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2239 lines
75 KiB
2239 lines
75 KiB
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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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\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 generate_signals import SignalGenerator"
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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": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"self = SignalGenerator(config_name='test_0731',\n",
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" month=7,\n",
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" day=31,\n",
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" hour=9,\n",
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" minute=5)"
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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": 3,
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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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"2. 신호이력 테이블을 변환합니다.\n"
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]
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}
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],
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"source": [
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"self.prepare_data()\n",
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"self.process_history()"
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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": 4,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>start_unix</th>\n",
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" <th>inter_no</th>\n",
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" <th>phas_A</th>\n",
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" <th>phas_B</th>\n",
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" <th>STOS_NO</th>\n",
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" <th>move_A</th>\n",
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" <th>move_B</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>1722383926</td>\n",
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" <td>436</td>\n",
|
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" <td>2</td>\n",
|
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" <td>2</td>\n",
|
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" <td>0</td>\n",
|
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" <td>8</td>\n",
|
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" <td>3</td>\n",
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" </tr>\n",
|
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" <tr>\n",
|
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" <th>1</th>\n",
|
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" <td>1722383926</td>\n",
|
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" <td>437</td>\n",
|
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" <td>3</td>\n",
|
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" <td>3</td>\n",
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" <td>0</td>\n",
|
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" <td>8</td>\n",
|
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" <td>3</td>\n",
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" </tr>\n",
|
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" <tr>\n",
|
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" <th>2</th>\n",
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" <td>1722383926</td>\n",
|
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" <td>438</td>\n",
|
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" <td>1</td>\n",
|
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" <td>1</td>\n",
|
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" <td>0</td>\n",
|
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" <td>6</td>\n",
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" <td>2</td>\n",
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" </tr>\n",
|
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" <tr>\n",
|
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" <th>3</th>\n",
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" <td>1722383926</td>\n",
|
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" <td>442</td>\n",
|
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" <td>1</td>\n",
|
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" <td>1</td>\n",
|
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" <td>0</td>\n",
|
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" <td>6</td>\n",
|
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" <td>1</td>\n",
|
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" </tr>\n",
|
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" <tr>\n",
|
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" <th>4</th>\n",
|
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" <td>1722383926</td>\n",
|
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" <td>443</td>\n",
|
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" <td>1</td>\n",
|
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" <td>1</td>\n",
|
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" <td>0</td>\n",
|
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" <td>6</td>\n",
|
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" <td>2</td>\n",
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" </tr>\n",
|
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" <tr>\n",
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" <th>...</th>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
|
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>11095</th>\n",
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" <td>1722385043</td>\n",
|
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" <td>444</td>\n",
|
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" <td>4</td>\n",
|
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" <td>4</td>\n",
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" <td>0</td>\n",
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" <td>-1</td>\n",
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" <td>-1</td>\n",
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" </tr>\n",
|
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" <tr>\n",
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" <th>11096</th>\n",
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" <td>1722385043</td>\n",
|
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" <td>455</td>\n",
|
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" <td>2</td>\n",
|
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" <td>2</td>\n",
|
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" <td>0</td>\n",
|
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" <td>-1</td>\n",
|
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" <td>-1</td>\n",
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" </tr>\n",
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" <tr>\n",
|
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" <th>11097</th>\n",
|
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" <td>1722385043</td>\n",
|
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" <td>456</td>\n",
|
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" <td>4</td>\n",
|
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" <td>4</td>\n",
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" <td>0</td>\n",
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" <td>17</td>\n",
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" <td>-1</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>11098</th>\n",
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" <td>1722385043</td>\n",
|
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" <td>457</td>\n",
|
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" <td>3</td>\n",
|
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" <td>3</td>\n",
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" <td>0</td>\n",
|
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" <td>17</td>\n",
|
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" <td>17</td>\n",
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" </tr>\n",
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" <tr>\n",
|
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" <th>11099</th>\n",
|
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" <td>1722385043</td>\n",
|
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" <td>458</td>\n",
|
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" <td>2</td>\n",
|
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" <td>2</td>\n",
|
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" <td>0</td>\n",
|
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" <td>17</td>\n",
|
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" <td>17</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"<p>11100 rows × 7 columns</p>\n",
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"</div>"
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],
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"text/plain": [
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" start_unix inter_no phas_A phas_B STOS_NO move_A move_B\n",
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"0 1722383926 436 2 2 0 8 3\n",
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"1 1722383926 437 3 3 0 8 3\n",
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"2 1722383926 438 1 1 0 6 2\n",
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"3 1722383926 442 1 1 0 6 1\n",
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"4 1722383926 443 1 1 0 6 2\n",
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"... ... ... ... ... ... ... ...\n",
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"11095 1722385043 444 4 4 0 -1 -1\n",
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"11096 1722385043 455 2 2 0 -1 -1\n",
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"11097 1722385043 456 4 4 0 17 -1\n",
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"11098 1722385043 457 3 3 0 17 17\n",
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"11099 1722385043 458 2 2 0 17 17\n",
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"\n",
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"[11100 rows x 7 columns]"
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]
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},
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"execution_count": 4,
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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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"phases = pd.read_csv(os.path.join(self.path_tables, 'TL_IF_SIGL.csv'))\n",
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"phases = phases.drop(columns=['FRST_REG_DT', 'RINGA_FLOW', 'RINGB_FLOW'])\n",
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"phases = phases.rename(columns={\n",
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" 'PHASE_DT':'start_unix','CRSRD_ID':'inter_no',\n",
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" 'RINGA_PHASE':'phas_A', 'RINGB_PHASE':'phas_B',\n",
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" 'MAP_MODE':'STOS_NO'\n",
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" })\n",
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"isp2move_A = self.isp2move['A']\n",
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"isp2move_B = self.isp2move['B']\n",
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"phases['move_A'] = phases.apply(\n",
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" lambda row: int(isp2move_A.get((row.inter_no, row.STOS_NO, row.phas_A), -1)), axis=1)\n",
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"phases['move_B'] = phases.apply(\n",
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" lambda row: int(isp2move_B.get((row.inter_no, row.STOS_NO, row.phas_B), -1)), axis=1)\n",
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"phases['start_unix'] = phases['start_unix'].apply(lambda x:int(datetime.strptime(x, '%Y-%m-%d %H:%M:%S').timestamp()))\n",
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"phases"
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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": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"self.history['end_unix'] = self.history['end_unix'].apply(lambda x:int(datetime.strptime(x, '%Y-%m-%d %H:%M:%S').timestamp()))\n"
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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": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"fsecs = list(range(self.present_time - self.sim_timespan, self.present_time + 1, 5))"
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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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"name": "stdout",
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"output_type": "stream",
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"text": [
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"1722383926\n",
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"1722385043\n",
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"1722384300\n",
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"1722384000\n",
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"1722384300\n"
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]
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}
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],
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"source": [
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"print(phases.start_unix.min())\n",
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"print(phases.start_unix.max())\n",
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"print(self.present_time)\n",
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"print(fsecs[0])\n",
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"print(fsecs[-1])"
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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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"source": [
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"fsecs = list(range(self.present_time - self.sim_timespan, self.present_time + 1, 5))"
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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": 7,
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"metadata": {},
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"outputs": [
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{
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"ename": "ValueError",
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"evalue": "Cannot merge a Series without a name",
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"output_type": "error",
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"traceback": [
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"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[1;31mValueError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[1;32mIn[7], line 20\u001b[0m\n\u001b[0;32m 18\u001b[0m recent_unix \u001b[38;5;241m=\u001b[39m rhistory[[\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;124mend_unix\u001b[39m\u001b[38;5;124m'\u001b[39m]]\n\u001b[0;32m 19\u001b[0m \u001b[38;5;66;03m# 3. 상태 테이블 조회정보(A)와 이력 테이블 조회정보(B) 조인(키값 : 교차로번호) : C\u001b[39;00m\n\u001b[1;32m---> 20\u001b[0m move \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmerge\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmove\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrecent_unix\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mhow\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mleft\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mon\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43minter_no\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[0;32m 21\u001b[0m move[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mend_unix\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m move[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mend_unix\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m.\u001b[39mfillna(\u001b[38;5;241m0\u001b[39m)\u001b[38;5;241m.\u001b[39mastype(\u001b[38;5;28mint\u001b[39m)\n\u001b[0;32m 22\u001b[0m \u001b[38;5;66;03m# # 4. C데이터 프레임에 신규 컬럼(시작 유닉스타임) 생성 후 종료유닉스 타임 값 입력, 종료 유닉스 타임 컬럼 제거\u001b[39;00m\n",
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"File \u001b[1;32mc:\\github\\siggen\\siggen_env\\Lib\\site-packages\\pandas\\core\\reshape\\merge.py:152\u001b[0m, in \u001b[0;36mmerge\u001b[1;34m(left, right, how, on, left_on, right_on, left_index, right_index, sort, suffixes, copy, indicator, validate)\u001b[0m\n\u001b[0;32m 135\u001b[0m \u001b[38;5;129m@Substitution\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124mleft : DataFrame or named Series\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m 136\u001b[0m \u001b[38;5;129m@Appender\u001b[39m(_merge_doc, indents\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0\u001b[39m)\n\u001b[0;32m 137\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mmerge\u001b[39m(\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 150\u001b[0m validate: \u001b[38;5;28mstr\u001b[39m \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[0;32m 151\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m DataFrame:\n\u001b[1;32m--> 152\u001b[0m left_df \u001b[38;5;241m=\u001b[39m \u001b[43m_validate_operand\u001b[49m\u001b[43m(\u001b[49m\u001b[43mleft\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 153\u001b[0m right_df \u001b[38;5;241m=\u001b[39m _validate_operand(right)\n\u001b[0;32m 154\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m how \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcross\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n",
|
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"File \u001b[1;32mc:\\github\\siggen\\siggen_env\\Lib\\site-packages\\pandas\\core\\reshape\\merge.py:2689\u001b[0m, in \u001b[0;36m_validate_operand\u001b[1;34m(obj)\u001b[0m\n\u001b[0;32m 2687\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(obj, ABCSeries):\n\u001b[0;32m 2688\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m obj\u001b[38;5;241m.\u001b[39mname \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m-> 2689\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 merge a Series without a name\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m 2690\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m obj\u001b[38;5;241m.\u001b[39mto_frame()\n\u001b[0;32m 2691\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
|
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"\u001b[1;31mValueError\u001b[0m: Cannot merge a Series without a name"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
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"fsec = fsecs[5]\n",
|
|
"# 1. 상태 테이블 조회해서 전체 데이터중 필요데이터(교차로번호, A링 현시번호, A링 이동류번호, B링 현시번호, B링 이동류번호)만 수집 : A\n",
|
|
"moves = [group.iloc[-1] for _, group in phases[phases.start_unix < fsec].groupby('inter_no')]\n",
|
|
"if not moves:\n",
|
|
" move = pd.DataFrame({\n",
|
|
" 'start_unix':[], 'inter_no':[], 'phas_A':[], 'phas_B':[],\n",
|
|
" 'STOS_NO':[], 'move_A':[], 'move_B':[]})\n",
|
|
"else:\n",
|
|
" move = pd.concat(moves)\n",
|
|
"move = move.drop(columns='start_unix')\n",
|
|
"# 2. 이력 테이블 조회해서 교차로별로 유닉스시간 최대인 데이터(교차로번호, 종료유닉스타임)만 수집 : B\n",
|
|
"recent_histories = [group.iloc[-1:] for _, group in self.history[self.history['end_unix'] < fsec].groupby('inter_no')] # 교차로별로 유닉스시간이 최대인 행들\n",
|
|
"\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",
|
|
"# 3. 상태 테이블 조회정보(A)와 이력 테이블 조회정보(B) 조인(키값 : 교차로번호) : C\n",
|
|
"move = pd.merge(move, recent_unix, how='left', on='inter_no')\n",
|
|
"move['end_unix'] = move['end_unix'].fillna(0).astype(int)\n",
|
|
"# # 4. C데이터 프레임에 신규 컬럼(시작 유닉스타임) 생성 후 종료유닉스 타임 값 입력, 종료 유닉스 타임 컬럼 제거\n",
|
|
"move = move.rename(columns = {'end_unix':'start_unix'})\n",
|
|
"# 5. 이동류 이력정보 READ\n",
|
|
"# - CSV 파일로 서버에 저장된 이동류정보를 읽어옴(파일이 없는 경우에는 데이터가 없는 프레임 D 생성)\n",
|
|
"try:\n",
|
|
" movement # movement가 존재할 경우 그걸 그대로 씀.\n",
|
|
"except NameError: # movement가 존재하지 않는 경우 생성\n",
|
|
" movement = pd.DataFrame()\n",
|
|
"# 6. 이동류 이력정보 데이터테이블(D)에 C데이터 add\n",
|
|
"movement = pd.concat([movement, move])\n",
|
|
"# 7. D데이터 프레임에서 중복데이터 제거(교차로번호, 시작 유닉스타임, A링 현시번호, B링 현시번호 같은 행은 제거)\n",
|
|
"movement = movement.drop_duplicates(['inter_no','phas_A','phas_B','start_unix'])\n",
|
|
"# 8. D데이터 보관 시간 기준시간을 시작 유닉스 타임의 최대값 - self.subtractor // 2을 값으로 산출하고, 보관 시간 기준시간보다 작은 시작 유닉스 타임을 가진 행은 모두 제거(1시간 데이터만 보관)\n",
|
|
"movement = movement[movement.start_unix > fsec - self.subtractor // 2]\n",
|
|
"movement\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 7,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/html": [
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|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>start_unix</th>\n",
|
|
" <th>inter_no</th>\n",
|
|
" <th>phas_A</th>\n",
|
|
" <th>phas_B</th>\n",
|
|
" <th>STOS_NO</th>\n",
|
|
" <th>move_A</th>\n",
|
|
" <th>move_B</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>1722416326</td>\n",
|
|
" <td>436</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>0</td>\n",
|
|
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|
|
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|
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|
|
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|
|
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|
|
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|
|
" <td>3</td>\n",
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|
" <td>3</td>\n",
|
|
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|
|
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|
|
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|
|
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|
|
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|
|
" <th>2</th>\n",
|
|
" <td>1722416326</td>\n",
|
|
" <td>438</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>2</td>\n",
|
|
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|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>1722416326</td>\n",
|
|
" <td>442</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>1</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>1722416326</td>\n",
|
|
" <td>443</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>2</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>...</th>\n",
|
|
" <td>...</td>\n",
|
|
" <td>...</td>\n",
|
|
" <td>...</td>\n",
|
|
" <td>...</td>\n",
|
|
" <td>...</td>\n",
|
|
" <td>...</td>\n",
|
|
" <td>...</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>11095</th>\n",
|
|
" <td>1722417443</td>\n",
|
|
" <td>444</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>-1</td>\n",
|
|
" <td>-1</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>11096</th>\n",
|
|
" <td>1722417443</td>\n",
|
|
" <td>455</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>-1</td>\n",
|
|
" <td>-1</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>11097</th>\n",
|
|
" <td>1722417443</td>\n",
|
|
" <td>456</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>17</td>\n",
|
|
" <td>-1</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>11098</th>\n",
|
|
" <td>1722417443</td>\n",
|
|
" <td>457</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>17</td>\n",
|
|
" <td>17</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>11099</th>\n",
|
|
" <td>1722417443</td>\n",
|
|
" <td>458</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>17</td>\n",
|
|
" <td>17</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"<p>11100 rows × 7 columns</p>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" start_unix inter_no phas_A phas_B STOS_NO move_A move_B\n",
|
|
"0 1722416326 436 2 2 0 8 3\n",
|
|
"1 1722416326 437 3 3 0 8 3\n",
|
|
"2 1722416326 438 1 1 0 6 2\n",
|
|
"3 1722416326 442 1 1 0 6 1\n",
|
|
"4 1722416326 443 1 1 0 6 2\n",
|
|
"... ... ... ... ... ... ... ...\n",
|
|
"11095 1722417443 444 4 4 0 -1 -1\n",
|
|
"11096 1722417443 455 2 2 0 -1 -1\n",
|
|
"11097 1722417443 456 4 4 0 17 -1\n",
|
|
"11098 1722417443 457 3 3 0 17 17\n",
|
|
"11099 1722417443 458 2 2 0 17 17\n",
|
|
"\n",
|
|
"[11100 rows x 7 columns]"
|
|
]
|
|
},
|
|
"execution_count": 7,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"phases"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"self.movement = pd.read_csv(os.path.join(self.path_tables, 'TL_IF_SIGL.csv'))\n",
|
|
"self.movement = self.movement.drop(columns=['FRST_REG_DT', 'RINGA_FLOW', 'RINGB_FLOW'])\n",
|
|
"self.movement = self.movement.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",
|
|
"self.movement['move_A'] = self.movement.apply(\n",
|
|
" lambda row: int(isp2move_A.get((row.inter_no, row.STOS_NO, row.phas_A), -1)), axis=1)\n",
|
|
"self.movement['move_B'] = self.movement.apply(\n",
|
|
" lambda row: int(isp2move_B.get((row.inter_no, row.STOS_NO, row.phas_B), -1)), axis=1)\n",
|
|
"self.movement['start_unix'] = pd.to_datetime(self.movement['start_unix'])\n",
|
|
"self.movement['start_unix'] = self.movement['start_unix'].apply(lambda x: int(x.timestamp()))\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 10,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
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|
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|
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|
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|
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|
|
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|
|
" }\n",
|
|
"</style>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>PHASE_DT</th>\n",
|
|
" <th>CRSRD_ID</th>\n",
|
|
" <th>RINGA_PHASE</th>\n",
|
|
" <th>RINGA_FLOW</th>\n",
|
|
" <th>RINGB_PHASE</th>\n",
|
|
" <th>RINGB_FLOW</th>\n",
|
|
" <th>MAP_MODE</th>\n",
|
|
" <th>FRST_REG_DT</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>2024-07-31 08:58:46</td>\n",
|
|
" <td>436</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>8</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>2024-07-31 08:58:46.799000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>2024-07-31 08:58:46</td>\n",
|
|
" <td>437</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>8</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>2024-07-31 08:58:46.799000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>2024-07-31 08:58:46</td>\n",
|
|
" <td>438</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>2024-07-31 08:58:46.799000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>2024-07-31 08:58:46</td>\n",
|
|
" <td>442</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>2024-07-31 08:58:46.799000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>2024-07-31 08:58:46</td>\n",
|
|
" <td>443</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>2024-07-31 08:58:46.799000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>...</th>\n",
|
|
" <td>...</td>\n",
|
|
" <td>...</td>\n",
|
|
" <td>...</td>\n",
|
|
" <td>...</td>\n",
|
|
" <td>...</td>\n",
|
|
" <td>...</td>\n",
|
|
" <td>...</td>\n",
|
|
" <td>...</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>11095</th>\n",
|
|
" <td>2024-07-31 09:17:23</td>\n",
|
|
" <td>444</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>7</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>2024-07-31 09:17:23.051000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>11096</th>\n",
|
|
" <td>2024-07-31 09:17:23</td>\n",
|
|
" <td>455</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>2024-07-31 09:17:23.051000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>11097</th>\n",
|
|
" <td>2024-07-31 09:17:23</td>\n",
|
|
" <td>456</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>17</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>2024-07-31 09:17:23.051000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>11098</th>\n",
|
|
" <td>2024-07-31 09:17:23</td>\n",
|
|
" <td>457</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>17</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>17</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>2024-07-31 09:17:23.051000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>11099</th>\n",
|
|
" <td>2024-07-31 09:17:23</td>\n",
|
|
" <td>458</td>\n",
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|
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|
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|
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|
|
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|
|
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|
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" PHASE_DT CRSRD_ID RINGA_PHASE RINGA_FLOW RINGB_PHASE \\\n",
|
|
"0 2024-07-31 08:58:46 436 2 8 2 \n",
|
|
"1 2024-07-31 08:58:46 437 3 8 3 \n",
|
|
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|
|
"3 2024-07-31 08:58:46 442 1 6 1 \n",
|
|
"4 2024-07-31 08:58:46 443 1 6 1 \n",
|
|
"... ... ... ... ... ... \n",
|
|
"11095 2024-07-31 09:17:23 444 4 7 4 \n",
|
|
"11096 2024-07-31 09:17:23 455 2 1 2 \n",
|
|
"11097 2024-07-31 09:17:23 456 4 17 4 \n",
|
|
"11098 2024-07-31 09:17:23 457 3 17 3 \n",
|
|
"11099 2024-07-31 09:17:23 458 2 17 2 \n",
|
|
"\n",
|
|
" RINGB_FLOW MAP_MODE FRST_REG_DT \n",
|
|
"0 3 0 2024-07-31 08:58:46.799000 \n",
|
|
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|
|
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|
"3 1 0 2024-07-31 08:58:46.799000 \n",
|
|
"4 2 0 2024-07-31 08:58:46.799000 \n",
|
|
"... ... ... ... \n",
|
|
"11095 4 0 2024-07-31 09:17:23.051000 \n",
|
|
"11096 1 0 2024-07-31 09:17:23.051000 \n",
|
|
"11097 1 0 2024-07-31 09:17:23.051000 \n",
|
|
"11098 17 0 2024-07-31 09:17:23.051000 \n",
|
|
"11099 17 0 2024-07-31 09:17:23.051000 \n",
|
|
"\n",
|
|
"[11100 rows x 8 columns]"
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
|
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|
|
" <td>455</td>\n",
|
|
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|
|
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|
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|
|
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|
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|
" <th>11097</th>\n",
|
|
" <td>2024-07-31 09:17:23</td>\n",
|
|
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|
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|
" <th>11098</th>\n",
|
|
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|
|
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|
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|
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|
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|
|
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|
|
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|
|
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|
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|
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|
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" PHASE_DT CRSRD_ID RINGA_PHASE RINGB_PHASE MAP_MODE\n",
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"0 2024-07-31 08:58:46 436 2 2 0\n",
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|
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|
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|
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|
|
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|
|
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|
|
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|
|
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|
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|
|
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|
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|
|
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|
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|
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|
|
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|
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|
|
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|
|
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|
|
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|
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|
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|
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|
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" start_unix inter_no phas_A phas_B STOS_NO\n",
|
|
"0 2024-07-31 08:58:46 436 2 2 0\n",
|
|
"1 2024-07-31 08:58:46 437 3 3 0\n",
|
|
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|
|
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|
|
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|
|
"... ... ... ... ... ...\n",
|
|
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|
|
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|
|
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|
|
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|
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|
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|
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|
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|
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|
|
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|
|
" <td>2024-07-31 09:17:23</td>\n",
|
|
" <td>444</td>\n",
|
|
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|
|
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|
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|
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|
|
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|
|
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|
|
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|
|
" <th>11096</th>\n",
|
|
" <td>2024-07-31 09:17:23</td>\n",
|
|
" <td>455</td>\n",
|
|
" <td>2</td>\n",
|
|
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|
|
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|
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|
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|
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|
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|
|
" <th>11097</th>\n",
|
|
" <td>2024-07-31 09:17:23</td>\n",
|
|
" <td>456</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>17</td>\n",
|
|
" <td>-1</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>11098</th>\n",
|
|
" <td>2024-07-31 09:17:23</td>\n",
|
|
" <td>457</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>17</td>\n",
|
|
" <td>17</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>11099</th>\n",
|
|
" <td>2024-07-31 09:17:23</td>\n",
|
|
" <td>458</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>17</td>\n",
|
|
" <td>17</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"<p>11100 rows × 7 columns</p>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" start_unix inter_no phas_A phas_B STOS_NO move_A move_B\n",
|
|
"0 2024-07-31 08:58:46 436 2 2 0 8 3\n",
|
|
"1 2024-07-31 08:58:46 437 3 3 0 8 3\n",
|
|
"2 2024-07-31 08:58:46 438 1 1 0 6 2\n",
|
|
"3 2024-07-31 08:58:46 442 1 1 0 6 1\n",
|
|
"4 2024-07-31 08:58:46 443 1 1 0 6 2\n",
|
|
"... ... ... ... ... ... ... ...\n",
|
|
"11095 2024-07-31 09:17:23 444 4 4 0 -1 -1\n",
|
|
"11096 2024-07-31 09:17:23 455 2 2 0 -1 -1\n",
|
|
"11097 2024-07-31 09:17:23 456 4 4 0 17 -1\n",
|
|
"11098 2024-07-31 09:17:23 457 3 3 0 17 17\n",
|
|
"11099 2024-07-31 09:17:23 458 2 2 0 17 17\n",
|
|
"\n",
|
|
"[11100 rows x 7 columns]"
|
|
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|
|
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|
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|
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|
|
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"text/plain": [
|
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" start_unix inter_no phas_A phas_B STOS_NO move_A move_B\n",
|
|
"0 1722416326 436 2 2 0 8 3\n",
|
|
"1 1722416326 437 3 3 0 8 3\n",
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|
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|
|
"11097 1722417443 456 4 4 0 17 -1\n",
|
|
"11098 1722417443 457 3 3 0 17 17\n",
|
|
"11099 1722417443 458 2 2 0 17 17\n",
|
|
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|
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"metadata": {},
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}
|
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],
|
|
"source": [
|
|
"self.movement = pd.read_csv(os.path.join(self.path_tables, 'TL_IF_SIGL.csv'))\n",
|
|
"display(self.movement)\n",
|
|
"self.movement = self.movement.drop(columns=['FRST_REG_DT', 'RINGA_FLOW', 'RINGB_FLOW'])\n",
|
|
"display(self.movement)\n",
|
|
"self.movement = self.movement.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",
|
|
"display(self.movement)\n",
|
|
"isp2move_A = self.isp2move['A']\n",
|
|
"isp2move_B = self.isp2move['B']\n",
|
|
"self.movement['move_A'] = self.movement.apply(\n",
|
|
" lambda row: int(isp2move_A.get((row.inter_no, row.STOS_NO, row.phas_A), -1)), axis=1)\n",
|
|
"self.movement['move_B'] = self.movement.apply(\n",
|
|
" lambda row: int(isp2move_B.get((row.inter_no, row.STOS_NO, row.phas_B), -1)), axis=1)\n",
|
|
"display(self.movement)\n",
|
|
"self.movement['start_unix'] = pd.to_datetime(self.movement['start_unix'])\n",
|
|
"self.movement['start_unix'] = self.movement['start_unix'].apply(lambda x: int(x.timestamp()))\n",
|
|
"display(self.movement)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
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|
|
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|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>start_unix</th>\n",
|
|
" <th>inter_no</th>\n",
|
|
" <th>phas_A</th>\n",
|
|
" <th>phas_B</th>\n",
|
|
" <th>STOS_NO</th>\n",
|
|
" <th>move_A</th>\n",
|
|
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|
|
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|
|
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|
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|
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|
|
" <td>3</td>\n",
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|
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|
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|
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|
|
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|
|
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|
|
" <td>438</td>\n",
|
|
" <td>1</td>\n",
|
|
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|
|
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|
|
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|
|
" <td>2</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>1722416326</td>\n",
|
|
" <td>442</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>1</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>1722416326</td>\n",
|
|
" <td>443</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>2</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>...</th>\n",
|
|
" <td>...</td>\n",
|
|
" <td>...</td>\n",
|
|
" <td>...</td>\n",
|
|
" <td>...</td>\n",
|
|
" <td>...</td>\n",
|
|
" <td>...</td>\n",
|
|
" <td>...</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>11095</th>\n",
|
|
" <td>1722417443</td>\n",
|
|
" <td>444</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>-1</td>\n",
|
|
" <td>-1</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>11096</th>\n",
|
|
" <td>1722417443</td>\n",
|
|
" <td>455</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>-1</td>\n",
|
|
" <td>-1</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>11097</th>\n",
|
|
" <td>1722417443</td>\n",
|
|
" <td>456</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>17</td>\n",
|
|
" <td>-1</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>11098</th>\n",
|
|
" <td>1722417443</td>\n",
|
|
" <td>457</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>17</td>\n",
|
|
" <td>17</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>11099</th>\n",
|
|
" <td>1722417443</td>\n",
|
|
" <td>458</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>17</td>\n",
|
|
" <td>17</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"<p>11100 rows × 7 columns</p>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" start_unix inter_no phas_A phas_B STOS_NO move_A move_B\n",
|
|
"0 1722416326 436 2 2 0 8 3\n",
|
|
"1 1722416326 437 3 3 0 8 3\n",
|
|
"2 1722416326 438 1 1 0 6 2\n",
|
|
"3 1722416326 442 1 1 0 6 1\n",
|
|
"4 1722416326 443 1 1 0 6 2\n",
|
|
"... ... ... ... ... ... ... ...\n",
|
|
"11095 1722417443 444 4 4 0 -1 -1\n",
|
|
"11096 1722417443 455 2 2 0 -1 -1\n",
|
|
"11097 1722417443 456 4 4 0 17 -1\n",
|
|
"11098 1722417443 457 3 3 0 17 17\n",
|
|
"11099 1722417443 458 2 2 0 17 17\n",
|
|
"\n",
|
|
"[11100 rows x 7 columns]"
|
|
]
|
|
},
|
|
"execution_count": 6,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"display(self.movement)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"self.process_movement()\n",
|
|
"self.make_histids()\n",
|
|
"self.get_signals()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"import pandas as pd\n",
|
|
"import numpy as np\n",
|
|
"\n",
|
|
"# 예제 DataFrame 생성\n",
|
|
"data = {\n",
|
|
" 'A': [1, 2, np.nan, 4, np.nan, 6],\n",
|
|
" 'B': [np.nan, 2, 3, np.nan, 5, 6],\n",
|
|
" 'C': [1, np.nan, np.nan, 4, 5, 6]\n",
|
|
"}\n",
|
|
"df = pd.DataFrame(data)\n",
|
|
"\n",
|
|
"print(\"원본 DataFrame:\")\n",
|
|
"display(df)\n",
|
|
"\n",
|
|
"# 결측값을 앞의 값으로 채우기\n",
|
|
"# df_filled = df.fillna(method='ffill')\n",
|
|
"df_filled = df.ffill()#fillna(method='ffill')\n",
|
|
"\n",
|
|
"print(\"\\n결측값을 앞의 값으로 채운 DataFrame:\")\n",
|
|
"display(df_filled)\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"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())\n",
|
|
"print(time_unix)\n",
|
|
"print(datetime.fromtimestamp(time_unix))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"self = SignalGenerator(config_name='test_0731',\n",
|
|
" month=7,\n",
|
|
" day=31,\n",
|
|
" hour=9,\n",
|
|
" minute=5)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"self.load_networks()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"self.load_tables()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"print(self.history.end_unix.min())\n",
|
|
"print(self.history.end_unix.max())\n",
|
|
"print(self.present_time)\n",
|
|
"print(self.midnight)\n",
|
|
"print(self.next_day)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"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": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"self.prepare_auxiliaries()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# valid_parent_ids = [self.inter2node[inter_no] for inter_no in set(self.history.inter_no)]\n",
|
|
"# invalid_parent_ids = [parent_id for parent_id in self.parent_ids if not parent_id in valid_parent_ids ]\n",
|
|
"# print(sorted(self.parent_ids))\n",
|
|
"# print(sorted(valid_parent_ids))\n",
|
|
"# print(sorted(invalid_parent_ids))\n",
|
|
"# invalid_child_ids = []\n",
|
|
"# for parent_id in invalid_parent_ids:\n",
|
|
"# invalid_child_ids.extend(self.pa2ch[parent_id])\n",
|
|
"# print(sorted(invalid_child_ids))\n",
|
|
"\n",
|
|
"# print()\n",
|
|
"# print()\n",
|
|
"# self.parent_ids = sorted(set(self.parent_ids) - set(invalid_parent_ids))\n",
|
|
"# self.node_ids = sorted(set(self.node_ids) - set(invalid_parent_ids))\n",
|
|
"# self.child_ids = sorted(set(self.child_ids) - set(invalid_child_ids))\n",
|
|
"# self.uturn_ids = sorted(set(self.uturn_ids) - set(invalid_child_ids))\n",
|
|
"# self.coord_ids = sorted(set(self.coord_ids) - set(invalid_child_ids))\n",
|
|
"# print(self.parent_ids)\n",
|
|
"# print(self.node_ids)\n",
|
|
"# print(self.child_ids)\n",
|
|
"# print(self.uturn_ids)\n",
|
|
"# print(self.coord_ids)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sorted(inter_no for inter_no in set(self.history.inter_no))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"self.process_history()\n",
|
|
"sorted(inter_no for inter_no in set(self.rhistory.inter_no))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sorted(inter_no for inter_no in set(self.rhists.inter_no))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sorted(inter_no for inter_no in set(self.hrhists.inter_no))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"self.process_movement()\n",
|
|
"sorted(inter_no for inter_no in set(self.movement.inter_no))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"self.make_histids()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sorted(inter_no for inter_no in set(self.movement_updated.inter_no))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sorted(inter_no for inter_no in set(self.movedur.inter_no))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sorted(inter_no for inter_no in set(self.histid.inter_no))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sorted(node_id for node_id in set(self.histid.node_id))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sorted(inter_no for inter_no in set(self.histids.inter_no))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sorted(node_id for node_id in set(self.histids.node_id))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"self.set_timepoints()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"self.assign_red_yellow()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"self.make_tl_file()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"self.plan[self.plan.inter_no==455]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"self.SIGTABLE = []\n",
|
|
"node_id = self.node_ids[11]\n",
|
|
"print(node_id)\n",
|
|
"sig = self.sigtable.query('node_id==@node_id')\n",
|
|
"display(sig)\n",
|
|
"for i, row in sig.iterrows():\n",
|
|
" inter_no = row.inter_no\n",
|
|
" phas_A = row.phas_A\n",
|
|
" phas_B = row.phas_B\n",
|
|
" start_unix = row.start_unix\n",
|
|
" prow = self.load_prow(inter_no, start_unix)[1].iloc[0]\n",
|
|
" # 황색 및 적색시간 컬럼 생성\n",
|
|
" red_A = prow[f'red_A{phas_A}']\n",
|
|
" yellow_A = prow[f'yellow_A{phas_A}']\n",
|
|
" red_B = prow[f'red_B{phas_B}']\n",
|
|
" yellow_B = prow[f'yellow_B{phas_B}']\n",
|
|
" sig.loc[i, ['red_A', 'red_B', 'yellow_A', 'yellow_B']] = red_A, red_B, yellow_A, yellow_B\n",
|
|
"display(sig)\n",
|
|
"sig = sig.astype({'red_A': int, 'red_B': int, 'yellow_A': int, 'yellow_B': int,\n",
|
|
" 'phas_A':str, 'phas_B':str})\n",
|
|
"sig = sig.drop(['move_A','move_B'], axis=1)\n",
|
|
"display(sig)\n",
|
|
"\n",
|
|
"sig_A = sig[['start_unix', 'phas_A', 'duration', 'state_A', 'red_A', 'yellow_A']].reset_index(drop=True)\n",
|
|
"sig_B = sig[['start_unix', 'phas_B', 'duration', 'state_B', 'red_B', 'yellow_B']].reset_index(drop=True)\n",
|
|
"display(sig_A)\n",
|
|
"display(sig_B)\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"self.parent_ids"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# csig_A = self.cumulate(sig_A, 'A')\n",
|
|
"sig = sig_A\n",
|
|
"alph = 'A'\n",
|
|
"csig = [] # cumulated sig\n",
|
|
"pre = pd.Series({f'phas_{alph}':None})\n",
|
|
"\n",
|
|
"sig[f'phas_{alph}'] = sig[f'phas_{alph}'].astype(int)\n",
|
|
"# 만약 현시번호가 1로 일정하면 2현시를 가상으로 추가\n",
|
|
"if (sig[f'phas_{alph}']==1).all():\n",
|
|
" sig_dup = sig.copy() \n",
|
|
" sig_dup[f'phas_{alph}'] = 2\n",
|
|
" sig = pd.concat([sig, sig_dup]).sort_values(by=['start_unix', f'phas_{alph}'])\n",
|
|
"\n",
|
|
"start_time = 0\n",
|
|
"elapsed = 0\n",
|
|
"for i, cur in sig.iterrows():\n",
|
|
" start_unix = cur.start_unix\n",
|
|
" \n",
|
|
" # pre, nex\n",
|
|
" if i != 0:\n",
|
|
" pre = sig.iloc[i-1]\n",
|
|
" \n",
|
|
" if i != len(sig) - 1:\n",
|
|
" nex = sig.iloc[i+1]\n",
|
|
" \n",
|
|
" # duration\n",
|
|
" if cur[f'phas_{alph}'] == nex[f'phas_{alph}']:\n",
|
|
" continue\n",
|
|
" if cur[f'phas_{alph}'] == pre[f'phas_{alph}']:\n",
|
|
" duration = cur.duration + pre.duration\n",
|
|
" else:\n",
|
|
" duration = cur.duration\n",
|
|
" start_times = []\n",
|
|
" states = []\n",
|
|
" phases = []\n",
|
|
"\n",
|
|
" # red\n",
|
|
" if i != 0:\n",
|
|
" start_time += elapsed\n",
|
|
" start_times.append(start_time)\n",
|
|
" states.append(self.get_red(pre[f'state_{alph}'], cur[f'state_{alph}']))\n",
|
|
" phases.append(f'{cur[f\"phas_{alph}\"]}r')\n",
|
|
"\n",
|
|
" elapsed = cur[f'red_{alph}']\n",
|
|
"\n",
|
|
" # green\n",
|
|
" if i == 0:\n",
|
|
" start_time = 0\n",
|
|
" else:\n",
|
|
" start_time += elapsed\n",
|
|
" start_times.append(start_time)\n",
|
|
" states.append(cur[f'state_{alph}'])\n",
|
|
" phases.append(f'{cur[f\"phas_{alph}\"]}g')\n",
|
|
" if i == 0:\n",
|
|
" elapsed = duration - cur[f'yellow_{alph}']\n",
|
|
" else:\n",
|
|
" elapsed = duration - cur[f'yellow_{alph}'] - cur[f'red_{alph}']\n",
|
|
"\n",
|
|
" # yellow\n",
|
|
" if i != len(sig) - 1:\n",
|
|
" start_time += elapsed\n",
|
|
" start_times.append(start_time)\n",
|
|
" states.append(self.get_yellow(cur[f'state_{alph}'], nex[f'state_{alph}']))\n",
|
|
" phases.append(f'{cur[f\"phas_{alph}\"]}y')\n",
|
|
" elapsed = cur[f'yellow_{alph}']\n",
|
|
" sig_ = pd.DataFrame({'start_time':start_times, f'phas_{alph}':phases, f'state_{alph}':states})\n",
|
|
" sig_['start_unix'] = start_unix\n",
|
|
" csig.append(sig_)\n",
|
|
"csig = pd.concat(csig).reset_index(drop=True)\n",
|
|
"csig\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"self.SIGTABLE = []\n",
|
|
"node_id = self.node_ids[11]\n",
|
|
"print(node_id)\n",
|
|
"sig = self.sigtable.query('node_id==@node_id')\n",
|
|
"display(sig)\n",
|
|
"for i, row in sig.iterrows():\n",
|
|
" inter_no = row.inter_no\n",
|
|
" phas_A = row.phas_A\n",
|
|
" phas_B = row.phas_B\n",
|
|
" start_unix = row.start_unix\n",
|
|
" prow = self.load_prow(inter_no, start_unix)[1].iloc[0]\n",
|
|
" # 황색 및 적색시간 컬럼 생성\n",
|
|
" red_A = prow[f'red_A{phas_A}']\n",
|
|
" yellow_A = prow[f'yellow_A{phas_A}']\n",
|
|
" red_B = prow[f'red_B{phas_B}']\n",
|
|
" yellow_B = prow[f'yellow_B{phas_B}']\n",
|
|
" sig.loc[i, ['red_A', 'red_B', 'yellow_A', 'yellow_B']] = red_A, red_B, yellow_A, yellow_B\n",
|
|
"display(sig)\n",
|
|
"sig = sig.astype({'red_A': int, 'red_B': int, 'yellow_A': int, 'yellow_B': int,\n",
|
|
" 'phas_A':str, 'phas_B':str})\n",
|
|
"sig = sig.drop(['move_A','move_B'], axis=1)\n",
|
|
"display(sig)\n",
|
|
"\n",
|
|
"sig_A = sig[['start_unix', 'phas_A', 'duration', 'state_A', 'red_A', 'yellow_A']].reset_index(drop=True)\n",
|
|
"sig_B = sig[['start_unix', 'phas_B', 'duration', 'state_B', 'red_B', 'yellow_B']].reset_index(drop=True)\n",
|
|
"display(sig_A)\n",
|
|
"display(sig_B)\n",
|
|
"\n",
|
|
"csig_A = self.cumulate(sig_A, 'A')\n",
|
|
"csig_B = self.cumulate(sig_B, 'B')\n",
|
|
"display(csig_A)\n",
|
|
"display(csig_B)\n",
|
|
"\n",
|
|
"SIG = pd.merge(csig_A, csig_B, on=['start_time', 'start_unix'], how='outer')\n",
|
|
"display(SIG[:40])\n",
|
|
"SIG = SIG.sort_values(by='start_time').reset_index(drop=True)\n",
|
|
"SIG[['phas_A', 'state_A']] = SIG[['phas_A', 'state_A']].fillna(method='ffill')\n",
|
|
"SIG[['phas_B', 'state_B']] = SIG[['phas_B', 'state_B']].fillna(method='ffill')\n",
|
|
"SIG['phase'] = SIG['phas_A'] + \"_\" + SIG['phas_B']\n",
|
|
"SIG['node_id'] = node_id\n",
|
|
"SIG = SIG[['node_id', 'start_unix', 'start_time', 'phase', 'state_A', 'state_B']]\n",
|
|
"SIG['duration'] = SIG['start_time'].shift(-1) - SIG['start_time']\n",
|
|
"SIG = SIG[:-1]\n",
|
|
"SIG['duration'] = SIG['duration'].astype(int)\n",
|
|
"display(SIG[:40])\n",
|
|
"for row in SIG.itertuples():\n",
|
|
" state = ''\n",
|
|
" for a, b, in zip(row.state_A, row.state_B):\n",
|
|
" if a == 'r':\n",
|
|
" state += b\n",
|
|
" elif b == 'r':\n",
|
|
" state += a\n",
|
|
" elif a == b:\n",
|
|
" state += a\n",
|
|
" else:\n",
|
|
" raise ValueError(f\"예상되지 않은 조합 발생: a={a}, b={b}\")\n",
|
|
" SIG.at[row.Index, 'state'] = state\n",
|
|
"display(SIG[:40])\n",
|
|
"SIG = SIG[SIG.duration!=0]\n",
|
|
"SIG = SIG.drop(columns=['start_time', 'state_A', 'state_B'])\n",
|
|
"display(SIG[:40])\n",
|
|
"self.SIGTABLE.append(SIG)\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"self.offsets = {}\n",
|
|
"self.sigtable = []\n",
|
|
"sim_start = self.present_time - self.sim_timespan\n",
|
|
"print(self.present_time)\n",
|
|
"print(self.sim_timespan)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"node_id = '106231'\n",
|
|
"group = self.histids[self.histids.node_id==node_id]\n",
|
|
"min_start_unix = int(group['start_unix'].min())\n",
|
|
"min_start_unix"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"node_id = '107587'\n",
|
|
"group = self.histids[self.histids.node_id==node_id]\n",
|
|
"series = group[group['start_unix'] < sim_start]['start_unix']\n",
|
|
"min_start_unix = int(group['start_unix'].min())\n",
|
|
"inter_no = self.node2inter[node_id]\n",
|
|
"_, prow = self.load_prow(inter_no, min_start_unix)\n",
|
|
"cycle = prow.iloc[0]['cycle']\n",
|
|
"lsbs = min_start_unix\n",
|
|
"print(lsbs, sim_start, cycle)\n",
|
|
"print(lsbs > sim_start)\n",
|
|
"print(type(lsbs), 'hello', type(sim_start))\n",
|
|
"while lsbs > sim_start:\n",
|
|
" lsbs -= cycle\n",
|
|
"print(min_start_unix)\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"self.offsets = {}\n",
|
|
"self.sigtable = []\n",
|
|
"sim_start = self.present_time - self.sim_timespan\n",
|
|
"for node_id, group in self.histids.groupby('node_id'):\n",
|
|
" series = group[group['start_unix'] < sim_start]['start_unix']\n",
|
|
" # lsbs : the last start_unix before sim_start\n",
|
|
" if len(series):\n",
|
|
" lsbs = series.max()\n",
|
|
" else:\n",
|
|
" min_start_unix = int(group['start_unix'].min())\n",
|
|
" inter_no = self.node2inter[node_id]\n",
|
|
" _, prow = self.load_prow(inter_no, min_start_unix)\n",
|
|
" cycle = prow.iloc[0]['cycle']\n",
|
|
" lsbs = min_start_unix\n",
|
|
" while lsbs > sim_start:\n",
|
|
" lsbs -= cycle\n",
|
|
" self.offsets[node_id] = lsbs - sim_start\n",
|
|
" group = group[group.start_unix >= lsbs]\n",
|
|
" start_unixes = np.array(group.start_unix)\n",
|
|
" start_unixes = np.sort(np.unique(start_unixes))[:self.node2num_cycles[node_id]]\n",
|
|
"\n",
|
|
" group = group[group.start_unix.isin(start_unixes)]\n",
|
|
" self.sigtable.append(group)\n",
|
|
"self.sigtable = pd.concat(self.sigtable).reset_index(drop=True)\n",
|
|
"self.sigtable['phase_sumo'] = self.sigtable.groupby(['node_id', 'start_unix']).cumcount()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sorted(inter_no for inter_no in set(self.sigtable.inter_no))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sorted(node_id for node_id in set(self.sigtable.node_id))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# 5-1\n",
|
|
"self.set_timepoints()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"self.SIGTABLE = []\n",
|
|
"for node_id in self.node_ids:\n",
|
|
" sig = self.sigtable.query('node_id==@node_id')\n",
|
|
" display(sig)\n",
|
|
" for i, row in sig.iterrows():\n",
|
|
" inter_no = row.inter_no\n",
|
|
" phas_A = row.phas_A\n",
|
|
" phas_B = row.phas_B\n",
|
|
" start_unix = row.start_unix\n",
|
|
" prow = self.load_prow(inter_no, start_unix)[1].iloc[0]\n",
|
|
" red_A = prow[f'red_A{phas_A}']\n",
|
|
" yellow_A = prow[f'yellow_A{phas_A}']\n",
|
|
" red_B = prow[f'red_B{phas_B}']\n",
|
|
" yellow_B = prow[f'yellow_B{phas_B}']\n",
|
|
" sig.loc[i, ['red_A', 'red_B', 'yellow_A', 'yellow_B']] = red_A, red_B, yellow_A, yellow_B\n",
|
|
" try:\n",
|
|
" sig = sig.astype({'red_A': int, 'red_B': int, 'yellow_A': int, 'yellow_B': int,\n",
|
|
" 'phas_A':str, 'phas_B':str})\n",
|
|
" sig = sig.drop(['move_A','move_B'], axis=1)\n",
|
|
" except:\n",
|
|
" print(node_id)\n",
|
|
"\n",
|
|
" # sig_A = sig[['start_unix', 'phas_A', 'duration', 'state_A', 'red_A', 'yellow_A']].reset_index(drop=True)\n",
|
|
" # sig_B = sig[['start_unix', 'phas_B', 'duration', 'state_B', 'red_B', 'yellow_B']].reset_index(drop=True)\n",
|
|
"\n",
|
|
" # csig_A = self.cumulate(sig_A, 'A')\n",
|
|
" # csig_B = self.cumulate(sig_B, 'B')\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# 5-2. 적색 및 황색신호 부여\n",
|
|
"self.assign_red_yellow()"
|
|
]
|
|
}
|
|
],
|
|
"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
|
|
}
|