diff --git a/Data/tables/0105_make_sample_table.ipynb b/Data/tables/raw_tables/0105_make_sample_table.ipynb similarity index 100% rename from Data/tables/0105_make_sample_table.ipynb rename to Data/tables/raw_tables/0105_make_sample_table.ipynb diff --git a/Data/tables/0105_make_sample_table2.ipynb b/Data/tables/raw_tables/0105_make_sample_table2.ipynb similarity index 100% rename from Data/tables/0105_make_sample_table2.ipynb rename to Data/tables/raw_tables/0105_make_sample_table2.ipynb diff --git a/Data/tables/raw_tables/0108_make_sample_table.ipynb b/Data/tables/raw_tables/0108_make_sample_table.ipynb new file mode 100644 index 000000000..744687a7f --- /dev/null +++ b/Data/tables/raw_tables/0108_make_sample_table.ipynb @@ -0,0 +1,4963 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "from datetime import datetime\n", + "import os" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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inter_nointer_nameinter_latinter_longroup_no
0175한솔삼거리(한솔마을3거리)37.36857127.114783
1176느티마을4단지37.36724127.114803
2177한솔6단지(정자동사무소)37.36619127.114803
3178신기4거리37.36346127.114803
4201느티마을4거리37.36854127.109843
5202느티마을 안촌유치원37.36855127.112413
6206상록마을 321동37.36483127.109813
7210상록4거리(상록마을입구4거리)37.36347127.109823
8211상록마을단일로37.36346127.112373
9212상록마을302동 단일로37.36347127.113063
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" + ], + "text/plain": [ + " inter_no inter_name inter_lat inter_lon group_no\n", + "0 175 한솔삼거리(한솔마을3거리) 37.36857 127.11478 3\n", + "1 176 느티마을4단지 37.36724 127.11480 3\n", + "2 177 한솔6단지(정자동사무소) 37.36619 127.11480 3\n", + "3 178 신기4거리 37.36346 127.11480 3\n", + "4 201 느티마을4거리 37.36854 127.10984 3\n", + "5 202 느티마을 안촌유치원 37.36855 127.11241 3\n", + "6 206 상록마을 321동 37.36483 127.10981 3\n", + "7 210 상록4거리(상록마을입구4거리) 37.36347 127.10982 3\n", + "8 211 상록마을단일로 37.36346 127.11237 3\n", + "9 212 상록마을302동 단일로 37.36347 127.11306 3" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# 교차로정보\n", + "inter_info = pd.read_csv(\"inter_info.csv\")\n", + "inter_info['group_no'] = 3\n", + "inter_info" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " inter_no main_phase mg1A mg1B mg2A mg2B mg3A mg3B mg4A mg4B mg5A \\\n", + "0 175 2 24 27 33 12 15 39 15 19 0 \n", + "1 176 2 21 31 33 30 16 0 0 0 0 \n", + "2 177 2 35 18 36 36 0 0 38 13 0 \n", + "3 178 2 18 19 35 26 36 29 17 37 0 \n", + "4 201 2 25 20 21 32 31 28 31 17 27 \n", + "5 202 2 12 30 0 0 0 0 0 0 0 \n", + "6 206 2 36 29 0 0 31 31 0 0 0 \n", + "7 210 2 19 0 12 13 21 37 12 22 0 \n", + "8 211 2 32 35 0 0 0 0 0 0 0 \n", + "9 212 2 23 30 0 0 0 0 0 0 0 \n", + "\n", + " mg5B mg6A mg6B mg7A mg7B mg8A mg8B r1A r1B r2A r2B r3A r3B \\\n", + "0 0 0 0 0 0 0 0 1 1 1 1 1 1 \n", + "1 0 0 0 0 0 0 0 1 1 1 1 1 0 \n", + "2 0 0 0 0 0 0 0 1 1 1 1 1 0 \n", + "3 0 0 0 0 0 0 0 1 1 1 1 1 1 \n", + "4 27 0 0 0 0 0 0 1 1 1 1 1 1 \n", + "5 0 0 0 0 0 0 0 1 1 1 0 0 0 \n", + "6 0 0 0 0 0 0 0 1 1 1 0 1 1 \n", + "7 0 0 0 0 0 0 0 1 0 1 1 1 1 \n", + "8 0 0 0 0 0 0 0 1 1 1 0 0 0 \n", + "9 0 0 0 0 0 0 0 1 1 1 0 0 0 \n", + "\n", + " r4A r4B r5A r5B r6A r6B r7A r7B r8A r8B y1A y1B y2A y2B y3A \\\n", + "0 1 1 0 0 0 0 0 0 0 0 4 4 4 4 4 \n", + "1 0 0 0 0 0 0 0 0 0 0 4 4 4 4 4 \n", + "2 1 1 0 0 0 0 0 0 0 0 4 4 4 4 0 \n", + "3 1 1 0 0 0 0 0 0 0 0 4 4 4 4 4 \n", + "4 1 1 1 1 0 0 0 0 0 0 4 4 4 4 4 \n", + "5 0 0 0 0 0 0 0 0 0 0 4 4 0 0 0 \n", + "6 1 0 0 0 0 0 0 0 0 0 4 4 0 0 4 \n", + "7 1 1 0 0 0 0 0 0 0 0 4 0 4 4 4 \n", + "8 0 0 0 0 0 0 0 0 0 0 4 4 0 0 0 \n", + "9 0 0 0 0 0 0 0 0 0 0 4 4 0 0 0 \n", + "\n", + " y3B y4A y4B y5A y5B y6A y6B y7A y7B y8A y8B \n", + "0 4 4 4 0 0 0 0 0 0 0 0 \n", + "1 0 0 0 0 0 0 0 0 0 0 0 \n", + "2 0 4 4 0 0 0 0 0 0 0 0 \n", + "3 4 4 4 0 0 0 0 0 0 0 0 \n", + "4 4 4 4 4 4 0 0 0 0 0 0 \n", + "5 0 0 0 0 0 0 0 0 0 0 0 \n", + "6 4 0 0 0 0 0 0 0 0 0 0 \n", + "7 4 4 4 0 0 0 0 0 0 0 0 \n", + "8 0 0 0 0 0 0 0 0 0 0 0 \n", + "9 0 0 0 0 0 0 0 0 0 0 0 " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# 현시구성\n", + "phase_info = pd.read_csv(\"phase_info.csv\")\n", + "phase_info.drop('flow_no', axis=1, inplace=True)\n", + "# display(phase_info)\n", + "mg = phase_info.pivot_table(index='inter_no', columns=['phase_no', 'ring_type'], values='min_green_dur').fillna(0).astype(int)\n", + "y = phase_info.pivot_table(index='inter_no', columns=['phase_no', 'ring_type'], values='yellow_dur').fillna(0).astype(int)\n", + "r = phase_info.pivot_table(index='inter_no', columns=['phase_no', 'ring_type'], values='red_dur').fillna(0).astype(int)\n", + "max_phase_no = phase_info['phase_no'].max()\n", + "new_columns = [f'{col}{phase}{ring}' for col in ['mg', 'y', 'r'] for phase in range(1, max_phase_no + 1) for ring in ['A', 'B']]\n", + "phase_info = pd.concat([mg, y, r], axis=1)\n", + "phase_info.columns = new_columns\n", + "phase_info['main_phase'] = 2\n", + "phase_info['mg6A'] = phase_info['mg6B'] = phase_info['mg7A'] = phase_info['mg7B'] = phase_info['mg8A'] = phase_info['mg8B']= 0\n", + "phase_info['y6A'] = phase_info['y6B'] = phase_info['y7A'] = phase_info['y7B'] = phase_info['y8A'] = phase_info['y8B']= 0\n", + "phase_info['r6A'] = phase_info['r6B'] = phase_info['r7A'] = phase_info['r7B'] = phase_info['r8A'] = phase_info['r8B']= 0\n", + "phase_info = phase_info[sorted(phase_info.columns)]\n", + "phase_info.reset_index(inplace=True)\n", + "with pd.option_context('display.max_rows', None, 'display.max_columns', None): \n", + " display(phase_info)" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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inter_no
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177180000000090stop268000NaNNaNNaNNaN001176179270NaN090180NaNNaNNaNNaN
178180000000090270000090270NaNNaNNaNNaN000180180270270090090180NaNNaNNaNNaN
201180000270000090270090270000090NaNNaNNaN180270270090270090090180000180NaNNaNNaN
202090270stopNaNNaNNaNNaNNaNNaN270090NaNNaNNaNNaNNaNNaNNaN
206180000stop180000stopNaNNaNNaNNaN000180NaN000180NaNNaNNaNNaNNaN
210090270268000359090180000NaNNaNNaNNaNNaN270090000180180270NaNNaNNaNNaN
211090270stopNaNNaNNaNNaNNaNNaN270090NaNNaNNaNNaNNaNNaNNaN
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" + ], + "text/plain": [ + " angle_A1 angle_A2 angle_A3 angle_A4 angle_A5 angle_A6 angle_A7 \\\n", + "inter_no \n", + "175 179004 001095 090270 268000 NaN NaN NaN \n", + "176 180000 180000 270356 NaN NaN NaN NaN \n", + "177 180000 000090 stop 268000 NaN NaN NaN \n", + "178 180000 000090 270000 090270 NaN NaN NaN \n", + "201 180000 270000 090270 090270 000090 NaN NaN \n", + "202 090270 stop NaN NaN NaN NaN NaN \n", + "206 180000 stop 180000 stop NaN NaN NaN \n", + "210 090270 268000 359090 180000 NaN NaN NaN \n", + "211 090270 stop NaN NaN NaN NaN NaN \n", + "212 090270 stop NaN NaN NaN NaN NaN \n", + "\n", + " angle_A8 angle_B1 angle_B2 angle_B3 angle_B4 angle_B5 angle_B6 \\\n", + "inter_no \n", + "175 NaN 003176 179270 090180 270090 NaN NaN \n", + "176 NaN 359180 180270 NaN NaN NaN NaN \n", + "177 NaN 001176 179270 NaN 090180 NaN NaN \n", + "178 NaN 000180 180270 270090 090180 NaN NaN \n", + "201 NaN 180270 270090 270090 090180 000180 NaN \n", + "202 NaN 270090 NaN NaN NaN NaN NaN \n", + "206 NaN 000180 NaN 000180 NaN NaN NaN \n", + "210 NaN NaN 270090 000180 180270 NaN NaN \n", + "211 NaN 270090 NaN NaN NaN NaN NaN \n", + "212 NaN 268090 NaN NaN NaN NaN NaN \n", + "\n", + " angle_B7 angle_B8 \n", + "inter_no \n", + "175 NaN NaN \n", + "176 NaN NaN \n", + "177 NaN NaN \n", + "178 NaN NaN \n", + "201 NaN NaN \n", + "202 NaN NaN \n", + "206 NaN NaN \n", + "210 NaN NaN \n", + "211 NaN NaN \n", + "212 NaN NaN " + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# 방위각정보\n", + "flow_angle = pd.read_csv(\"flow_angle.csv\")\n", + "angle = flow_angle.pivot_table(index='inter_no', columns=['phase_no', 'ring_type'], values='angle_code', aggfunc='first').fillna('NaN')\n", + "new_columns = [f'angle_{ring}{phase}' for phase in range(1, 6) for ring in ['A', 'B']]\n", + "angle.columns = new_columns\n", + "angle['angle_A6'] = angle['angle_A7'] = angle['angle_A8'] = np.nan\n", + "angle['angle_B6'] = angle['angle_B7'] = angle['angle_B8'] = np.nan\n", + "angle = angle[sorted(angle.columns)]\n", + "angle" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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inter_nophas_Aphas_Bmove_Amove_B
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" + ], + "text/plain": [ + " inter_no phas_A phas_B move_A move_B\n", + "0 175 2 2 7 3\n", + "0 176 2 2 8 3\n", + "0 177 2 2 7 3\n", + "0 178 1 1 8 4\n", + "0 201 1 1 8 3\n", + "0 202 1 1 6 2\n", + "0 206 4 4 17 18\n", + "0 210 2 2 5 2\n", + "0 211 1 1 6 2\n", + "0 212 2 2 17 18" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# 이동류번호\n", + "plan = pd.read_csv(\"time_plan.csv\")\n", + "phase = pd.read_csv('phase_info.csv')\n", + "plan = plan[plan.ID.isin([1, 5, 8, 11])]\n", + "ID2starttime = {1:\"00:00\", 5:\"07:00\", 8:\"09:00\", 11:\"18:30\"}\n", + "plan['start_hour'] = plan.ID.apply(lambda id:ID2starttime[id].split(\":\")[0])\n", + "plan['start_minute']=plan.ID.apply(lambda id:ID2starttime[id].split(\":\")[1])\n", + "plan = plan[['inter_no', 'start_hour', 'start_minute', 'phase_no', 'ring_type', 'duration', 'cycle']]\n", + "plan_ = pd.merge(plan, phase[['inter_no', 'phase_no', 'ring_type', 'flow_no']], on=['inter_no', 'phase_no', 'ring_type'], how='left')\n", + "plan_['flow_no'] = plan_['flow_no'].fillna(18).astype(int)\n", + "plan_['start_second'] = plan_.start_hour.astype(int)*3600 + plan_.start_minute.astype(int)*60\n", + "plan_ = plan_[['inter_no', 'start_second', 'phase_no', 'ring_type', 'duration', 'flow_no', 'cycle']]\n", + "cycle_dict = dict(zip(zip(plan_['inter_no'], plan_['start_second']), plan_['cycle']))\n", + "df = plan_[['inter_no','start_second','cycle']].drop_duplicates()\n", + "df = df.reset_index(drop=True)\n", + "df['start_second_exact'] = 0\n", + "for i in range(1, len(df)):\n", + " if i % 4 != 0:\n", + " prev = df.loc[i-1, 'start_second_exact']\n", + " start_second = df.loc[i, 'start_second']\n", + " cycle = df.loc[i-1, 'cycle']\n", + " df.loc[i, 'start_second_exact'] = (start_second - prev) % cycle + start_second\n", + "inter2start = {inter_no:list(df[df.inter_no==inter_no]['start_second_exact']) for inter_no in df.inter_no}\n", + "plan_ = plan_.pivot_table(index=['inter_no', 'start_second', 'phase_no'],\n", + " columns='ring_type',\n", + " values=['duration', 'flow_no'],\n", + " aggfunc='first').reset_index()\n", + "plan_.columns = ['inter_no', 'start_second', 'phase_no', 'dura_A', 'dura_B', 'move_A', 'move_B']\n", + "inter2no_phase = {inter_no:group.phase_no.unique().max() for (inter_no, group) in plan.groupby('inter_no')}\n", + "\n", + "midnight = int(datetime(2024, 1, 5, 0, 0, 0).timestamp())\n", + "present = int(datetime(2024, 1, 5, 3, 55, 48).timestamp()) # <===== 현재시각\n", + "sec = present - midnight\n", + "the_start_second = np.max(df.start_second[df.start_second <= sec])\n", + "move = []\n", + "for inter_no in plan_.inter_no.unique():\n", + " cycle = cycle_dict[(inter_no, the_start_second)]\n", + " df = plan_[(plan_.inter_no==inter_no)&(plan_.start_second==the_start_second)].reset_index(drop=True)\n", + " remainder = sec % cycle\n", + " df['cums_A'] = df.copy().dura_A.cumsum()\n", + " df['cums_B'] = df.copy().dura_B.cumsum()\n", + " ind_A = len(df.cums_A[df.cums_A <= remainder])%inter2no_phase[inter_no]\n", + " ind_B = len(df.cums_B[df.cums_B <= remainder])%inter2no_phase[inter_no]\n", + " dura_A = df.loc[ind_A,'dura_A']\n", + " dura_B = df.loc[ind_B,'dura_B']\n", + " phas_A = df.loc[ind_A,'phase_no']\n", + " phas_B = df.loc[ind_B,'phase_no']\n", + " move_A = df.loc[ind_A,'move_A']\n", + " move_B = df.loc[ind_B,'move_B']\n", + " move.append(pd.DataFrame({'inter_no':[inter_no],'phas_A':[phas_A], 'phas_B':[phas_B],'move_A':[move_A], 'move_B':[move_B]}))\n", + "move = pd.concat(move)\n", + "move" + ] + }, + { + "cell_type": "code", + "execution_count": 368, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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inter_nogroup_notimeplan_noIDphase_noring_typedurationcycleoffset
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" + ], + "text/plain": [ + " inter_no group_no timeplan_no ID phase_no ring_type duration \\\n", + "0 175 27 1 1 1 A 37 \n", + "1 175 27 1 1 1 B 37 \n", + "2 175 27 1 1 2 A 39 \n", + "3 175 27 1 1 2 B 39 \n", + "4 175 27 1 1 3 A 55 \n", + "... ... ... ... .. ... ... ... \n", + "1083 212 27 1 15 2 B 211 \n", + "1084 212 27 1 16 1 A 39 \n", + "1085 212 27 1 16 1 B 39 \n", + "1086 212 27 1 16 2 A 211 \n", + "1087 212 27 1 16 2 B 211 \n", + "\n", + " cycle offset \n", + "0 160 57 \n", + "1 160 57 \n", + "2 160 57 \n", + "3 160 57 \n", + "4 160 57 \n", + "... ... ... \n", + "1083 250 0 \n", + "1084 250 0 \n", + "1085 250 0 \n", + "1086 250 0 \n", + "1087 250 0 \n", + "\n", + "[1088 rows x 9 columns]" + ] + }, + "execution_count": 368, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "plan = pd.read_csv(\"time_plan.csv\")\n", + "plan" + ] + }, + { + "cell_type": "code", + "execution_count": 509, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " inter_no start_hour start_minute ddur_1 ddur_2 ddur_3 ddur_4 ddur_5 \\\n", + "0 175 00 00 37 39 25 30 29 \n", + "1 175 07 00 40 42 29 26 33 \n", + "2 175 09 00 43 45 33 22 37 \n", + "3 175 18 30 46 48 37 18 41 \n", + "4 176 00 00 37 73 40 0 0 \n", + "5 176 07 00 37 93 40 0 0 \n", + "6 176 09 00 37 103 40 0 0 \n", + "7 176 18 30 37 113 40 0 0 \n", + "8 177 00 00 36 20 68 26 0 \n", + "9 177 07 00 40 25 71 34 0 \n", + "10 177 09 00 43 27 70 40 0 \n", + "11 177 18 30 45 32 77 36 0 \n", + "12 178 00 00 38 39 40 23 0 \n", + "13 178 07 00 38 39 42 20 21 \n", + "14 178 09 00 38 39 43 28 22 \n", + "15 178 18 30 38 39 44 36 23 \n", + "16 201 00 00 24 24 17 58 17 \n", + "17 201 07 00 30 36 18 58 18 \n", + "18 201 09 00 33 36 25 58 18 \n", + "19 201 18 30 36 50 18 58 18 \n", + "20 202 00 00 39 101 0 0 0 \n", + "21 202 07 00 46 114 0 0 0 \n", + "22 202 09 00 46 114 0 0 0 \n", + "23 202 18 30 48 122 0 0 0 \n", + "24 206 00 00 33 35 26 26 0 \n", + "25 206 07 00 44 44 26 26 0 \n", + "26 206 09 00 45 53 26 26 0 \n", + "27 206 18 30 46 62 26 26 0 \n", + "28 210 00 00 24 19 29 56 22 \n", + "29 210 07 00 24 19 39 65 23 \n", + "30 210 09 00 28 15 43 70 24 \n", + "31 210 18 30 24 19 47 75 25 \n", + "32 211 00 00 28 97 0 0 0 \n", + "33 211 07 00 28 107 0 0 0 \n", + "34 211 09 00 28 112 0 0 0 \n", + "35 211 18 30 28 117 0 0 0 \n", + "36 212 00 00 39 161 0 0 0 \n", + "37 212 07 00 39 181 0 0 0 \n", + "38 212 09 00 39 191 0 0 0 \n", + "39 212 18 30 39 201 0 0 0 \n", + "\n", + " ddur_6 ddur_7 ddur_8 cycle offset \n", + "0 0 0 0 160 57 \n", + "1 0 0 0 170 40 \n", + "2 0 0 0 180 28 \n", + "3 0 0 0 190 18 \n", + "4 0 0 0 150 131 \n", + "5 0 0 0 170 153 \n", + "6 0 0 0 180 169 \n", + "7 0 0 0 190 185 \n", + "8 0 0 0 150 35 \n", + "9 0 0 0 170 33 \n", + "10 0 0 0 180 41 \n", + "11 0 0 0 190 49 \n", + "12 0 0 0 140 50 \n", + "13 0 0 0 160 90 \n", + "14 0 0 0 170 80 \n", + "15 0 0 0 180 75 \n", + "16 0 0 0 140 133 \n", + "17 0 0 0 160 132 \n", + "18 0 0 0 170 134 \n", + "19 0 0 0 180 137 \n", + "20 0 0 0 140 103 \n", + "21 0 0 0 160 103 \n", + "22 0 0 0 160 103 \n", + "23 0 0 0 170 103 \n", + "24 0 0 0 120 10 \n", + "25 0 0 0 140 7 \n", + "26 0 0 0 150 17 \n", + "27 0 0 0 160 10 \n", + "28 0 0 0 150 115 \n", + "29 0 0 0 170 131 \n", + "30 0 0 0 180 137 \n", + "31 0 0 0 190 143 \n", + "32 0 0 0 125 45 \n", + "33 0 0 0 135 45 \n", + "34 0 0 0 140 55 \n", + "35 0 0 0 145 55 \n", + "36 0 0 0 200 0 \n", + "37 0 0 0 220 0 \n", + "38 0 0 0 230 0 \n", + "39 0 0 0 240 0 " + ] + }, + "execution_count": 509, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# 신호계획\n", + "plan = pd.read_csv(\"time_plan.csv\")\n", + "plan = plan[plan.ID.isin([1, 5, 8, 11])]\n", + "ID2starttime = {1:\"00:00\", 5:\"07:00\", 8:\"09:00\", 11:\"18:30\"}\n", + "plan['start_hour'] = plan.ID.apply(lambda id:ID2starttime[id].split(\":\")[0])\n", + "plan['start_minute']=plan.ID.apply(lambda id:ID2starttime[id].split(\":\")[1])\n", + "plan = plan[['inter_no', 'start_hour', 'start_minute', 'phase_no', 'ring_type', 'duration', 'cycle', 'offset']]\n", + "plan = plan.pivot_table(index=['inter_no', 'start_hour', 'start_minute', 'cycle', 'offset'], columns=['phase_no','ring_type'], values='duration', aggfunc='first').fillna(0).astype(int)\n", + "new_columns = [f'dura_{ring}{phase}' for phase in range(1, 6) for ring in ['A', 'B']]\n", + "plan.columns = new_columns\n", + "new_columns = [f'dura_{ring}{phase}' for phase in range(1, 9) for ring in ['A', 'B']]\n", + "for col in new_columns:\n", + " if col not in plan.columns:\n", + " plan[col] = 0\n", + "plan.reset_index(inplace=True)\n", + "plan = plan[list(plan.columns)[:3] + sorted(plan.columns)[1:-4] + list(plan.columns)[3:5]]\n", + "\n", + "cums_A = np.array(plan[[f'dura_A{k}' for k in range(1,9)]].cumsum(axis=1))\n", + "cums_B = np.array(plan[[f'dura_B{k}' for k in range(1,9)]].cumsum(axis=1))\n", + "detailed_cums = []\n", + "i = 0\n", + "for row_A, row_B in zip(cums_A, cums_B):\n", + " combined_row = np.unique(np.concatenate((row_A, row_B)))\n", + " ddur = np.concatenate(([combined_row[0]], np.diff(combined_row)))\n", + " ddur = np.pad(ddur, (0, 8 - len(ddur)), constant_values=(0))\n", + " detailed_cums.append(ddur)\n", + " for j in range(8):\n", + " plan.at[i, f'ddur_{j+1}'] = ddur[j]\n", + " i+=1\n", + "plan = plan[['inter_no', 'start_hour', 'start_minute'] + [f'ddur_{i}' for i in range(1,9)] + ['cycle', 'offset']\n", + " #+ [f'dura_{phase}{i}' for phase in ['A','B'] for i in range(1,9)]\n", + " ]\n", + "plan[[f'ddur_{i}' for i in range(1,9)]] = plan[[f'ddur_{i}' for i in range(1,9)]].astype(int)\n", + "\n", + "plan" + ] + }, + { + "cell_type": "code", + "execution_count": 528, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " inter_no start_hour start_minute ddur_1 ddur_2 ddur_3 ddur_4 ddur_5 \\\n", + "0 175 00 00 37 39 25 30 29 \n", + "1 175 07 00 40 42 29 26 33 \n", + "2 175 09 00 43 45 33 22 37 \n", + "3 175 18 30 46 48 37 18 41 \n", + "\n", + " ddur_6 ddur_7 ddur_8 cycle offset unix \n", + "0 0 0 0 160 57 1704380400 \n", + "1 0 0 0 170 40 1704405600 \n", + "2 0 0 0 180 28 1704412800 \n", + "3 0 0 0 190 18 1704447000 " + ] + }, + "execution_count": 528, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "planned = plan.copy()\n", + "midnight = int(datetime(2024, 1, 5, 0, 0, 0).timestamp())\n", + "next_day = int(datetime(2024, 1, 6, 0, 0, 0).timestamp())\n", + "# planned['seconds'] = planned['start_hour'].astype(int)*3600 + planned['start_minute'].astype(int)*60\n", + "planned['unix'] = planned['start_hour'].astype(int)*3600 + plan['start_minute'].astype(int)*60 + midnight\n", + "plan175 = planned[planned.inter_no==175]" + ] + }, + { + "cell_type": "code", + "execution_count": 589, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0\n" + ] + } + ], + "source": [ + "import random\n", + "r = random.choices([0, -1, 1], weights=[80, 10, 10])[0]\n", + "print(r)" + ] + }, + { + "cell_type": "code", + "execution_count": 622, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0 160 1704405600\n", + "1 170 1704412800\n", + "2 180 1704447000\n", + "3 190 1704380400\n" + ] + }, + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " inter_no start_hour start_minute ddur_1 ddur_2 ddur_3 ddur_4 ddur_5 ddur_6 \\\n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "2 175 09 00 43 45 33 22 37 0 \n", + "\n", + " ddur_7 ddur_8 cycle offset unix \n", + "2 0 0 180 28 1704434600 \n", + "2 0 0 180 28 1704434780 \n", + "2 0 0 180 28 1704434960 \n", + "2 0 0 180 28 1704435140 \n", + "2 0 0 180 28 1704435320 \n", + "2 0 0 180 28 1704435500 \n", + "2 0 0 180 28 1704435680 \n", + "2 0 0 180 28 1704435860 \n", + "2 0 0 180 28 1704436040 \n", + "2 0 0 180 28 1704436221 \n", + "2 0 0 180 28 1704436580 \n", + "2 0 0 180 28 1704436760 \n", + "2 0 0 180 28 1704436940 \n", + "2 0 0 180 28 1704437120 \n", + "2 0 0 180 28 1704437300 \n", + "2 0 0 180 28 1704437480 \n", + "2 0 0 180 28 1704437660 \n", + "2 0 0 180 28 1704437841 \n", + "2 0 0 180 28 1704438200 \n", + "2 0 0 180 28 1704438380 \n", + "2 0 0 180 28 1704438560 \n", + "2 0 0 180 28 1704438740 \n", + "2 0 0 180 28 1704438920 \n", + "2 0 0 180 28 1704439100 \n", + "2 0 0 180 28 1704439280 \n", + "2 0 0 180 28 1704439460 \n", + "2 0 0 180 28 1704439640 \n", + "2 0 0 180 28 1704439821 \n", + "2 0 0 180 28 1704440180 \n", + "2 0 0 180 28 1704440360 \n", + "2 0 0 180 28 1704440540 \n", + "2 0 0 180 28 1704440721 \n", + "2 0 0 180 28 1704441080 \n", + "2 0 0 180 28 1704441260 \n", + "2 0 0 180 28 1704441441 \n", + "2 0 0 180 28 1704441800 \n", + "2 0 0 180 28 1704441980 \n", + "2 0 0 180 28 1704442161 \n", + "2 0 0 180 28 1704442520 \n", + "2 0 0 180 28 1704442700 \n", + "2 0 0 180 28 1704442880 \n", + "2 0 0 180 28 1704443060 \n", + "2 0 0 180 28 1704443240 \n", + "2 0 0 180 28 1704443420 \n", + "2 0 0 180 28 1704443600 \n", + "2 0 0 180 28 1704443780 \n", + "2 0 0 180 28 1704443960 \n", + "2 0 0 180 28 1704444139 \n", + "2 0 0 180 28 1704444500 \n", + "2 0 0 180 28 1704444680 \n", + "2 0 0 180 28 1704444860 \n", + "2 0 0 180 28 1704445041 \n", + "2 0 0 180 28 1704445400 \n", + "2 0 0 180 28 1704445581 \n", + "2 0 0 180 28 1704445940 \n", + "2 0 0 180 28 1704446120 \n", + "2 0 0 180 28 1704446300 \n", + "2 0 0 180 28 1704446479 \n", + "2 0 0 180 28 1704446840 \n", + "2 0 0 180 28 1704447019 " + ] + }, + "execution_count": 622, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "rows = []\n", + "current_time = midnight\n", + "for i in range(len(plan175)):\n", + " first_row = planned.iloc[i]\n", + " cycle = first_row['cycle']\n", + " unix_end = planned.iloc[i+1]['unix'] if i < len(plan175) else next_day\n", + " r=0\n", + " print(i, cycle, unix_end)\n", + " while current_time <= unix_end:\n", + " r = random.choices([0, -1, 1], weights=[10, 1, 1])[0]\n", + " if current_time % 10 == 9:\n", + " r = cycle + 1\n", + " elif current_time % 10 == 1:\n", + " r = cycle - 1\n", + " current_time += cycle + r\n", + " new_row = first_row.copy()\n", + " new_row['unix'] = current_time\n", + " rows.append(new_row)\n", + "history = pd.concat(rows, axis=1).transpose()\n", + "history[-60:]" + ] + }, + { + "cell_type": "code", + "execution_count": 483, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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b/Data/tables/raw_tables/U_TURN.csv new file mode 100644 index 000000000..cea876faa --- /dev/null +++ b/Data/tables/raw_tables/U_TURN.csv @@ -0,0 +1,8 @@ +inode_id,unode_id,from_edge_id,to_edge_id,adj_from_edge_id,adj_to_edge_id +i0,u00,571500487_02,571500487_01.32,-571500487_01,571500487_01 +i2,u20,571542810_01.51,571542810_02,571542811_02,571542811_01 +,u_0,571542808_02,571542808_01.14,-571542808_01,571542808_01 +i3,u30,571556452_01,571556452_02,571556450_02,571556450_01 +i3,u31,571500475_02,571500475_01.26,-571500475_01,571500475_01 +i3,u32,571540303_02,-571540303_02,571540303_02.21,571540303_01 +i6,u60,571500535_02,-571500535_02,571500535_02.18,571500535_01 diff --git a/Data/tables/raw_tables/flow_3points.csv b/Data/tables/raw_tables/flow_3points.csv new file mode 100644 index 000000000..eb26fe748 --- /dev/null +++ b/Data/tables/raw_tables/flow_3points.csv @@ -0,0 +1,61 @@ +inter_no,phase_no,ring_type,flow_lat_1,flow_lon_1,flow_lat_2,flow_lon_2,flow_lat_3,flow_lon_3 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+27,03-01,1,4 +27,05-05,1,4 +27,06-06,1,4 +27,08-15,1,4 +27,10-03,1,4 +27,10-09,1,4 +27,12-25,1,4 diff --git a/Data/tables/raw_tables/inter_info.csv b/Data/tables/raw_tables/inter_info.csv new file mode 100644 index 000000000..728193f21 --- /dev/null +++ b/Data/tables/raw_tables/inter_info.csv @@ -0,0 +1,11 @@ +inter_no,inter_name,inter_lat,inter_lon +175,한솔삼거리(한솔마을3거리),37.36857,127.11478 +176,느티마을4단지,37.36724,127.1148 +177,한솔6단지(정자동사무소),37.36619,127.1148 +178,신기4거리,37.36346,127.1148 +201,느티마을4거리,37.36854,127.10984 +202,느티마을 안촌유치원,37.36855,127.11241 +206,상록마을 321동,37.36483,127.10981 +210,상록4거리(상록마을입구4거리),37.36347,127.10982 +211,상록마을단일로,37.36346,127.11237 +212,상록마을302동 단일로,37.36347,127.11306 diff --git a/Data/tables/raw_tables/phase_info.csv b/Data/tables/raw_tables/phase_info.csv new file mode 100644 index 000000000..bdb1eb1e7 --- /dev/null +++ b/Data/tables/raw_tables/phase_info.csv @@ -0,0 +1,61 @@ +inter_no,phase_no,ring_type,flow_no,option,min_green_dur,yellow_dur,red_dur 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+212,27,1,16,1,B,39,250,0 +212,27,1,16,2,A,211,250,0 +212,27,1,16,2,B,211,250,0 diff --git a/Data/tables/raw_tables/tod_plan.csv b/Data/tables/raw_tables/tod_plan.csv new file mode 100644 index 000000000..e35b784ad --- /dev/null +++ b/Data/tables/raw_tables/tod_plan.csv @@ -0,0 +1,51 @@ +group_no,timeplan_no,todplan_no,start_time,ID +55,1,1,6:00,2 +55,1,1,7:00,8 +55,1,1,9:30,6 +55,1,1,17:00,10 +55,1,1,20:30,3 +55,1,1,23:30,1 +55,1,2,6:00,2 +55,1,2,7:00,8 +55,1,2,9:30,6 +55,1,2,17:00,10 +55,1,2,20:30,3 +55,1,2,23:30,1 +55,1,3,6:00,2 +55,1,3,7:00,8 +55,1,3,9:30,7 +55,1,3,17:00,10 +55,1,3,20:30,3 +55,1,3,23:30,1 +55,1,4,6:00,2 +55,1,4,7:00,6 +55,1,4,20:30,3 +55,1,4,23:30,1 +27,1,1,5:30,2 +27,1,1,6:30,5 +27,1,1,7:00,8 +27,1,1,9:30,6 +27,1,1,17:00,10 +27,1,1,21:00,7 +27,1,1,22:00,4 +27,1,1,23:30,1 +27,1,2,5:30,2 +27,1,2,6:30,5 +27,1,2,7:00,8 +27,1,2,9:30,6 +27,1,2,17:00,10 +27,1,2,21:00,7 +27,1,2,22:00,4 +27,1,2,23:30,1 +27,1,3,5:30,2 +27,1,3,6:30,5 +27,1,3,7:00,8 +27,1,3,9:30,6 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