import os, sys, json, argparse, pickle\n",
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"import sumolib, traci\n",
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"from tqdm import tqdm\n",
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"from datetime import datetime, timedelta\n",
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"import pandas as pd\n",
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"import numpy as np\n",
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"import os, sys, copy, argparse, json, pickle\n",
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"import sumolib, traci\n",
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"from tqdm import tqdm\n",
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"from datetime import datetime\n",
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"\n",
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"\n",
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"path_root = os.path.dirname(os.path.dirname(os.path.abspath('.')))\n",
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"path_scr = os.path.join(path_root, 'scripts')\n",
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"sys.path.append(path_scr)\n",
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"from preprocess_daily import DailyPreprocessor"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 22,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"1. 데이터를 로드합니다.\n",
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"1-1. 네트워크가 로드되었습니다.\n",
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"1-2. 테이블들이 로드되었습니다.\n",
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"1-5. 테이블을 표준화했습니다.\n",
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"1-6. 주요 객체 (리스트, 딕셔너리)들을 저장했습니다.\n"
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]
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}
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],
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"source": [
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"self = DailyPreprocessor(config_name='test_0731')\n",
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"self.load_data()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 23,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"2. 중간산출물을 생성합니다.\n",
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"2-1. 매칭 테이블들을 생성했습니다.\n",
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"2-2. 초기화 신호가 지정되었습니다. (우회전 : g)\n",
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"2-3. 유턴 인덱스 / 비보호좌회전 인덱스를 지정했습니다.\n",
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"2-4. 직진 및 좌회전(G)을 배정했습니다.\n",
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"2-5. 모든 현시에서 적색신호인 경우에 대한 처리 완료\n",
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"2-6. node2num_cycles.json를 저장했습니다.\n"
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]
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}
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],
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"source": [
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"self.get_intermediates()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 26,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"40 gGGGgrrrrrgggggrrrrrrrgrrrr\n",
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"41 grrrgGGrrrgggggrrrrrrrgrrrr\n",
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"42 gGGGgrrrrrgggggrrrrrrrgrrrr\n",
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"43 grrrgrrrrrgggggGGGGGrrgrrrr\n",
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"44 grrrgrrrrrgggggrrrrrGGgrrrr\n",
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"45 grrrgrrrrrgggggGGGGGrrgrrrr\n",
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"46 grrrgrrrrrgggggrrrrrrrgrrrG\n",
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"47 grrrgrrrrrgggggrrrrrrrgGGGr\n",
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"48 grrrgrrGGrgggggrrrrrrrgrrrr\n",
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"49 grrrgrrrrGgggggrrrrrrrgrrrr\n",
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"50 grrrgrrGGrgggggrrrrrrrgrrrr\n",
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"51 grrrgrrrrGgggggrrrrrrrgrrrr\n",
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"Name: state, dtype: object"
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]
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},
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"execution_count": 26,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# match6 = pd.read_csv(os.path.join(path_root, 'test_0731', 'intermediates', 'match6.csv'), index_col=0)\n",
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"m6 = self.match6[self.match6.node_id=='106332']\n",
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"m6.state"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"1. 데이터를 준비합니다.\n",
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"1-1. 네트워크가 로드되었습니다.\n",
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"1-2. 테이블들이 로드되었습니다.\n",
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"1-5. 필요한 보조 객체들이 모두 준비되었습니다.\n"
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]
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}
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],
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"source": [
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"self = SignalGenerator(config_name='test_0731')\n",
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"self.prepare_data()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"40 gGGGrrrrrrgrrgrrrrrrrrgrrrr\n",
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"41 grrrrGGrrrgrrgrrrrrrrrgrrrr\n",
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"42 gGGGrrrrrrgrrgrrrrrrrrgrrrr\n",
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"43 grrrrrrrrrgrrgrGGGGGrrgrrrr\n",
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"44 grrrrrrrrrgrrgrrrrrrGGgrrrr\n",
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"45 grrrrrrrrrgrrgrGGGGGrrgrrrr\n",
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"46 grrrrrrrrrgrrgrrrrrrrrgrrrG\n",
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"47 grrrrrrrrrgrrgrrrrrrrrgGGGr\n",
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"48 grrrrrrGGrgrrgrrrrrrrrgrrrr\n",
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"49 grrrrrrrrGgrrgrrrrrrrrgrrrr\n",
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"50 grrrrrrGGrgrrgrrrrrrrrgrrrr\n",
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"51 grrrrrrrrGgrrgrrrrrrrrgrrrr\n",
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"Name: state, dtype: object"
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]
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},
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"execution_count": 18,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"match6 = pd.read_csv(os.path.join(path_root, 'test_0731', 'intermediates', 'match6.csv'), index_col=0)\n",
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"m6 = self.match6[self.match6.node_id=='106332']\n",
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"m6.state"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"40 gGGGrrrrrrgrrgrrrrrrrrgrrrr\n",
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"41 grrrrGGrrrgrrgrrrrrrrrgrrrr\n",
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"42 gGGGrrrrrrgrrgrrrrrrrrgrrrr\n",
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"43 grrrrrrrrrgrrgrGGGGGrrgrrrr\n",
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"44 grrrrrrrrrgrrgrrrrrrGGgrrrr\n",
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"45 grrrrrrrrrgrrgrGGGGGrrgrrrr\n",
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"46 grrrrrrrrrgrrgrrrrrrrrgrrrG\n",
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"47 grrrrrrrrrgrrgrrrrrrrrgGGGr\n",
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"48 grrrrrrGGrgrrgrrrrrrrrgrrrr\n",
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"49 grrrrrrrrGgrrgrrrrrrrrgrrrr\n",
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"50 grrrrrrGGrgrrgrrrrrrrrgrrrr\n",
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"51 grrrrrrrrGgrrgrrrrrrrrgrrrr\n",
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"Name: state, dtype: object"
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]
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},
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"execution_count": 12,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"m6 = self.match6[self.match6.node_id=='106332']\n",
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"m6.state"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"40 gGGGrrrrrrgrrgrrrrrrrrgrrrr\n",
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"41 grrrrGGrrrgrrgrrrrrrrrgrrrr\n",
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"42 gGGGrrrrrrgrrgrrrrrrrrgrrrr\n",
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"43 grrrrrrrrrgrrgrGGGGGrrgrrrr\n",
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"44 grrrrrrrrrgrrgrrrrrrGGgrrrr\n",
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"45 grrrrrrrrrgrrgrGGGGGrrgrrrr\n",
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"46 grrrrrrrrrgrrgrrrrrrrrgrrrG\n",
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"47 grrrrrrrrrgrrgrrrrrrrrgGGGr\n",
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"48 grrrrrrGGrgrrgrrrrrrrrgrrrr\n",
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"49 grrrrrrrrGgrrgrrrrrrrrgrrrr\n",
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"50 grrrrrrGGrgrrgrrrrrrrrgrrrr\n",
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"51 grrrrrrrrGgrrgrrrrrrrrgrrrr\n",
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"Name: state, dtype: object"
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]
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},
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"execution_count": 11,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"self.match6[self.match6.node_id=='106332'].state"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "siggen_env",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.4"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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