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2174 lines
69 KiB
2174 lines
69 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\n",
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"import sumolib\n",
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"import random\n",
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"from tqdm import tqdm\n",
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"from datetime import datetime"
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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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"# plan_original = pd.read_csv('../../Data/tables/plan_original.csv', index_col=0)\n",
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"# plan_original_ = plan_original[plan_original.start_hour==0]\n",
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"# # plan_original_ = plan_original_[plan_original_.inter_no.isin([175, 210])]\n",
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"# with pd.option_context('display.max_rows', None, 'display.max_columns', None):\n",
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"# display(plan_original_) # overlap : 175, 201, 210"
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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": "stderr",
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"output_type": "stream",
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"text": [
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" 0%| | 0/17280 [00:00<?, ?it/s]"
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]
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"name": "stderr",
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"text": [
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"100%|██████████| 17280/17280 [00:13<00:00, 1267.22it/s]\n"
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]
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},
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>inter_no</th>\n",
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" <th>phas_A</th>\n",
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" <th>phas_B</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>175</td>\n",
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" <td>1</td>\n",
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" <td>1</td>\n",
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" <td>8</td>\n",
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" <td>4</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>175</td>\n",
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" <td>2</td>\n",
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" <td>2</td>\n",
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" <td>7</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>175</td>\n",
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" <td>3</td>\n",
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" <td>3</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>3</th>\n",
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" <td>175</td>\n",
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" <td>3</td>\n",
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" <td>4</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>4</th>\n",
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" <td>175</td>\n",
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" <td>4</td>\n",
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" <td>4</td>\n",
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" <td>5</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>5</th>\n",
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" <td>176</td>\n",
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" <td>1</td>\n",
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" <td>1</td>\n",
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" <td>8</td>\n",
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" <td>4</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>6</th>\n",
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" <td>176</td>\n",
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" <td>2</td>\n",
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" <td>2</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>7</th>\n",
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" <td>176</td>\n",
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" <td>3</td>\n",
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" <td>3</td>\n",
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" <td>5</td>\n",
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" <td>18</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>8</th>\n",
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" <td>177</td>\n",
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" <td>1</td>\n",
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" <td>1</td>\n",
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" <td>8</td>\n",
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" <td>4</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>9</th>\n",
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" <td>177</td>\n",
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" <td>2</td>\n",
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" <td>2</td>\n",
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" <td>7</td>\n",
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" <td>3</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" inter_no phas_A phas_B move_A move_B\n",
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"0 175 1 1 8 4\n",
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"1 175 2 2 7 3\n",
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"2 175 3 3 6 1\n",
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"3 175 3 4 6 2\n",
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"4 175 4 4 5 2\n",
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"5 176 1 1 8 4\n",
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"6 176 2 2 8 3\n",
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"7 176 3 3 5 18\n",
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"8 177 1 1 8 4\n",
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"9 177 2 2 7 3"
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]
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},
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"execution_count": 3,
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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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"# [이동류번호] 불러오기\n",
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"path_moves = '../../Data/tables/movements/'\n",
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"csv_moves = os.listdir('../../Data/tables/movements/')\n",
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"moves = [pd.read_csv(path_moves + csv_movement, index_col=0) for csv_movement in tqdm(csv_moves)]\n",
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"match1 = pd.concat(moves).drop_duplicates().sort_values(by=['inter_no','phas_A','phas_B']).reset_index(drop=True)\n",
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"match1 = match1[match1.inter_no!=212]\n",
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"match1.head(10)"
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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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"\n",
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" .dataframe tbody tr th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
|
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" <th>inter_no</th>\n",
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" <th>phase_no</th>\n",
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" <th>ring_type</th>\n",
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" <th>move_no</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>175</td>\n",
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" <td>1</td>\n",
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" <td>A</td>\n",
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" <td>8</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>175</td>\n",
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" <td>1</td>\n",
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" <td>B</td>\n",
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" <td>4</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>175</td>\n",
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" <td>2</td>\n",
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" <td>A</td>\n",
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" <td>7</td>\n",
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" </tr>\n",
|
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" <tr>\n",
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" <th>1</th>\n",
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" <td>175</td>\n",
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" <td>2</td>\n",
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" <td>B</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>175</td>\n",
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" <td>3</td>\n",
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" <td>A</td>\n",
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" <td>6</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>175</td>\n",
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" <td>3</td>\n",
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" <td>B</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>175</td>\n",
|
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" <td>4</td>\n",
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" <td>A</td>\n",
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" <td>5</td>\n",
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" </tr>\n",
|
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" <tr>\n",
|
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" <th>3</th>\n",
|
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" <td>175</td>\n",
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" <td>4</td>\n",
|
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" <td>B</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>5</th>\n",
|
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" <td>176</td>\n",
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" <td>1</td>\n",
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" <td>A</td>\n",
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" <td>8</td>\n",
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" </tr>\n",
|
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" <tr>\n",
|
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" <th>5</th>\n",
|
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" <td>176</td>\n",
|
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" <td>1</td>\n",
|
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" <td>B</td>\n",
|
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" <td>4</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" inter_no phase_no ring_type move_no\n",
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"0 175 1 A 8\n",
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"0 175 1 B 4\n",
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"1 175 2 A 7\n",
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"1 175 2 B 3\n",
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"2 175 3 A 6\n",
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"2 175 3 B 1\n",
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"4 175 4 A 5\n",
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"3 175 4 B 2\n",
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"5 176 1 A 8\n",
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"5 176 1 B 4"
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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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"# 계층화\n",
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"moveA = match1[['inter_no', 'phas_A', 'move_A']].copy()\n",
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"moveA.columns = ['inter_no', 'phase_no', 'move_no']\n",
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"moveA['ring_type'] = 'A'\n",
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"moveB = match1[['inter_no', 'phas_B', 'move_B']].copy()\n",
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"moveB.columns = ['inter_no', 'phase_no', 'move_no']\n",
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"moveB['ring_type'] = 'B'\n",
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"match2 = pd.concat([moveA, moveB]).drop_duplicates()\n",
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"match2 = match2[['inter_no', 'phase_no', 'ring_type', 'move_no']]\n",
|
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"match2 = match2.sort_values(by=list(match2.columns))\n",
|
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"match2.head(10)"
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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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{
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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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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
|
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" <th></th>\n",
|
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" <th>inter_no</th>\n",
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" <th>phase_no</th>\n",
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" <th>ring_type</th>\n",
|
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" <th>move_no</th>\n",
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" <th>inc_dir</th>\n",
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" <th>out_dir</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
|
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" <td>175</td>\n",
|
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" <td>1</td>\n",
|
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" <td>A</td>\n",
|
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" <td>8</td>\n",
|
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" <td>남</td>\n",
|
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" <td>북</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
|
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" <td>175</td>\n",
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" <td>1</td>\n",
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" <td>B</td>\n",
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" <td>4</td>\n",
|
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" <td>북</td>\n",
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" <td>남</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
|
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" <td>175</td>\n",
|
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" <td>2</td>\n",
|
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" <td>A</td>\n",
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" <td>7</td>\n",
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" <td>북</td>\n",
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" <td>동</td>\n",
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" </tr>\n",
|
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" <tr>\n",
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" <th>3</th>\n",
|
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" <td>175</td>\n",
|
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" <td>2</td>\n",
|
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" <td>B</td>\n",
|
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" <td>3</td>\n",
|
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" <td>남</td>\n",
|
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" <td>서</td>\n",
|
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" </tr>\n",
|
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" <tr>\n",
|
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" <th>4</th>\n",
|
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" <td>175</td>\n",
|
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" <td>3</td>\n",
|
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" <td>A</td>\n",
|
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" <td>6</td>\n",
|
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" <td>동</td>\n",
|
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" <td>서</td>\n",
|
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" </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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" </tr>\n",
|
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" <tr>\n",
|
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" <th>59</th>\n",
|
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" <td>210</td>\n",
|
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" <td>4</td>\n",
|
|
" <td>B</td>\n",
|
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" <td>3</td>\n",
|
|
" <td>남</td>\n",
|
|
" <td>서</td>\n",
|
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" </tr>\n",
|
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" <tr>\n",
|
|
" <th>60</th>\n",
|
|
" <td>211</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>A</td>\n",
|
|
" <td>6</td>\n",
|
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" <td>동</td>\n",
|
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" <td>서</td>\n",
|
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" </tr>\n",
|
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" <tr>\n",
|
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" <th>61</th>\n",
|
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" <td>211</td>\n",
|
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" <td>1</td>\n",
|
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" <td>B</td>\n",
|
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" <td>2</td>\n",
|
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" <td>서</td>\n",
|
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" <td>동</td>\n",
|
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" </tr>\n",
|
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" <tr>\n",
|
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" <th>62</th>\n",
|
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" <td>211</td>\n",
|
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" <td>2</td>\n",
|
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" <td>A</td>\n",
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" <td>17</td>\n",
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" <td>NaN</td>\n",
|
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" <td>NaN</td>\n",
|
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" </tr>\n",
|
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" <tr>\n",
|
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" <th>63</th>\n",
|
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" <td>211</td>\n",
|
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" <td>2</td>\n",
|
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" <td>B</td>\n",
|
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" <td>18</td>\n",
|
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" <td>NaN</td>\n",
|
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" <td>NaN</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>64 rows × 6 columns</p>\n",
|
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"</div>"
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],
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"text/plain": [
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" inter_no phase_no ring_type move_no inc_dir out_dir\n",
|
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"0 175 1 A 8 남 북\n",
|
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"1 175 1 B 4 북 남\n",
|
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"2 175 2 A 7 북 동\n",
|
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"3 175 2 B 3 남 서\n",
|
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"4 175 3 A 6 동 서\n",
|
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".. ... ... ... ... ... ...\n",
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"59 210 4 B 3 남 서\n",
|
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"60 211 1 A 6 동 서\n",
|
|
"61 211 1 B 2 서 동\n",
|
|
"62 211 2 A 17 NaN NaN\n",
|
|
"63 211 2 B 18 NaN NaN\n",
|
|
"\n",
|
|
"[64 rows x 6 columns]"
|
|
]
|
|
},
|
|
"execution_count": 5,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# [nema 이동류목록] 불러오기 및 병합\n",
|
|
"nema = pd.read_csv('../../Data/tables/nema.csv', encoding='cp949')\n",
|
|
"match3 = pd.merge(match2, nema, how='left', left_on='move_no', right_on='이동류번호').drop_duplicates()\n",
|
|
"match3.rename(columns={'진입방향': 'inc_dir', '진출방향': 'out_dir'}, inplace=True)\n",
|
|
"match3.drop('이동류번호', axis=1, inplace=True)\n",
|
|
"match3"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 6,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/html": [
|
|
"<div>\n",
|
|
"<style scoped>\n",
|
|
" .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",
|
|
" text-align: right;\n",
|
|
" }\n",
|
|
"</style>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>inter_no</th>\n",
|
|
" <th>phase_no</th>\n",
|
|
" <th>ring_type</th>\n",
|
|
" <th>move_no</th>\n",
|
|
" <th>inc_dir</th>\n",
|
|
" <th>out_dir</th>\n",
|
|
" <th>inc_angle</th>\n",
|
|
" <th>out_angle</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>175</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>A</td>\n",
|
|
" <td>8</td>\n",
|
|
" <td>남</td>\n",
|
|
" <td>북</td>\n",
|
|
" <td>179</td>\n",
|
|
" <td>004</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>175</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>B</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>북</td>\n",
|
|
" <td>남</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>175</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>A</td>\n",
|
|
" <td>7</td>\n",
|
|
" <td>북</td>\n",
|
|
" <td>동</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>175</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>B</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>남</td>\n",
|
|
" <td>서</td>\n",
|
|
" <td>179</td>\n",
|
|
" <td>270</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>175</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>A</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>동</td>\n",
|
|
" <td>서</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</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>59</th>\n",
|
|
" <td>210</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>B</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>남</td>\n",
|
|
" <td>서</td>\n",
|
|
" <td>180</td>\n",
|
|
" <td>270</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>60</th>\n",
|
|
" <td>211</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>A</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>동</td>\n",
|
|
" <td>서</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>61</th>\n",
|
|
" <td>211</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>B</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>서</td>\n",
|
|
" <td>동</td>\n",
|
|
" <td>270</td>\n",
|
|
" <td>090</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>62</th>\n",
|
|
" <td>211</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>A</td>\n",
|
|
" <td>17</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>63</th>\n",
|
|
" <td>211</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>B</td>\n",
|
|
" <td>18</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"<p>64 rows × 8 columns</p>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" inter_no phase_no ring_type move_no inc_dir out_dir inc_angle out_angle\n",
|
|
"0 175 1 A 8 남 북 179 004\n",
|
|
"1 175 1 B 4 북 남 NaN NaN\n",
|
|
"2 175 2 A 7 북 동 NaN NaN\n",
|
|
"3 175 2 B 3 남 서 179 270\n",
|
|
"4 175 3 A 6 동 서 NaN NaN\n",
|
|
".. ... ... ... ... ... ... ... ...\n",
|
|
"59 210 4 B 3 남 서 180 270\n",
|
|
"60 211 1 A 6 동 서 NaN NaN\n",
|
|
"61 211 1 B 2 서 동 270 090\n",
|
|
"62 211 2 A 17 NaN NaN NaN NaN\n",
|
|
"63 211 2 B 18 NaN NaN NaN NaN\n",
|
|
"\n",
|
|
"[64 rows x 8 columns]"
|
|
]
|
|
},
|
|
"execution_count": 6,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# [방위각정보] 불러오기 및 병합\n",
|
|
"angle = pd.read_csv('../../Data/tables/angle.csv', index_col=0)\n",
|
|
"six_chars = angle.angle_code.apply(lambda x:len(x)==6)\n",
|
|
"angle.loc[six_chars,'inc_angle'] = angle.angle_code.apply(lambda x:x[:3])\n",
|
|
"angle.loc[six_chars,'out_angle'] = angle.angle_code.apply(lambda x:x[3:])\n",
|
|
"angle = angle.drop('angle_code', axis=1)\n",
|
|
"match4 = pd.merge(match3, angle, how='left', left_on=['inter_no', 'phase_no', 'ring_type'],\n",
|
|
" right_on=['inter_no', 'phase_no', 'ring_type']).drop_duplicates()\n",
|
|
"match4"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 7,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/html": [
|
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|
|
"<style scoped>\n",
|
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|
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|
|
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|
|
"\n",
|
|
" .dataframe tbody tr th {\n",
|
|
" vertical-align: top;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe thead th {\n",
|
|
" text-align: right;\n",
|
|
" }\n",
|
|
"</style>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>inter_no</th>\n",
|
|
" <th>node_id</th>\n",
|
|
" <th>move_no</th>\n",
|
|
" <th>inc_edge</th>\n",
|
|
" <th>out_edge</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>175</td>\n",
|
|
" <td>i0</td>\n",
|
|
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|
|
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|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>175</td>\n",
|
|
" <td>i0</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>571510153_02</td>\n",
|
|
" <td>571545870_01</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>175</td>\n",
|
|
" <td>i0</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>-571542797_02</td>\n",
|
|
" <td>571510153_01</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>175</td>\n",
|
|
" <td>i0</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>175</td>\n",
|
|
" <td>i0</td>\n",
|
|
" <td>5</td>\n",
|
|
" <td>571510153_02</td>\n",
|
|
" <td>571500487_01</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>5</th>\n",
|
|
" <td>175</td>\n",
|
|
" <td>i0</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>6</th>\n",
|
|
" <td>175</td>\n",
|
|
" <td>i0</td>\n",
|
|
" <td>7</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>7</th>\n",
|
|
" <td>175</td>\n",
|
|
" <td>i0</td>\n",
|
|
" <td>8</td>\n",
|
|
" <td>-571542797_02</td>\n",
|
|
" <td>571500487_01</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>8</th>\n",
|
|
" <td>176</td>\n",
|
|
" <td>i1</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>-571542810_01</td>\n",
|
|
" <td>571543469_01</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>9</th>\n",
|
|
" <td>176</td>\n",
|
|
" <td>i1</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>571542797_02.99</td>\n",
|
|
" <td>571542810_01</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>10</th>\n",
|
|
" <td>176</td>\n",
|
|
" <td>i1</td>\n",
|
|
" <td>5</td>\n",
|
|
" <td>571543469_02</td>\n",
|
|
" <td>-571542797_02.99</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>11</th>\n",
|
|
" <td>176</td>\n",
|
|
" <td>i1</td>\n",
|
|
" <td>8</td>\n",
|
|
" <td>-571542810_01</td>\n",
|
|
" <td>-571542797_02.99</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>12</th>\n",
|
|
" <td>176</td>\n",
|
|
" <td>i1</td>\n",
|
|
" <td>8</td>\n",
|
|
" <td>-571542810_01</td>\n",
|
|
" <td>-571542797_02.99</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>13</th>\n",
|
|
" <td>176</td>\n",
|
|
" <td>i1</td>\n",
|
|
" <td>18</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>14</th>\n",
|
|
" <td>177</td>\n",
|
|
" <td>i2</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>15</th>\n",
|
|
" <td>177</td>\n",
|
|
" <td>i2</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>-571542809_01</td>\n",
|
|
" <td>571542809_01</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>16</th>\n",
|
|
" <td>177</td>\n",
|
|
" <td>i2</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>17</th>\n",
|
|
" <td>177</td>\n",
|
|
" <td>i2</td>\n",
|
|
" <td>5</td>\n",
|
|
" <td>-571542809_01</td>\n",
|
|
" <td>571542811_01</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>18</th>\n",
|
|
" <td>177</td>\n",
|
|
" <td>i2</td>\n",
|
|
" <td>7</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>19</th>\n",
|
|
" <td>177</td>\n",
|
|
" <td>i2</td>\n",
|
|
" <td>8</td>\n",
|
|
" <td>-571542809_01</td>\n",
|
|
" <td>571542811_01</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>20</th>\n",
|
|
" <td>177</td>\n",
|
|
" <td>i2</td>\n",
|
|
" <td>17</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>21</th>\n",
|
|
" <td>177</td>\n",
|
|
" <td>i2</td>\n",
|
|
" <td>18</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>22</th>\n",
|
|
" <td>178</td>\n",
|
|
" <td>i3</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>23</th>\n",
|
|
" <td>178</td>\n",
|
|
" <td>i3</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>571540303_02.21</td>\n",
|
|
" <td>571500475_01</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>24</th>\n",
|
|
" <td>178</td>\n",
|
|
" <td>i3</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>571540304_02</td>\n",
|
|
" <td>571540303_01</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>25</th>\n",
|
|
" <td>178</td>\n",
|
|
" <td>i3</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>26</th>\n",
|
|
" <td>178</td>\n",
|
|
" <td>i3</td>\n",
|
|
" <td>5</td>\n",
|
|
" <td>571540303_02.21</td>\n",
|
|
" <td>571556450_01</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>27</th>\n",
|
|
" <td>178</td>\n",
|
|
" <td>i3</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>28</th>\n",
|
|
" <td>178</td>\n",
|
|
" <td>i3</td>\n",
|
|
" <td>7</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>29</th>\n",
|
|
" <td>178</td>\n",
|
|
" <td>i3</td>\n",
|
|
" <td>8</td>\n",
|
|
" <td>571540304_02</td>\n",
|
|
" <td>571556450_01</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>30</th>\n",
|
|
" <td>201</td>\n",
|
|
" <td>i8</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>31</th>\n",
|
|
" <td>201</td>\n",
|
|
" <td>i8</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>571500618_02</td>\n",
|
|
" <td>571500617_01</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>32</th>\n",
|
|
" <td>201</td>\n",
|
|
" <td>i8</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>571500618_02</td>\n",
|
|
" <td>571500617_01</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>33</th>\n",
|
|
" <td>201</td>\n",
|
|
" <td>i8</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>-571500569_01</td>\n",
|
|
" <td>571500618_01</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>34</th>\n",
|
|
" <td>201</td>\n",
|
|
" <td>i8</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>35</th>\n",
|
|
" <td>201</td>\n",
|
|
" <td>i8</td>\n",
|
|
" <td>5</td>\n",
|
|
" <td>571500618_02</td>\n",
|
|
" <td>571500583_02</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>36</th>\n",
|
|
" <td>201</td>\n",
|
|
" <td>i8</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>37</th>\n",
|
|
" <td>201</td>\n",
|
|
" <td>i8</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>38</th>\n",
|
|
" <td>201</td>\n",
|
|
" <td>i8</td>\n",
|
|
" <td>7</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>39</th>\n",
|
|
" <td>201</td>\n",
|
|
" <td>i8</td>\n",
|
|
" <td>8</td>\n",
|
|
" <td>-571500569_01</td>\n",
|
|
" <td>571500583_02</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>40</th>\n",
|
|
" <td>202</td>\n",
|
|
" <td>i9</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>571510152_01</td>\n",
|
|
" <td>571510152_01.65</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>41</th>\n",
|
|
" <td>202</td>\n",
|
|
" <td>i9</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>42</th>\n",
|
|
" <td>202</td>\n",
|
|
" <td>i9</td>\n",
|
|
" <td>17</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>43</th>\n",
|
|
" <td>202</td>\n",
|
|
" <td>i9</td>\n",
|
|
" <td>18</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>44</th>\n",
|
|
" <td>206</td>\n",
|
|
" <td>i7</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>45</th>\n",
|
|
" <td>206</td>\n",
|
|
" <td>i7</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>46</th>\n",
|
|
" <td>206</td>\n",
|
|
" <td>i7</td>\n",
|
|
" <td>8</td>\n",
|
|
" <td>-571511538_02</td>\n",
|
|
" <td>571542073_02</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>47</th>\n",
|
|
" <td>206</td>\n",
|
|
" <td>i7</td>\n",
|
|
" <td>8</td>\n",
|
|
" <td>-571511538_02</td>\n",
|
|
" <td>571542073_02</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>48</th>\n",
|
|
" <td>206</td>\n",
|
|
" <td>i7</td>\n",
|
|
" <td>17</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>49</th>\n",
|
|
" <td>206</td>\n",
|
|
" <td>i7</td>\n",
|
|
" <td>17</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>50</th>\n",
|
|
" <td>206</td>\n",
|
|
" <td>i7</td>\n",
|
|
" <td>18</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>51</th>\n",
|
|
" <td>206</td>\n",
|
|
" <td>i7</td>\n",
|
|
" <td>18</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>52</th>\n",
|
|
" <td>210</td>\n",
|
|
" <td>i6</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>571500535_02.18</td>\n",
|
|
" <td>571542115_01</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>53</th>\n",
|
|
" <td>210</td>\n",
|
|
" <td>i6</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>571500585_02</td>\n",
|
|
" <td>571500535_01</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>54</th>\n",
|
|
" <td>210</td>\n",
|
|
" <td>i6</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>55</th>\n",
|
|
" <td>210</td>\n",
|
|
" <td>i6</td>\n",
|
|
" <td>5</td>\n",
|
|
" <td>571500535_02.18</td>\n",
|
|
" <td>571511538_01</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>56</th>\n",
|
|
" <td>210</td>\n",
|
|
" <td>i6</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>57</th>\n",
|
|
" <td>210</td>\n",
|
|
" <td>i6</td>\n",
|
|
" <td>7</td>\n",
|
|
" <td>571511538_02.121</td>\n",
|
|
" <td>571542115_01</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>58</th>\n",
|
|
" <td>210</td>\n",
|
|
" <td>i6</td>\n",
|
|
" <td>8</td>\n",
|
|
" <td>571500585_02</td>\n",
|
|
" <td>571511538_01</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>59</th>\n",
|
|
" <td>210</td>\n",
|
|
" <td>i6</td>\n",
|
|
" <td>18</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" inter_no node_id move_no inc_edge out_edge\n",
|
|
"0 175 i0 1 NaN NaN\n",
|
|
"1 175 i0 2 571510153_02 571545870_01\n",
|
|
"2 175 i0 3 -571542797_02 571510153_01\n",
|
|
"3 175 i0 4 NaN NaN\n",
|
|
"4 175 i0 5 571510153_02 571500487_01\n",
|
|
"5 175 i0 6 NaN NaN\n",
|
|
"6 175 i0 7 NaN NaN\n",
|
|
"7 175 i0 8 -571542797_02 571500487_01\n",
|
|
"8 176 i1 3 -571542810_01 571543469_01\n",
|
|
"9 176 i1 4 571542797_02.99 571542810_01\n",
|
|
"10 176 i1 5 571543469_02 -571542797_02.99\n",
|
|
"11 176 i1 8 -571542810_01 -571542797_02.99\n",
|
|
"12 176 i1 8 -571542810_01 -571542797_02.99\n",
|
|
"13 176 i1 18 NaN NaN\n",
|
|
"14 177 i2 1 NaN NaN\n",
|
|
"15 177 i2 3 -571542809_01 571542809_01\n",
|
|
"16 177 i2 4 NaN NaN\n",
|
|
"17 177 i2 5 -571542809_01 571542811_01\n",
|
|
"18 177 i2 7 NaN NaN\n",
|
|
"19 177 i2 8 -571542809_01 571542811_01\n",
|
|
"20 177 i2 17 NaN NaN\n",
|
|
"21 177 i2 18 NaN NaN\n",
|
|
"22 178 i3 1 NaN NaN\n",
|
|
"23 178 i3 2 571540303_02.21 571500475_01\n",
|
|
"24 178 i3 3 571540304_02 571540303_01\n",
|
|
"25 178 i3 4 NaN NaN\n",
|
|
"26 178 i3 5 571540303_02.21 571556450_01\n",
|
|
"27 178 i3 6 NaN NaN\n",
|
|
"28 178 i3 7 NaN NaN\n",
|
|
"29 178 i3 8 571540304_02 571556450_01\n",
|
|
"30 201 i8 1 NaN NaN\n",
|
|
"31 201 i8 2 571500618_02 571500617_01\n",
|
|
"32 201 i8 2 571500618_02 571500617_01\n",
|
|
"33 201 i8 3 -571500569_01 571500618_01\n",
|
|
"34 201 i8 4 NaN NaN\n",
|
|
"35 201 i8 5 571500618_02 571500583_02\n",
|
|
"36 201 i8 6 NaN NaN\n",
|
|
"37 201 i8 6 NaN NaN\n",
|
|
"38 201 i8 7 NaN NaN\n",
|
|
"39 201 i8 8 -571500569_01 571500583_02\n",
|
|
"40 202 i9 2 571510152_01 571510152_01.65\n",
|
|
"41 202 i9 6 NaN NaN\n",
|
|
"42 202 i9 17 NaN NaN\n",
|
|
"43 202 i9 18 NaN NaN\n",
|
|
"44 206 i7 4 NaN NaN\n",
|
|
"45 206 i7 4 NaN NaN\n",
|
|
"46 206 i7 8 -571511538_02 571542073_02\n",
|
|
"47 206 i7 8 -571511538_02 571542073_02\n",
|
|
"48 206 i7 17 NaN NaN\n",
|
|
"49 206 i7 17 NaN NaN\n",
|
|
"50 206 i7 18 NaN NaN\n",
|
|
"51 206 i7 18 NaN NaN\n",
|
|
"52 210 i6 2 571500535_02.18 571542115_01\n",
|
|
"53 210 i6 3 571500585_02 571500535_01\n",
|
|
"54 210 i6 4 NaN NaN\n",
|
|
"55 210 i6 5 571500535_02.18 571511538_01\n",
|
|
"56 210 i6 6 NaN NaN\n",
|
|
"57 210 i6 7 571511538_02.121 571542115_01\n",
|
|
"58 210 i6 8 571500585_02 571511538_01\n",
|
|
"59 210 i6 18 NaN NaN"
|
|
]
|
|
},
|
|
"execution_count": 7,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# [네트워크], [교차로-노드 매칭], [교차로정보] 불러오기 \n",
|
|
"net = sumolib.net.readNet('../../Data/networks/SN_sample.net.xml')\n",
|
|
"inter_node = pd.read_csv('../../Data/tables/inter_node.csv', index_col=0)\n",
|
|
"inter_info = pd.read_csv('../../Data/tables/inter_info.csv', index_col=0)\n",
|
|
"\n",
|
|
"inter_node1 = inter_node[inter_node.inter_type == 'parent'].drop('inter_type', axis=1)\n",
|
|
"inter_info1 = inter_info[['inter_no', 'inter_lat', 'inter_lon']]\n",
|
|
"inter = pd.merge(inter_node1, inter_info1, how='left', left_on=['inter_no'],\n",
|
|
" right_on=['inter_no']).drop_duplicates()\n",
|
|
"\n",
|
|
"inter2node = dict(zip(inter['inter_no'], inter['node_id']))\n",
|
|
"\n",
|
|
"match5 = match4.copy()\n",
|
|
"# 진입진출ID 매칭\n",
|
|
"for index, row in match5.iterrows():\n",
|
|
" node_id = inter2node[row.inter_no]\n",
|
|
" node = net.getNode(node_id)\n",
|
|
" # 교차로의 모든 (from / to) edges\n",
|
|
" inc_edges = [edge for edge in node.getIncoming() if edge.getFunction() == ''] # incoming edges\n",
|
|
" out_edges = [edge for edge in node.getOutgoing() if edge.getFunction() == ''] # outgoing edges\n",
|
|
" # 교차로의 모든 (from / to) directions\n",
|
|
" inc_dirs = []\n",
|
|
" for inc_edge in inc_edges:\n",
|
|
" start = inc_edge.getShape()[-2]\n",
|
|
" end = inc_edge.getShape()[-1]\n",
|
|
" inc_dir = np.array(end) - np.array(start)\n",
|
|
" inc_dir = inc_dir / (inc_dir ** 2).sum() ** 0.5\n",
|
|
" inc_dirs.append(inc_dir)\n",
|
|
" out_dirs = []\n",
|
|
" for out_edge in out_edges:\n",
|
|
" start = out_edge.getShape()[0]\n",
|
|
" end = out_edge.getShape()[1]\n",
|
|
" out_dir = np.array(end) - np.array(start)\n",
|
|
" out_dir = out_dir / (out_dir ** 2).sum() ** 0.5\n",
|
|
" out_dirs.append(out_dir)\n",
|
|
" # 진입각, 진출각 불러오기\n",
|
|
" if not pd.isna(row.inc_angle):\n",
|
|
" inc_angle = int(row.inc_angle)\n",
|
|
" out_angle = int(row.out_angle)\n",
|
|
" # 방위각을 일반각으로 가공, 라디안 변환, 단위벡터로 변환\n",
|
|
" inc_angle = (-90 - inc_angle) % 360\n",
|
|
" inc_angle = inc_angle * np.pi / 180.\n",
|
|
" inc_dir_true = np.array([np.cos(inc_angle), np.sin(inc_angle)])\n",
|
|
" out_angle = (90 - out_angle) % 360\n",
|
|
" out_angle = out_angle * np.pi / 180.\n",
|
|
" out_dir_true = np.array([np.cos(out_angle), np.sin(out_angle)])\n",
|
|
" # 매칭 엣지 반환\n",
|
|
" inc_index = np.array([np.dot(inc_dir, inc_dir_true) for inc_dir in inc_dirs]).argmax()\n",
|
|
" out_index = np.array([np.dot(out_dir, out_dir_true) for out_dir in out_dirs]).argmax()\n",
|
|
" inc_edge_id = inc_edges[inc_index].getID()\n",
|
|
" out_edge_id = out_edges[out_index].getID()\n",
|
|
" match5.at[index, 'inc_edge'] = inc_edge_id\n",
|
|
" match5.at[index, 'out_edge'] = out_edge_id\n",
|
|
"match5['node_id'] = match5['inter_no'].map(inter2node)\n",
|
|
"match5 = match5[['inter_no', 'node_id', 'move_no', 'inc_edge', 'out_edge']]\n",
|
|
"match5 = match5.sort_values(by=['inter_no', 'move_no']).reset_index(drop=True)\n",
|
|
"match5[:60]"
|
|
]
|
|
},
|
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{
|
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"cell_type": "code",
|
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"execution_count": 8,
|
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"metadata": {},
|
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"outputs": [],
|
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"source": [
|
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"midnight = int(datetime(2024, 1, 5, 0, 0, 0).timestamp())\n",
|
|
"next_day = int(datetime(2024, 1, 6, 0, 0, 0).timestamp())"
|
|
]
|
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},
|
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{
|
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"cell_type": "code",
|
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"execution_count": 9,
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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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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
|
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
|
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" <th></th>\n",
|
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" <th>inter_no</th>\n",
|
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" <th>phas_A</th>\n",
|
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" <th>phas_B</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>175</td>\n",
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" <td>3</td>\n",
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" <td>3</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>0</th>\n",
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" <td>176</td>\n",
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" <td>2</td>\n",
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" <td>2</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>0</th>\n",
|
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" <td>177</td>\n",
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" <td>3</td>\n",
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" <td>3</td>\n",
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" <td>17</td>\n",
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" <td>18</td>\n",
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" </tr>\n",
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" <tr>\n",
|
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" <th>0</th>\n",
|
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" <td>178</td>\n",
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" <td>2</td>\n",
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" <td>2</td>\n",
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" <td>7</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>0</th>\n",
|
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" <td>201</td>\n",
|
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" <td>3</td>\n",
|
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" <td>3</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>0</th>\n",
|
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" <td>202</td>\n",
|
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" <td>2</td>\n",
|
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" <td>2</td>\n",
|
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" <td>17</td>\n",
|
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" <td>18</td>\n",
|
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" </tr>\n",
|
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" <tr>\n",
|
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" <th>0</th>\n",
|
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" <td>206</td>\n",
|
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" <td>3</td>\n",
|
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" <td>3</td>\n",
|
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" <td>8</td>\n",
|
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" <td>4</td>\n",
|
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" </tr>\n",
|
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" <tr>\n",
|
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" <th>0</th>\n",
|
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" <td>210</td>\n",
|
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" <td>3</td>\n",
|
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" <td>3</td>\n",
|
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" <td>7</td>\n",
|
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" <td>4</td>\n",
|
|
" </tr>\n",
|
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" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>211</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>2</td>\n",
|
|
" </tr>\n",
|
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" </tbody>\n",
|
|
"</table>\n",
|
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"</div>"
|
|
],
|
|
"text/plain": [
|
|
" inter_no phas_A phas_B move_A move_B\n",
|
|
"0 175 3 3 6 1\n",
|
|
"0 176 2 2 8 3\n",
|
|
"0 177 3 3 17 18\n",
|
|
"0 178 2 2 7 3\n",
|
|
"0 201 3 3 6 2\n",
|
|
"0 202 2 2 17 18\n",
|
|
"0 206 3 3 8 4\n",
|
|
"0 210 3 3 7 4\n",
|
|
"0 211 1 1 6 2"
|
|
]
|
|
},
|
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"metadata": {},
|
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"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"times = range(midnight, next_day, 5)\n",
|
|
"time = random.choice(times)\n",
|
|
"# 1. 상태 테이블 조회해서 전체 데이터중 필요데이터(교차로번호, A링 현시번호, A링 이동류번호, B링 현시번호, B링 이동류번호)만 수집 : A\n",
|
|
"time2move = dict(zip(range(midnight, next_day, 5),moves))\n",
|
|
"move1 = time2move[time]\n",
|
|
"display(move1)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 10,
|
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"metadata": {},
|
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"outputs": [
|
|
{
|
|
"data": {
|
|
"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",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>inter_no</th>\n",
|
|
" <th>end_unix</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>1317</th>\n",
|
|
" <td>175</td>\n",
|
|
" <td>1704409269</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1313</th>\n",
|
|
" <td>176</td>\n",
|
|
" <td>1704409150</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1314</th>\n",
|
|
" <td>177</td>\n",
|
|
" <td>1704409151</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>830</th>\n",
|
|
" <td>178</td>\n",
|
|
" <td>1704397060</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1316</th>\n",
|
|
" <td>201</td>\n",
|
|
" <td>1704409260</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1115</th>\n",
|
|
" <td>202</td>\n",
|
|
" <td>1704403380</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1315</th>\n",
|
|
" <td>206</td>\n",
|
|
" <td>1704409220</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1318</th>\n",
|
|
" <td>210</td>\n",
|
|
" <td>1704409280</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1040</th>\n",
|
|
" <td>211</td>\n",
|
|
" <td>1704401645</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" inter_no end_unix\n",
|
|
"1317 175 1704409269\n",
|
|
"1313 176 1704409150\n",
|
|
"1314 177 1704409151\n",
|
|
"830 178 1704397060\n",
|
|
"1316 201 1704409260\n",
|
|
"1115 202 1704403380\n",
|
|
"1315 206 1704409220\n",
|
|
"1318 210 1704409280\n",
|
|
"1040 211 1704401645"
|
|
]
|
|
},
|
|
"execution_count": 10,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# 2. 이력 테이블 조회해서 교차로별로 유닉스시간 최대인 데이터(교차로변호, 종료유닉스타임)만 수집 : B\n",
|
|
"history = pd.read_csv('../../Data/tables/history.csv', index_col=0)\n",
|
|
"recent_history = pd.concat([group.iloc[-1:] for inter_no, group in history[history['end_unix'] < time].groupby('inter_no')])\n",
|
|
"recent_history = recent_history[['inter_no', 'end_unix']]\n",
|
|
"recent_history"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 11,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"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",
|
|
" text-align: right;\n",
|
|
" }\n",
|
|
"</style>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>inter_no</th>\n",
|
|
" <th>phas_A</th>\n",
|
|
" <th>phas_B</th>\n",
|
|
" <th>move_A</th>\n",
|
|
" <th>move_B</th>\n",
|
|
" <th>end_unix</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>175</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>1704409269</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>176</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>8</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>1704409150</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>177</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>17</td>\n",
|
|
" <td>18</td>\n",
|
|
" <td>1704409151</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>178</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>7</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>1704397060</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>201</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>1704409260</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>5</th>\n",
|
|
" <td>202</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>17</td>\n",
|
|
" <td>18</td>\n",
|
|
" <td>1704403380</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>6</th>\n",
|
|
" <td>206</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>8</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>1704409220</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>7</th>\n",
|
|
" <td>210</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>7</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>1704409280</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>8</th>\n",
|
|
" <td>211</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>1704401645</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" inter_no phas_A phas_B move_A move_B end_unix\n",
|
|
"0 175 3 3 6 1 1704409269\n",
|
|
"1 176 2 2 8 3 1704409150\n",
|
|
"2 177 3 3 17 18 1704409151\n",
|
|
"3 178 2 2 7 3 1704397060\n",
|
|
"4 201 3 3 6 2 1704409260\n",
|
|
"5 202 2 2 17 18 1704403380\n",
|
|
"6 206 3 3 8 4 1704409220\n",
|
|
"7 210 3 3 7 4 1704409280\n",
|
|
"8 211 1 1 6 2 1704401645"
|
|
]
|
|
},
|
|
"execution_count": 11,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# 3. 상태 테이블 조회정보(A)와 이력 테이블 조회정보(B) 조인(키값 : 교차로번호) : C\n",
|
|
"move2 = pd.merge(move1.copy(), recent_history, how='left', left_on='inter_no', right_on='inter_no').drop_duplicates()\n",
|
|
"move2\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 12,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"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",
|
|
" vertical-align: top;\n",
|
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" }\n",
|
|
"\n",
|
|
" .dataframe thead th {\n",
|
|
" text-align: right;\n",
|
|
" }\n",
|
|
"</style>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>inter_no</th>\n",
|
|
" <th>phas_A</th>\n",
|
|
" <th>phas_B</th>\n",
|
|
" <th>move_A</th>\n",
|
|
" <th>move_B</th>\n",
|
|
" <th>start_unix</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>175</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>1704409269</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>176</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>8</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>1704409150</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>177</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>17</td>\n",
|
|
" <td>18</td>\n",
|
|
" <td>1704409151</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>178</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>7</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>1704397060</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>201</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>1704409260</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>5</th>\n",
|
|
" <td>202</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>17</td>\n",
|
|
" <td>18</td>\n",
|
|
" <td>1704403380</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>6</th>\n",
|
|
" <td>206</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>8</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>1704409220</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>7</th>\n",
|
|
" <td>210</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>7</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>1704409280</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>8</th>\n",
|
|
" <td>211</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>1704401645</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" inter_no phas_A phas_B move_A move_B start_unix\n",
|
|
"0 175 3 3 6 1 1704409269\n",
|
|
"1 176 2 2 8 3 1704409150\n",
|
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"2 177 3 3 17 18 1704409151\n",
|
|
"3 178 2 2 7 3 1704397060\n",
|
|
"4 201 3 3 6 2 1704409260\n",
|
|
"5 202 2 2 17 18 1704403380\n",
|
|
"6 206 3 3 8 4 1704409220\n",
|
|
"7 210 3 3 7 4 1704409280\n",
|
|
"8 211 1 1 6 2 1704401645"
|
|
]
|
|
},
|
|
"execution_count": 12,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# 4. C데이터 프레임에 신규 컬럼(시작 유닉스타임) 생성 후 종료유닉스 타임 값 입력, 종료 유닉스 타임 컬럼 제거\n",
|
|
"move3 = move2.copy().rename(columns = {'end_unix':'start_unix'})\n",
|
|
"move3"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 13,
|
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"metadata": {},
|
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"outputs": [
|
|
{
|
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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",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>inter_no</th>\n",
|
|
" <th>phas_A</th>\n",
|
|
" <th>phas_B</th>\n",
|
|
" <th>move_A</th>\n",
|
|
" <th>move_B</th>\n",
|
|
" <th>start_unix</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>175</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>1704409269</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>176</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>8</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>1704409150</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>177</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>17</td>\n",
|
|
" <td>18</td>\n",
|
|
" <td>1704409151</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>201</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>1704409260</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>6</th>\n",
|
|
" <td>206</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>8</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>1704409220</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>7</th>\n",
|
|
" <td>210</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>7</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>1704409280</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" inter_no phas_A phas_B move_A move_B start_unix\n",
|
|
"0 175 3 3 6 1 1704409269\n",
|
|
"1 176 2 2 8 3 1704409150\n",
|
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"2 177 3 3 17 18 1704409151\n",
|
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"4 201 3 3 6 2 1704409260\n",
|
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"6 206 3 3 8 4 1704409220\n",
|
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"7 210 3 3 7 4 1704409280"
|
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]
|
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},
|
|
"execution_count": 13,
|
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"metadata": {},
|
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"output_type": "execute_result"
|
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}
|
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],
|
|
"source": [
|
|
"# 5. 이동류 이력정보 READ\n",
|
|
"# - CSV 파일로 서버에 저장된 이동류정보를 읽어옮(파일이 없는 경우에는 데이터가 없는 프레임 D 생성)\n",
|
|
"try:\n",
|
|
" if isinstance(movement, pd.DataFrame):\n",
|
|
" pass\n",
|
|
" else:\n",
|
|
" movement = pd.DataFrame()\n",
|
|
"except NameError:\n",
|
|
" movement = pd.DataFrame()\n",
|
|
"# 6. 이동류 이력정보 데이터테이블(D)에 C데이터 add\n",
|
|
"movement = pd.concat([movement, move3])\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 - 3600을 값으로 산출하고, 보관 시간 기준시간보다 작은 시작 유닉스 타임을 가진 행은 모두 제거(1시간 데이터만 보관)\n",
|
|
"movement = movement[movement.start_unix > time - 3600]\n",
|
|
"movement"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 14,
|
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"metadata": {},
|
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"outputs": [
|
|
{
|
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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",
|
|
" }\n",
|
|
"</style>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>inter_no</th>\n",
|
|
" <th>phas_A</th>\n",
|
|
" <th>phas_B</th>\n",
|
|
" <th>move_A</th>\n",
|
|
" <th>move_B</th>\n",
|
|
" <th>start_unix</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>175</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>1704409269</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>176</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>8</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>1704409150</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>177</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>17</td>\n",
|
|
" <td>18</td>\n",
|
|
" <td>1704409151</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>201</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>1704409260</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>6</th>\n",
|
|
" <td>206</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>8</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>1704409220</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>7</th>\n",
|
|
" <td>210</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>7</td>\n",
|
|
" <td>4</td>\n",
|
|
" <td>1704409280</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" inter_no phas_A phas_B move_A move_B start_unix\n",
|
|
"0 175 3 3 6 1 1704409269\n",
|
|
"1 176 2 2 8 3 1704409150\n",
|
|
"2 177 3 3 17 18 1704409151\n",
|
|
"4 201 3 3 6 2 1704409260\n",
|
|
"6 206 3 3 8 4 1704409220\n",
|
|
"7 210 3 3 7 4 1704409280"
|
|
]
|
|
},
|
|
"execution_count": 14,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"movement"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 15,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# # 2. 이력 테이블 조회해서 교차로별로 유닉스시간 최대인 데이터(교차로변호, 종료유닉스타임)만 수집 : B\n",
|
|
"# history = pd.read_csv('../../Data/tables/history.csv', index_col=0)\n",
|
|
"# recent_history = pd.concat([group.iloc[-2:] for inter_no, group in history[history['unix'] < time].groupby('inter_no')])\n",
|
|
"# display(recent_history)\n",
|
|
"# # 3. 상태 테이블 조회정보(A)와 이력 테이블 조회정보(B) 조인(키값 : 교차로번호) : C\n",
|
|
"# ddurs = [f'ddur_{i}' for i in range(1,9)]\n",
|
|
"# inter2stt_unix = {}\n",
|
|
"# for (inter_no, group) in recent_history.groupby('inter_no'):\n",
|
|
"# pre_unix = group.iloc[-2]['unix'] # previous unix time\n",
|
|
"# end_unix = group.iloc[-1]['unix'] # end unix time\n",
|
|
"# sum_dura = group.iloc[-1][ddurs].sum() # the sum of the duration\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 함.\n",
|
|
"# if abs((end_unix - sum_dura) - pre_unix) <= 10:\n",
|
|
"# stt_unix = pre_unix # start unix time\n",
|
|
"# else:\n",
|
|
"# stt_unix = end_unix - sum_dura\n",
|
|
"# inter2stt_unix[inter_no] = stt_unix\n",
|
|
"# move['end_unix'] = move['inter_no'].map(inter2stt_unix)\n",
|
|
"# display(move)"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
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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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|
|
"nbformat_minor": 2
|
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|