From 1c3ca4153b809c9193ac13fe1b53539dc69b61d1 Mon Sep 17 00:00:00 2001 From: govin08 Date: Thu, 7 Mar 2024 21:24:18 +0900 Subject: [PATCH] tested for new yellow-red code. I'll apply to the generate_signals.py soon --- .gitignore | 3 +- Analysis/0221_three_points/flow_3points.csv | 61 + Analysis/0221_three_points/three_points.ipynb | 1515 ++++ .../0307_red_yellow/0307_red_yellow.ipynb | 7186 +++++++++++++++++ .../0307_red_yellow/0307_red_yellow_2.ipynb | 1527 ++++ Analysis/0307_red_yellow/setup_tls_program.py | 274 + Data/tables/plan.csv | 66 +- .../raw_tables/0116_make_sample_table.ipynb | 1451 +++- Documents/0116_header_unix.txt | 8 + ...΄ 제곡 λ°©μ•ˆ_20240108_κ²€ν† μ˜κ²¬.hwpx | Bin 0 -> 286073 bytes ...³΄ 제곡 λ°©μ•ˆ_20240108_κ²€ν† μ˜κ²¬.pdf | Bin 0 -> 402151 bytes ...œκ³΅ λ°©μ•ˆ_20240108_μˆ˜μ •_김선쀑.hwpx | Bin 0 -> 286530 bytes ...œ μ‹ ν˜Έμ •λ³΄ 제곡 λ°©μ•ˆ_20240111.hwpx | Bin 0 -> 289872 bytes ...‘œ μ‹ ν˜Έμ •λ³΄ 제곡 λ°©μ•ˆ_20240111.pdf | Bin ...œ μ‹ ν˜Έμ •λ³΄ 제곡 λ°©μ•ˆ_20240220.hwpx | Bin 0 -> 297320 bytes ...‘œ μ‹ ν˜Έμ •λ³΄ 제곡 λ°©μ•ˆ_20240220.pdf | Bin 0 -> 418285 bytes Results/sn_1704416700.add.xml | 682 +- .../generate_signals.cpython-38.pyc | Bin 27443 -> 23000 bytes .../preprocess_daily.cpython-38.pyc | Bin 27695 -> 30995 bytes Scripts/generate_signals.py | 4 +- Scripts/generate_signals_until_4-1.py | 876 -- 21 files changed, 12294 insertions(+), 1359 deletions(-) create mode 100644 Analysis/0221_three_points/flow_3points.csv create mode 100644 Analysis/0221_three_points/three_points.ipynb create mode 100644 Analysis/0307_red_yellow/0307_red_yellow.ipynb create mode 100644 Analysis/0307_red_yellow/0307_red_yellow_2.ipynb create mode 100644 Analysis/0307_red_yellow/setup_tls_program.py create mode 100644 Documents/0116_header_unix.txt create mode 100644 Documents/동뢀ICT/κ΅ν†΅μ‹ ν˜Έμ œμ–΄μ„Όν„°μ˜ ꡐ차둜 μ‹ ν˜Έμ •λ³΄ 제곡 λ°©μ•ˆ_20240108_κ²€ν† μ˜κ²¬.hwpx create mode 100644 Documents/동뢀ICT/κ΅ν†΅μ‹ ν˜Έμ œμ–΄μ„Όν„°μ˜ ꡐ차둜 μ‹ ν˜Έμ •λ³΄ 제곡 λ°©μ•ˆ_20240108_κ²€ν† μ˜κ²¬.pdf create mode 100644 Documents/동뢀ICT/κ΅ν†΅μ‹ ν˜Έμ œμ–΄μ„Όν„°μ˜ ꡐ차둜 μ‹ ν˜Έμ •λ³΄ 제곡 λ°©μ•ˆ_20240108_μˆ˜μ •_김선쀑.hwpx create mode 100644 Documents/동뢀ICT/κ΅ν†΅μ‹ ν˜Έμ œμ–΄μ„Όν„°μ˜ ꡐ차둜 μ‹ ν˜Έμ •λ³΄ 제곡 λ°©μ•ˆ_20240111.hwpx rename Documents/{ => 동뢀ICT}/κ΅ν†΅μ‹ ν˜Έμ œμ–΄μ„Όν„°μ˜ ꡐ차둜 μ‹ ν˜Έμ •λ³΄ 제곡 λ°©μ•ˆ_20240111.pdf (100%) create mode 100644 Documents/동뢀ICT/κ΅ν†΅μ‹ ν˜Έμ œμ–΄μ„Όν„°μ˜ ꡐ차둜 μ‹ ν˜Έμ •λ³΄ 제곡 λ°©μ•ˆ_20240220.hwpx create mode 100644 Documents/동뢀ICT/κ΅ν†΅μ‹ ν˜Έμ œμ–΄μ„Όν„°μ˜ ꡐ차둜 μ‹ ν˜Έμ •λ³΄ 제곡 λ°©μ•ˆ_20240220.pdf delete mode 100644 Scripts/generate_signals_until_4-1.py diff --git a/.gitignore b/.gitignore index 44ce6dd9c..1499b991c 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,4 @@ Data/tables/move/* Intermediates/histid/* -Intermediates/movement/* \ No newline at end of file +Intermediates/movement/* +Analysis/0215_augmentation/* \ No newline at end of file diff --git a/Analysis/0221_three_points/flow_3points.csv b/Analysis/0221_three_points/flow_3points.csv new file mode 100644 index 000000000..eb26fe748 --- /dev/null +++ b/Analysis/0221_three_points/flow_3points.csv @@ -0,0 +1,61 @@ 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+212,1,B,37.36336,127.11266,37.36337,127.11306,37.36337,127.11321 +212,2,A,19.69448,117.9926,19.69448,117.9926,19.69448,117.9926 diff --git a/Analysis/0221_three_points/three_points.ipynb b/Analysis/0221_three_points/three_points.ipynb new file mode 100644 index 000000000..9ae79a609 --- /dev/null +++ b/Analysis/0221_three_points/three_points.ipynb @@ -0,0 +1,1515 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "def calculate_angle_code(lat1, lng1, lat2, lng2, lat3, lng3):\n", + " # λͺ¨λ“  μ’Œν‘œκ°€ λ™μΌν•œ 경우 NaN λ°˜ν™˜\n", + " if ((lat1 == lat2) and (lng1 == lng2)) or ((lat2 == lat3) and (lng2 == lng3)):\n", + " return np.nan\n", + " # μœ„λ„μ™€ 경도λ₯Ό λΌλ””μ•ˆμœΌλ‘œ λ³€ν™˜\n", + " lat1, lng1, lat2, lng2, lat3, lng3 = map(np.radians, [lat1, lng1, lat2, lng2, lat3, lng3])\n", + " # μ§„μž…λ°©μœ„κ° 계산\n", + " dlng_entry = lng1 - lng2\n", + " x_entry = np.sin(dlng_entry) * np.cos(lat1)\n", + " y_entry = np.cos(lat2) * np.sin(lat1) - (np.sin(lat2) * np.cos(lat1) * np.cos(dlng_entry))\n", + " entry_bearing = np.arctan2(x_entry, y_entry)\n", + " entry_bearing = np.degrees(entry_bearing)\n", + " entry_bearing = round((entry_bearing + 360) % 360)\n", + " # μ§„μΆœλ°©μœ„κ° 계산\n", + " dlng_exit = lng3 - lng2\n", + " x_exit = np.sin(dlng_exit) * np.cos(lat3)\n", + " y_exit = np.cos(lat2) * np.sin(lat3) - (np.sin(lat2) * np.cos(lat3) * np.cos(dlng_exit))\n", + " exit_bearing = np.arctan2(x_exit, y_exit)\n", + " exit_bearing = np.degrees(exit_bearing)\n", + " exit_bearing = round((exit_bearing + 360) % 360)\n", + " # angle_code 생성\n", + " angle_code = f\"{entry_bearing:03}{exit_bearing:03}\"\n", + " return angle_code\n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'331047'" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "calculate_angle_code(37.5665, 126.9780, 37.5515, 126.9885, 37.5666, 127.0089)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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inter_nophase_noring_typeflow_lat_1flow_lon_1flow_lat_2flow_lon_2flow_lat_3flow_lon_3
01751A37.36825127.1149137.36857127.1149037.36869127.11491
11751B37.36890127.1146737.36857127.1146537.36845127.11466
21752A37.36889127.1149137.36857127.1149037.36856127.11505
31752B37.36824127.1146637.36857127.1146537.36857127.11451
41753A37.36867127.1151937.36867127.1147837.36867127.11463
51753B37.36847127.1151837.36847127.1147837.36835127.11478
61754A37.36866127.1143737.36867127.1147837.36878127.11478
71754B37.36847127.1143737.36847127.1147837.36847127.11493
81761A37.36691127.1149337.36724127.1149337.36735127.11493
91761B37.36756127.1146737.36723127.1146837.36712127.11468
101762A37.36691127.1149337.36724127.1149337.36735127.11493
111762B37.36691127.1146837.36724127.1146837.36724127.11453
121763A37.36734127.1144037.36734127.1148137.36745127.11480
131771A37.36587127.1149237.36619127.1149237.36631127.11492
141771B37.36652127.1146837.36619127.1146737.36608127.11468
151772A37.36652127.1149237.36619127.1149237.36619127.11507
161772B37.36587127.1146837.36619127.1146737.36619127.11453
171773A19.69448117.9926019.69448117.9926019.69448117.99260
181774A37.36628127.1143937.36629127.1148037.36641127.11480
191774B37.36609127.1152037.36609127.1148037.36598127.11480
201781A37.36313127.1149337.36346127.1149337.36358127.11493
211781B37.36378127.1146837.36346127.1146837.36334127.11468
221782A37.36378127.1149337.36346127.1149337.36346127.11507
231782B37.36313127.1146837.36346127.1146837.36346127.11453
241783A37.36356127.1144037.36356127.1148037.36367127.11480
251783B37.36336127.1143937.36336127.1148037.36336127.11495
261784A37.36356127.1152137.36356127.1148037.36356127.11465
271784B37.36336127.1152137.36336127.1148037.36324127.11480
282011A37.36822127.1099637.36854127.1099637.36866127.10996
292011B37.36822127.1097137.36854127.1097137.36854127.10957
302012A37.36864127.1094337.36864127.1098437.36876127.10984
312012B37.36844127.1094337.36844127.1098437.36844127.10999
322013A37.36864127.1102537.36864127.1098437.36864127.10969
332013B37.36844127.1094337.36844127.1098437.36844127.10999
342014A37.36864127.1102537.36864127.1098437.36864127.10969
352014B37.36844127.1102537.36844127.1098437.36832127.10984
362015A37.36887127.1099637.36854127.1099637.36854127.11011
372015B37.36886127.1097137.36854127.1097137.36842127.10971
382021A37.36865127.1128237.36865127.1124137.36865127.11227
392021B37.36845127.1120137.36845127.1124137.36845127.11256
402022A19.69448117.9926019.69448117.9926019.69448117.99260
412061A37.36451127.1099437.36483127.1099437.36495127.10994
422061B37.36516127.1096937.36484127.1096937.36472127.10969
432062A19.69448117.9926019.69448117.9926019.69448117.99260
442063A37.36451127.1099437.36483127.1099437.36495127.10994
452063B37.36516127.1096937.36484127.1096937.36472127.10969
462064A19.69448117.9926019.69448117.9926019.69448117.99260
472101A37.36357127.1102337.36357127.1098237.36357127.10968
482102A37.36356127.1094137.36357127.1098237.36369127.10982
492102B37.36337127.1094237.36337127.1098237.36337127.10997
502103A37.36380127.1099437.36347127.1099537.36347127.11009
512103B37.36380127.1097037.36347127.1097037.36336127.10970
522104A37.36315127.1099537.36347127.1099537.36359127.10995
532104B37.36315127.1097037.36347127.1097037.36347127.10955
542111A37.36356127.1127737.36356127.1123737.36356127.11222
552111B37.36336127.1119637.36336127.1123737.36336127.11252
562112A19.69448117.9926019.69448117.9926019.69448117.99260
572121A37.36357127.1134737.36357127.1130637.36357127.11291
582121B37.36336127.1126637.36337127.1130637.36337127.11321
592122A19.69448117.9926019.69448117.9926019.69448117.99260
\n", + "
" + ], + "text/plain": [ + " inter_no phase_no ring_type flow_lat_1 flow_lon_1 flow_lat_2 \\\n", + "0 175 1 A 37.36825 127.11491 37.36857 \n", + "1 175 1 B 37.36890 127.11467 37.36857 \n", + "2 175 2 A 37.36889 127.11491 37.36857 \n", + "3 175 2 B 37.36824 127.11466 37.36857 \n", + "4 175 3 A 37.36867 127.11519 37.36867 \n", + "5 175 3 B 37.36847 127.11518 37.36847 \n", + "6 175 4 A 37.36866 127.11437 37.36867 \n", + "7 175 4 B 37.36847 127.11437 37.36847 \n", + "8 176 1 A 37.36691 127.11493 37.36724 \n", + "9 176 1 B 37.36756 127.11467 37.36723 \n", + "10 176 2 A 37.36691 127.11493 37.36724 \n", + "11 176 2 B 37.36691 127.11468 37.36724 \n", + "12 176 3 A 37.36734 127.11440 37.36734 \n", + "13 177 1 A 37.36587 127.11492 37.36619 \n", + "14 177 1 B 37.36652 127.11468 37.36619 \n", + "15 177 2 A 37.36652 127.11492 37.36619 \n", + "16 177 2 B 37.36587 127.11468 37.36619 \n", + "17 177 3 A 19.69448 117.99260 19.69448 \n", + "18 177 4 A 37.36628 127.11439 37.36629 \n", + "19 177 4 B 37.36609 127.11520 37.36609 \n", + "20 178 1 A 37.36313 127.11493 37.36346 \n", + "21 178 1 B 37.36378 127.11468 37.36346 \n", + "22 178 2 A 37.36378 127.11493 37.36346 \n", + "23 178 2 B 37.36313 127.11468 37.36346 \n", + "24 178 3 A 37.36356 127.11440 37.36356 \n", + "25 178 3 B 37.36336 127.11439 37.36336 \n", + "26 178 4 A 37.36356 127.11521 37.36356 \n", + "27 178 4 B 37.36336 127.11521 37.36336 \n", + "28 201 1 A 37.36822 127.10996 37.36854 \n", + "29 201 1 B 37.36822 127.10971 37.36854 \n", + "30 201 2 A 37.36864 127.10943 37.36864 \n", + "31 201 2 B 37.36844 127.10943 37.36844 \n", + "32 201 3 A 37.36864 127.11025 37.36864 \n", + "33 201 3 B 37.36844 127.10943 37.36844 \n", + "34 201 4 A 37.36864 127.11025 37.36864 \n", + "35 201 4 B 37.36844 127.11025 37.36844 \n", + "36 201 5 A 37.36887 127.10996 37.36854 \n", + "37 201 5 B 37.36886 127.10971 37.36854 \n", + "38 202 1 A 37.36865 127.11282 37.36865 \n", + "39 202 1 B 37.36845 127.11201 37.36845 \n", + "40 202 2 A 19.69448 117.99260 19.69448 \n", + "41 206 1 A 37.36451 127.10994 37.36483 \n", + "42 206 1 B 37.36516 127.10969 37.36484 \n", + "43 206 2 A 19.69448 117.99260 19.69448 \n", + "44 206 3 A 37.36451 127.10994 37.36483 \n", + "45 206 3 B 37.36516 127.10969 37.36484 \n", + "46 206 4 A 19.69448 117.99260 19.69448 \n", + "47 210 1 A 37.36357 127.11023 37.36357 \n", + "48 210 2 A 37.36356 127.10941 37.36357 \n", + "49 210 2 B 37.36337 127.10942 37.36337 \n", + "50 210 3 A 37.36380 127.10994 37.36347 \n", + "51 210 3 B 37.36380 127.10970 37.36347 \n", + "52 210 4 A 37.36315 127.10995 37.36347 \n", + "53 210 4 B 37.36315 127.10970 37.36347 \n", + "54 211 1 A 37.36356 127.11277 37.36356 \n", + "55 211 1 B 37.36336 127.11196 37.36336 \n", + "56 211 2 A 19.69448 117.99260 19.69448 \n", + "57 212 1 A 37.36357 127.11347 37.36357 \n", + "58 212 1 B 37.36336 127.11266 37.36337 \n", + "59 212 2 A 19.69448 117.99260 19.69448 \n", + "\n", + " flow_lon_2 flow_lat_3 flow_lon_3 \n", + "0 127.11490 37.36869 127.11491 \n", + "1 127.11465 37.36845 127.11466 \n", + "2 127.11490 37.36856 127.11505 \n", + "3 127.11465 37.36857 127.11451 \n", + "4 127.11478 37.36867 127.11463 \n", + "5 127.11478 37.36835 127.11478 \n", + "6 127.11478 37.36878 127.11478 \n", + "7 127.11478 37.36847 127.11493 \n", + "8 127.11493 37.36735 127.11493 \n", + "9 127.11468 37.36712 127.11468 \n", + "10 127.11493 37.36735 127.11493 \n", + "11 127.11468 37.36724 127.11453 \n", + "12 127.11481 37.36745 127.11480 \n", + "13 127.11492 37.36631 127.11492 \n", + "14 127.11467 37.36608 127.11468 \n", + "15 127.11492 37.36619 127.11507 \n", + "16 127.11467 37.36619 127.11453 \n", + "17 117.99260 19.69448 117.99260 \n", + "18 127.11480 37.36641 127.11480 \n", + "19 127.11480 37.36598 127.11480 \n", + "20 127.11493 37.36358 127.11493 \n", + "21 127.11468 37.36334 127.11468 \n", + "22 127.11493 37.36346 127.11507 \n", + "23 127.11468 37.36346 127.11453 \n", + "24 127.11480 37.36367 127.11480 \n", + "25 127.11480 37.36336 127.11495 \n", + "26 127.11480 37.36356 127.11465 \n", + "27 127.11480 37.36324 127.11480 \n", + "28 127.10996 37.36866 127.10996 \n", + "29 127.10971 37.36854 127.10957 \n", + "30 127.10984 37.36876 127.10984 \n", + "31 127.10984 37.36844 127.10999 \n", + "32 127.10984 37.36864 127.10969 \n", + "33 127.10984 37.36844 127.10999 \n", + "34 127.10984 37.36864 127.10969 \n", + "35 127.10984 37.36832 127.10984 \n", + "36 127.10996 37.36854 127.11011 \n", + "37 127.10971 37.36842 127.10971 \n", + "38 127.11241 37.36865 127.11227 \n", + "39 127.11241 37.36845 127.11256 \n", + "40 117.99260 19.69448 117.99260 \n", + "41 127.10994 37.36495 127.10994 \n", + "42 127.10969 37.36472 127.10969 \n", + "43 117.99260 19.69448 117.99260 \n", + "44 127.10994 37.36495 127.10994 \n", + "45 127.10969 37.36472 127.10969 \n", + "46 117.99260 19.69448 117.99260 \n", + "47 127.10982 37.36357 127.10968 \n", + "48 127.10982 37.36369 127.10982 \n", + "49 127.10982 37.36337 127.10997 \n", + "50 127.10995 37.36347 127.11009 \n", + "51 127.10970 37.36336 127.10970 \n", + "52 127.10995 37.36359 127.10995 \n", + "53 127.10970 37.36347 127.10955 \n", + "54 127.11237 37.36356 127.11222 \n", + "55 127.11237 37.36336 127.11252 \n", + "56 117.99260 19.69448 117.99260 \n", + "57 127.11306 37.36357 127.11291 \n", + "58 127.11306 37.36337 127.11321 \n", + "59 117.99260 19.69448 117.99260 " + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "tp = pd.read_csv('flow_3points.csv') # three points\n", + "tp" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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inter_nophase_noring_typeangle_code
01751A179004
11751B003176
21752A001095
31752B179270
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51753B090180
61754A268000
71754B270090
81761A180000
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161772B179270
171773ANaN
181774A268000
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251783B270090
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282011A180000
292011B180270
302012A270000
312012B270090
322013A090270
332013B270090
342014A090270
352014B090180
362015A000090
372015B000180
382021A090270
392021B270090
402022ANaN
412061A180000
422061B000180
432062ANaN
442063A180000
452063B000180
462064ANaN
472101A090270
482102A268000
492102B270090
502103A359090
512103B000180
522104A180000
532104B180270
542111A090270
552111B270090
562112ANaN
572121A090270
582121B268090
592122ANaN
\n", + "
" + ], + "text/plain": [ + " inter_no phase_no ring_type angle_code\n", + "0 175 1 A 179004\n", + "1 175 1 B 003176\n", + "2 175 2 A 001095\n", + "3 175 2 B 179270\n", + "4 175 3 A 090270\n", + "5 175 3 B 090180\n", + "6 175 4 A 268000\n", + "7 175 4 B 270090\n", + "8 176 1 A 180000\n", + "9 176 1 B 359180\n", + "10 176 2 A 180000\n", + "11 176 2 B 180270\n", + "12 176 3 A 270356\n", + "13 177 1 A 180000\n", + "14 177 1 B 001176\n", + "15 177 2 A 000090\n", + "16 177 2 B 179270\n", + "17 177 3 A NaN\n", + "18 177 4 A 268000\n", + "19 177 4 B 090180\n", + "20 178 1 A 180000\n", + "21 178 1 B 000180\n", + "22 178 2 A 000090\n", + "23 178 2 B 180270\n", + "24 178 3 A 270000\n", + "25 178 3 B 270090\n", + "26 178 4 A 090270\n", + "27 178 4 B 090180\n", + "28 201 1 A 180000\n", + "29 201 1 B 180270\n", + "30 201 2 A 270000\n", + "31 201 2 B 270090\n", + "32 201 3 A 090270\n", + "33 201 3 B 270090\n", + "34 201 4 A 090270\n", + "35 201 4 B 090180\n", + "36 201 5 A 000090\n", + "37 201 5 B 000180\n", + "38 202 1 A 090270\n", + "39 202 1 B 270090\n", + "40 202 2 A NaN\n", + "41 206 1 A 180000\n", + "42 206 1 B 000180\n", + "43 206 2 A NaN\n", + "44 206 3 A 180000\n", + "45 206 3 B 000180\n", + "46 206 4 A NaN\n", + "47 210 1 A 090270\n", + "48 210 2 A 268000\n", + "49 210 2 B 270090\n", + "50 210 3 A 359090\n", + "51 210 3 B 000180\n", + "52 210 4 A 180000\n", + "53 210 4 B 180270\n", + "54 211 1 A 090270\n", + "55 211 1 B 270090\n", + "56 211 2 A NaN\n", + "57 212 1 A 090270\n", + "58 212 1 B 268090\n", + "59 212 2 A NaN" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "tp['angle_code'] = tp.apply(lambda row: calculate_angle_code(row['flow_lat_1'], row['flow_lon_1'], row['flow_lat_2'], row['flow_lon_2'], row['flow_lat_3'], row['flow_lon_3']), axis=1)\n", + "tp[['inter_no', 'phase_no', 'ring_type', 'angle_code']]\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "sts", + "language": "python", + "name": "sts" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/Analysis/0307_red_yellow/0307_red_yellow.ipynb b/Analysis/0307_red_yellow/0307_red_yellow.ipynb new file mode 100644 index 000000000..4ae002d96 --- /dev/null +++ b/Analysis/0307_red_yellow/0307_red_yellow.ipynb @@ -0,0 +1,7186 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 86, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "os.listdir('../../scripts')\n", + "import sys\n", + "sys.path.append('../../Scripts')" + ] + }, + { + "cell_type": "code", + "execution_count": 87, + "metadata": {}, + "outputs": [], + "source": [ + "from generate_signals import SignalGenerator" + ] + }, + { + "cell_type": "code", + "execution_count": 88, + "metadata": {}, + "outputs": [], + "source": [ + "from preprocess_daily import DailyPreprocessor" + ] + }, + { + "cell_type": "code", + "execution_count": 89, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1. 데이터λ₯Ό μ€€λΉ„ν•©λ‹ˆλ‹€.\n", + "1-1. λ„€νŠΈμ›Œν¬κ°€ λ‘œλ“œλ˜μ—ˆμŠ΅λ‹ˆλ‹€.\n", + "1-2. ν…Œμ΄λΈ”λ“€μ΄ λ‘œλ“œλ˜μ—ˆμŠ΅λ‹ˆλ‹€.\n", + "2. μ‹ ν˜Έμ΄λ ₯ ν…Œμ΄λΈ”μ„ λ³€ν™˜ν•©λ‹ˆλ‹€.\n", + "3. 이동λ₯˜μ •λ³΄ ν…Œμ΄λΈ”μ„ λ³€ν™˜ν•©λ‹ˆλ‹€.\n", + "4. 톡합 ν…Œμ΄λΈ”μ„ μƒμ„±ν•©λ‹ˆλ‹€.\n" + ] + } + ], + "source": [ + "self = SignalGenerator()\n", + "self.prepare_data()\n", + "self.process_history()\n", + "self.process_movement()\n", + "self.make_histids()\n", + "self.set_timepoints()" + ] + }, + { + "cell_type": "code", + "execution_count": 90, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Unnamed: 0inter_noend_unixdura_A1dura_A2dura_A3dura_A4dura_A5dura_A6dura_A7...dura_B1dura_B2dura_B3dura_B4dura_B5dura_B6dura_B7dura_B8cycleoffset
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1515175170438072137395529000...37392559000016057
2424175170438088037395529000...37392559000016057
3333175170438104037395529000...37392559000016057
4141175170438119937395529000...37392559000016057
..................................................................
38863886175170446288046485541000...46483759000019018
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478 rows Γ— 21 columns

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" + ], + "text/plain": [ + " inter_no start_unix phas_A phas_B move_A move_B duration node_id \\\n", + "185 175 1704415950 1 1 8 4 43 i0 \n", + "186 175 1704415950 2 2 7 3 45 i0 \n", + "187 175 1704415950 3 3 6 1 33 i0 \n", + "188 175 1704415950 3 4 6 2 22 i0 \n", + "189 175 1704415950 4 4 5 2 37 i0 \n", + "190 175 1704416178 1 1 8 4 54 i0 \n", + "191 175 1704416178 2 2 7 3 57 i0 \n", + "192 175 1704416178 3 3 6 1 42 i0 \n", + "193 175 1704416178 3 4 6 2 28 i0 \n", + "194 175 1704416178 4 4 5 2 47 i0 \n", + "195 175 1704416358 1 1 8 4 43 i0 \n", + "196 175 1704416358 2 2 7 3 45 i0 \n", + "197 175 1704416358 3 3 6 1 33 i0 \n", + "198 175 1704416358 3 4 6 2 22 i0 \n", + "199 175 1704416358 4 4 5 2 37 i0 \n", + "\n", + " state \n", + "185 gGGrgrrrgGGGGrgrr \n", + "186 grrGgrrrgrrrrGgrr \n", + "187 grrrgGGGgrrrrrgrr \n", + "188 grrrgGGrgrrrrrgGr \n", + "189 grrrgrrrgrrrrrgGG \n", + "190 gGGrgrrrgGGGGrgrr \n", + "191 grrGgrrrgrrrrGgrr \n", + "192 grrrgGGGgrrrrrgrr \n", + "193 grrrgGGrgrrrrrgGr \n", + "194 grrrgrrrgrrrrrgGG \n", + "195 gGGrgrrrgGGGGrgrr \n", + "196 grrGgrrrgrrrrGgrr \n", + "197 grrrgGGGgrrrrrgrr \n", + "198 grrrgGGrgrrrrrgGr \n", + "199 grrrgrrrgrrrrrgGG " + ] + }, + "execution_count": 94, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "self.histid.query('node_id==@Node_id')[:15] # 4-2 state λΆ™μž„" + ] + }, + { + "cell_type": "code", + "execution_count": 95, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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inter_nonode_idstart_unixphas_Aphas_Bmove_Amove_Bdurationstate
44175i01704415950118443gGGrgrrrgGGGGrgrr
45175i01704415950227345grrGgrrrgrrrrGgrr
46175i01704415950336133grrrgGGGgrrrrrgrr
47175i01704415950346222grrrgGGrgrrrrrgGr
48175i01704415950445237grrrgrrrgrrrrrgGG
118175i01704416178118454gGGrgrrrgGGGGrgrr
119175i01704416178227357grrGgrrrgrrrrGgrr
120175i01704416178336142grrrgGGGgrrrrrgrr
121175i01704416178346228grrrgGGrgrrrrrgGr
122175i01704416178445247grrrgrrrgrrrrrgGG
200175i01704416358118443gGGrgrrrgGGGGrgrr
201175i01704416358227345grrGgrrrgrrrrGgrr
202175i01704416358336133grrrgGGGgrrrrrgrr
203175i01704416358346222grrrgGGrgrrrrrgGr
204175i01704416358445237grrrgrrrgrrrrrgGG
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" + ], + "text/plain": [ + " inter_no node_id start_unix phas_A phas_B move_A move_B duration \\\n", + "44 175 i0 1704415950 1 1 8 4 43 \n", + "45 175 i0 1704415950 2 2 7 3 45 \n", + "46 175 i0 1704415950 3 3 6 1 33 \n", + "47 175 i0 1704415950 3 4 6 2 22 \n", + "48 175 i0 1704415950 4 4 5 2 37 \n", + "118 175 i0 1704416178 1 1 8 4 54 \n", + "119 175 i0 1704416178 2 2 7 3 57 \n", + "120 175 i0 1704416178 3 3 6 1 42 \n", + "121 175 i0 1704416178 3 4 6 2 28 \n", + "122 175 i0 1704416178 4 4 5 2 47 \n", + "200 175 i0 1704416358 1 1 8 4 43 \n", + "201 175 i0 1704416358 2 2 7 3 45 \n", + "202 175 i0 1704416358 3 3 6 1 33 \n", + "203 175 i0 1704416358 3 4 6 2 22 \n", + "204 175 i0 1704416358 4 4 5 2 37 \n", + "\n", + " state \n", + "44 gGGrgrrrgGGGGrgrr \n", + "45 grrGgrrrgrrrrGgrr \n", + "46 grrrgGGGgrrrrrgrr \n", + "47 grrrgGGrgrrrrrgGr \n", + "48 grrrgrrrgrrrrrgGG \n", + "118 gGGrgrrrgGGGGrgrr \n", + "119 grrGgrrrgrrrrGgrr \n", + "120 grrrgGGGgrrrrrgrr \n", + "121 grrrgGGrgrrrrrgGr \n", + "122 grrrgrrrgrrrrrgGG \n", + "200 gGGrgrrrgGGGGrgrr \n", + "201 grrGgrrrgrrrrGgrr \n", + "202 grrrgGGGgrrrrrgrr \n", + "203 grrrgGGrgrrrrrgGr \n", + "204 grrrgrrrgrrrrrgGG " + ] + }, + "execution_count": 95, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "self.histids.query('node_id==@Node_id')[:15] # 4-3 λΆ€κ΅μ°¨λ‘œ 정보 μΆ”κ°€" + ] + }, + { + "cell_type": "code", + "execution_count": 96, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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inter_nonode_idstart_unixphas_Aphas_Bmove_Amove_Bdurationstatephase_sumo
16175i01704415950118443gGGrgrrrgGGGGrgrr0
17175i01704415950227345grrGgrrrgrrrrGgrr1
18175i01704415950336133grrrgGGGgrrrrrgrr2
19175i01704415950346222grrrgGGrgrrrrrgGr3
20175i01704415950445237grrrgrrrgrrrrrgGG4
21175i01704416178118454gGGrgrrrgGGGGrgrr0
22175i01704416178227357grrGgrrrgrrrrGgrr1
23175i01704416178336142grrrgGGGgrrrrrgrr2
24175i01704416178346228grrrgGGrgrrrrrgGr3
25175i01704416178445247grrrgrrrgrrrrrgGG4
26175i01704416358118443gGGrgrrrgGGGGrgrr0
27175i01704416358227345grrGgrrrgrrrrGgrr1
28175i01704416358336133grrrgGGGgrrrrrgrr2
29175i01704416358346222grrrgGGrgrrrrrgGr3
30175i01704416358445237grrrgrrrgrrrrrgGG4
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" + ], + "text/plain": [ + " inter_no node_id start_unix phas_A phas_B move_A move_B duration \\\n", + "16 175 i0 1704415950 1 1 8 4 43 \n", + "17 175 i0 1704415950 2 2 7 3 45 \n", + "18 175 i0 1704415950 3 3 6 1 33 \n", + "19 175 i0 1704415950 3 4 6 2 22 \n", + "20 175 i0 1704415950 4 4 5 2 37 \n", + "21 175 i0 1704416178 1 1 8 4 54 \n", + "22 175 i0 1704416178 2 2 7 3 57 \n", + "23 175 i0 1704416178 3 3 6 1 42 \n", + "24 175 i0 1704416178 3 4 6 2 28 \n", + "25 175 i0 1704416178 4 4 5 2 47 \n", + "26 175 i0 1704416358 1 1 8 4 43 \n", + "27 175 i0 1704416358 2 2 7 3 45 \n", + "28 175 i0 1704416358 3 3 6 1 33 \n", + "29 175 i0 1704416358 3 4 6 2 22 \n", + "30 175 i0 1704416358 4 4 5 2 37 \n", + "\n", + " state phase_sumo \n", + "16 gGGrgrrrgGGGGrgrr 0 \n", + "17 grrGgrrrgrrrrGgrr 1 \n", + "18 grrrgGGGgrrrrrgrr 2 \n", + "19 grrrgGGrgrrrrrgGr 3 \n", + "20 grrrgrrrgrrrrrgGG 4 \n", + "21 gGGrgrrrgGGGGrgrr 0 \n", + "22 grrGgrrrgrrrrGgrr 1 \n", + "23 grrrgGGGgrrrrrgrr 2 \n", + "24 grrrgGGrgrrrrrgGr 3 \n", + "25 grrrgrrrgrrrrrgGG 4 \n", + "26 gGGrgrrrgGGGGrgrr 0 \n", + "27 grrGgrrrgrrrrGgrr 1 \n", + "28 grrrgGGGgrrrrrgrr 2 \n", + "29 grrrgGGrgrrrrrgGr 3 \n", + "30 grrrgrrrgrrrrrgGG 4 " + ] + }, + "execution_count": 96, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "######\n", + "self.sigtable.query('node_id==@Node_id')[:15] # 5-1 μ‹œμž‘, μ’…λ£Œμ‹œμ  μ„€μ •" + ] + }, + { + "cell_type": "code", + "execution_count": 97, + "metadata": {}, + "outputs": [], + "source": [ + "# self.SIGTABLE.query('node_id==@Node_id')[:15] # 5-2 적색 ν™©μƒ‰μ‹ ν˜Έ λΆ€μ—¬" + ] + }, + { + "cell_type": "code", + "execution_count": 98, + "metadata": {}, + "outputs": [], + "source": [ + "# dp = DailyPreprocessor()\n", + "# dp.load_data()\n", + "# dp.get_intermediates()" + ] + }, + { + "cell_type": "code", + "execution_count": 99, + "metadata": {}, + "outputs": [], + "source": [ + "# 4-2. histid\n", + "self.histid = self.movedur.copy()\n", + "self.histid['node_id'] = self.histid['inter_no'].map(self.inter2node)\n", + "histid_start = self.present_time - 600\n", + "self.histid = self.histid[self.histid.start_unix > histid_start]\n", + "\n", + "mapping_dict = self.matching.set_index(['node_id', 'move_no'])['state'].to_dict()\n", + "\n", + "for i, row in self.histid.iterrows():\n", + " node_id = row.node_id\n", + " move_A = row.move_A\n", + " move_B = row.move_B\n", + " \n", + " # A링의 state 지정\n", + " if (node_id, move_A) in mapping_dict:\n", + " state_A = mapping_dict[(node_id, move_A)]\n", + " else:\n", + " state_A = ''.join(self.node2init[node_id])\n", + " self.histid.at[i, 'state_A'] = state_A\n", + "\n", + " # B링의 state 지정\n", + " if (node_id, move_B) in mapping_dict:\n", + " state_B = mapping_dict[(node_id, move_B)]\n", + " else:\n", + " state_B = ''.join(self.node2init[node_id])\n", + " self.histid.at[i, 'state_B'] = state_B " + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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inter_nonode_idstart_unixphas_Aphas_Bmove_Amove_Bdurationstate_Astate_B
44175i01704415950118443grrrgrrrgGGGGrgrrgGGrgrrrgrrrrrgrr
45175i01704415950227345grrGgrrrgrrrrrgrrgrrrgrrrgrrrrGgrr
46175i01704415950336133grrrgGGrgrrrrrgrrgrrrgrrGgrrrrrgrr
47175i01704415950346222grrrgGGrgrrrrrgrrgrrrgrrrgrrrrrgGr
48175i01704415950445237grrrgrrrgrrrrrgrGgrrrgrrrgrrrrrgGr
118175i01704416178118454grrrgrrrgGGGGrgrrgGGrgrrrgrrrrrgrr
119175i01704416178227357grrGgrrrgrrrrrgrrgrrrgrrrgrrrrGgrr
120175i01704416178336142grrrgGGrgrrrrrgrrgrrrgrrGgrrrrrgrr
121175i01704416178346228grrrgGGrgrrrrrgrrgrrrgrrrgrrrrrgGr
122175i01704416178445247grrrgrrrgrrrrrgrGgrrrgrrrgrrrrrgGr
200175i01704416358118443grrrgrrrgGGGGrgrrgGGrgrrrgrrrrrgrr
201175i01704416358227345grrGgrrrgrrrrrgrrgrrrgrrrgrrrrGgrr
202175i01704416358336133grrrgGGrgrrrrrgrrgrrrgrrGgrrrrrgrr
203175i01704416358346222grrrgGGrgrrrrrgrrgrrrgrrrgrrrrrgGr
204175i01704416358445237grrrgrrrgrrrrrgrGgrrrgrrrgrrrrrgGr
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" + ], + "text/plain": [ + " inter_no node_id start_unix phas_A phas_B move_A move_B duration \\\n", + "44 175 i0 1704415950 1 1 8 4 43 \n", + "45 175 i0 1704415950 2 2 7 3 45 \n", + "46 175 i0 1704415950 3 3 6 1 33 \n", + "47 175 i0 1704415950 3 4 6 2 22 \n", + "48 175 i0 1704415950 4 4 5 2 37 \n", + "118 175 i0 1704416178 1 1 8 4 54 \n", + "119 175 i0 1704416178 2 2 7 3 57 \n", + "120 175 i0 1704416178 3 3 6 1 42 \n", + "121 175 i0 1704416178 3 4 6 2 28 \n", + "122 175 i0 1704416178 4 4 5 2 47 \n", + "200 175 i0 1704416358 1 1 8 4 43 \n", + "201 175 i0 1704416358 2 2 7 3 45 \n", + "202 175 i0 1704416358 3 3 6 1 33 \n", + "203 175 i0 1704416358 3 4 6 2 22 \n", + "204 175 i0 1704416358 4 4 5 2 37 \n", + "262 175 i0 1704416538 1 1 8 4 43 \n", + "263 175 i0 1704416538 2 2 7 3 45 \n", + "264 175 i0 1704416538 3 3 6 1 33 \n", + "265 175 i0 1704416538 3 4 6 2 22 \n", + "266 175 i0 1704416538 4 4 5 2 37 \n", + "324 175 i0 1704416718 1 1 8 4 43 \n", + "325 175 i0 1704416718 2 2 7 3 45 \n", + "326 175 i0 1704416718 3 3 6 1 33 \n", + "327 175 i0 1704416718 3 4 6 2 22 \n", + "328 175 i0 1704416718 4 4 5 2 37 \n", + "362 175 i0 1704416820 1 1 8 4 24 \n", + "363 175 i0 1704416820 2 2 7 3 26 \n", + "364 175 i0 1704416820 3 3 6 1 19 \n", + "365 175 i0 1704416820 3 4 6 2 12 \n", + "366 175 i0 1704416820 4 4 5 2 21 \n", + "\n", + " state_A state_B \n", + "44 grrrgrrrgGGGGrgrr gGGrgrrrgrrrrrgrr \n", + "45 grrGgrrrgrrrrrgrr grrrgrrrgrrrrGgrr \n", + "46 grrrgGGrgrrrrrgrr grrrgrrGgrrrrrgrr \n", + "47 grrrgGGrgrrrrrgrr grrrgrrrgrrrrrgGr \n", + "48 grrrgrrrgrrrrrgrG grrrgrrrgrrrrrgGr \n", + "118 grrrgrrrgGGGGrgrr gGGrgrrrgrrrrrgrr \n", + "119 grrGgrrrgrrrrrgrr grrrgrrrgrrrrGgrr \n", + "120 grrrgGGrgrrrrrgrr grrrgrrGgrrrrrgrr \n", + "121 grrrgGGrgrrrrrgrr grrrgrrrgrrrrrgGr \n", + "122 grrrgrrrgrrrrrgrG grrrgrrrgrrrrrgGr \n", + "200 grrrgrrrgGGGGrgrr gGGrgrrrgrrrrrgrr \n", + "201 grrGgrrrgrrrrrgrr grrrgrrrgrrrrGgrr \n", + "202 grrrgGGrgrrrrrgrr grrrgrrGgrrrrrgrr \n", + "203 grrrgGGrgrrrrrgrr grrrgrrrgrrrrrgGr \n", + "204 grrrgrrrgrrrrrgrG grrrgrrrgrrrrrgGr \n", + "262 grrrgrrrgGGGGrgrr gGGrgrrrgrrrrrgrr \n", + "263 grrGgrrrgrrrrrgrr grrrgrrrgrrrrGgrr \n", + "264 grrrgGGrgrrrrrgrr grrrgrrGgrrrrrgrr \n", + "265 grrrgGGrgrrrrrgrr grrrgrrrgrrrrrgGr \n", + "266 grrrgrrrgrrrrrgrG grrrgrrrgrrrrrgGr \n", + "324 grrrgrrrgGGGGrgrr gGGrgrrrgrrrrrgrr \n", + "325 grrGgrrrgrrrrrgrr grrrgrrrgrrrrGgrr \n", + "326 grrrgGGrgrrrrrgrr grrrgrrGgrrrrrgrr \n", + "327 grrrgGGrgrrrrrgrr grrrgrrrgrrrrrgGr \n", + "328 grrrgrrrgrrrrrgrG grrrgrrrgrrrrrgGr \n", + "362 grrrgrrrgGGGGrgrr gGGrgrrrgrrrrrgrr \n", + "363 grrGgrrrgrrrrrgrr grrrgrrrgrrrrGgrr \n", + "364 grrrgGGrgrrrrrgrr grrrgrrGgrrrrrgrr \n", + "365 grrrgGGrgrrrrrgrr grrrgrrrgrrrrrgGr \n", + "366 grrrgrrrgrrrrrgrG grrrgrrrgrrrrrgGr " + ] + }, + "execution_count": 100, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# 4-3. histids\n", + "new_histids = []\n", + "for parent_id in self.parent_ids:\n", + " for child_id in self.pa2ch[parent_id]:\n", + " new_histid = self.histid.copy()[self.histid.node_id==parent_id].drop(columns=['state_A', 'state_B'])\n", + " # new_histid[['inc_edge_A', 'out_edge_A', 'inc_edge_B', 'out_edge_B']] = np.nan\n", + " for i, row in new_histid.iterrows():\n", + " phas_A = row.phas_A\n", + " phas_B = row.phas_B\n", + " new_match = self.match6[self.match6.node_id==child_id]\n", + " Arow = new_match[(new_match.phase_no==phas_A) & (new_match.ring_type=='A')]\n", + "\n", + " # A링의 state 지정\n", + " state_A = Arow.iloc[0].state\n", + " new_histid.at[i, 'state_A'] = state_A\n", + "\n", + " # B링의 state 지정\n", + " Brow = new_match[(new_match.phase_no==phas_B) & (new_match.ring_type=='B')]\n", + " state_B = Brow.iloc[0].state\n", + " new_histid.at[i, 'state_B'] = state_B\n", + "\n", + " new_histid.at[i, 'node_id'] = child_id\n", + " new_histids.append(new_histid)\n", + "import pandas as pd\n", + "new_histids = pd.concat(new_histids)\n", + "self.histids = pd.concat([self.histid.copy(), new_histids])\n", + "self.histids = self.histids.sort_values(by=['start_unix', 'node_id', 'phas_A', 'phas_B']).reset_index(drop=True)\n", + "self.histids = self.histids[['inter_no', 'node_id', 'start_unix', 'phas_A', 'phas_B', 'move_A', 'move_B', 'duration', 'state_A', 'state_B']]\n", + "self.histids.query('node_id==@Node_id')" + ] + }, + { + "cell_type": "code", + "execution_count": 101, + "metadata": {}, + "outputs": [], + "source": [ + "self.set_timepoints()" + ] + }, + { + "cell_type": "code", + "execution_count": 102, + "metadata": {}, + "outputs": [], + "source": [ + "df = self.sigtable.query('node_id==@Node_id')" + ] + }, + { + "cell_type": "code", + "execution_count": 103, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " inter_no node_id start_unix phas_A phas_B move_A move_B duration \\\n", + "16 175 i0 1704415950 1 1 8 4 43 \n", + "17 175 i0 1704415950 2 2 7 3 45 \n", + "18 175 i0 1704415950 3 3 6 1 33 \n", + "19 175 i0 1704415950 3 4 6 2 22 \n", + "20 175 i0 1704415950 4 4 5 2 37 \n", + "21 175 i0 1704416178 1 1 8 4 54 \n", + "22 175 i0 1704416178 2 2 7 3 57 \n", + "23 175 i0 1704416178 3 3 6 1 42 \n", + "24 175 i0 1704416178 3 4 6 2 28 \n", + "25 175 i0 1704416178 4 4 5 2 47 \n", + "26 175 i0 1704416358 1 1 8 4 43 \n", + "27 175 i0 1704416358 2 2 7 3 45 \n", + "28 175 i0 1704416358 3 3 6 1 33 \n", + "29 175 i0 1704416358 3 4 6 2 22 \n", + "30 175 i0 1704416358 4 4 5 2 37 \n", + "\n", + " state_A state_B phase_sumo \n", + "16 grrrgrrrgGGGGrgrr gGGrgrrrgrrrrrgrr 0 \n", + "17 grrGgrrrgrrrrrgrr grrrgrrrgrrrrGgrr 1 \n", + "18 grrrgGGrgrrrrrgrr grrrgrrGgrrrrrgrr 2 \n", + "19 grrrgGGrgrrrrrgrr grrrgrrrgrrrrrgGr 3 \n", + "20 grrrgrrrgrrrrrgrG grrrgrrrgrrrrrgGr 4 \n", + "21 grrrgrrrgGGGGrgrr gGGrgrrrgrrrrrgrr 0 \n", + "22 grrGgrrrgrrrrrgrr grrrgrrrgrrrrGgrr 1 \n", + "23 grrrgGGrgrrrrrgrr grrrgrrGgrrrrrgrr 2 \n", + "24 grrrgGGrgrrrrrgrr grrrgrrrgrrrrrgGr 3 \n", + "25 grrrgrrrgrrrrrgrG grrrgrrrgrrrrrgGr 4 \n", + "26 grrrgrrrgGGGGrgrr gGGrgrrrgrrrrrgrr 0 \n", + "27 grrGgrrrgrrrrrgrr grrrgrrrgrrrrGgrr 1 \n", + "28 grrrgGGrgrrrrrgrr grrrgrrGgrrrrrgrr 2 \n", + "29 grrrgGGrgrrrrrgrr grrrgrrrgrrrrrgGr 3 \n", + "30 grrrgrrrgrrrrrgrG grrrgrrrgrrrrrgGr 4 " + ] + }, + "execution_count": 104, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = self.sigtable.query('node_id==@Node_id')\n", + "df" + ] + }, + { + "cell_type": "code", + "execution_count": 105, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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inter_nonode_idstart_unixphas_Aphas_Bdurationstate_Astate_Bphase_sumored_Ared_Byellow_Ayellow_B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\n", + "
" + ], + "text/plain": [ + " inter_no node_id start_unix phas_A phas_B duration state_A \\\n", + "16 175 i0 1704415950 1 1 43 grrrgrrrgGGGGrgrr \n", + "17 175 i0 1704415950 2 2 45 grrGgrrrgrrrrrgrr \n", + "18 175 i0 1704415950 3 3 33 grrrgGGrgrrrrrgrr \n", + "19 175 i0 1704415950 3 4 22 grrrgGGrgrrrrrgrr \n", + "20 175 i0 1704415950 4 4 37 grrrgrrrgrrrrrgrG \n", + "21 175 i0 1704416178 1 1 54 grrrgrrrgGGGGrgrr \n", + "22 175 i0 1704416178 2 2 57 grrGgrrrgrrrrrgrr \n", + "23 175 i0 1704416178 3 3 42 grrrgGGrgrrrrrgrr \n", + "24 175 i0 1704416178 3 4 28 grrrgGGrgrrrrrgrr \n", + "25 175 i0 1704416178 4 4 47 grrrgrrrgrrrrrgrG \n", + "26 175 i0 1704416358 1 1 43 grrrgrrrgGGGGrgrr \n", + "27 175 i0 1704416358 2 2 45 grrGgrrrgrrrrrgrr \n", + "28 175 i0 1704416358 3 3 33 grrrgGGrgrrrrrgrr \n", + "29 175 i0 1704416358 3 4 22 grrrgGGrgrrrrrgrr \n", + "30 175 i0 1704416358 4 4 37 grrrgrrrgrrrrrgrG \n", + "\n", + " state_B phase_sumo red_A red_B yellow_A yellow_B \n", + "16 gGGrgrrrgrrrrrgrr 0 1 1 4 4 \n", + "17 grrrgrrrgrrrrGgrr 1 1 1 4 4 \n", + "18 grrrgrrGgrrrrrgrr 2 1 1 4 4 \n", + "19 grrrgrrrgrrrrrgGr 3 1 1 4 4 \n", + "20 grrrgrrrgrrrrrgGr 4 1 1 4 4 \n", + "21 gGGrgrrrgrrrrrgrr 0 1 1 4 4 \n", + "22 grrrgrrrgrrrrGgrr 1 1 1 4 4 \n", + "23 grrrgrrGgrrrrrgrr 2 1 1 4 4 \n", + "24 grrrgrrrgrrrrrgGr 3 1 1 4 4 \n", + "25 grrrgrrrgrrrrrgGr 4 1 1 4 4 \n", + "26 gGGrgrrrgrrrrrgrr 0 1 1 4 4 \n", + "27 grrrgrrrgrrrrGgrr 1 1 1 4 4 \n", + "28 grrrgrrGgrrrrrgrr 2 1 1 4 4 \n", + "29 grrrgrrrgrrrrrgGr 3 1 1 4 4 \n", + "30 grrrgrrrgrrrrrgGr 4 1 1 4 4 " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for i, row in df.iterrows():\n", + " inter_no = row.inter_no\n", + " phas_A = row.phas_A\n", + " phas_B = row.phas_B\n", + " start_unix = row.start_unix\n", + " prow = self.load_prow(inter_no, start_unix)[1].iloc[0]\n", + " red_A = prow[f'red_A{phas_A}']\n", + " yellow_A = prow[f'yellow_A{phas_A}']\n", + " red_B = prow[f'red_B{phas_B}']\n", + " yellow_B = prow[f'yellow_B{phas_B}']\n", + " df.loc[i, ['red_A', 'red_B', 'yellow_A', 'yellow_B']] = red_A, red_B, yellow_A, yellow_B\n", + "df = df.astype({'red_A': int, 'red_B': int, 'yellow_A': int, 'yellow_B': int,\n", + " 'phas_A':str, 'phas_B':str})\n", + "df = df.drop(['move_A','move_B'], axis=1)\n", + "display(df)" + ] + }, + { + "cell_type": "code", + "execution_count": 110, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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phas_Adurationstate_Ared_Ayellow_A
0143grrrgrrrgGGGGrgrr14
1245grrGgrrrgrrrrrgrr14
2333grrrgGGrgrrrrrgrr14
3322grrrgGGrgrrrrrgrr14
4437grrrgrrrgrrrrrgrG14
5154grrrgrrrgGGGGrgrr14
6257grrGgrrrgrrrrrgrr14
7342grrrgGGrgrrrrrgrr14
8328grrrgGGrgrrrrrgrr14
9447grrrgrrrgrrrrrgrG14
10143grrrgrrrgGGGGrgrr14
11245grrGgrrrgrrrrrgrr14
12333grrrgGGrgrrrrrgrr14
13322grrrgGGrgrrrrrgrr14
14437grrrgrrrgrrrrrgrG14
\n", + "
" + ], + "text/plain": [ + " phas_A duration state_A red_A yellow_A\n", + "0 1 43 grrrgrrrgGGGGrgrr 1 4\n", + "1 2 45 grrGgrrrgrrrrrgrr 1 4\n", + "2 3 33 grrrgGGrgrrrrrgrr 1 4\n", + "3 3 22 grrrgGGrgrrrrrgrr 1 4\n", + "4 4 37 grrrgrrrgrrrrrgrG 1 4\n", + "5 1 54 grrrgrrrgGGGGrgrr 1 4\n", + "6 2 57 grrGgrrrgrrrrrgrr 1 4\n", + "7 3 42 grrrgGGrgrrrrrgrr 1 4\n", + "8 3 28 grrrgGGrgrrrrrgrr 1 4\n", + "9 4 47 grrrgrrrgrrrrrgrG 1 4\n", + "10 1 43 grrrgrrrgGGGGrgrr 1 4\n", + "11 2 45 grrGgrrrgrrrrrgrr 1 4\n", + "12 3 33 grrrgGGrgrrrrrgrr 1 4\n", + "13 3 22 grrrgGGrgrrrrrgrr 1 4\n", + "14 4 37 grrrgrrrgrrrrrgrG 1 4" + ] + }, + "execution_count": 110, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_A = df[['phas_A', 'duration', 'state_A', 'red_A', 'yellow_A']]\n", + "df_B = df[['phas_B', 'duration', 'state_B', 'red_B', 'yellow_B']]\n", + "df_A = df_A.reset_index(drop=True)\n", + "df_A" + ] + }, + { + "cell_type": "code", + "execution_count": 119, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'aa'" + ] + }, + "execution_count": 119, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "state_y = ''\n", + "state_y += 'a'\n", + "state_y += 'a'\n", + "state_y" + ] + }, + { + "cell_type": "code", + "execution_count": 134, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "grrrgrrrgGGGGrgrr\n", + "grrrgrrrgrrrrrgrr\n", + "grrrgrrrgyyyyrgrr\n", + "grrGgrrrgrrrrrgrr\n", + "grrrgrrrgrrrrrgrr\n", + "grrygrrrgrrrrrgrr\n", + "grrrgGGrgrrrrrgrr\n" + ] + } + ], + "source": [ + "pre_state = 'grrrgrrrgGGGGrgrr'\n", + "cur_state = 'grrGgrrrgrrrrrgrr'\n", + "nex_state = 'grrrgGGrgrrrrrgrr'\n", + "\n", + "def get_red(pre_state:str, cur_state:str):\n", + " assert len(pre_state) == len(cur_state), \"cur_state, nex_state의 길이가 μ„œλ‘œ λ‹€λ¦…λ‹ˆλ‹€.\"\n", + " state_r = ''\n", + " for c, n in zip(pre_state, cur_state):\n", + " if c == n:\n", + " state_r += c\n", + " elif (c == 'r') and (n == 'G'):\n", + " state_r += 'r'\n", + " elif (c == 'G') and (n == 'r'):\n", + " state_r += 'r'\n", + " else:\n", + " raise ValueError(f\"μ˜ˆμƒμΉ˜ λͺ»ν•œ μ‹ ν˜Έμ‘°ν•©: current={c}, next={n}\")\n", + " return state_r\n", + "\n", + "def get_yellow(cur_state:str, nex_state:str):\n", + " assert len(cur_state) == len(nex_state), \"cur_state, nex_state의 길이가 μ„œλ‘œ λ‹€λ¦…λ‹ˆλ‹€.\"\n", + " state_y = ''\n", + " for c, n in zip(cur_state, nex_state):\n", + " if c == n:\n", + " state_y += c\n", + " elif (c == 'r') and (n == 'G'):\n", + " state_y += 'r'\n", + " elif (c == 'G') and (n == 'r'):\n", + " state_y += 'y'\n", + " else:\n", + " raise ValueError(f\"μ˜ˆμƒμΉ˜ λͺ»ν•œ μ‹ ν˜Έμ‘°ν•©: current={c}, next={n}\")\n", + " return state_y\n", + "print(pre_state)\n", + "print(get_red(pre_state, cur_state))\n", + "print(get_yellow(pre_state, cur_state))\n", + "print(cur_state)\n", + "print(get_red(cur_state, nex_state))\n", + "print(get_yellow(cur_state, nex_state))\n", + "print(nex_state)" + ] + }, + { + "cell_type": "code", + "execution_count": 161, + "metadata": {}, + "outputs": [], + "source": [ + "df_A = df_A.reset_index(drop=True)\n", + "df_B = df_B.reset_index(drop=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 171, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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phas_Adurationstate_Ared_Ayellow_A
0143grrrgrrrgGGGGrgrr14
1245grrGgrrrgrrrrrgrr14
2333grrrgGGrgrrrrrgrr14
3322grrrgGGrgrrrrrgrr14
4437grrrgrrrgrrrrrgrG14
5154grrrgrrrgGGGGrgrr14
6257grrGgrrrgrrrrrgrr14
7342grrrgGGrgrrrrrgrr14
8328grrrgGGrgrrrrrgrr14
9447grrrgrrrgrrrrrgrG14
10143grrrgrrrgGGGGrgrr14
11245grrGgrrrgrrrrrgrr14
12333grrrgGGrgrrrrrgrr14
13322grrrgGGrgrrrrrgrr14
14437grrrgrrrgrrrrrgrG14
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" + ], + "text/plain": [ + " phas_A duration state_A red_A yellow_A\n", + "0 1 43 grrrgrrrgGGGGrgrr 1 4\n", + "1 2 45 grrGgrrrgrrrrrgrr 1 4\n", + "2 3 33 grrrgGGrgrrrrrgrr 1 4\n", + "3 3 22 grrrgGGrgrrrrrgrr 1 4\n", + "4 4 37 grrrgrrrgrrrrrgrG 1 4\n", + "5 1 54 grrrgrrrgGGGGrgrr 1 4\n", + "6 2 57 grrGgrrrgrrrrrgrr 1 4\n", + "7 3 42 grrrgGGrgrrrrrgrr 1 4\n", + "8 3 28 grrrgGGrgrrrrrgrr 1 4\n", + "9 4 47 grrrgrrrgrrrrrgrG 1 4\n", + "10 1 43 grrrgrrrgGGGGrgrr 1 4\n", + "11 2 45 grrGgrrrgrrrrrgrr 1 4\n", + "12 3 33 grrrgGGrgrrrrrgrr 1 4\n", + "13 3 22 grrrgGGrgrrrrrgrr 1 4\n", + "14 4 37 grrrgrrrgrrrrrgrG 1 4" + ] + }, + "execution_count": 171, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_A" + ] + }, + { + "cell_type": "code", + "execution_count": 163, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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durationdurationdurationdurationphas_Aphas_Bred_Ared_Bstate_Astate_Byellow_Ayellow_B
0434343431111grrrgrrrgGGGGrgrrgGGrgrrrgrrrrrgrr44
1454545452211grrGgrrrgrrrrrgrrgrrrgrrrgrrrrGgrr44
2333333333311grrrgGGrgrrrrrgrrgrrrgrrGgrrrrrgrr44
3222222223411grrrgGGrgrrrrrgrrgrrrgrrrgrrrrrgGr44
4373737374411grrrgrrrgrrrrrgrGgrrrgrrrgrrrrrgGr44
5545454541111grrrgrrrgGGGGrgrrgGGrgrrrgrrrrrgrr44
6575757572211grrGgrrrgrrrrrgrrgrrrgrrrgrrrrGgrr44
7424242423311grrrgGGrgrrrrrgrrgrrrgrrGgrrrrrgrr44
8282828283411grrrgGGrgrrrrrgrrgrrrgrrrgrrrrrgGr44
9474747474411grrrgrrrgrrrrrgrGgrrrgrrrgrrrrrgGr44
10434343431111grrrgrrrgGGGGrgrrgGGrgrrrgrrrrrgrr44
11454545452211grrGgrrrgrrrrrgrrgrrrgrrrgrrrrGgrr44
12333333333311grrrgGGrgrrrrrgrrgrrrgrrGgrrrrrgrr44
13222222223411grrrgGGrgrrrrrgrrgrrrgrrrgrrrrrgGr44
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\n", + "
" + ], + "text/plain": [ + " duration duration duration duration phas_A phas_B red_A red_B \\\n", + "0 43 43 43 43 1 1 1 1 \n", + "1 45 45 45 45 2 2 1 1 \n", + "2 33 33 33 33 3 3 1 1 \n", + "3 22 22 22 22 3 4 1 1 \n", + "4 37 37 37 37 4 4 1 1 \n", + "5 54 54 54 54 1 1 1 1 \n", + "6 57 57 57 57 2 2 1 1 \n", + "7 42 42 42 42 3 3 1 1 \n", + "8 28 28 28 28 3 4 1 1 \n", + "9 47 47 47 47 4 4 1 1 \n", + "10 43 43 43 43 1 1 1 1 \n", + "11 45 45 45 45 2 2 1 1 \n", + "12 33 33 33 33 3 3 1 1 \n", + "13 22 22 22 22 3 4 1 1 \n", + "14 37 37 37 37 4 4 1 1 \n", + "\n", + " state_A state_B yellow_A yellow_B \n", + "0 grrrgrrrgGGGGrgrr gGGrgrrrgrrrrrgrr 4 4 \n", + "1 grrGgrrrgrrrrrgrr grrrgrrrgrrrrGgrr 4 4 \n", + "2 grrrgGGrgrrrrrgrr grrrgrrGgrrrrrgrr 4 4 \n", + "3 grrrgGGrgrrrrrgrr grrrgrrrgrrrrrgGr 4 4 \n", + "4 grrrgrrrgrrrrrgrG grrrgrrrgrrrrrgGr 4 4 \n", + "5 grrrgrrrgGGGGrgrr gGGrgrrrgrrrrrgrr 4 4 \n", + "6 grrGgrrrgrrrrrgrr grrrgrrrgrrrrGgrr 4 4 \n", + "7 grrrgGGrgrrrrrgrr grrrgrrGgrrrrrgrr 4 4 \n", + "8 grrrgGGrgrrrrrgrr grrrgrrrgrrrrrgGr 4 4 \n", + "9 grrrgrrrgrrrrrgrG grrrgrrrgrrrrrgGr 4 4 \n", + "10 grrrgrrrgGGGGrgrr gGGrgrrrgrrrrrgrr 4 4 \n", + "11 grrGgrrrgrrrrrgrr grrrgrrrgrrrrGgrr 4 4 \n", + "12 grrrgGGrgrrrrrgrr grrrgrrGgrrrrrgrr 4 4 \n", + "13 grrrgGGrgrrrrrgrr grrrgrrrgrrrrrgGr 4 4 \n", + "14 grrrgrrrgrrrrrgrG grrrgrrrgrrrrrgGr 4 4 " + ] + }, + "execution_count": 163, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = pd.concat([df_A, df_B], axis=1)\n", + "df[sorted(df.columns)]" + ] + }, + { + "cell_type": "code", + "execution_count": 218, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "phas_A 3\n", + "duration 22\n", + "state_A grrrgGGrgrrrrrgrr\n", + "red_A 1\n", + "yellow_A 4\n", + "Name: 13, dtype: object" + ] + }, + "execution_count": 218, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pre" + ] + }, + { + "cell_type": "code", + "execution_count": 258, + "metadata": {}, + "outputs": [], + "source": [ + "import time\n", + "\n", + "now = time.time()\n", + "def cumulate(df, alph):\n", + " df = df.reset_index(drop=True)\n", + "\n", + " DF = []\n", + " pre = pd.Series({f'phas_{alph}':None})\n", + "\n", + " start_time = 0\n", + " elapsed = 0\n", + " for i, cur in df.iterrows():\n", + " \n", + " # pre, nex\n", + " if i != 0:\n", + " pre = df.iloc[i-1]\n", + " \n", + " if i != len(df) - 1:\n", + " nex = df.iloc[i+1]\n", + " \n", + " # duration\n", + " if cur[f'phas_{alph}'] == nex[f'phas_{alph}']:\n", + " continue\n", + " if cur[f'phas_{alph}'] == pre[f'phas_{alph}']:\n", + " duration = cur.duration + pre.duration\n", + " else:\n", + " duration = cur.duration\n", + " start_times = []\n", + " states = []\n", + " phases = []\n", + "\n", + " # red\n", + " if i != 0:\n", + " start_time += elapsed\n", + " start_times.append(start_time)\n", + " states.append(get_red(pre[f'state_{alph}'], cur[f'state_{alph}']))\n", + " phases.append(f'{cur[f\"phas_{alph}\"]}r')\n", + "\n", + " elapsed = cur[f'red_{alph}']\n", + "\n", + " # green\n", + " if i == 0:\n", + " start_time = 0\n", + " else:\n", + " start_time += elapsed\n", + " start_times.append(start_time)\n", + " states.append(cur[f'state_{alph}'])\n", + " phases.append(f'{cur[f\"phas_{alph}\"]}g')\n", + " if i == 0:\n", + " elapsed = duration - cur[f'yellow_{alph}']\n", + " else:\n", + " elapsed = duration - cur[f'yellow_{alph}'] - cur[f'red_{alph}']\n", + "\n", + " # yellow\n", + " if i != len(df) - 1:\n", + " start_time += elapsed\n", + " start_times.append(start_time)\n", + " states.append(get_yellow(cur[f'state_{alph}'], nex[f'state_{alph}']))\n", + " phases.append(f'{cur[f\"phas_{alph}\"]}y')\n", + " elapsed = cur[f'yellow_{alph}']\n", + " df_ = pd.DataFrame({'start_time':start_times, f'phas_{alph}':phases, f'state_{alph}':states})\n", + " DF.append(df_)\n", + " DF = pd.concat(DF).reset_index(drop=True)\n", + " return DF\n", + "df_a = cumulate(df_A, 'A')\n", + "df_b = cumulate(df_B, 'B')" + ] + }, + { + "cell_type": "code", + "execution_count": 262, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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start_timephas_Astate_A
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1391ygrrrgrrrgyyyyrgrr
2432rgrrrgrrrgrrrrrgrr
3442ggrrGgrrrgrrrrrgrr
4842ygrrygrrrgrrrrrgrr
5883rgrrrgGGrgrrrrrgrr
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91444ggrrrgrrrgrrrrrgrG
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274522ggrrGgrrrgrrrrrgrr
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start_timephas_Bstate_B
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315253ygrrrgrrygrrrrrgrr
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" + ], + "text/plain": [ + " start_time phas_B state_B\n", + "0 0 1g gGGrgrrrgrrrrrgrr\n", + "1 39 1y gyyrgrrrgrrrrrgrr\n", + "2 43 2r grrrgrrrgrrrrrgrr\n", + "3 44 2g grrrgrrrgrrrrGgrr\n", + "4 84 2y grrrgrrrgrrrrygrr\n", + "5 88 3r grrrgrrrgrrrrrgrr\n", + "6 89 3g grrrgrrGgrrrrrgrr\n", + "7 117 3y grrrgrrygrrrrrgrr\n", + "8 121 4r grrrgrrrgrrrrrgGr\n", + "9 122 4g grrrgrrrgrrrrrgGr\n", + "10 176 4y grrrgrrrgrrrrrgyr\n", + "11 180 1r grrrgrrrgrrrrrgrr\n", + "12 181 1g gGGrgrrrgrrrrrgrr\n", + "13 230 1y gyyrgrrrgrrrrrgrr\n", + "14 234 2r grrrgrrrgrrrrrgrr\n", + "15 235 2g grrrgrrrgrrrrGgrr\n", + "16 287 2y grrrgrrrgrrrrygrr\n", + "17 291 3r grrrgrrrgrrrrrgrr\n", + "18 292 3g grrrgrrGgrrrrrgrr\n", + "19 329 3y grrrgrrygrrrrrgrr\n", + "20 333 4r grrrgrrrgrrrrrgGr\n", + "21 334 4g grrrgrrrgrrrrrgGr\n", + "22 404 4y grrrgrrrgrrrrrgyr\n", + "23 408 1r grrrgrrrgrrrrrgrr\n", + "24 409 1g gGGrgrrrgrrrrrgrr\n", + "25 447 1y gyyrgrrrgrrrrrgrr\n", + "26 451 2r grrrgrrrgrrrrrgrr\n", + "27 452 2g grrrgrrrgrrrrGgrr\n", + "28 492 2y grrrgrrrgrrrrygrr\n", + "29 496 3r grrrgrrrgrrrrrgrr\n", + "30 497 3g grrrgrrGgrrrrrgrr\n", + "31 525 3y grrrgrrygrrrrrgrr" + ] + }, + "execution_count": 263, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_b" + ] + }, + { + "cell_type": "code", + "execution_count": 302, + "metadata": {}, + "outputs": [], + "source": [ + "pairs = set()\n", + "pairs.add(2)" + ] + }, + { + "cell_type": "code", + "execution_count": 304, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{('G', 'r'), ('g', 'g'), ('r', 'G'), ('r', 'r'), ('r', 'y'), ('y', 'r')}" + ] + }, + "execution_count": 304, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pairs = set()\n", + "for A, B in zip(df['state_A'], df['state_B']):\n", + " for a, b in zip(A, B):\n", + " pairs.add((a,b))\n", + "pairs" + ] + }, + { + "cell_type": "code", + "execution_count": 311, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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start_timephasestate_Astate_Bdurationstate
001g_1ggrrrgrrrgGGGGrgrrgGGrgrrrgrrrrrgrr39gGGrgrrrgGGGGrgrr
1391y_1ygrrrgrrrgyyyyrgrrgyyrgrrrgrrrrrgrr4gyyrgrrrgyyyyrgrr
2432r_2rgrrrgrrrgrrrrrgrrgrrrgrrrgrrrrrgrr1grrrgrrrgrrrrrgrr
3442g_2ggrrGgrrrgrrrrrgrrgrrrgrrrgrrrrGgrr40grrGgrrrgrrrrGgrr
4842y_2ygrrygrrrgrrrrrgrrgrrrgrrrgrrrrygrr4grrygrrrgrrrrygrr
5883r_3rgrrrgGGrgrrrrrgrrgrrrgrrrgrrrrrgrr1grrrgGGrgrrrrrgrr
6893g_3ggrrrgGGrgrrrrrgrrgrrrgrrGgrrrrrgrr28grrrgGGGgrrrrrgrr
71173g_3ygrrrgGGrgrrrrrgrrgrrrgrrygrrrrrgrr4grrrgGGygrrrrrgrr
81213g_4rgrrrgGGrgrrrrrgrrgrrrgrrrgrrrrrgGr1grrrgGGrgrrrrrgGr
91223g_4ggrrrgGGrgrrrrrgrrgrrrgrrrgrrrrrgGr17grrrgGGrgrrrrrgGr
101393y_4ggrrrgyyrgrrrrrgrrgrrrgrrrgrrrrrgGr4grrrgyyrgrrrrrgGr
111434r_4ggrrrgrrrgrrrrrgrrgrrrgrrrgrrrrrgGr1grrrgrrrgrrrrrgGr
121444g_4ggrrrgrrrgrrrrrgrGgrrrgrrrgrrrrrgGr32grrrgrrrgrrrrrgGG
131764y_4ygrrrgrrrgrrrrrgrygrrrgrrrgrrrrrgyr4grrrgrrrgrrrrrgyy
141801r_1rgrrrgrrrgrrrrrgrrgrrrgrrrgrrrrrgrr1grrrgrrrgrrrrrgrr
151811g_1ggrrrgrrrgGGGGrgrrgGGrgrrrgrrrrrgrr49gGGrgrrrgGGGGrgrr
162301y_1ygrrrgrrrgyyyyrgrrgyyrgrrrgrrrrrgrr4gyyrgrrrgyyyyrgrr
172342r_2rgrrrgrrrgrrrrrgrrgrrrgrrrgrrrrrgrr1grrrgrrrgrrrrrgrr
182352g_2ggrrGgrrrgrrrrrgrrgrrrgrrrgrrrrGgrr52grrGgrrrgrrrrGgrr
192872y_2ygrrygrrrgrrrrrgrrgrrrgrrrgrrrrygrr4grrygrrrgrrrrygrr
202913r_3rgrrrgGGrgrrrrrgrrgrrrgrrrgrrrrrgrr1grrrgGGrgrrrrrgrr
212923g_3ggrrrgGGrgrrrrrgrrgrrrgrrGgrrrrrgrr37grrrgGGGgrrrrrgrr
223293g_3ygrrrgGGrgrrrrrgrrgrrrgrrygrrrrrgrr4grrrgGGygrrrrrgrr
233333g_4rgrrrgGGrgrrrrrgrrgrrrgrrrgrrrrrgGr1grrrgGGrgrrrrrgGr
243343g_4ggrrrgGGrgrrrrrgrrgrrrgrrrgrrrrrgGr23grrrgGGrgrrrrrgGr
253573y_4ggrrrgyyrgrrrrrgrrgrrrgrrrgrrrrrgGr4grrrgyyrgrrrrrgGr
263614r_4ggrrrgrrrgrrrrrgrrgrrrgrrrgrrrrrgGr1grrrgrrrgrrrrrgGr
273624g_4ggrrrgrrrgrrrrrgrGgrrrgrrrgrrrrrgGr42grrrgrrrgrrrrrgGG
284044y_4ygrrrgrrrgrrrrrgrygrrrgrrrgrrrrrgyr4grrrgrrrgrrrrrgyy
294081r_1rgrrrgrrrgrrrrrgrrgrrrgrrrgrrrrrgrr1grrrgrrrgrrrrrgrr
304091g_1ggrrrgrrrgGGGGrgrrgGGrgrrrgrrrrrgrr38gGGrgrrrgGGGGrgrr
314471y_1ygrrrgrrrgyyyyrgrrgyyrgrrrgrrrrrgrr4gyyrgrrrgyyyyrgrr
324512r_2rgrrrgrrrgrrrrrgrrgrrrgrrrgrrrrrgrr1grrrgrrrgrrrrrgrr
334522g_2ggrrGgrrrgrrrrrgrrgrrrgrrrgrrrrGgrr40grrGgrrrgrrrrGgrr
344922y_2ygrrygrrrgrrrrrgrrgrrrgrrrgrrrrygrr4grrygrrrgrrrrygrr
354963r_3rgrrrgGGrgrrrrrgrrgrrrgrrrgrrrrrgrr1grrrgGGrgrrrrrgrr
364973g_3ggrrrgGGrgrrrrrgrrgrrrgrrGgrrrrrgrr28grrrgGGGgrrrrrgrr
375253g_3ygrrrgGGrgrrrrrgrrgrrrgrrygrrrrrgrr22grrrgGGygrrrrrgrr
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" + ], + "text/plain": [ + " start_time phase state_A state_B duration \\\n", + "0 0 1g_1g grrrgrrrgGGGGrgrr gGGrgrrrgrrrrrgrr 39 \n", + "1 39 1y_1y grrrgrrrgyyyyrgrr gyyrgrrrgrrrrrgrr 4 \n", + "2 43 2r_2r grrrgrrrgrrrrrgrr grrrgrrrgrrrrrgrr 1 \n", + "3 44 2g_2g grrGgrrrgrrrrrgrr grrrgrrrgrrrrGgrr 40 \n", + "4 84 2y_2y grrygrrrgrrrrrgrr grrrgrrrgrrrrygrr 4 \n", + "5 88 3r_3r grrrgGGrgrrrrrgrr grrrgrrrgrrrrrgrr 1 \n", + "6 89 3g_3g grrrgGGrgrrrrrgrr grrrgrrGgrrrrrgrr 28 \n", + "7 117 3g_3y grrrgGGrgrrrrrgrr grrrgrrygrrrrrgrr 4 \n", + "8 121 3g_4r grrrgGGrgrrrrrgrr grrrgrrrgrrrrrgGr 1 \n", + "9 122 3g_4g grrrgGGrgrrrrrgrr grrrgrrrgrrrrrgGr 17 \n", + "10 139 3y_4g grrrgyyrgrrrrrgrr grrrgrrrgrrrrrgGr 4 \n", + "11 143 4r_4g grrrgrrrgrrrrrgrr grrrgrrrgrrrrrgGr 1 \n", + "12 144 4g_4g grrrgrrrgrrrrrgrG grrrgrrrgrrrrrgGr 32 \n", + "13 176 4y_4y grrrgrrrgrrrrrgry grrrgrrrgrrrrrgyr 4 \n", + "14 180 1r_1r grrrgrrrgrrrrrgrr grrrgrrrgrrrrrgrr 1 \n", + "15 181 1g_1g grrrgrrrgGGGGrgrr gGGrgrrrgrrrrrgrr 49 \n", + "16 230 1y_1y grrrgrrrgyyyyrgrr gyyrgrrrgrrrrrgrr 4 \n", + "17 234 2r_2r grrrgrrrgrrrrrgrr grrrgrrrgrrrrrgrr 1 \n", + "18 235 2g_2g grrGgrrrgrrrrrgrr grrrgrrrgrrrrGgrr 52 \n", + "19 287 2y_2y grrygrrrgrrrrrgrr grrrgrrrgrrrrygrr 4 \n", + "20 291 3r_3r grrrgGGrgrrrrrgrr grrrgrrrgrrrrrgrr 1 \n", + "21 292 3g_3g grrrgGGrgrrrrrgrr grrrgrrGgrrrrrgrr 37 \n", + "22 329 3g_3y grrrgGGrgrrrrrgrr grrrgrrygrrrrrgrr 4 \n", + "23 333 3g_4r grrrgGGrgrrrrrgrr grrrgrrrgrrrrrgGr 1 \n", + "24 334 3g_4g grrrgGGrgrrrrrgrr grrrgrrrgrrrrrgGr 23 \n", + "25 357 3y_4g grrrgyyrgrrrrrgrr grrrgrrrgrrrrrgGr 4 \n", + "26 361 4r_4g grrrgrrrgrrrrrgrr grrrgrrrgrrrrrgGr 1 \n", + "27 362 4g_4g grrrgrrrgrrrrrgrG grrrgrrrgrrrrrgGr 42 \n", + "28 404 4y_4y grrrgrrrgrrrrrgry grrrgrrrgrrrrrgyr 4 \n", + "29 408 1r_1r grrrgrrrgrrrrrgrr grrrgrrrgrrrrrgrr 1 \n", + "30 409 1g_1g grrrgrrrgGGGGrgrr gGGrgrrrgrrrrrgrr 38 \n", + "31 447 1y_1y grrrgrrrgyyyyrgrr gyyrgrrrgrrrrrgrr 4 \n", + "32 451 2r_2r grrrgrrrgrrrrrgrr grrrgrrrgrrrrrgrr 1 \n", + "33 452 2g_2g grrGgrrrgrrrrrgrr grrrgrrrgrrrrGgrr 40 \n", + "34 492 2y_2y grrygrrrgrrrrrgrr grrrgrrrgrrrrygrr 4 \n", + "35 496 3r_3r grrrgGGrgrrrrrgrr grrrgrrrgrrrrrgrr 1 \n", + "36 497 3g_3g grrrgGGrgrrrrrgrr grrrgrrGgrrrrrgrr 28 \n", + "37 525 3g_3y grrrgGGrgrrrrrgrr grrrgrrygrrrrrgrr 22 \n", + "\n", + " state \n", + "0 gGGrgrrrgGGGGrgrr \n", + "1 gyyrgrrrgyyyyrgrr \n", + "2 grrrgrrrgrrrrrgrr \n", + "3 grrGgrrrgrrrrGgrr \n", + "4 grrygrrrgrrrrygrr \n", + "5 grrrgGGrgrrrrrgrr \n", + "6 grrrgGGGgrrrrrgrr \n", + "7 grrrgGGygrrrrrgrr \n", + "8 grrrgGGrgrrrrrgGr \n", + "9 grrrgGGrgrrrrrgGr \n", + "10 grrrgyyrgrrrrrgGr \n", + "11 grrrgrrrgrrrrrgGr \n", + "12 grrrgrrrgrrrrrgGG \n", + "13 grrrgrrrgrrrrrgyy \n", + "14 grrrgrrrgrrrrrgrr \n", + "15 gGGrgrrrgGGGGrgrr \n", + "16 gyyrgrrrgyyyyrgrr \n", + "17 grrrgrrrgrrrrrgrr \n", + "18 grrGgrrrgrrrrGgrr \n", + "19 grrygrrrgrrrrygrr \n", + "20 grrrgGGrgrrrrrgrr \n", + "21 grrrgGGGgrrrrrgrr \n", + "22 grrrgGGygrrrrrgrr \n", + "23 grrrgGGrgrrrrrgGr \n", + "24 grrrgGGrgrrrrrgGr \n", + "25 grrrgyyrgrrrrrgGr \n", + "26 grrrgrrrgrrrrrgGr \n", + "27 grrrgrrrgrrrrrgGG \n", + "28 grrrgrrrgrrrrrgyy \n", + "29 grrrgrrrgrrrrrgrr \n", + "30 gGGrgrrrgGGGGrgrr \n", + "31 gyyrgrrrgyyyyrgrr \n", + "32 grrrgrrrgrrrrrgrr \n", + "33 grrGgrrrgrrrrGgrr \n", + "34 grrygrrrgrrrrygrr \n", + "35 grrrgGGrgrrrrrgrr \n", + "36 grrrgGGGgrrrrrgrr \n", + "37 grrrgGGygrrrrrgrr " + ] + }, + "execution_count": 311, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = pd.merge(df_a, df_b, on='start_time', how='outer')\n", + "df = df.sort_values(by='start_time').reset_index(drop=True)\n", + "df[['phas_A', 'state_A']] = df[['phas_A', 'state_A']].fillna(method='ffill')\n", + "df[['phas_B', 'state_B']] = df[['phas_B', 'state_B']].fillna(method='ffill')\n", + "df['phase'] = df['phas_A'] + \"_\" + df['phas_B']\n", + "df = df[['start_time', 'phase', 'state_A', 'state_B']]\n", + "df['duration'] = df['start_time'].shift(-1) - df['start_time']\n", + "df = df[:-1]\n", + "df['duration'] = df['duration'].astype(int)\n", + "for row in df.itertuples():\n", + " state = ''\n", + " for a, b, in zip(row.state_A, row.state_B):\n", + " if a == 'r':\n", + " state += b\n", + " elif b == 'r':\n", + " state += a\n", + " elif a == b:\n", + " state += a\n", + " else:\n", + " raise ValueError(f\"μ˜ˆμƒλ˜μ§€ μ•Šμ€ μ‘°ν•© λ°œμƒ: a={a}, b={b}\")\n", + " df.at[row.Index, 'state'] = state\n", + "df" + ] + }, + { + "cell_type": "code", + "execution_count": 276, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0, 39, 43, 44, 84, 88, 89, 139, 143, 144, 176, 180, 181, 230, 234, 235, 287, 291, 292, 357, 361, 362, 404, 408, 409, 447, 451, 452, 492, 496, 497, 547]\n" + ] + } + ], + "source": [ + "start_times = set.union(set(df_a.start_time.unique()), set(df_a.start_time.unique()))\n", + "start_times = sorted(start_times)\n", + "print(start_times)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df = df_a.copy()\n", + "start_times_additional = set(df_b.start_time.unique()) - set(df_a.start_time.unique())\n", + "for i, row in df.iterrows():\n", + " st = row.start_time\n", + " if st in start_times_additional:" + ] + }, + { + "cell_type": "code", + "execution_count": 207, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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start_timephas_Astate_A
001ggrrrgrrrgGGGGrgrr
1391ygrrrgrrrgyyyyrgrr
2432rgrrrgrrrgrrrrrgrr
3442ggrrGgrrrgrrrrrgrr
4842ygrrygrrrgrrrrrgrr
5883rgrrrgGGrgrrrrrgrr
6893ggrrrgGGrgrrrrrgrr
71393ygrrrgyyrgrrrrrgrr
81434rgrrrgrrrgrrrrrgrr
91444ggrrrgrrrgrrrrrgrG
101764ygrrrgrrrgrrrrrgry
111801rgrrrgrrrgrrrrrgrr
121811ggrrrgrrrgGGGGrgrr
132301ygrrrgrrrgyyyyrgrr
142342rgrrrgrrrgrrrrrgrr
152352ggrrGgrrrgrrrrrgrr
162872ygrrygrrrgrrrrrgrr
172913rgrrrgGGrgrrrrrgrr
182923ggrrrgGGrgrrrrrgrr
193573ygrrrgyyrgrrrrrgrr
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213624ggrrrgrrrgrrrrrgrG
224044ygrrrgrrrgrrrrrgry
234081rgrrrgrrrgrrrrrgrr
244091ggrrrgrrrgGGGGrgrr
254471ygrrrgrrrgyyyyrgrr
264512rgrrrgrrrgrrrrrgrr
274522ggrrGgrrrgrrrrrgrr
284922ygrrygrrrgrrrrrgrr
294963rgrrrgGGrgrrrrrgrr
304973ggrrrgGGrgrrrrrgrr
315473ygrrrgyyrgrrrrrgrr
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" + ], + "text/plain": [ + " start_time phas_A state_A\n", + "0 0 1g grrrgrrrgGGGGrgrr\n", + "1 39 1y grrrgrrrgyyyyrgrr\n", + "2 43 2r grrrgrrrgrrrrrgrr\n", + "3 44 2g grrGgrrrgrrrrrgrr\n", + "4 84 2y grrygrrrgrrrrrgrr\n", + "5 88 3r grrrgGGrgrrrrrgrr\n", + "6 89 3g grrrgGGrgrrrrrgrr\n", + "7 139 3y grrrgyyrgrrrrrgrr\n", + "8 143 4r grrrgrrrgrrrrrgrr\n", + "9 144 4g grrrgrrrgrrrrrgrG\n", + "10 176 4y grrrgrrrgrrrrrgry\n", + "11 180 1r grrrgrrrgrrrrrgrr\n", + "12 181 1g grrrgrrrgGGGGrgrr\n", + "13 230 1y grrrgrrrgyyyyrgrr\n", + "14 234 2r grrrgrrrgrrrrrgrr\n", + "15 235 2g grrGgrrrgrrrrrgrr\n", + "16 287 2y grrygrrrgrrrrrgrr\n", + "17 291 3r grrrgGGrgrrrrrgrr\n", + "18 292 3g grrrgGGrgrrrrrgrr\n", + "19 357 3y grrrgyyrgrrrrrgrr\n", + "20 361 4r grrrgrrrgrrrrrgrr\n", + "21 362 4g grrrgrrrgrrrrrgrG\n", + "22 404 4y grrrgrrrgrrrrrgry\n", + "23 408 1r grrrgrrrgrrrrrgrr\n", + "24 409 1g grrrgrrrgGGGGrgrr\n", + "25 447 1y grrrgrrrgyyyyrgrr\n", + "26 451 2r grrrgrrrgrrrrrgrr\n", + "27 452 2g grrGgrrrgrrrrrgrr\n", + "28 492 2y grrygrrrgrrrrrgrr\n", + "29 496 3r grrrgGGrgrrrrrgrr\n", + "30 497 3g grrrgGGrgrrrrrgrr\n", + "31 547 3y grrrgyyrgrrrrrgrr" + ] + }, + "execution_count": 207, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_A = df_A.reset_index(drop=True)\n", + "\n", + "df_a = []\n", + "\n", + "start_time = 0\n", + "elapsed = 0\n", + "for i, cur in df_A.iterrows():\n", + " \n", + " # pre, nex\n", + " if i != 0:\n", + " pre = df_A.iloc[i-1]\n", + " if i != len(df_A) - 1:\n", + " nex = df_A.iloc[i+1]\n", + " \n", + " # duration\n", + " if cur.phas_A == nex.phas_A:\n", + " continue\n", + " if cur.phas_A == pre.phas_A:\n", + " duration = cur.duration + pre.duration\n", + " else:\n", + " duration = cur.duration\n", + " start_times = []\n", + " state_As = []\n", + " phas_As = []\n", + "\n", + " # red\n", + " if i != 0:\n", + " start_time += elapsed\n", + " start_times.append(start_time)\n", + " state_As.append(get_red(pre.state_A, cur.state_A))\n", + " phas_As.append(f'{cur.phas_A}r')\n", + " elapsed = cur.red_A\n", + " \n", + " # green\n", + " if i == 0:\n", + " start_time = 0\n", + " else:\n", + " start_time += elapsed\n", + " start_times.append(start_time)\n", + " state_As.append(cur.state_A)\n", + " phas_As.append(f'{cur.phas_A}g')\n", + " if i == 0:\n", + " elapsed = duration - cur.yellow_A\n", + " else:\n", + " elapsed = duration - cur.yellow_A - cur.red_A\n", + " # yellow\n", + " if i != len(df_A) - 1:\n", + " start_time += elapsed\n", + " start_times.append(start_time)\n", + " state_As.append(get_yellow(cur.state_A, nex.state_A))\n", + " phas_As.append(f'{cur.phas_A}y')\n", + " elapsed = cur.yellow_A\n", + " df_ = pd.DataFrame({'start_time':start_times, 'phas_A':phas_As, 'state_A':state_As})\n", + " df_a.append(df_)\n", + "df_a = pd.concat(df_a).reset_index(drop=True)\n", + "df_a" + ] + }, + { + "cell_type": "code", + "execution_count": 152, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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start_timephas_Astate_A
001ggrrrgrrrgGGGGrgrr
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1442ggrrGgrrrgrrrrrgrr
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" + ], + "text/plain": [ + " start_time phas_A state_A\n", + "0 0 1g grrrgrrrgGGGGrgrr\n", + "1 39 1y grrrgrrrgyyyyrgrr\n", + "0 43 2r grrrgrrrgrrrrrgrr\n", + "1 44 2g grrGgrrrgrrrrrgrr\n", + "2 84 2y grrygrrrgrrrrrgrr" + ] + }, + "execution_count": 152, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_A = df_A.reset_index(drop=True)\n", + "df_a = []\n", + "\n", + "###\n", + "i = 0\n", + "cur = df_A.iloc[i]\n", + "nex = df_A.iloc[i+1]\n", + "\n", + "start_times = []\n", + "state_As = []\n", + "phas_As = []\n", + "\n", + "# green\n", + "start_time = 0\n", + "start_times.append(start_time)\n", + "state_As.append(cur.state_A)\n", + "phas_As.append(f'{cur.phas_A}g')\n", + "elapsed = cur.duration - cur.yellow_A\n", + "\n", + "# yellow\n", + "start_time += elapsed\n", + "start_times.append(start_time)\n", + "state_As.append(get_yellow(cur.state_A, nex.state_A))\n", + "phas_As.append(f'{cur.phas_A}y')\n", + "elapsed = cur.yellow_A\n", + "\n", + "df_ = pd.DataFrame({'start_time':start_times, 'phas_A':phas_As, 'state_A':state_As})\n", + "df_a.append(df_)\n", + "\n", + "###\n", + "i = 1\n", + "pre = df_A.iloc[i-1]\n", + "cur = df_A.iloc[i]\n", + "nex = df_A.iloc[i+1]\n", + "\n", + "start_times = []\n", + "state_As = []\n", + "phas_As = []\n", + "\n", + "# red\n", + "start_time += elapsed\n", + "start_times.append(start_time)\n", + "state_As.append(get_red(pre.state_A, cur.state_A))\n", + "phas_As.append(f'{cur.phas_A}r')\n", + "elapsed = cur.red_A\n", + "\n", + "# green\n", + "start_time += elapsed\n", + "start_times.append(start_time)\n", + "state_As.append(cur.state_A)\n", + "phas_As.append(f'{cur.phas_A}g')\n", + "\n", + "elapsed = cur.duration - cur.yellow_A - cur.red_A\n", + "\n", + "# yellow\n", + "start_time += elapsed\n", + "start_times.append(start_time)\n", + "state_As.append(get_yellow(cur.state_A, nex.state_A))\n", + "phas_As.append(f'{cur.phas_A}y')\n", + "\n", + "df_ = pd.DataFrame({'start_time':start_times, 'phas_A':phas_As, 'state_A':state_As})\n", + "df_a.append(df_)\n", + "\n", + "df_a = pd.concat(df_a)\n", + "df_a" + ] + }, + { + "cell_type": "code", + "execution_count": 153, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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phas_Adurationstate_Ared_Ayellow_A
0143grrrgrrrgGGGGrgrr14
1245grrGgrrrgrrrrrgrr14
2333grrrgGGrgrrrrrgrr14
3322grrrgGGrgrrrrrgrr14
4437grrrgrrrgrrrrrgrG14
5154grrrgrrrgGGGGrgrr14
6257grrGgrrrgrrrrrgrr14
7342grrrgGGrgrrrrrgrr14
8328grrrgGGrgrrrrrgrr14
9447grrrgrrrgrrrrrgrG14
10143grrrgrrrgGGGGrgrr14
11245grrGgrrrgrrrrrgrr14
12333grrrgGGrgrrrrrgrr14
13322grrrgGGrgrrrrrgrr14
14437grrrgrrrgrrrrrgrG14
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" + ], + "text/plain": [ + " phas_A duration state_A red_A yellow_A\n", + "0 1 43 grrrgrrrgGGGGrgrr 1 4\n", + "1 2 45 grrGgrrrgrrrrrgrr 1 4\n", + "2 3 33 grrrgGGrgrrrrrgrr 1 4\n", + "3 3 22 grrrgGGrgrrrrrgrr 1 4\n", + "4 4 37 grrrgrrrgrrrrrgrG 1 4\n", + "5 1 54 grrrgrrrgGGGGrgrr 1 4\n", + "6 2 57 grrGgrrrgrrrrrgrr 1 4\n", + "7 3 42 grrrgGGrgrrrrrgrr 1 4\n", + "8 3 28 grrrgGGrgrrrrrgrr 1 4\n", + "9 4 47 grrrgrrrgrrrrrgrG 1 4\n", + "10 1 43 grrrgrrrgGGGGrgrr 1 4\n", + "11 2 45 grrGgrrrgrrrrrgrr 1 4\n", + "12 3 33 grrrgGGrgrrrrrgrr 1 4\n", + "13 3 22 grrrgGGrgrrrrrgrr 1 4\n", + "14 4 37 grrrgrrrgrrrrrgrG 1 4" + ] + }, + "execution_count": 153, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_A" + ] + }, + { + "cell_type": "code", + "execution_count": 149, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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phas_Astate_Astart_time
01ggrrrgrrrgGGGGrgrr0
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" + ], + "text/plain": [ + " phas_A state_A start_time\n", + "0 1g grrrgrrrgGGGGrgrr 0" + ] + }, + "execution_count": 149, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_a = pd.concat(df_a)\n", + "df_a" + ] + }, + { + "cell_type": "code", + "execution_count": 83, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Unnamed: 0inter_nophas_Aphas_Bmove_Amove_B
001751184
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" + ], + "text/plain": [ + " Unnamed: 0 inter_no phas_A phas_B move_A move_B\n", + "0 0 175 1 1 8 4\n", + "1 1 175 2 2 7 3\n", + "2 2 175 3 3 6 1\n", + "3 3 175 3 4 6 2\n", + "4 4 175 4 4 5 2" + ] + }, + "execution_count": 83, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "self.match1.query('inter_no==@inter_no')" + ] + }, + { + "cell_type": "code", + "execution_count": 85, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Unnamed: 0inter_nonode_idphase_noring_typemove_nostate
00175i01A8grrrgrrrgGGGGrgrr
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44175i03A6grrrgGGrgrrrrrgrr
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" + ], + "text/plain": [ + " Unnamed: 0 inter_no node_id phase_no ring_type move_no \\\n", + "0 0 175 i0 1 A 8 \n", + "1 1 175 i0 1 B 4 \n", + "2 2 175 i0 2 A 7 \n", + "3 3 175 i0 2 B 3 \n", + "4 4 175 i0 3 A 6 \n", + "5 5 175 i0 3 B 1 \n", + "6 6 175 i0 4 A 5 \n", + "7 7 175 i0 4 B 2 \n", + "\n", + " state \n", + "0 grrrgrrrgGGGGrgrr \n", + "1 gGGrgrrrgrrrrrgrr \n", + "2 grrGgrrrgrrrrrgrr \n", + "3 grrrgrrrgrrrrGgrr \n", + "4 grrrgGGrgrrrrrgrr \n", + "5 grrrgrrGgrrrrrgrr \n", + "6 grrrgrrrgrrrrrgrG \n", + "7 grrrgrrrgrrrrrgGr " + ] + }, + "execution_count": 85, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "self.match6.query('node_id==@Node_id')" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Unnamed: 0dura_A1dura_A2dura_A3dura_A4dura_A5dura_A6dura_A7dura_A8dura_B1...red_B4red_A5red_B5red_A6red_B6red_A7red_B7red_A8red_B8inter_no
0243455537000043...111111111175
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1 rows Γ— 52 columns

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" + ], + "text/plain": [ + " Unnamed: 0 dura_A1 dura_A2 dura_A3 dura_A4 dura_A5 dura_A6 dura_A7 \\\n", + "0 2 43 45 55 37 0 0 0 \n", + "\n", + " dura_A8 dura_B1 ... red_B4 red_A5 red_B5 red_A6 red_B6 red_A7 \\\n", + "0 0 43 ... 1 1 1 1 1 1 \n", + "\n", + " red_B7 red_A8 red_B8 inter_no \n", + "0 1 1 1 175 \n", + "\n", + "[1 rows x 52 columns]" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from datetime import datetime \n", + "start_unix = self.sigtable.start_unix.iloc[0]\n", + "self.load_prow(inter_no, start_unix)[1]" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Unnamed: 0inter_nostart_hourstart_minutedura_A1dura_A2dura_A3dura_A4dura_A5dura_A6...red_A4red_B4red_A5red_B5red_A6red_B6red_A7red_B7red_A8red_B8
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4 rows Γ— 54 columns

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" + ], + "text/plain": [ + " Unnamed: 0 inter_no start_hour start_minute dura_A1 dura_A2 dura_A3 \\\n", + "0 0 175 0 0 37 39 55 \n", + "1 1 175 7 0 40 42 55 \n", + "2 2 175 9 0 43 45 55 \n", + "3 3 175 18 30 46 48 55 \n", + "\n", + " dura_A4 dura_A5 dura_A6 ... red_A4 red_B4 red_A5 red_B5 red_A6 \\\n", + "0 29 0 0 ... 1 1 1 1 1 \n", + "1 33 0 0 ... 1 1 1 1 1 \n", + "2 37 0 0 ... 1 1 1 1 1 \n", + "3 41 0 0 ... 1 1 1 1 1 \n", + "\n", + " red_B6 red_A7 red_B7 red_A8 red_B8 \n", + "0 1 1 1 1 1 \n", + "1 1 1 1 1 1 \n", + "2 1 1 1 1 1 \n", + "3 1 1 1 1 1 \n", + "\n", + "[4 rows x 54 columns]" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "self.plan.query('inter_no==@inter_no')" + ] + }, + { + "cell_type": "code", + "execution_count": 132, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "4. 톡합 ν…Œμ΄λΈ”μ„ μƒμ„±ν•©λ‹ˆλ‹€.\n", + "5. μ‹ ν˜Έλ₯Ό μƒμ„±ν•©λ‹ˆλ‹€.\n" + ] + }, + { + "data": { + "text/html": [ + "
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inter_nonode_idstart_unixphas_Aphas_Bmove_Amove_Bdurationstatephase_sumo
16175i01704416358118443gGGrgrrrgGGGGrgrr0
17175i01704416358227345grrGgrrrgrrrrGgrr1
18175i01704416358336133grrrgGGGgrrrrrgrr2
19175i01704416358346222grrrgGGrgrrrrrgGr3
20175i01704416358445237grrrgrrrgrrrrrgGG4
21175i01704416538118443gGGrgrrrgGGGGrgrr0
22175i01704416538227345grrGgrrrgrrrrGgrr1
23175i01704416538336133grrrgGGGgrrrrrgrr2
24175i01704416538346222grrrgGGrgrrrrrgGr3
25175i01704416538445237grrrgrrrgrrrrrgGG4
26175i01704416718118443gGGrgrrrgGGGGrgrr0
27175i01704416718227345grrGgrrrgrrrrGgrr1
28175i01704416718336133grrrgGGGgrrrrrgrr2
29175i01704416718346222grrrgGGrgrrrrrgGr3
30175i01704416718445237grrrgrrrgrrrrrgGG4
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" + ], + "text/plain": [ + " inter_no node_id start_unix phas_A phas_B move_A move_B duration \\\n", + "16 175 i0 1704416358 1 1 8 4 43 \n", + "17 175 i0 1704416358 2 2 7 3 45 \n", + "18 175 i0 1704416358 3 3 6 1 33 \n", + "19 175 i0 1704416358 3 4 6 2 22 \n", + "20 175 i0 1704416358 4 4 5 2 37 \n", + "21 175 i0 1704416538 1 1 8 4 43 \n", + "22 175 i0 1704416538 2 2 7 3 45 \n", + "23 175 i0 1704416538 3 3 6 1 33 \n", + "24 175 i0 1704416538 3 4 6 2 22 \n", + "25 175 i0 1704416538 4 4 5 2 37 \n", + "26 175 i0 1704416718 1 1 8 4 43 \n", + "27 175 i0 1704416718 2 2 7 3 45 \n", + "28 175 i0 1704416718 3 3 6 1 33 \n", + "29 175 i0 1704416718 3 4 6 2 22 \n", + "30 175 i0 1704416718 4 4 5 2 37 \n", + "\n", + " state phase_sumo \n", + "16 gGGrgrrrgGGGGrgrr 0 \n", + "17 grrGgrrrgrrrrGgrr 1 \n", + "18 grrrgGGGgrrrrrgrr 2 \n", + "19 grrrgGGrgrrrrrgGr 3 \n", + "20 grrrgrrrgrrrrrgGG 4 \n", + "21 gGGrgrrrgGGGGrgrr 0 \n", + "22 grrGgrrrgrrrrGgrr 1 \n", + "23 grrrgGGGgrrrrrgrr 2 \n", + "24 grrrgGGrgrrrrrgGr 3 \n", + "25 grrrgrrrgrrrrrgGG 4 \n", + "26 gGGrgrrrgGGGGrgrr 0 \n", + "27 grrGgrrrgrrrrGgrr 1 \n", + "28 grrrgGGGgrrrrrgrr 2 \n", + "29 grrrgGGrgrrrrrgGr 3 \n", + "30 grrrgrrrgrrrrrgGG 4 " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "self.make_histids()\n", + "self.get_signals()\n", + "display(self.sigtable.query('node_id==@Node_id'))" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "sts", + "language": "python", + "name": "sts" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/Analysis/0307_red_yellow/0307_red_yellow_2.ipynb b/Analysis/0307_red_yellow/0307_red_yellow_2.ipynb new file mode 100644 index 000000000..186b07f51 --- /dev/null +++ b/Analysis/0307_red_yellow/0307_red_yellow_2.ipynb @@ -0,0 +1,1527 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "os.listdir('../../scripts')\n", + "import sys\n", + "sys.path.append('../../Scripts')" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "from generate_signals import SignalGenerator\n", + "from preprocess_daily import DailyPreprocessor" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "inter_no = 175\n", + "Node_id = 'i0'" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1. 데이터λ₯Ό μ€€λΉ„ν•©λ‹ˆλ‹€.\n", + "1-1. λ„€νŠΈμ›Œν¬κ°€ λ‘œλ“œλ˜μ—ˆμŠ΅λ‹ˆλ‹€.\n", + "1-2. ν…Œμ΄λΈ”λ“€μ΄ λ‘œλ“œλ˜μ—ˆμŠ΅λ‹ˆλ‹€.\n", + "2. μ‹ ν˜Έμ΄λ ₯ ν…Œμ΄λΈ”μ„ λ³€ν™˜ν•©λ‹ˆλ‹€.\n", + "3. 이동λ₯˜μ •λ³΄ ν…Œμ΄λΈ”μ„ λ³€ν™˜ν•©λ‹ˆλ‹€.\n", + "4. 톡합 ν…Œμ΄λΈ”μ„ μƒμ„±ν•©λ‹ˆλ‹€.\n" + ] + }, + { + "data": { + "text/html": [ + "
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inter_nonode_idstart_unixphas_Aphas_Bmove_Amove_Bdurationstatephase_sumo
0178c301704418730118433gggggg0_g
1178c30170441873011844gggggg0_y
2178c30170441873022731gggggg1__r
0178c301704418730227334GGGGGG1_g
1178c30170441873022734GGGGGG1_y
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2210u60170441929933741ggggggggr3__r
0210u601704419299337465ggggggggr3_g
1210u60170441929933744ggggggggr3_y
2210u60170441929944831ggggggggr4__r
237210u601704419299448319ggggggggr4_g
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684 rows Γ— 10 columns

\n", + "
" + ], + "text/plain": [ + " inter_no node_id start_unix phas_A phas_B move_A move_B duration \\\n", + "0 178 c30 1704418730 1 1 8 4 33 \n", + "1 178 c30 1704418730 1 1 8 4 4 \n", + "2 178 c30 1704418730 2 2 7 3 1 \n", + "0 178 c30 1704418730 2 2 7 3 34 \n", + "1 178 c30 1704418730 2 2 7 3 4 \n", + ".. ... ... ... ... ... ... ... ... \n", + "2 210 u60 1704419299 3 3 7 4 1 \n", + "0 210 u60 1704419299 3 3 7 4 65 \n", + "1 210 u60 1704419299 3 3 7 4 4 \n", + "2 210 u60 1704419299 4 4 8 3 1 \n", + "237 210 u60 1704419299 4 4 8 3 19 \n", + "\n", + " state phase_sumo \n", + "0 gggggg 0_g \n", + "1 gggggg 0_y \n", + "2 gggggg 1__r \n", + "0 GGGGGG 1_g \n", + "1 GGGGGG 1_y \n", + ".. ... ... \n", + "2 ggggggggr 3__r \n", + "0 ggggggggr 3_g \n", + "1 ggggggggr 3_y \n", + "2 ggggggggr 4__r \n", + "237 ggggggggr 4_g \n", + "\n", + "[684 rows x 10 columns]" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# desired result\n", + "self = SignalGenerator()\n", + "self.prepare_data()\n", + "self.process_history()\n", + "self.process_movement()\n", + "self.make_histids()\n", + "self.set_timepoints()\n", + "self.assign_red_yellow()\n", + "self.self.self.self.self.self.self.self.self.self.self.self.self.self.SIGTABLETABLETABLETABLETABLETABLETABLETABLETABLETABLETABLETABLETABLETABLE" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1. 데이터λ₯Ό μ€€λΉ„ν•©λ‹ˆλ‹€.\n", + "1-1. λ„€νŠΈμ›Œν¬κ°€ λ‘œλ“œλ˜μ—ˆμŠ΅λ‹ˆλ‹€.\n", + "1-2. ν…Œμ΄λΈ”λ“€μ΄ λ‘œλ“œλ˜μ—ˆμŠ΅λ‹ˆλ‹€.\n", + "2. μ‹ ν˜Έμ΄λ ₯ ν…Œμ΄λΈ”μ„ λ³€ν™˜ν•©λ‹ˆλ‹€.\n", + "3. 이동λ₯˜μ •λ³΄ ν…Œμ΄λΈ”μ„ λ³€ν™˜ν•©λ‹ˆλ‹€.\n" + ] + } + ], + "source": [ + "self = SignalGenerator()\n", + "self.prepare_data()\n", + "self.process_history()\n", + "self.process_movement()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "self.merge_dfs()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "# 4-2. histid\n", + "self.histid = self.movedur.copy()\n", + "self.histid['node_id'] = self.histid['inter_no'].map(self.inter2node)\n", + "histid_start = self.present_time - 600\n", + "self.histid = self.histid[self.histid.start_unix > histid_start]\n", + "\n", + "mapping_dict = self.matching.set_index(['node_id', 'move_no'])['state'].to_dict()\n", + "\n", + "for i, row in self.histid.iterrows():\n", + " node_id = row.node_id\n", + " move_A = row.move_A\n", + " move_B = row.move_B\n", + " \n", + " # A링의 state 지정\n", + " if (node_id, move_A) in mapping_dict:\n", + " state_A = mapping_dict[(node_id, move_A)]\n", + " else:\n", + " state_A = ''.join(self.node2init[node_id])\n", + " self.histid.at[i, 'state_A'] = state_A\n", + "\n", + " # B링의 state 지정\n", + " if (node_id, move_B) in mapping_dict:\n", + " state_B = mapping_dict[(node_id, move_B)]\n", + " else:\n", + " state_B = ''.join(self.node2init[node_id])\n", + " self.histid.at[i, 'state_B'] = state_B " + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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inter_nonode_idstart_unixphas_Aphas_Bmove_Amove_Bdurationstate_Astate_B
0175i01704418520118443grrrgrrrgGGGGrgrrgGGrgrrrgrrrrrgrr
1175i01704418520227345grrGgrrrgrrrrrgrrgrrrgrrrgrrrrGgrr
2175i01704418520336133grrrgGGrgrrrrrgrrgrrrgrrGgrrrrrgrr
3175i01704418520346222grrrgGGrgrrrrrgrrgrrrgrrrgrrrrrgGr
4175i01704418520445237grrrgrrrgrrrrrgrGgrrrgrrrgrrrrrgGr
62175i01704418699118443grrrgrrrgGGGGrgrrgGGrgrrrgrrrrrgrr
63175i01704418699227345grrGgrrrgrrrrrgrrgrrrgrrrgrrrrGgrr
64175i01704418699336133grrrgGGrgrrrrrgrrgrrrgrrGgrrrrrgrr
65175i01704418699346222grrrgGGrgrrrrrgrrgrrrgrrrgrrrrrgGr
66175i01704418699445237grrrgrrrgrrrrrgrGgrrrgrrrgrrrrrgGr
131175i01704418880118443grrrgrrrgGGGGrgrrgGGrgrrrgrrrrrgrr
132175i01704418880227345grrGgrrrgrrrrrgrrgrrrgrrrgrrrrGgrr
133175i01704418880336133grrrgGGrgrrrrrgrrgrrrgrrGgrrrrrgrr
134175i01704418880346222grrrgGGrgrrrrrgrrgrrrgrrrgrrrrrgGr
135175i01704418880445237grrrgrrrgrrrrrgrGgrrrgrrrgrrrrrgGr
193175i01704419060118443grrrgrrrgGGGGrgrrgGGrgrrrgrrrrrgrr
194175i01704419060227345grrGgrrrgrrrrrgrrgrrrgrrrgrrrrGgrr
195175i01704419060336133grrrgGGrgrrrrrgrrgrrrgrrGgrrrrrgrr
196175i01704419060346222grrrgGGrgrrrrrgrrgrrrgrrrgrrrrrgGr
197175i01704419060445237grrrgrrrgrrrrrgrGgrrrgrrrgrrrrrgGr
259175i01704419240118443grrrgrrrgGGGGrgrrgGGrgrrrgrrrrrgrr
260175i01704419240227345grrGgrrrgrrrrrgrrgrrrgrrrgrrrrGgrr
261175i01704419240336133grrrgGGrgrrrrrgrrgrrrgrrGgrrrrrgrr
262175i01704419240346222grrrgGGrgrrrrrgrrgrrrgrrrgrrrrrgGr
263175i01704419240445237grrrgrrrgrrrrrgrGgrrrgrrrgrrrrrgGr
337175i01704419420118443grrrgrrrgGGGGrgrrgGGrgrrrgrrrrrgrr
338175i01704419420227345grrGgrrrgrrrrrgrrgrrrgrrrgrrrrGgrr
339175i01704419420336133grrrgGGrgrrrrrgrrgrrrgrrGgrrrrrgrr
340175i01704419420346222grrrgGGrgrrrrrgrrgrrrgrrrgrrrrrgGr
341175i01704419420445237grrrgrrrgrrrrrgrGgrrrgrrrgrrrrrgGr
380175i01704419520118424grrrgrrrgGGGGrgrrgGGrgrrrgrrrrrgrr
381175i01704419520227325grrGgrrrgrrrrrgrrgrrrgrrrgrrrrGgrr
382175i01704419520336118grrrgGGrgrrrrrgrrgrrrgrrGgrrrrrgrr
383175i01704419520346213grrrgGGrgrrrrrgrrgrrrgrrrgrrrrrgGr
384175i01704419520445220grrrgrrrgrrrrrgrGgrrrgrrrgrrrrrgGr
\n", + "
" + ], + "text/plain": [ + " inter_no node_id start_unix phas_A phas_B move_A move_B duration \\\n", + "0 175 i0 1704418520 1 1 8 4 43 \n", + "1 175 i0 1704418520 2 2 7 3 45 \n", + "2 175 i0 1704418520 3 3 6 1 33 \n", + "3 175 i0 1704418520 3 4 6 2 22 \n", + "4 175 i0 1704418520 4 4 5 2 37 \n", + "62 175 i0 1704418699 1 1 8 4 43 \n", + "63 175 i0 1704418699 2 2 7 3 45 \n", + "64 175 i0 1704418699 3 3 6 1 33 \n", + "65 175 i0 1704418699 3 4 6 2 22 \n", + "66 175 i0 1704418699 4 4 5 2 37 \n", + "131 175 i0 1704418880 1 1 8 4 43 \n", + "132 175 i0 1704418880 2 2 7 3 45 \n", + "133 175 i0 1704418880 3 3 6 1 33 \n", + "134 175 i0 1704418880 3 4 6 2 22 \n", + "135 175 i0 1704418880 4 4 5 2 37 \n", + "193 175 i0 1704419060 1 1 8 4 43 \n", + "194 175 i0 1704419060 2 2 7 3 45 \n", + "195 175 i0 1704419060 3 3 6 1 33 \n", + "196 175 i0 1704419060 3 4 6 2 22 \n", + "197 175 i0 1704419060 4 4 5 2 37 \n", + "259 175 i0 1704419240 1 1 8 4 43 \n", + "260 175 i0 1704419240 2 2 7 3 45 \n", + "261 175 i0 1704419240 3 3 6 1 33 \n", + "262 175 i0 1704419240 3 4 6 2 22 \n", + "263 175 i0 1704419240 4 4 5 2 37 \n", + "337 175 i0 1704419420 1 1 8 4 43 \n", + "338 175 i0 1704419420 2 2 7 3 45 \n", + "339 175 i0 1704419420 3 3 6 1 33 \n", + "340 175 i0 1704419420 3 4 6 2 22 \n", + "341 175 i0 1704419420 4 4 5 2 37 \n", + "380 175 i0 1704419520 1 1 8 4 24 \n", + "381 175 i0 1704419520 2 2 7 3 25 \n", + "382 175 i0 1704419520 3 3 6 1 18 \n", + "383 175 i0 1704419520 3 4 6 2 13 \n", + "384 175 i0 1704419520 4 4 5 2 20 \n", + "\n", + " state_A state_B \n", + "0 grrrgrrrgGGGGrgrr gGGrgrrrgrrrrrgrr \n", + "1 grrGgrrrgrrrrrgrr grrrgrrrgrrrrGgrr \n", + "2 grrrgGGrgrrrrrgrr grrrgrrGgrrrrrgrr \n", + "3 grrrgGGrgrrrrrgrr grrrgrrrgrrrrrgGr \n", + "4 grrrgrrrgrrrrrgrG grrrgrrrgrrrrrgGr \n", + "62 grrrgrrrgGGGGrgrr gGGrgrrrgrrrrrgrr \n", + "63 grrGgrrrgrrrrrgrr grrrgrrrgrrrrGgrr \n", + "64 grrrgGGrgrrrrrgrr grrrgrrGgrrrrrgrr \n", + "65 grrrgGGrgrrrrrgrr grrrgrrrgrrrrrgGr \n", + "66 grrrgrrrgrrrrrgrG grrrgrrrgrrrrrgGr \n", + "131 grrrgrrrgGGGGrgrr gGGrgrrrgrrrrrgrr \n", + "132 grrGgrrrgrrrrrgrr grrrgrrrgrrrrGgrr \n", + "133 grrrgGGrgrrrrrgrr grrrgrrGgrrrrrgrr \n", + "134 grrrgGGrgrrrrrgrr grrrgrrrgrrrrrgGr \n", + "135 grrrgrrrgrrrrrgrG grrrgrrrgrrrrrgGr \n", + "193 grrrgrrrgGGGGrgrr gGGrgrrrgrrrrrgrr \n", + "194 grrGgrrrgrrrrrgrr grrrgrrrgrrrrGgrr \n", + "195 grrrgGGrgrrrrrgrr grrrgrrGgrrrrrgrr \n", + "196 grrrgGGrgrrrrrgrr grrrgrrrgrrrrrgGr \n", + "197 grrrgrrrgrrrrrgrG grrrgrrrgrrrrrgGr \n", + "259 grrrgrrrgGGGGrgrr gGGrgrrrgrrrrrgrr \n", + "260 grrGgrrrgrrrrrgrr grrrgrrrgrrrrGgrr \n", + "261 grrrgGGrgrrrrrgrr grrrgrrGgrrrrrgrr \n", + "262 grrrgGGrgrrrrrgrr grrrgrrrgrrrrrgGr \n", + "263 grrrgrrrgrrrrrgrG grrrgrrrgrrrrrgGr \n", + "337 grrrgrrrgGGGGrgrr gGGrgrrrgrrrrrgrr \n", + "338 grrGgrrrgrrrrrgrr grrrgrrrgrrrrGgrr \n", + "339 grrrgGGrgrrrrrgrr grrrgrrGgrrrrrgrr \n", + "340 grrrgGGrgrrrrrgrr grrrgrrrgrrrrrgGr \n", + "341 grrrgrrrgrrrrrgrG grrrgrrrgrrrrrgGr \n", + "380 grrrgrrrgGGGGrgrr gGGrgrrrgrrrrrgrr \n", + "381 grrGgrrrgrrrrrgrr grrrgrrrgrrrrGgrr \n", + "382 grrrgGGrgrrrrrgrr grrrgrrGgrrrrrgrr \n", + "383 grrrgGGrgrrrrrgrr grrrgrrrgrrrrrgGr \n", + "384 grrrgrrrgrrrrrgrG grrrgrrrgrrrrrgGr " + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# 4-3. histids\n", + "new_histids = []\n", + "for parent_id in self.parent_ids:\n", + " for child_id in self.pa2ch[parent_id]:\n", + " new_histid = self.histid.copy()[self.histid.node_id==parent_id].drop(columns=['state_A', 'state_B'])\n", + " # new_histid[['inc_edge_A', 'out_edge_A', 'inc_edge_B', 'out_edge_B']] = np.nan\n", + " for i, row in new_histid.iterrows():\n", + " phas_A = row.phas_A\n", + " phas_B = row.phas_B\n", + " new_match = self.match6[self.match6.node_id==child_id]\n", + " Arow = new_match[(new_match.phase_no==phas_A) & (new_match.ring_type=='A')]\n", + "\n", + " # A링의 state 지정\n", + " state_A = Arow.iloc[0].state\n", + " new_histid.at[i, 'state_A'] = state_A\n", + "\n", + " # B링의 state 지정\n", + " Brow = new_match[(new_match.phase_no==phas_B) & (new_match.ring_type=='B')]\n", + " state_B = Brow.iloc[0].state\n", + " new_histid.at[i, 'state_B'] = state_B\n", + "\n", + " new_histid.at[i, 'node_id'] = child_id\n", + " new_histids.append(new_histid)\n", + "import pandas as pd\n", + "new_histids = pd.concat(new_histids)\n", + "self.histids = pd.concat([self.histid.copy(), new_histids])\n", + "self.histids = self.histids.sort_values(by=['start_unix', 'node_id', 'phas_A', 'phas_B']).reset_index(drop=True)\n", + "self.histids = self.histids[['inter_no', 'node_id', 'start_unix', 'phas_A', 'phas_B', 'move_A', 'move_B', 'duration', 'state_A', 'state_B']]\n", + "self.histids.query('node_id==@Node_id')" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "self.set_timepoints()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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inter_nonode_idstart_unixphas_Aphas_Bmove_Amove_Bdurationstate_Astate_Bphase_sumo
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3178c301704418730446122GGGggggggGGG3
4178c301704418900118438gggggggggggg0
....................................
233210u6017044192991161828ggggggggrggggggggr0
234210u601704419299126215ggggggggrggggggggr1
235210u601704419299225243ggggggggGggggggggr2
236210u601704419299337470ggggggggrggggggggr3
237210u601704419299448324ggggggggrggggggggr4
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238 rows Γ— 11 columns

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" + ], + "text/plain": [ + " inter_no node_id start_unix phas_A phas_B move_A move_B duration \\\n", + "0 178 c30 1704418730 1 1 8 4 38 \n", + "1 178 c30 1704418730 2 2 7 3 39 \n", + "2 178 c30 1704418730 3 3 5 2 43 \n", + "3 178 c30 1704418730 4 4 6 1 22 \n", + "4 178 c30 1704418900 1 1 8 4 38 \n", + ".. ... ... ... ... ... ... ... ... \n", + "233 210 u60 1704419299 1 1 6 18 28 \n", + "234 210 u60 1704419299 1 2 6 2 15 \n", + "235 210 u60 1704419299 2 2 5 2 43 \n", + "236 210 u60 1704419299 3 3 7 4 70 \n", + "237 210 u60 1704419299 4 4 8 3 24 \n", + "\n", + " state_A state_B phase_sumo \n", + "0 gggggg gggggg 0 \n", + "1 GGGggg gggGGG 1 \n", + "2 GGGggg gggGGG 2 \n", + "3 GGGggg gggGGG 3 \n", + "4 gggggg gggggg 0 \n", + ".. ... ... ... \n", + "233 ggggggggr ggggggggr 0 \n", + "234 ggggggggr ggggggggr 1 \n", + "235 ggggggggG ggggggggr 2 \n", + "236 ggggggggr ggggggggr 3 \n", + "237 ggggggggr ggggggggr 4 \n", + "\n", + "[238 rows x 11 columns]" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "self.sigtable" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [], + "source": [ + "def get_red(pre_state:str, cur_state:str):\n", + " assert len(pre_state) == len(cur_state), \"cur_state, nex_state의 길이가 μ„œλ‘œ λ‹€λ¦…λ‹ˆλ‹€.\"\n", + " state_r = ''\n", + " for c, n in zip(pre_state, cur_state):\n", + " if c == n:\n", + " state_r += c\n", + " elif (c == 'r') and (n == 'G'):\n", + " state_r += 'r'\n", + " elif (c == 'G') and (n == 'r'):\n", + " state_r += 'r'\n", + " else:\n", + " raise ValueError(f\"μ˜ˆμƒμΉ˜ λͺ»ν•œ μ‹ ν˜Έμ‘°ν•©: current={c}, next={n}\")\n", + " return state_r\n", + "\n", + "def get_yellow(cur_state:str, nex_state:str):\n", + " assert len(cur_state) == len(nex_state), \"cur_state, nex_state의 길이가 μ„œλ‘œ λ‹€λ¦…λ‹ˆλ‹€.\"\n", + " state_y = ''\n", + " for c, n in zip(cur_state, nex_state):\n", + " if c == n:\n", + " state_y += c\n", + " elif (c == 'r') and (n == 'G'):\n", + " state_y += 'r'\n", + " elif (c == 'G') and (n == 'r'):\n", + " state_y += 'y'\n", + " else:\n", + " raise ValueError(f\"μ˜ˆμƒμΉ˜ λͺ»ν•œ μ‹ ν˜Έμ‘°ν•©: current={c}, next={n}\")\n", + " return state_y\n", + "\n", + "def cumulate(sig, alph):\n", + " csig = [] # cumulated sig\n", + " pre = pd.Series({f'phas_{alph}':None})\n", + "\n", + " start_time = 0\n", + " elapsed = 0\n", + " for i, cur in sig.iterrows():\n", + " start_unix = cur.start_unix\n", + " \n", + " # pre, nex\n", + " if i != 0:\n", + " pre = sig.iloc[i-1]\n", + " \n", + " if i != len(sig) - 1:\n", + " nex = sig.iloc[i+1]\n", + " \n", + " # duration\n", + " if cur[f'phas_{alph}'] == nex[f'phas_{alph}']:\n", + " continue\n", + " if cur[f'phas_{alph}'] == pre[f'phas_{alph}']:\n", + " duration = cur.duration + pre.duration\n", + " else:\n", + " duration = cur.duration\n", + " start_times = []\n", + " states = []\n", + " phases = []\n", + "\n", + " # red\n", + " if i != 0:\n", + " start_time += elapsed\n", + " start_times.append(start_time)\n", + " states.append(get_red(pre[f'state_{alph}'], cur[f'state_{alph}']))\n", + " phases.append(f'{cur[f\"phas_{alph}\"]}r')\n", + "\n", + " elapsed = cur[f'red_{alph}']\n", + "\n", + " # green\n", + " if i == 0:\n", + " start_time = 0\n", + " else:\n", + " start_time += elapsed\n", + " start_times.append(start_time)\n", + " states.append(cur[f'state_{alph}'])\n", + " phases.append(f'{cur[f\"phas_{alph}\"]}g')\n", + " if i == 0:\n", + " elapsed = duration - cur[f'yellow_{alph}']\n", + " else:\n", + " elapsed = duration - cur[f'yellow_{alph}'] - cur[f'red_{alph}']\n", + "\n", + " # yellow\n", + " if i != len(sig) - 1:\n", + " start_time += elapsed\n", + " start_times.append(start_time)\n", + " states.append(get_yellow(cur[f'state_{alph}'], nex[f'state_{alph}']))\n", + " phases.append(f'{cur[f\"phas_{alph}\"]}y')\n", + " elapsed = cur[f'yellow_{alph}']\n", + " sig_ = pd.DataFrame({'start_time':start_times, f'phas_{alph}':phases, f'state_{alph}':states})\n", + " sig_['start_unix'] = start_unix\n", + " csig.append(sig_)\n", + " csig = pd.concat(csig).reset_index(drop=True)\n", + " return csig" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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node_idstart_unixphasedurationstate
0c3017044186991g_1g39gGGrgrrrgGGGGrgrr
1c3017044186991y_1y4gyyrgrrrgyyyyrgrr
2c3017044186992r_2r1grrrgrrrgrrrrrgrr
3c3017044186992g_2g40grrGgrrrgrrrrGgrr
4c3017044186992y_2y4grrygrrrgrrrrygrr
..................
33u6017044190602g_2g40grrGgrrrgrrrrGgrr
34u6017044190602y_2y4grrygrrrgrrrrygrr
35u6017044190603r_3r1grrrgGGrgrrrrrgrr
36u6017044190603g_3g28grrrgGGGgrrrrrgrr
37u6017044190603g_3y22grrrgGGygrrrrrgrr
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570 rows Γ— 5 columns

\n", + "
" + ], + "text/plain": [ + " node_id start_unix phase duration state\n", + "0 c30 1704418699 1g_1g 39 gGGrgrrrgGGGGrgrr\n", + "1 c30 1704418699 1y_1y 4 gyyrgrrrgyyyyrgrr\n", + "2 c30 1704418699 2r_2r 1 grrrgrrrgrrrrrgrr\n", + "3 c30 1704418699 2g_2g 40 grrGgrrrgrrrrGgrr\n", + "4 c30 1704418699 2y_2y 4 grrygrrrgrrrrygrr\n", + ".. ... ... ... ... ...\n", + "33 u60 1704419060 2g_2g 40 grrGgrrrgrrrrGgrr\n", + "34 u60 1704419060 2y_2y 4 grrygrrrgrrrrygrr\n", + "35 u60 1704419060 3r_3r 1 grrrgGGrgrrrrrgrr\n", + "36 u60 1704419060 3g_3g 28 grrrgGGGgrrrrrgrr\n", + "37 u60 1704419060 3g_3y 22 grrrgGGygrrrrrgrr\n", + "\n", + "[570 rows x 5 columns]" + ] + }, + "execution_count": 65, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "self.SIGTABLE = []\n", + "for node_id in self.sigtable.node_id.unique():\n", + " sig = self.sigtable.query('node_id==@Node_id')\n", + " for i, row in sig.iterrows():\n", + " inter_no = row.inter_no\n", + " phas_A = row.phas_A\n", + " phas_B = row.phas_B\n", + " start_unix = row.start_unix\n", + " prow = self.load_prow(inter_no, start_unix)[1].iloc[0]\n", + " red_A = prow[f'red_A{phas_A}']\n", + " yellow_A = prow[f'yellow_A{phas_A}']\n", + " red_B = prow[f'red_B{phas_B}']\n", + " yellow_B = prow[f'yellow_B{phas_B}']\n", + " sig.loc[i, ['red_A', 'red_B', 'yellow_A', 'yellow_B']] = red_A, red_B, yellow_A, yellow_B\n", + " sig = sig.astype({'red_A': int, 'red_B': int, 'yellow_A': int, 'yellow_B': int,\n", + " 'phas_A':str, 'phas_B':str})\n", + " sig = sig.drop(['move_A','move_B'], axis=1)\n", + "\n", + " sig_A = sig[['start_unix', 'phas_A', 'duration', 'state_A', 'red_A', 'yellow_A']].reset_index(drop=True)\n", + " sig_B = sig[['start_unix', 'phas_B', 'duration', 'state_B', 'red_B', 'yellow_B']].reset_index(drop=True)\n", + "\n", + " csig_A = cumulate(sig_A, 'A')\n", + " csig_B = cumulate(sig_B, 'B')\n", + "\n", + " SIG = pd.merge(csig_A, csig_B, on=['start_time', 'start_unix'], how='outer')\n", + " SIG = SIG.sort_values(by='start_time').reset_index(drop=True)\n", + " SIG[['phas_A', 'state_A']] = SIG[['phas_A', 'state_A']].fillna(method='ffill')\n", + " SIG[['phas_B', 'state_B']] = SIG[['phas_B', 'state_B']].fillna(method='ffill')\n", + " SIG['phase'] = SIG['phas_A'] + \"_\" + SIG['phas_B']\n", + " SIG['node_id'] = node_id\n", + " SIG = SIG[['node_id', 'start_unix', 'start_time', 'phase', 'state_A', 'state_B']]\n", + " SIG['duration'] = SIG['start_time'].shift(-1) - SIG['start_time']\n", + " SIG = SIG[:-1]\n", + " SIG['duration'] = SIG['duration'].astype(int)\n", + " for row in SIG.itertuples():\n", + " state = ''\n", + " for a, b, in zip(row.state_A, row.state_B):\n", + " if a == 'r':\n", + " state += b\n", + " elif b == 'r':\n", + " state += a\n", + " elif a == b:\n", + " state += a\n", + " else:\n", + " raise ValueError(f\"μ˜ˆμƒλ˜μ§€ μ•Šμ€ μ‘°ν•© λ°œμƒ: a={a}, b={b}\")\n", + " SIG.at[row.Index, 'state'] = state\n", + " SIG = SIG.drop(columns=['start_time', 'state_A', 'state_B'])\n", + " self.SIGTABLE.append(SIG)\n", + "self.SIGTABLE = pd.concat(self.SIGTABLE)\n", + "self.SIGTABLE" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "sts", + "language": "python", + "name": "sts" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/Analysis/0307_red_yellow/setup_tls_program.py b/Analysis/0307_red_yellow/setup_tls_program.py new file mode 100644 index 000000000..a07bdd3e5 --- /dev/null +++ b/Analysis/0307_red_yellow/setup_tls_program.py @@ -0,0 +1,274 @@ +import os +import sys +if '__file__' in globals(): + script_dir = os.path.dirname(os.path.abspath(__file__)) + sys.path.append(script_dir) + +import numpy as np +import pandas as pd + +GREEN_SET = {'g', 'G'} +YELLOW_SET = {'y'} +RED_SET = {'r'} +def get_intermediate_signal_state(prev, cur, signal_type='yellow'): + ''' + https://github.com/cts198859/deeprl_signal_control/blob/master/envs/env.py#L128-L152 + 'signal_type' has one of the following two values. ['yellow', 'red'] + ''' + + # μ΄μ „μ‹ ν˜Έμ™€ κ°™μ„λ•Œ + if prev == cur: + return cur, False + + # 각 μΈλ±μŠ€μ— ν•΄λ‹Ήν•˜λŠ” 문자λ₯Ό 비ꡐ + switch_reds, switch_greens = [], [] + for i, (p0, p1) in enumerate(zip(prev, cur)): + + # λ…Ήμƒ‰μ—μ„œ μ μƒ‰μœΌλ‘œ λ°”λ€” λ•Œ + if (p0 in GREEN_SET) and (p1 == 'r'): + switch_reds.append(i) + + # μ μƒ‰μ—μ„œ λ…Ήμƒ‰μœΌλ‘œ λ°”λ€” λ•Œ + elif (p0 in 'r') and (p1 in GREEN_SET): + switch_greens.append(i) + + # λ…Ήμƒ‰μ—μ„œ μ μƒ‰μœΌλ‘œ λ°”λ€ŒλŠ” κ²½μš°κ°€ μ—†μœΌλ©΄ + if (not switch_reds) and (signal_type == 'yellow'): + return cur, False + + mid = list(cur) + for i in switch_reds: + if signal_type == 'yellow': + mid[i] = 'y' + for i in switch_greens: + mid[i] = 'r' + + return ''.join(mid), True + + +class SetupTLSProgram: + def __init__(self, durations, reds, yellows, offset, states, path_tll_xml, name=None): + self.durations = self.as_array(durations) + self.reds = self.as_array(reds) + self.yellows = self.as_array(yellows) + self.offset = offset + self.states = states + self.path_tll_xml = path_tll_xml + self.name = name + self.num_phase = len(states) // 2 + + + def as_array(self, x): + if isinstance(x, list): + return np.array(x) + return x + + + def _val(self): + + # 길이가 μ§μˆ˜μΈμ§€ 확인 + if len(self.states) % 2 != 0: + raise ValueError("It must have an even number of elements. Odd length detected.") + + length = self.num_phase * 2 + if length != len(self.durations) or length != len(self.reds) or length != len(self.yellows): + raise ValueError("The length must all match length.") + + if len(set([len(s) for s in self.states])) != 1: + ValueError("All elements in 'states' must have the same length.") + + if np.sum(self.durations[:self.num_phase]) != np.sum(self.durations[self.num_phase:]): + raise ValueError("The sums of the two halves of durations do not match") + + self._check_always_red(self.states) + + self._validate_non_negative_elements(self.durations) + self._validate_non_negative_elements(self.reds) + self._validate_non_negative_elements(self.yellows) + self._validate_non_negative_elements(self.durations - self.reds - self.yellows) + + + def _validate_non_negative_elements(self, lst): + if any(x < 0 for x in lst): + raise ValueError('The list contains values less than 0. Please ensure all elements in the list are non-negative.') + + + def _check_always_red(self, states): + colors = ['r'] * len(states[0]) + for s in states: + for i, char in enumerate(s.lower()): + if char != 'r': + colors[i] = char + if 'r' in colors: + raise ValueError("'r' is not allowed in the colors collection.") + + + def _merge(self, s1, s2): + + if len(s1) != len(s2): + raise ValueError("The lengths of s1 and s2 must be the same.") + + new_s = [] + for c1, c2 in zip(s1, s2): + + if c1 == 'r': + new_s.append(c2) + elif c2 == 'r': + new_s.append(c1) + elif c1 == c2: + new_s.append(c1) + else: + raise ValueError(f"Unexpected characters encountered: c1={c1}, c2={c2}") + + return ''.join(new_s) + + + def _add(self, durations, reds, yellows, states, ring_type='None'): + greens = durations - reds - yellows + colors = [] + phase_numbers = [] + new_states = [] + for curr_i in range(len(states)): + + prev_i = (curr_i - 1 + len(states)) % len(states) + next_i = (curr_i + 1) % len(states) + phase_no = curr_i + 1 + + r_state, _ = get_intermediate_signal_state(states[prev_i], states[curr_i], signal_type='red') + y_state, has_y = get_intermediate_signal_state(states[curr_i], states[next_i], signal_type='yellow') + g_state = states[curr_i] + + # red + if reds[curr_i] != 0: + new_states += [r_state] * reds[curr_i] + colors += [1] * reds[curr_i] # 'r' + phase_numbers += [phase_no] * reds[curr_i] + + # green + new_states += [g_state] * greens[curr_i] + colors += [2] * greens[curr_i] # 'g' + phase_numbers += [phase_no] * greens[curr_i] + + # yellow + if has_y and yellows[curr_i] == 0: + raise ValueError('Yellow signal is required, but the yellow duration is 0.') + + if not has_y and yellows[curr_i] != 0: + y_state = g_state + + new_states += [y_state] * yellows[curr_i] + colors += [3] * yellows[curr_i] # 'y' + phase_numbers += [phase_no] * yellows[curr_i] + + df = pd.DataFrame( + { + f'{ring_type}_ring_phase_no':phase_numbers, + f'{ring_type}_ring_color':colors, + f'{ring_type}_ring_state':new_states} + ) + return df + + + def write_tll_xml(self, df_plan, path_tll_xml): + strings = ['\n'] + tllogic_id = 'None' if self.name is None else self.name + strings.append(f' \n') + for _, row in df_plan.iterrows(): + name = str(row['A_ring_phase_no']) + row['A_ring_color'] + name += '_' + str(row['B_ring_phase_no']) + row['B_ring_color'] + duration = row['duration'] + signal_state = row['signal_state'] + strings.append(f' \n') + strings.append(' \n') + strings.append('') + strings = ''.join(strings) + with open(path_tll_xml, 'w') as f: + f.write(strings) + + + def main(self): + + durations, reds, yellows, states = self.durations, self.reds, self.yellows, self.states + n = self.num_phase + + self._val() + + df_a = self._add(durations[:n], reds[:n], yellows[:n], states[:n], 'A') + df_b = self._add(durations[n:], reds[n:], yellows[n:], states[n:], 'B') + group_cols = ['A_ring_phase_no', 'A_ring_color', 'A_ring_state', 'B_ring_phase_no', 'B_ring_color', 'B_ring_state'] + sort_cols = ['A_ring_phase_no', 'A_ring_color', 'B_ring_phase_no', 'B_ring_color'] + df_plan = pd.concat([df_a, df_b], axis=1) \ + .groupby(group_cols) \ + .size() \ + .reset_index(name='duration') \ + .sort_values(by=sort_cols) \ + .reset_index(drop=True) + + mapping = {1: 'r', 2: 'g', 3: 'y'} + df_plan['A_ring_color'] = df_plan['A_ring_color'].map(mapping) + df_plan['B_ring_color'] = df_plan['B_ring_color'].map(mapping) + df_plan['signal_state'] = df_plan.apply(lambda row: self._merge(row['A_ring_state'], row['B_ring_state']), axis=1) + + assert df_plan['duration'].sum() == np.sum(durations[:n]) + assert df_plan['duration'].sum() == np.sum(durations[n:]) + + self.write_tll_xml(df_plan, self.path_tll_xml) + + return df_plan + + +if __name__ == '__main__': + + ''' + Test data + + - ꡐ차둜번호: 5034 + - μ•žμ—μ„œ λΆ€ν„° μˆœμ„œλŒ€λ‘œ A링1ν˜„μ‹œ, A링2ν˜„μ‹œ, ..., B링1ν˜„μ‹œ, B링2ν˜„μ‹œ, ... + ''' + + # μ˜€λ²„λž© ν…ŒμŠ€νŠΈ + durations = [51, 34, 52, 43, 46, 39, 52, 43] + reds = [2, 2, 2, 2, 2, 2, 2, 2] + yellows = [4, 4, 4, 4, 4, 4, 4, 4] + offset = 5 + + # # 원본 + # durations = [53, 33, 51, 43, 26, 60, 51, 43] + # reds = [0, 0, 0, 0, 0, 0, 0, 0] + # yellows = [4, 4, 4, 4, 4, 4, 4, 4] + # offset = 0 + + # # 1795 (2023λ…„ 12μ›” 20일 7μ‹œ) + # durations = [58, 29, 50, 43, 28, 59, 50, 43] + # reds = [0, 0, 0, 0, 0, 0, 0, 0] + # yellows = [4, 4, 4, 4, 4, 4, 4, 4] + # offset = 0 + + # # 1888 (2023λ…„ 12μ›” 21일 7μ‹œ) + # durations = [61, 28, 48, 43, 27, 62, 48, 43] + # reds = [0, 0, 0, 0, 0, 0, 0, 0] + # yellows = [4, 4, 4, 4, 4, 4, 4, 4] + # offset = 0 + + # 각 ν˜„μ‹œμ˜ 이동λ₯˜μ— ν•΄λ‹Ήν•˜λŠ” signal state + signal_states = [ + 'rrrrrrrrrGGGGrrrrrrrr', + 'rrrGrrrrrrrrrrrrrrrrr', + 'rrrrGGGrrrrrrrrrrrrrr', + 'rrrrrrrrrrrrrrrrrrrGG', + 'rrrrrrrrrrrrrGGrrrrrr', + 'GGGrrrrrrrrrrrrrrrrrr', + 'rrrrrrrGGrrrrrrrrrrrr', + 'rrrrrrrrrrrrrrrGGGGrr' + ] + + # μ €μž₯ν•  경둜 + path_xml = 'test.tll.xml' + path_csv = 'test.tll.csv' + + # λ…Έλ“œid + node_id = '11053' # ꡐ차둜번호: 5034 + + args = durations, reds, yellows, offset, signal_states, path_xml, node_id + SetupTLSProgram(*args).main().to_csv(path_csv, index=False) + print('hello') \ No newline at end of file diff --git a/Data/tables/plan.csv b/Data/tables/plan.csv index fc0924a78..8c9f751b1 100644 --- a/Data/tables/plan.csv +++ b/Data/tables/plan.csv @@ -1,33 +1,33 @@ -,inter_no,start_hour,start_minute,dura_A1,dura_A2,dura_A3,dura_A4,dura_A5,dura_A6,dura_A7,dura_A8,dura_B1,dura_B2,dura_B3,dura_B4,dura_B5,dura_B6,dura_B7,dura_B8,cycle,offset -0,175,00,00,37,39,55,29,0,0,0,0,37,39,25,59,0,0,0,0,160,57 -1,175,07,00,40,42,55,33,0,0,0,0,40,42,29,59,0,0,0,0,170,40 -2,175,09,00,43,45,55,37,0,0,0,0,43,45,33,59,0,0,0,0,180,28 -3,175,18,30,46,48,55,41,0,0,0,0,46,48,37,59,0,0,0,0,190,18 -4,176,00,00,37,73,40,0,0,0,0,0,37,73,40,0,0,0,0,0,150,131 -5,176,07,00,37,93,40,0,0,0,0,0,37,93,40,0,0,0,0,0,170,153 -6,176,09,00,37,103,40,0,0,0,0,0,37,103,40,0,0,0,0,0,180,169 -7,176,18,30,37,113,40,0,0,0,0,0,37,113,40,0,0,0,0,0,190,185 -8,177,00,00,36,20,68,26,0,0,0,0,36,20,68,26,0,0,0,0,150,35 -9,177,07,00,40,25,71,34,0,0,0,0,40,25,71,34,0,0,0,0,170,33 -10,177,09,00,43,27,70,40,0,0,0,0,43,27,70,40,0,0,0,0,180,41 -11,177,18,30,45,32,77,36,0,0,0,0,45,32,77,36,0,0,0,0,190,49 -12,178,00,00,38,39,40,23,0,0,0,0,38,39,40,23,0,0,0,0,140,50 -13,178,07,00,38,39,42,41,0,0,0,0,38,39,62,21,0,0,0,0,160,90 -14,178,09,00,38,39,43,50,0,0,0,0,38,39,71,22,0,0,0,0,170,80 -15,178,18,30,38,39,44,59,0,0,0,0,38,39,80,23,0,0,0,0,180,75 -16,201,00,00,24,24,17,58,17,0,0,0,24,24,17,58,17,0,0,0,140,133 -17,201,07,00,30,36,18,58,18,0,0,0,30,36,18,58,18,0,0,0,160,132 -18,201,09,00,33,36,25,58,18,0,0,0,33,36,25,58,18,0,0,0,170,134 -19,201,18,30,36,50,18,58,18,0,0,0,36,50,18,58,18,0,0,0,180,137 -20,202,00,00,39,101,0,0,0,0,0,0,39,101,0,0,0,0,0,0,140,103 -21,202,07,00,46,114,0,0,0,0,0,0,46,114,0,0,0,0,0,0,160,103 -22,202,09,00,46,114,0,0,0,0,0,0,46,114,0,0,0,0,0,0,160,103 -23,202,18,30,48,122,0,0,0,0,0,0,48,122,0,0,0,0,0,0,170,103 -24,206,00,00,33,35,26,26,0,0,0,0,33,35,26,26,0,0,0,0,120,10 -25,206,07,00,44,44,26,26,0,0,0,0,44,44,26,26,0,0,0,0,140,7 -26,206,09,00,45,53,26,26,0,0,0,0,45,53,26,26,0,0,0,0,150,17 -27,206,18,30,46,62,26,26,0,0,0,0,46,62,26,26,0,0,0,0,160,10 -28,210,00,00,43,29,56,22,0,0,0,0,24,48,56,22,0,0,0,0,150,115 -29,210,07,00,43,39,65,23,0,0,0,0,24,58,65,23,0,0,0,0,170,131 -30,210,09,00,43,43,70,24,0,0,0,0,28,58,70,24,0,0,0,0,180,137 -31,210,18,30,43,47,75,25,0,0,0,0,24,66,75,25,0,0,0,0,190,143 +,inter_no,start_hour,start_minute,dura_A1,dura_A2,dura_A3,dura_A4,dura_A5,dura_A6,dura_A7,dura_A8,dura_B1,dura_B2,dura_B3,dura_B4,dura_B5,dura_B6,dura_B7,dura_B8,cycle,offset,yellow_A1,yellow_B1,yellow_A2,yellow_B2,yellow_A3,yellow_B3,yellow_A4,yellow_B4,yellow_A5,yellow_B5,yellow_A6,yellow_B6,yellow_A7,yellow_B7,yellow_A8,yellow_B8,red_A1,red_B1,red_A2,red_B2,red_A3,red_B3,red_A4,red_B4,red_A5,red_B5,red_A6,red_B6,red_A7,red_B7,red_A8,red_B8 +0,175,00,00,37,39,55,29,0,0,0,0,37,39,25,59,0,0,0,0,160,57,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1 +1,175,07,00,40,42,55,33,0,0,0,0,40,42,29,59,0,0,0,0,170,40,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1 +2,175,09,00,43,45,55,37,0,0,0,0,43,45,33,59,0,0,0,0,180,28,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1 +3,175,18,30,46,48,55,41,0,0,0,0,46,48,37,59,0,0,0,0,190,18,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1 +4,176,00,00,37,73,40,0,0,0,0,0,37,73,40,0,0,0,0,0,150,131,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1 +5,176,07,00,37,93,40,0,0,0,0,0,37,93,40,0,0,0,0,0,170,153,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1 +6,176,09,00,37,103,40,0,0,0,0,0,37,103,40,0,0,0,0,0,180,169,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1 +7,176,18,30,37,113,40,0,0,0,0,0,37,113,40,0,0,0,0,0,190,185,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1 +8,177,00,00,36,20,68,26,0,0,0,0,36,20,68,26,0,0,0,0,150,35,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1 +9,177,07,00,40,25,71,34,0,0,0,0,40,25,71,34,0,0,0,0,170,33,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1 +10,177,09,00,43,27,70,40,0,0,0,0,43,27,70,40,0,0,0,0,180,41,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1 +11,177,18,30,45,32,77,36,0,0,0,0,45,32,77,36,0,0,0,0,190,49,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1 +12,178,00,00,38,39,40,23,0,0,0,0,38,39,40,23,0,0,0,0,140,50,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 +13,178,07,00,38,39,42,41,0,0,0,0,38,39,62,21,0,0,0,0,160,90,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 +14,178,09,00,38,39,43,50,0,0,0,0,38,39,71,22,0,0,0,0,170,80,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 +15,178,18,30,38,39,44,59,0,0,0,0,38,39,80,23,0,0,0,0,180,75,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 +16,201,00,00,24,24,17,58,17,0,0,0,24,24,17,58,17,0,0,0,140,133,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 +17,201,07,00,30,36,18,58,18,0,0,0,30,36,18,58,18,0,0,0,160,132,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 +18,201,09,00,33,36,25,58,18,0,0,0,33,36,25,58,18,0,0,0,170,134,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 +19,201,18,30,36,50,18,58,18,0,0,0,36,50,18,58,18,0,0,0,180,137,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 +20,202,00,00,39,101,0,0,0,0,0,0,39,101,0,0,0,0,0,0,140,103,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1 +21,202,07,00,46,114,0,0,0,0,0,0,46,114,0,0,0,0,0,0,160,103,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1 +22,202,09,00,46,114,0,0,0,0,0,0,46,114,0,0,0,0,0,0,160,103,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1 +23,202,18,30,48,122,0,0,0,0,0,0,48,122,0,0,0,0,0,0,170,103,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1 +24,206,00,00,33,35,26,26,0,0,0,0,33,35,26,26,0,0,0,0,120,10,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1 +25,206,07,00,44,44,26,26,0,0,0,0,44,44,26,26,0,0,0,0,140,7,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1 +26,206,09,00,45,53,26,26,0,0,0,0,45,53,26,26,0,0,0,0,150,17,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1 +27,206,18,30,46,62,26,26,0,0,0,0,46,62,26,26,0,0,0,0,160,10,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1 +28,210,00,00,43,29,56,22,0,0,0,0,24,48,56,22,0,0,0,0,150,115,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 +29,210,07,00,43,39,65,23,0,0,0,0,24,58,65,23,0,0,0,0,170,131,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 +30,210,09,00,43,43,70,24,0,0,0,0,28,58,70,24,0,0,0,0,180,137,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 +31,210,18,30,43,47,75,25,0,0,0,0,24,66,75,25,0,0,0,0,190,143,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 diff --git a/Data/tables/raw_tables/0116_make_sample_table.ipynb b/Data/tables/raw_tables/0116_make_sample_table.ipynb index 8fd16a5d2..7f30e8d47 100644 --- a/Data/tables/raw_tables/0116_make_sample_table.ipynb +++ b/Data/tables/raw_tables/0116_make_sample_table.ipynb @@ -501,7 +501,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 75, "metadata": {}, "outputs": [ { @@ -535,7 +535,7 @@ " dura_A5\n", " dura_A6\n", " dura_A7\n", - " ...\n", + " dura_A8\n", " dura_B1\n", " dura_B2\n", " dura_B3\n", @@ -546,6 +546,38 @@ " dura_B8\n", " cycle\n", " offset\n", + " yellow_A1\n", + " yellow_B1\n", + " yellow_A2\n", + " yellow_B2\n", + " yellow_A3\n", + " yellow_B3\n", + " yellow_A4\n", + " yellow_B4\n", + " yellow_A5\n", + " yellow_B5\n", + " yellow_A6\n", + " yellow_B6\n", + " yellow_A7\n", + " yellow_B7\n", + " yellow_A8\n", + " yellow_B8\n", + " red_A1\n", + " red_B1\n", + " red_A2\n", + " red_B2\n", + " red_A3\n", + " red_B3\n", + " red_A4\n", + " red_B4\n", + " red_A5\n", + " red_B5\n", + " red_A6\n", + " red_B6\n", + " red_A7\n", + " red_B7\n", + " red_A8\n", + " red_B8\n", " \n", " \n", " \n", @@ -561,7 +593,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 37\n", " 39\n", " 25\n", @@ -572,6 +604,38 @@ " 0\n", " 160\n", " 57\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", " \n", " \n", " 1\n", @@ -585,7 +649,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 40\n", " 42\n", " 29\n", @@ -596,6 +660,38 @@ " 0\n", " 170\n", " 40\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", " \n", " \n", " 2\n", @@ -609,7 +705,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 43\n", " 45\n", " 33\n", @@ -620,6 +716,38 @@ " 0\n", " 180\n", " 28\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", " \n", " \n", " 3\n", @@ -633,7 +761,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 46\n", " 48\n", " 37\n", @@ -644,6 +772,38 @@ " 0\n", " 190\n", " 18\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", " \n", " \n", " 4\n", @@ -657,7 +817,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 37\n", " 73\n", " 40\n", @@ -668,6 +828,38 @@ " 0\n", " 150\n", " 131\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", " \n", " \n", " 5\n", @@ -681,7 +873,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 37\n", " 93\n", " 40\n", @@ -692,6 +884,38 @@ " 0\n", " 170\n", " 153\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", " \n", " \n", " 6\n", @@ -705,7 +929,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 37\n", " 103\n", " 40\n", @@ -716,6 +940,38 @@ " 0\n", " 180\n", " 169\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", " \n", " \n", " 7\n", @@ -729,7 +985,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 37\n", " 113\n", " 40\n", @@ -740,6 +996,38 @@ " 0\n", " 190\n", " 185\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", " \n", " \n", " 8\n", @@ -753,7 +1041,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 36\n", " 20\n", " 68\n", @@ -764,6 +1052,38 @@ " 0\n", " 150\n", " 35\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", " \n", " \n", " 9\n", @@ -777,7 +1097,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 40\n", " 25\n", " 71\n", @@ -788,6 +1108,38 @@ " 0\n", " 170\n", " 33\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", " \n", " \n", " 10\n", @@ -801,7 +1153,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 43\n", " 27\n", " 70\n", @@ -812,6 +1164,38 @@ " 0\n", " 180\n", " 41\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", " \n", " \n", " 11\n", @@ -825,7 +1209,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 45\n", " 32\n", " 77\n", @@ -836,6 +1220,38 @@ " 0\n", " 190\n", " 49\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", " \n", " \n", " 12\n", @@ -849,7 +1265,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 38\n", " 39\n", " 40\n", @@ -860,6 +1276,38 @@ " 0\n", " 140\n", " 50\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", " \n", " \n", " 13\n", @@ -873,7 +1321,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 38\n", " 39\n", " 62\n", @@ -884,6 +1332,38 @@ " 0\n", " 160\n", " 90\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", " \n", " \n", " 14\n", @@ -897,7 +1377,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 38\n", " 39\n", " 71\n", @@ -908,6 +1388,38 @@ " 0\n", " 170\n", " 80\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", " \n", " \n", " 15\n", @@ -921,7 +1433,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 38\n", " 39\n", " 80\n", @@ -932,6 +1444,38 @@ " 0\n", " 180\n", " 75\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", " \n", " \n", " 16\n", @@ -945,7 +1489,7 @@ " 17\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 24\n", " 24\n", " 17\n", @@ -956,6 +1500,38 @@ " 0\n", " 140\n", " 133\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", " \n", " \n", " 17\n", @@ -969,7 +1545,7 @@ " 18\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 30\n", " 36\n", " 18\n", @@ -980,6 +1556,38 @@ " 0\n", " 160\n", " 132\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", " \n", " \n", " 18\n", @@ -993,7 +1601,7 @@ " 18\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 33\n", " 36\n", " 25\n", @@ -1004,6 +1612,38 @@ " 0\n", " 170\n", " 134\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", " \n", " \n", " 19\n", @@ -1017,7 +1657,7 @@ " 18\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 36\n", " 50\n", " 18\n", @@ -1028,6 +1668,38 @@ " 0\n", " 180\n", " 137\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 3\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", " \n", " \n", " 20\n", @@ -1041,7 +1713,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 39\n", " 101\n", " 0\n", @@ -1052,6 +1724,38 @@ " 0\n", " 140\n", " 103\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", " \n", " \n", " 21\n", @@ -1065,7 +1769,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 46\n", " 114\n", " 0\n", @@ -1076,6 +1780,38 @@ " 0\n", " 160\n", " 103\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", " \n", " \n", " 22\n", @@ -1089,7 +1825,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 46\n", " 114\n", " 0\n", @@ -1100,6 +1836,38 @@ " 0\n", " 160\n", " 103\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", " \n", " \n", " 23\n", @@ -1113,7 +1881,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 48\n", " 122\n", " 0\n", @@ -1124,6 +1892,38 @@ " 0\n", " 170\n", " 103\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", " \n", " \n", " 24\n", @@ -1137,7 +1937,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 33\n", " 35\n", " 26\n", @@ -1148,6 +1948,38 @@ " 0\n", " 120\n", " 10\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", " \n", " \n", " 25\n", @@ -1161,7 +1993,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 44\n", " 44\n", " 26\n", @@ -1172,6 +2004,38 @@ " 0\n", " 140\n", " 7\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", " \n", " \n", " 26\n", @@ -1185,7 +2049,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 45\n", " 53\n", " 26\n", @@ -1196,6 +2060,38 @@ " 0\n", " 150\n", " 17\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", " \n", " \n", " 27\n", @@ -1209,7 +2105,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 46\n", " 62\n", " 26\n", @@ -1220,6 +2116,38 @@ " 0\n", " 160\n", " 10\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", " \n", " \n", " 28\n", @@ -1233,7 +2161,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 24\n", " 48\n", " 56\n", @@ -1244,6 +2172,38 @@ " 0\n", " 150\n", " 115\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", " \n", " \n", " 29\n", @@ -1257,7 +2217,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 24\n", " 58\n", " 65\n", @@ -1268,6 +2228,38 @@ " 0\n", " 170\n", " 131\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", " \n", " \n", " 30\n", @@ -1281,7 +2273,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 28\n", " 58\n", " 70\n", @@ -1292,6 +2284,38 @@ " 0\n", " 180\n", " 137\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", " \n", " \n", " 31\n", @@ -1305,7 +2329,7 @@ " 0\n", " 0\n", " 0\n", - " ...\n", + " 0\n", " 24\n", " 66\n", " 75\n", @@ -1316,10 +2340,41 @@ " 0\n", " 190\n", " 143\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 4\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", + " 2\n", " \n", " \n", "\n", - "

32 rows Γ— 21 columns

\n", "" ], "text/plain": [ @@ -1357,75 +2412,243 @@ "30 210 09 00 43 43 70 24 \n", "31 210 18 30 43 47 75 25 \n", "\n", - " dura_A5 dura_A6 dura_A7 ... dura_B1 dura_B2 dura_B3 dura_B4 \\\n", - "0 0 0 0 ... 37 39 25 59 \n", - "1 0 0 0 ... 40 42 29 59 \n", - "2 0 0 0 ... 43 45 33 59 \n", - "3 0 0 0 ... 46 48 37 59 \n", - "4 0 0 0 ... 37 73 40 0 \n", - "5 0 0 0 ... 37 93 40 0 \n", - "6 0 0 0 ... 37 103 40 0 \n", - "7 0 0 0 ... 37 113 40 0 \n", - "8 0 0 0 ... 36 20 68 26 \n", - "9 0 0 0 ... 40 25 71 34 \n", - "10 0 0 0 ... 43 27 70 40 \n", - "11 0 0 0 ... 45 32 77 36 \n", - "12 0 0 0 ... 38 39 40 23 \n", - "13 0 0 0 ... 38 39 62 21 \n", - "14 0 0 0 ... 38 39 71 22 \n", - "15 0 0 0 ... 38 39 80 23 \n", - "16 17 0 0 ... 24 24 17 58 \n", - "17 18 0 0 ... 30 36 18 58 \n", - "18 18 0 0 ... 33 36 25 58 \n", - "19 18 0 0 ... 36 50 18 58 \n", - "20 0 0 0 ... 39 101 0 0 \n", - "21 0 0 0 ... 46 114 0 0 \n", - "22 0 0 0 ... 46 114 0 0 \n", - "23 0 0 0 ... 48 122 0 0 \n", - "24 0 0 0 ... 33 35 26 26 \n", - "25 0 0 0 ... 44 44 26 26 \n", - "26 0 0 0 ... 45 53 26 26 \n", - "27 0 0 0 ... 46 62 26 26 \n", - "28 0 0 0 ... 24 48 56 22 \n", - "29 0 0 0 ... 24 58 65 23 \n", - "30 0 0 0 ... 28 58 70 24 \n", - "31 0 0 0 ... 24 66 75 25 \n", + " dura_A5 dura_A6 dura_A7 dura_A8 dura_B1 dura_B2 dura_B3 dura_B4 \\\n", + "0 0 0 0 0 37 39 25 59 \n", + "1 0 0 0 0 40 42 29 59 \n", + "2 0 0 0 0 43 45 33 59 \n", + "3 0 0 0 0 46 48 37 59 \n", + "4 0 0 0 0 37 73 40 0 \n", + "5 0 0 0 0 37 93 40 0 \n", + "6 0 0 0 0 37 103 40 0 \n", + "7 0 0 0 0 37 113 40 0 \n", + "8 0 0 0 0 36 20 68 26 \n", + "9 0 0 0 0 40 25 71 34 \n", + "10 0 0 0 0 43 27 70 40 \n", + "11 0 0 0 0 45 32 77 36 \n", + "12 0 0 0 0 38 39 40 23 \n", + "13 0 0 0 0 38 39 62 21 \n", + "14 0 0 0 0 38 39 71 22 \n", + "15 0 0 0 0 38 39 80 23 \n", + "16 17 0 0 0 24 24 17 58 \n", + "17 18 0 0 0 30 36 18 58 \n", + "18 18 0 0 0 33 36 25 58 \n", + "19 18 0 0 0 36 50 18 58 \n", + "20 0 0 0 0 39 101 0 0 \n", + "21 0 0 0 0 46 114 0 0 \n", + "22 0 0 0 0 46 114 0 0 \n", + "23 0 0 0 0 48 122 0 0 \n", + "24 0 0 0 0 33 35 26 26 \n", + "25 0 0 0 0 44 44 26 26 \n", + "26 0 0 0 0 45 53 26 26 \n", + "27 0 0 0 0 46 62 26 26 \n", + "28 0 0 0 0 24 48 56 22 \n", + "29 0 0 0 0 24 58 65 23 \n", + "30 0 0 0 0 28 58 70 24 \n", + "31 0 0 0 0 24 66 75 25 \n", + "\n", + " dura_B5 dura_B6 dura_B7 dura_B8 cycle offset yellow_A1 yellow_B1 \\\n", + "0 0 0 0 0 160 57 4 4 \n", + "1 0 0 0 0 170 40 4 4 \n", + "2 0 0 0 0 180 28 4 4 \n", + "3 0 0 0 0 190 18 4 4 \n", + "4 0 0 0 0 150 131 4 4 \n", + "5 0 0 0 0 170 153 4 4 \n", + "6 0 0 0 0 180 169 4 4 \n", + "7 0 0 0 0 190 185 4 4 \n", + "8 0 0 0 0 150 35 4 4 \n", + "9 0 0 0 0 170 33 4 4 \n", + "10 0 0 0 0 180 41 4 4 \n", + "11 0 0 0 0 190 49 4 4 \n", + "12 0 0 0 0 140 50 4 4 \n", + "13 0 0 0 0 160 90 4 4 \n", + "14 0 0 0 0 170 80 4 4 \n", + "15 0 0 0 0 180 75 4 4 \n", + "16 17 0 0 0 140 133 3 3 \n", + "17 18 0 0 0 160 132 3 3 \n", + "18 18 0 0 0 170 134 3 3 \n", + "19 18 0 0 0 180 137 3 3 \n", + "20 0 0 0 0 140 103 4 4 \n", + "21 0 0 0 0 160 103 4 4 \n", + "22 0 0 0 0 160 103 4 4 \n", + "23 0 0 0 0 170 103 4 4 \n", + "24 0 0 0 0 120 10 4 4 \n", + "25 0 0 0 0 140 7 4 4 \n", + "26 0 0 0 0 150 17 4 4 \n", + "27 0 0 0 0 160 10 4 4 \n", + "28 0 0 0 0 150 115 4 4 \n", + "29 0 0 0 0 170 131 4 4 \n", + "30 0 0 0 0 180 137 4 4 \n", + "31 0 0 0 0 190 143 4 4 \n", + "\n", + " yellow_A2 yellow_B2 yellow_A3 yellow_B3 yellow_A4 yellow_B4 \\\n", + "0 4 4 4 4 4 4 \n", + "1 4 4 4 4 4 4 \n", + "2 4 4 4 4 4 4 \n", + "3 4 4 4 4 4 4 \n", + "4 4 4 4 4 4 4 \n", + "5 4 4 4 4 4 4 \n", + "6 4 4 4 4 4 4 \n", + "7 4 4 4 4 4 4 \n", + "8 4 4 4 4 4 4 \n", + "9 4 4 4 4 4 4 \n", + "10 4 4 4 4 4 4 \n", + "11 4 4 4 4 4 4 \n", + "12 4 4 4 4 4 4 \n", + "13 4 4 4 4 4 4 \n", + "14 4 4 4 4 4 4 \n", + "15 4 4 4 4 4 4 \n", + "16 3 3 3 3 3 3 \n", + "17 3 3 3 3 3 3 \n", + "18 3 3 3 3 3 3 \n", + "19 3 3 3 3 3 3 \n", + "20 4 4 4 4 4 4 \n", + "21 4 4 4 4 4 4 \n", + "22 4 4 4 4 4 4 \n", + "23 4 4 4 4 4 4 \n", + "24 4 4 4 4 4 4 \n", + "25 4 4 4 4 4 4 \n", + "26 4 4 4 4 4 4 \n", + "27 4 4 4 4 4 4 \n", + "28 4 4 4 4 4 4 \n", + "29 4 4 4 4 4 4 \n", + "30 4 4 4 4 4 4 \n", + "31 4 4 4 4 4 4 \n", + "\n", + " yellow_A5 yellow_B5 yellow_A6 yellow_B6 yellow_A7 yellow_B7 \\\n", + "0 4 4 4 4 4 4 \n", + "1 4 4 4 4 4 4 \n", + "2 4 4 4 4 4 4 \n", + "3 4 4 4 4 4 4 \n", + "4 4 4 4 4 4 4 \n", + "5 4 4 4 4 4 4 \n", + "6 4 4 4 4 4 4 \n", + "7 4 4 4 4 4 4 \n", + "8 4 4 4 4 4 4 \n", + "9 4 4 4 4 4 4 \n", + "10 4 4 4 4 4 4 \n", + "11 4 4 4 4 4 4 \n", + "12 4 4 4 4 4 4 \n", + "13 4 4 4 4 4 4 \n", + "14 4 4 4 4 4 4 \n", + "15 4 4 4 4 4 4 \n", + "16 3 3 3 3 3 3 \n", + "17 3 3 3 3 3 3 \n", + "18 3 3 3 3 3 3 \n", + "19 3 3 3 3 3 3 \n", + "20 4 4 4 4 4 4 \n", + "21 4 4 4 4 4 4 \n", + "22 4 4 4 4 4 4 \n", + "23 4 4 4 4 4 4 \n", + "24 4 4 4 4 4 4 \n", + "25 4 4 4 4 4 4 \n", + "26 4 4 4 4 4 4 \n", + "27 4 4 4 4 4 4 \n", + "28 4 4 4 4 4 4 \n", + "29 4 4 4 4 4 4 \n", + "30 4 4 4 4 4 4 \n", + "31 4 4 4 4 4 4 \n", "\n", - " dura_B5 dura_B6 dura_B7 dura_B8 cycle offset \n", - "0 0 0 0 0 160 57 \n", - "1 0 0 0 0 170 40 \n", - "2 0 0 0 0 180 28 \n", - "3 0 0 0 0 190 18 \n", - "4 0 0 0 0 150 131 \n", - "5 0 0 0 0 170 153 \n", - "6 0 0 0 0 180 169 \n", - "7 0 0 0 0 190 185 \n", - "8 0 0 0 0 150 35 \n", - "9 0 0 0 0 170 33 \n", - "10 0 0 0 0 180 41 \n", - "11 0 0 0 0 190 49 \n", - "12 0 0 0 0 140 50 \n", - "13 0 0 0 0 160 90 \n", - "14 0 0 0 0 170 80 \n", - "15 0 0 0 0 180 75 \n", - "16 17 0 0 0 140 133 \n", - "17 18 0 0 0 160 132 \n", - "18 18 0 0 0 170 134 \n", - "19 18 0 0 0 180 137 \n", - "20 0 0 0 0 140 103 \n", - "21 0 0 0 0 160 103 \n", - "22 0 0 0 0 160 103 \n", - "23 0 0 0 0 170 103 \n", - "24 0 0 0 0 120 10 \n", - "25 0 0 0 0 140 7 \n", - "26 0 0 0 0 150 17 \n", - "27 0 0 0 0 160 10 \n", - "28 0 0 0 0 150 115 \n", - "29 0 0 0 0 170 131 \n", - "30 0 0 0 0 180 137 \n", - "31 0 0 0 0 190 143 \n", + " yellow_A8 yellow_B8 red_A1 red_B1 red_A2 red_B2 red_A3 red_B3 \\\n", + "0 4 4 1 1 1 1 1 1 \n", + "1 4 4 1 1 1 1 1 1 \n", + "2 4 4 1 1 1 1 1 1 \n", + "3 4 4 1 1 1 1 1 1 \n", + "4 4 4 1 1 1 1 1 1 \n", + "5 4 4 1 1 1 1 1 1 \n", + "6 4 4 1 1 1 1 1 1 \n", + "7 4 4 1 1 1 1 1 1 \n", + "8 4 4 1 1 1 1 1 1 \n", + "9 4 4 1 1 1 1 1 1 \n", + "10 4 4 1 1 1 1 1 1 \n", + "11 4 4 1 1 1 1 1 1 \n", + "12 4 4 2 2 2 2 2 2 \n", + "13 4 4 2 2 2 2 2 2 \n", + "14 4 4 2 2 2 2 2 2 \n", + "15 4 4 2 2 2 2 2 2 \n", + "16 3 3 2 2 2 2 2 2 \n", + "17 3 3 2 2 2 2 2 2 \n", + "18 3 3 2 2 2 2 2 2 \n", + "19 3 3 2 2 2 2 2 2 \n", + "20 4 4 1 1 1 1 1 1 \n", + "21 4 4 1 1 1 1 1 1 \n", + "22 4 4 1 1 1 1 1 1 \n", + "23 4 4 1 1 1 1 1 1 \n", + "24 4 4 1 1 1 1 1 1 \n", + "25 4 4 1 1 1 1 1 1 \n", + "26 4 4 1 1 1 1 1 1 \n", + "27 4 4 1 1 1 1 1 1 \n", + "28 4 4 2 2 2 2 2 2 \n", + "29 4 4 2 2 2 2 2 2 \n", + "30 4 4 2 2 2 2 2 2 \n", + "31 4 4 2 2 2 2 2 2 \n", "\n", - "[32 rows x 21 columns]" + " red_A4 red_B4 red_A5 red_B5 red_A6 red_B6 red_A7 red_B7 red_A8 \\\n", + "0 1 1 1 1 1 1 1 1 1 \n", + "1 1 1 1 1 1 1 1 1 1 \n", + "2 1 1 1 1 1 1 1 1 1 \n", + "3 1 1 1 1 1 1 1 1 1 \n", + "4 1 1 1 1 1 1 1 1 1 \n", + "5 1 1 1 1 1 1 1 1 1 \n", + "6 1 1 1 1 1 1 1 1 1 \n", + "7 1 1 1 1 1 1 1 1 1 \n", + "8 1 1 1 1 1 1 1 1 1 \n", + "9 1 1 1 1 1 1 1 1 1 \n", + "10 1 1 1 1 1 1 1 1 1 \n", + "11 1 1 1 1 1 1 1 1 1 \n", + "12 2 2 2 2 2 2 2 2 2 \n", + "13 2 2 2 2 2 2 2 2 2 \n", + "14 2 2 2 2 2 2 2 2 2 \n", + "15 2 2 2 2 2 2 2 2 2 \n", + "16 2 2 2 2 2 2 2 2 2 \n", + "17 2 2 2 2 2 2 2 2 2 \n", + "18 2 2 2 2 2 2 2 2 2 \n", + "19 2 2 2 2 2 2 2 2 2 \n", + "20 1 1 1 1 1 1 1 1 1 \n", + "21 1 1 1 1 1 1 1 1 1 \n", + "22 1 1 1 1 1 1 1 1 1 \n", + "23 1 1 1 1 1 1 1 1 1 \n", + "24 1 1 1 1 1 1 1 1 1 \n", + "25 1 1 1 1 1 1 1 1 1 \n", + "26 1 1 1 1 1 1 1 1 1 \n", + "27 1 1 1 1 1 1 1 1 1 \n", + "28 2 2 2 2 2 2 2 2 2 \n", + "29 2 2 2 2 2 2 2 2 2 \n", + "30 2 2 2 2 2 2 2 2 2 \n", + "31 2 2 2 2 2 2 2 2 2 \n", + "\n", + " red_B8 \n", + "0 1 \n", + "1 1 \n", + "2 1 \n", + "3 1 \n", + "4 1 \n", + "5 1 \n", + "6 1 \n", + "7 1 \n", + "8 1 \n", + "9 1 \n", + "10 1 \n", + "11 1 \n", + "12 2 \n", + "13 2 \n", + "14 2 \n", + "15 2 \n", + "16 2 \n", + "17 2 \n", + "18 2 \n", + "19 2 \n", + "20 1 \n", + "21 1 \n", + "22 1 \n", + "23 1 \n", + "24 1 \n", + "25 1 \n", + "26 1 \n", + "27 1 \n", + "28 2 \n", + "29 2 \n", + "30 2 \n", + "31 2 " ] }, "metadata": {}, @@ -1449,6 +2672,23 @@ " 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", + "yellow_columns = [f'yellow_{ring}{phase}' for phase in range(1, 9) for ring in ['A', 'B']]\n", + "red_columns = [f'red_{ring}{phase}' for phase in range(1, 9) for ring in ['A', 'B']]\n", + "\n", + "inter_nos = plan.inter_no.unique()\n", + "yellow_list = np.random.choice([3, 4, 5], size=plan.inter_no.nunique(), p=[0.1, 0.7, 0.2])\n", + "inter2yellow = dict(zip(inter_nos, yellow_list))\n", + "red_list = np.random.choice([0, 1, 2], size=plan.inter_no.nunique(), p=[0.1, 0.7, 0.2])\n", + "inter2red = dict(zip(inter_nos, red_list))\n", + "\n", + "for phase in range(1, 9):\n", + " for ring in ['A', 'B']:\n", + " plan[f'yellow_{ring}{phase}'] = plan['inter_no'].map(inter2yellow)\n", + "for phase in range(1, 9):\n", + " for ring in ['A', 'B']:\n", + " plan[f'red_{ring}{phase}'] = plan['inter_no'].map(inter2red)\n", + "\n", "plan.to_csv('../plan.csv')\n", "pland = plan.copy()\n", "cums_A = np.array(pland[[f'dura_A{k}' for k in range(1,9)]].cumsum(axis=1))\n", @@ -1465,7 +2705,8 @@ " i+=1\n", "pland = pland[['inter_no', 'start_hour', 'start_minute'] + [f'ddur_{i}' for i in range(1,9)] + ['cycle', 'offset']] # plan detailed\n", "pland[[f'ddur_{i}' for i in range(1,9)]] = pland[[f'ddur_{i}' for i in range(1,9)]].astype(int)\n", - "display(plan)\n", + "with pd.option_context('display.max_rows', None, 'display.max_columns', None):\n", + " display(plan)\n", "# pland.to_csv('../pland.csv')\n", "# display(pland)" ] @@ -3265,9 +4506,9 @@ ], "metadata": { "kernelspec": { - "display_name": "rts", + "display_name": "sts", "language": "python", - "name": "python3" + "name": "sts" }, "language_info": { "codemirror_mode": { diff --git a/Documents/0116_header_unix.txt b/Documents/0116_header_unix.txt new file mode 100644 index 000000000..73166ac22 --- /dev/null +++ b/Documents/0116_header_unix.txt @@ -0,0 +1,8 @@ +김선쀑 λŒ€λ¦¬ 동뢀ICTμ—μ„œ ꡐ차둜 주기정보(주기별 ν˜„μ‹œλ³„ λ…Ήμƒ‰μ‹œκ°„) μ „μ†‘μ‹œ header에 μ‹œκ°„μ •λ³΄κ°€ μžˆμ–΄μ„œ ν•΄λ‹Ή 정보λ₯Ό +주기의 μ’…λ£Œμ‹œκ°„μœΌλ‘œ ν™œμš©ν•΄λ„ λ˜λŠ”μ§€ λ¬Έμ˜ν•˜μ˜€κ³  μ•„λž˜λ‚΄μš©μ€ νšŒμ‹ λ°›μ€ λ‚΄μš©μž…λ‹ˆλ‹€. μ°Έκ³ ν•˜μ„Έμš” +1) 메세지 headerμ—μ„œ μ œκ³΅ν•˜λŠ” time은 μ‹ ν˜Έμ œμ–΄μ„œλ²„μ˜ 정보 제곡 μ‹œμ μ˜ μ‹œκ°μž…λ‹ˆλ‹€. +2) μ‹ ν˜Έμ œμ–΄κΈ°μ—μ„œ μ£ΌκΈ°κ°€ μ’…λ£Œλ˜λ©΄, μš΄μ˜ν–ˆλ˜ SPLIT을 μ‹ ν˜Έμ œμ–΄μ„œλ²„λ‘œ μ „μ†‘ν•˜κ³  + μ‹ ν˜Έμ œμ–΄μ„œλ²„λŠ” 데이터λ₯Ό 큐에 μ €μž₯ν•œ λ‹€μŒ 1~2초 κ°„κ²©μœΌλ‘œ λ¬Άμ–΄μ„œ μ™ΈλΆ€ μ„œλ²„μ— μ œκ³΅ν•  μ˜ˆμ •μž…λ‹ˆλ‹€. +3) 이런 경우 μ™ΈλΆ€ μ„œλ²„μ— SPLIT 정보 전솑 지연이 μ΅œμ†Œ 1~2초둜 μ˜ˆμƒλ©λ‹ˆλ‹€. +4) λ”°λΌμ„œ μš”μ²­μ„ κ³ λ €ν•˜μ—¬ 전솑 간격을 1초둜 ν•˜λ©΄, 전솑 지연을 μ΅œμ†Œν™” ν•  수 μžˆμŠ΅λ‹ˆλ‹€. +김선쀑 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b/Results/sn_1704416700.add.xml index 6ec8852c0..e9fb412ec 100644 --- a/Results/sn_1704416700.add.xml +++ b/Results/sn_1704416700.add.xml @@ -1,8 +1,8 @@ - - - + + + @@ -10,11 +10,11 @@ - - - - - + + + + + @@ -22,11 +22,11 @@ - - - - - + + + + + @@ -34,11 +34,11 @@ - - - - - + + + + + @@ -48,241 +48,241 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + @@ -333,64 +333,64 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + @@ -462,52 +462,52 @@ - - - - - - + + + + + + - - - - - - - - - - - + + + + + + + + + + + - - - - - - - - - - - + + + + + + + + + + + - - - - - - - - - - - + + + + + + + + + + + - - - + + + diff --git a/Scripts/__pycache__/generate_signals.cpython-38.pyc b/Scripts/__pycache__/generate_signals.cpython-38.pyc index adbcc7a9a3e8ee714281d0b56038468a2d4426d9..2ba44d8bbdf4da3ce8ae370c3ab6aa4c7c716020 100644 GIT binary patch delta 7937 zcma)B3v?9Md7e8vyF2^T>b<;#gm^8MZ4fVG1OgfJjtT}FJhn5ec1F@jyR*xk5g@Y4 zriG?)PueoJ#FJ8b^rgL 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mapping_dict[(node_id, move_A)] else: state_A = ''.join(self.node2init[node_id]) - # self.histid.at[i, 'state_A'] = state_A # B링의 state 지정 if (node_id, move_B) in mapping_dict: state_B = mapping_dict[(node_id, move_B)] else: state_B = ''.join(self.node2init[node_id]) - # self.histid.at[i, 'state_B'] = state_B # ν†΅ν•©λœ state 지정 state = '' diff --git a/Scripts/generate_signals_until_4-1.py b/Scripts/generate_signals_until_4-1.py deleted file mode 100644 index 7ef3fb5c4..000000000 --- a/Scripts/generate_signals_until_4-1.py +++ /dev/null @@ -1,876 +0,0 @@ -# python .\Scripts\generate_signals.py -import pandas as pd -import numpy as np -import os, sys -import json -import copy -from tqdm import tqdm -import sumolib, traci -from datetime import datetime -import time - -class SignalGenerator(): - def __init__(self): - # λ£¨νŠΈν΄λ” 지정 - self.path_root = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) - with open(os.path.join(self.path_root, 'Scripts', 'config.json'), 'r') as config_file: - config = json.load(config_file) - # μ£Όμš” 폴더 경둜 지정 - self.paths = config['paths'] - self.path_data = os.path.join(self.path_root, *self.paths['data']) - self.path_intermediates = os.path.join(self.path_root, *self.paths['intermediates']) - self.path_results = os.path.join(self.path_root, *self.paths['results']) - self.path_tables = os.path.join(self.path_root, *self.paths['tables']) - self.path_networks = os.path.join(self.path_root, *self.paths['networks']) - self.path_scripts = os.path.join(self.path_root, *self.paths['scripts']) - # μ΄μŠˆμ‚¬ν•­ λͺ©λ‘ - self.issues = [] - - self.midnight = int(datetime(2024, 1, 5, 0, 0, 0).timestamp()) - self.next_day = int(datetime(2024, 1, 6, 0, 0, 0).timestamp()) - self.fsecs = range(self.midnight, self.next_day, 5) # fsecs : unix time by Five SECondS - self.fmins = range(self.midnight, self.next_day, 300) # fmins : unix time by Five MINuteS - - self.present_time = datetime.now().replace(month=1, day=5, hour=10).timestamp() - self.present_time = max([fmin for fmin in list(self.fmins) if fmin <= self.present_time]) - - self.adder = 600 # 10λΆ„ : 'ν˜„μž¬μ‹œμ  + 10λΆ„'에 κ°€μƒμ‹ ν˜Έλ₯Ό μƒμ„±ν•˜κΈ° μœ„ν•¨. - self.subtractor = 1800 # 30λΆ„ : 'ν˜„μž¬μ‹œμ  - 30λΆ„'의 μ‹ ν˜Έμ΄λ ₯을 κ°€μ Έμ˜¨λ‹€. - - # 1. 데이터 μ€€λΉ„ - def prepare_data(self): - print("1. 데이터λ₯Ό μ€€λΉ„ν•©λ‹ˆλ‹€.") - self.load_networks() - self.time11 = datetime.now() - self.load_tables() - self.time12 = datetime.now() - # self.check_networks() - self.time13 = datetime.now() - # self.check_tables() - self.time14 = datetime.now() - self.prepare_auxiliaries() - self.time15 = datetime.now() - - # 1-1. λ„€νŠΈμ›Œν¬ 뢈러였기 - def load_networks(self): - self.net = sumolib.net.readNet(os.path.join(self.path_networks, 'sn.net.xml')) - print("1-1. λ„€νŠΈμ›Œν¬κ°€ λ‘œλ“œλ˜μ—ˆμŠ΅λ‹ˆλ‹€.") - - # 1-2. ν…Œμ΄λΈ” 뢈러였기 - def load_tables(self): - # λͺ¨λ“  μ»¬λŸΌμ— λŒ€ν•˜μ—¬ λ°μ΄ν„°νƒ€μž… 지정 - loading_dtype = { - 'inter_no':'int', 'start_hour':'int', 'start_minute':'int', 'cycle':'int','offset':'int', - 'node_id':'str', 'inter_type':'str', 'parent_id':'str','child_id':'str', - 'direction':'str', 'condition':'str', 'inc_edge':'str', 'out_edge':'str', - 'end_unix':'int', 'inter_name':'str', 'inter_lat':'float', 'inter_lon':'float', - 'group_no':'int', 'main_phase_no':'int', 'phase_no':'int','ring_type':'str' - } - for alph in ['A', 'B']: - for j in range(1,9): - loading_dtype[f'angle_{alph}{j}'] = 'str' - loading_dtype[f'dura_{alph}{j}'] = 'int' - - # ν…Œμ΄λΈ” 뢈러였기 - self.inter_info = pd.read_csv(os.path.join(self.path_tables, 'inter_info.csv'), dtype=loading_dtype) - self.plan = pd.read_csv(os.path.join(self.path_tables, 'plan.csv'), dtype=loading_dtype) - self.history = pd.read_csv(os.path.join(self.path_tables, 'history.csv'), dtype=loading_dtype).sort_values(by='end_unix') - self.inter_node = pd.read_csv(os.path.join(self.path_tables, 'inter_node.csv'), dtype=loading_dtype) - self.matching = pd.read_csv(os.path.join(self.path_intermediates, 'matching.csv'), dtype=loading_dtype) - self.match1 = pd.read_csv(os.path.join(self.path_intermediates, 'match1.csv'), dtype=loading_dtype) - self.match6 = pd.read_csv(os.path.join(self.path_intermediates, 'match6.csv'), dtype=loading_dtype) - self.match6 = self.match6[['node_id', 'phase_no', 'ring_type', 'inc_edge', 'out_edge']].reset_index(drop=True) - - self.plan_set = self.plan.set_index(['inter_no','start_hour','start_minute']) - - # ꡐ차둜λͺ©λ‘ μ •μ˜ - self.inter_nos = sorted(self.inter_info.inter_no.unique()) - print("1-2. ν…Œμ΄λΈ”λ“€μ΄ λ‘œλ“œλ˜μ—ˆμŠ΅λ‹ˆλ‹€.") - - # 1-3. λ„€νŠΈμ›Œν¬ 무결성 검사 - def check_networks(self): - # https://sumo.dlr.de/docs/Netedit/neteditUsageExamples.html#simplify_tls_program_state_after_changing_connections - if 'SUMO_HOME' in os.environ: - tools = os.path.join(os.environ['SUMO_HOME'], 'tools') - if tools not in sys.path: - sys.path.append(tools) - else: - raise EnvironmentError("please declare environment variable 'SUMO_HOME'") - traci.start([sumolib.checkBinary('sumo'), "-n", os.path.join(self.path_networks, 'sn.net.xml')]) - nodes = [node for node in self.net.getNodes() if node.getType()=='traffic_light'] - for node in nodes: - node_id = node.getID() - from_xml = len([c for c in node.getConnections() if c.getTLLinkIndex() >= 0]) - from_traci = len(traci.trafficlight.getRedYellowGreenState(node_id)) - if from_xml != from_traci: - sub = {'id': node_id, 'type': 'node', 'note': 'μœ νš¨ν•˜μ§€ μ•Šμ€ μ—°κ²°μ΄μžˆμŒ. neteditμ—μ„œ clean states ν•„μš”.'} - self.issues.append(sub) - traci.close() - print("1-3. λ„€νŠΈμ›Œν¬μ˜ λͺ¨λ“  clean state requirement듀을 μ²΄ν¬ν–ˆμŠ΅λ‹ˆλ‹€.") - - # 1-4. ν…Œμ΄λΈ” 무결성 검사 - def check_tables(self): - self.check_history() - # κ΅μ°¨λ‘œμ •λ³΄, λ°©μœ„κ°μ •λ³΄, μ‹ ν˜Έκ³„νšμ— λŒ€ν•΄μ„œλŠ” preprocess_daily.pyμ—μ„œ - # 무결성검사λ₯Ό μ™„λ£Œν–ˆμœΌλ―€λ‘œ μ—¬κΈ°μ—μ„œλŠ” λ”°λ‘œ κ²€μ‚¬ν•˜μ§€ μ•ŠμŒ. - # self.check_moves() # 이동λ₯˜λ²ˆν˜Έμ— λŒ€ν•œ 무결성검사 ν•„μš”ν•˜λ‚˜ 아직 μž‘μ„±ν•˜μ§€ μ•ŠμŒ. (24. 2. 5 ν™”) - print("1-4. ν…Œμ΄λΈ”λ“€μ˜ 무결성 검사λ₯Ό μ™„λ£Œν–ˆμŠ΅λ‹ˆλ‹€.") - - # 1-4-1. μ‹ ν˜Έμ΄λ ₯(history) 검사 - def check_history(self): - # 1-4-1-1. inter_no 검사 - # self.history.loc[0, 'inter_no'] = '4' # μ—λŸ¬ λ°œμƒμ„ μœ„ν•œ μ½”λ“œ - missing_inter_nos = set(self.history.inter_no) - set(self.inter_nos) - if missing_inter_nos: - msg = f"1-4-1-1. history의 inter_no 쀑 ꡐ차둜 λͺ©λ‘(inter_nos)에 ν¬ν•¨λ˜μ§€ μ•ŠλŠ” ν•­λͺ©μ΄ μžˆμŠ΅λ‹ˆλ‹€: {missing_inter_nos}" - self.issues.append(msg) - - # 1-4-1-2. μ’…λ£Œμœ λ‹‰μŠ€ 검사 - # self.history.loc[0, 'end_unix'] = 38.0 # μ—λŸ¬ λ°œμƒμ„ μœ„ν•œ μ½”λ“œ - self.min_unix, self.max_unix = int(datetime(2020, 1, 1).timestamp()), int(datetime(2038, 1, 1).timestamp()) - for row in self.history.itertuples(index=True): - unixbool = self.min_unix <= row['end_unix'] <= self.max_unix - if not unixbool: - msg = f"1-4-1-2. 적정 λ²”μœ„λ₯Ό λ²—μ–΄λ‚œ μœ λ‹‰μŠ€μ‹œκ°(end_unix)이 μ‘΄μž¬ν•©λ‹ˆλ‹€ : inter_no : {row['inter_no']}" - self.issues.append(msg) - - # 1-4-1-3. ν˜„μ‹œμ‹œκ°„ 검사 - # self.history.loc[0, 'dura_A1'] = -2 # μ—λŸ¬ λ°œμƒμ„ μœ„ν•œ μ½”λ“œ - durations = self.history[[f'dura_{alph}{j}' for alph in ['A','B'] for j in range(1, 9)]] - valid_indices = ((durations >= 0) & (durations <= 200)).all(axis=1) - invalid_inter_nos = sorted(self.history[~ valid_indices].inter_no.unique()) - if invalid_inter_nos: - msg = f"1-4-1-3. μŒμˆ˜μ΄κ±°λ‚˜ 200보닀 큰 ν˜„μ‹œμ‹œκ°„μ΄ μ‘΄μž¬ν•©λ‹ˆλ‹€. : {invalid_inter_nos}" - - # 1-5. 보쑰 λ”•μ…”λ„ˆλ¦¬, λ°μ΄ν„°ν”„λ ˆμž„, 리슀트 λ“± λ§Œλ“€κΈ° - def prepare_auxiliaries(self): - # inter2node : a dictionary that maps inter_no to the node_id - inter_node_p = self.inter_node[self.inter_node.inter_type=='parent'] - self.inter2node = dict(zip(inter_node_p['inter_no'], inter_node_p['node_id'])) - self.node2inter = dict(zip(self.inter_node['node_id'], self.inter_node['inter_no'])) - - # split, isplit : A,B 뢄리 ν˜Ήμ€ ν†΅ν•©μ‹œ μ‚¬μš©λ  수 μžˆλŠ” λ”•μ…”λ„ˆλ¦¬ - self.splits = {} # splits maps (inter_no, start_hour, start_minute) to split - for i, row in self.plan.iterrows(): - inter_no = row.inter_no - start_hour = row.start_hour - start_minute = row.start_minute - cycle = row.cycle - - dura_A = np.array(row[[f'dura_A{j}' for j in range(1, 9)]]) - dura_B = np.array(row[[f'dura_B{j}' for j in range(1, 9)]]) - - cums_A = dura_A.cumsum() - cums_B = dura_B.cumsum() - combined_row = np.unique(np.concatenate((cums_A,cums_B))) - detailed_durations = np.concatenate(([combined_row[0]], np.diff(combined_row))) - - self.splits[(inter_no, start_hour, start_minute)] = {} # split maps (phas_A, phas_B) to k - ja = 0 - jb = 0 - for k in range(len(detailed_durations)): - dura_A[ja] -= detailed_durations[k] - dura_B[jb] -= detailed_durations[k] - self.splits[(inter_no, start_hour, start_minute)][(ja+1, jb+1)] = k+1 - if dura_A[ja] == 0: - ja += 1 - if dura_B[jb] == 0: - jb += 1 - - self.isplits = {} # the inverse of splits - for i in self.splits: - self.isplits[i] = {self.splits[i][k]:k for k in self.splits[i]} # isplit maps k to (phas_A, phas_B) - - # timetable : κ΅μ°¨λ‘œλ³„ ν”„λ‘œκ·Έλž¨ μ‹œμž‘μ‹œκ° - self.timetable = self.plan[['start_hour', 'start_minute']].drop_duplicates() - self.timetable['start_seconds'] = self.midnight + self.timetable['start_hour'] * 3600 + self.timetable['start_minute'] * 60 - - # A dictionary that maps parent_id to a list of child_ids - self.pa2ch = {'i0':['u00'], 'i1':[], 'i2':['u20'], 'i3':['c30', 'u30', 'u31', 'u32'], 'i6':['u60'], 'i7':[], 'i8':[], 'i9':[]} - self.node_ids = sorted(self.inter_node.node_id.unique()) - self.parent_ids = sorted(self.inter_node[self.inter_node.inter_type=='parent'].node_id.unique()) - self.nodes = [self.net.getNode(node_id) for node_id in self.node_ids] - - # node2num_cycles : A dictionary that maps a node_id to the number of cycles - with open(os.path.join(self.path_intermediates, 'node2num_cycles.json'), 'r') as file: - # json.load() ν•¨μˆ˜λ₯Ό μ‚¬μš©ν•΄ 파일 λ‚΄μš©μ„ Python λ”•μ…”λ„ˆλ¦¬λ‘œ λΆˆλŸ¬μ˜΅λ‹ˆλ‹€. - self.node2num_cycles = json.load(file) - - # 2. μ‹ ν˜Έμ΄λ ₯ μ „μ²˜λ¦¬ - def process_history(self): - print("2. μ‹ ν˜Έμ΄λ ₯ ν…Œμ΄λΈ”μ„ λ³€ν™˜ν•©λ‹ˆλ‹€.") - self.make_rhistory() - self.time21 = datetime.now() - self.make_rhists() - self.time22 = datetime.now() - self.make_hrhists() - self.time23 = datetime.now() - - # 2-1. rhistory - def make_rhistory(self): - # 1. μ‘°νšŒμ‹œμ μ˜ μœ λ‹‰μŠ€ νƒ€μž„ μ΄μ „μ˜ μ‹ ν˜Έμ΄λ ₯ μˆ˜μ§‘ - self.rhistory = self.history.copy() # recent history - self.rhistory = self.rhistory[(self.rhistory.end_unix <= self.present_time) & (self.rhistory.end_unix > self.present_time - self.subtractor)] - - # rhistory에 λͺ¨λ“  κ΅μ°¨λ‘œλ²ˆν˜Έκ°€ μ‘΄μž¬ν•˜μ§€ μ•ŠμœΌλ©΄ ν•΄λ‹Ή κ΅μ°¨λ‘œλ²ˆν˜Έμ— λŒ€ν•œ μ‹ ν˜Έμ΄λ ₯을 좔가함 (at 졜근 ν”„λ‘œκ·Έλž¨ μ‹œμž‘μ‹œκ°) - whole_inter_nos = set(self.history.inter_no.unique()) - recent_inter_nos = set(self.rhistory.inter_no.unique()) - if not whole_inter_nos==recent_inter_nos: - for inter_no in whole_inter_nos - recent_inter_nos: - program_start, prow = self.load_prow(inter_no, self.present_time - self.subtractor) - cycle = prow.cycle.iloc[0] - row1 = prow.copy() - row2 = prow.copy() - # prowμ—μ„œ ν•„μš”ν•œ 뢀뢄을 rhistory에 μΆ”κ°€ - row1['end_unix'] = program_start - row2['end_unix'] = program_start + cycle - self.rhistory = pd.concat([self.rhistory, row1, row2])#.reset_index(drop=True) - - # present_time + adder 의 μ‹œκ°μ— ν•œ 주기의 μ‹ ν˜Έ μΆ”κ°€ - for inter_no in set(whole_inter_nos): - program_start, prow = self.load_prow(inter_no, self.present_time) - cycle = prow.cycle.iloc[0] - row3 = prow.copy() - # prowμ—μ„œ ν•„μš”ν•œ 뢀뢄을 rhistory에 μΆ”κ°€ - row3['end_unix'] = self.present_time + self.adder - self.rhistory = pd.concat([self.rhistory, row3])#.reset_index(drop=True) - - # 2. μ‹œμž‘ μœ λ‹‰μŠ€ νƒ€μž„μ»¬λŸΌ 생성 ν›„ μ’…λ₯˜ μœ λ‹‰μŠ€ νƒ€μž„μ—μ„œ ν˜„μ‹œλ³„ ν˜„μ‹œκΈ°κ°„ 컬럼의 합을 λΊ€ κ°’μœΌλ‘œ μž…λ ₯ - # - ν˜„μ‹œμ‹œκ°„μ˜ 합을 λΊ€ μ‹œκ°„μ˜ +- 10초 이내에 이전 주기정보가 μ‘΄μž¬ν•˜λ©΄ κ·Έ μœ λ‹‰μŠ€ μ‹œκ°„μ„ μ‹œμž‘ μœ λ‹‰μŠ€μ‹œκ°„ κ°’μœΌλ‘œ ν•˜κ³ , μ‘΄μž¬ν•˜μ§€ μ•ŠμœΌλ©΄ ν˜„μ‹œμ‹œκ°„μ˜ 합을 λΊ€ μœ λ‹‰μŠ€ μ‹œκ°„μ„ μ‹œμž‘ μœ λ‹‰μŠ€ μ‹œκ°„μœΌλ‘œ 지정 - for i, row in self.rhistory.iterrows(): - inter_no = row.inter_no - end_unix = row.end_unix - elapsed_time = row[[f'dura_{alph}{j}' for alph in ['A', 'B'] for j in range(1,9)]].sum() // 2 # ν˜„μ‹œμ‹œκ°„ ν•© - # 이전 μœ λ‹‰μŠ€ μ‘΄μž¬ν•˜μ§€ μ•ŠμŒ : ν˜„μ‹œμ‹œκ°„ ν•©μ˜ μ°¨ - start_unix = end_unix - elapsed_time - pre_rows = self.history[:i] # previous rows - if inter_no in pre_rows.inter_no.unique(): # 이전 μœ λ‹‰μŠ€ 쑴재 - pre_unix = pre_rows[pre_rows.inter_no == inter_no]['end_unix'].iloc[-1] # previous unix time - # 이전 μœ λ‹‰μŠ€ 쑴재, abs < 10 : 이전 μœ λ‹‰μŠ€ - if abs(pre_unix - start_unix) < 10: - start_unix = pre_unix - # 이전 μœ λ‹‰μŠ€ 쑴재, abs >=10 : ν˜„μ‹œμ‹œκ°„ ν•©μ˜ μ°¨ - else: - pass - self.rhistory.loc[i, 'start_unix'] = start_unix - self.rhistory[self.rhistory.isna()] = 0 - self.rhistory['start_unix'] = self.rhistory['start_unix'].astype(int) - self.rhistory = self.rhistory[['inter_no', 'start_unix'] + [f'dura_{alph}{j}' for alph in ['A', 'B'] for j in range(1,9)] + ['cycle']] - - def load_prow(self, inter_no, time): - ''' - load planned row - ''' - # ν”„λ‘œκ·Έλž¨ μ‹œμž‘μ‹œκ° - program_starts = np.array(self.timetable.start_seconds) - idx = (program_starts <= time).sum() - 1 - program_start = program_starts[idx] - - # 졜근 ν”„λ‘œκ·Έλž¨ μ‹œμž‘μ‹œκ°μ— λŒ€ν•œ μ‹ ν˜Έκ³„νš - start_hour = self.timetable.iloc[idx].start_hour - start_minute = self.timetable.iloc[idx].start_minute - # prow = self.plan[(self.plan.inter_no==inter_no) & (self.plan.start_hour==start_hour) & (self.plan.start_minute==start_minute)] # planned row - prow = self.plan_set.loc[(inter_no, start_hour, start_minute)] - prow = pd.DataFrame([prow],index=[0]) - prow['inter_no'] = inter_no - - return program_start, prow - - # 2-2. rhists - def make_rhists(self): - self.rhists = [] - for inter_no in self.rhistory.inter_no.unique(): - self.rhist = self.rhistory.copy()[self.rhistory.inter_no==inter_no] - self.rhist = self.rhist.drop_duplicates(subset=['start_unix']).reset_index(drop=True) - - # D_n 및 S_n κ°’ μ •μ˜ - self.rhist['D_n'] = 0 # D_n : μ‹œκ°„μ°¨μ΄ - self.rhist['S_n'] = 0 # S_n : ν˜„μ‹œμ‹œκ°„ν•© - for n in range(len(self.rhist)): - curr_unix = self.rhist.iloc[n].start_unix # current start_unix - self.rhist.loc[n, ['D_n', 'S_n']] = self.calculate_DS(self.rhist, curr_unix) - - # μ΄μ „μ‹œκ°, ν˜„μž¬μ‹œκ° - prev_unix = self.rhist.loc[0, 'start_unix'] # previous start_unix - curr_unix = self.rhist.loc[1, 'start_unix'] # current start_unix - - # rhist의 λ§ˆμ§€λ§‰ 행에 도달할 λ•ŒκΉŒμ§€ 반볡 - while True: - n = self.rhist[self.rhist.start_unix==curr_unix].index[0] - cycle = self.rhist.loc[n, 'cycle'] - D_n = self.rhist.loc[n, 'D_n'] - S_n = self.rhist.loc[n, 'S_n'] - # 참값인 경우 - if (abs(D_n - S_n) <= 5): - pass - # 참값이 μ•„λ‹Œ 경우 - else: - # 2-1-1. 결츑치 처리 : μΈμ ‘ν•œ 두 start_unix의 차이가 κ³„νšλœ 주기의 두 배보닀 크면 결츑이 일어났닀고 νŒλ‹¨, μ‹ ν˜Έκ³„νšμ˜ ν˜„μ‹œμ‹œκ°„μœΌλ‘œ "λŒ€μ²΄" - if curr_unix - prev_unix >= 2 * cycle: - # prev_unixλ₯Ό κ³„νšλœ 주기만큼 λŠ˜λ €κ°€λ©΄μ„œ ν•œ ν–‰μ”© μ±„μ›Œλ‚˜κ°„λ‹€. - # (curr_unixμ™€μ˜ 차이가 κ³„νšλœ 주기보닀 μž‘κ±°λ‚˜ κ°™μ•„μ§ˆ λ•ŒκΉŒμ§€) - while curr_unix - prev_unix > cycle: - prev_unix += cycle - # μ‹ ν˜Έ κ³„νš(prow) 뢈러였기 - start_seconds = np.array(self.timetable.start_seconds) - idx = (start_seconds <= prev_unix).sum() - 1 - start_hour = self.timetable.iloc[idx].start_hour - start_minute = self.timetable.iloc[idx].start_minute - prow = self.plan.copy()[(self.plan.inter_no==inter_no) & (self.plan.start_hour==start_hour) & (self.plan.start_minute==start_minute)] # planned row - # prowμ—μ„œ ν•„μš”ν•œ 뢀뢄을 rhist에 μΆ”κ°€ - prow['start_unix'] = prev_unix - prow = prow.drop(['start_hour', 'start_minute', 'offset'], axis=1) - cycle = prow.iloc[0].cycle - self.rhist = pd.concat([self.rhist, prow]) - self.rhist = self.rhist.sort_values(by='start_unix').reset_index(drop=True) - n += 1 - - # 2-1-2. μ΄μƒμΉ˜ 처리 : λΉ„μœ¨μ— 따라 ν•΄λ‹Ή 행을 "μ‚­μ œ"(R_n <= 0.5) λ˜λŠ” "μ‘°μ •"(R_n > 0.5)ν•œλ‹€ - R_n = (curr_unix - prev_unix) / cycle # R_n : λΉ„μœ¨ - # R_n이 0.5보닀 μž‘κ±°λ‚˜ κ°™μœΌλ©΄ ν•΄λ‹Ή 행을 μ‚­μ œ - if R_n <= 0.5: - self.rhist = self.rhist.drop(index=n).reset_index(drop=True) - if n >= self.rhist.index[-1]: - break - # ν–‰μ‚­μ œμ— λ”°λ₯Έ curr_unix, R_n μž¬μ •μ˜ - curr_unix = self.rhist.loc[n, 'start_unix'] - R_n = (curr_unix - prev_unix) / cycle # R_n : λΉ„μœ¨ - - # R_n이 0.5보닀 크면 ν•΄λ‹Ή ν–‰ μ‘°μ • (λΉ„μœ¨μ„ μœ μ§€ν•œ μ±„λ‘œ ν˜„μ‹œμ‹œκ°„ λŒ€μ²΄) - if R_n > 0.5: - # μ‹ ν˜Έ κ³„νš(prow) 뢈러였기 - start_seconds = np.array(self.timetable.start_seconds) - idx = (start_seconds <= curr_unix).sum() - 1 - start_hour = self.timetable.iloc[idx].start_hour - start_minute = self.timetable.iloc[idx].start_minute - prow = self.plan[(self.plan.inter_no==inter_no) & (self.plan.start_hour==start_hour) & (self.plan.start_minute==start_minute)] # planned row - # μ‘°μ •λœ ν˜„μ‹œμ‹œκ°„ (prow에 R_n을 κ³±ν•˜κ³  μ •μˆ˜λ‘œ λ°”κΏˆ) - adjusted_dur = prow.copy()[[f'dura_{alph}{j}' for alph in ['A', 'B'] for j in range(1,9)]] * R_n - int_parts = adjusted_dur.iloc[0].apply(lambda x: int(x)) - frac_parts = adjusted_dur.iloc[0] - int_parts - difference = round(adjusted_dur.iloc[0].sum()) - int_parts.sum() - for _ in range(difference): # μ†Œμˆ˜ 뢀뢄이 κ°€μž₯ 큰 μƒμœ„ 'difference'개의 값에 λŒ€ν•΄ 올림 처리 - max_frac_index = frac_parts.idxmax() - int_parts[max_frac_index] += 1 - frac_parts[max_frac_index] = 0 # 이미 처리된 ν•­λͺ©μ€ 0으둜 μ„€μ • - # rhist에 μ‘°μ •λœ ν˜„μ‹œμ‹œκ°„μ„ 반영 - self.rhist.loc[n, [f'dura_{alph}{j}' for alph in ['A', 'B'] for j in range(1,9)]] = int_parts.values - self.rhist.loc[n, 'cycle'] = int_parts.sum().sum() // 2 - - if n >= self.rhist.index[-1]: - break - prev_unix = curr_unix - curr_unix = self.rhist.loc[n+1, 'start_unix'] - - # D_n 및 S_n κ°’ μž¬μ •μ˜ - # 이 ν•¨μˆ˜μ˜ κ²€μ¦μ‹œ ν•„μš”ν•˜λ‚˜ 전체 κ΅¬λ™μ—λŠ” ν•„μš”μ—†μœΌλ―€λ‘œ commentν•΄λ†“μŒ - # for n in range(len(self.rhist)): - # curr_unix = self.rhist.iloc[n].start_unix # current start_unix - # self.rhist.loc[n, ['D_n', 'S_n']] = self.calculate_DS(self.rhist, curr_unix) - - self.rhists.append(self.rhist) - self.rhists = pd.concat(self.rhists)#.sort_values(by=['start_unix','inter_no']) - self.rhists = self.rhists[self.rhists.start_unix >= self.present_time - self.subtractor // 2] - - def calculate_DS(self, rhist, curr_unix): - # program_starts = np.array(self.timetable.start_seconds) - # idx = (program_starts <= self.present_time).sum() - 1 - # program_start = program_starts[idx] - # if list(self.hours[self.hours <= curr_unix]): - # ghour_lt_curr_unix = self.hours[self.hours <= curr_unix].max() # the greatest hour less than or equal to curr_unix - # else: - # ghour_lt_curr_unix = program_start - # start_unixes = rhist.start_unix.unique() - # start_unixes_lt_ghour = np.sort(start_unixes[start_unixes < ghour_lt_curr_unix]) # start unixes less than ghour_lt_curr_unix - # # κΈ°μ€€μœ λ‹‰μŠ€(base_unix) : curr_unix보닀 μž‘μ€ hour μ€‘μ—μ„œ κ°€μž₯ 큰 κ°’μœΌλ‘œλΆ€ν„° λ‹€μ„― 번째둜 μž‘μ€ start_unix - # if len(start_unixes_lt_ghour) > 5: - # base_unix = start_unixes_lt_ghour[-5] - # # start_unixes_lt_ghour의 길이가 5 미만일 κ²½μš°μ—λŠ” 맨 μ•ž start_unix둜 base_unixλ₯Ό 지정 - # else: - # base_unix = rhist.start_unix.min() - base_unix = curr_unix - self.subtractor // 2 - abs_diff = (self.rhist['start_unix'] - base_unix).abs() - closest_index = abs_diff.idxmin() - base_unix = self.rhist.loc[closest_index, 'start_unix'] - - D_n = curr_unix - base_unix - S_n_durs = rhist[(rhist.start_unix > base_unix) & (rhist.start_unix <= curr_unix)] \ - [[f'dura_{alph}{j}' for alph in ['A', 'B'] for j in range(1,9)]] - S_n = S_n_durs.values.sum() // 2 - return D_n, S_n - - # 2-3. hrhists - def make_hrhists(self): - # κ³„μΈ΅ν™”λœ ν˜•νƒœλ‘œ λ³€ν™˜ - self.hrhists = [] # hierarchied recent history - for row in self.rhists.itertuples(index=True): - inter_no = row.inter_no - start_unix = row.start_unix - - ind = (self.timetable['start_seconds'] <= row.start_unix).sum() - 1 - start_hour = self.timetable.iloc[ind].start_hour - start_minute = self.timetable.iloc[ind].start_minute - self.isplit = self.isplits[(inter_no, start_hour, start_minute)] - phas_As = [self.isplit[j][0] for j in self.isplit.keys()] - phas_Bs = [self.isplit[j][1] for j in self.isplit.keys()] - # durs_A = row[[f'dura_A{j}' for j in range(1,9)]] - # durs_B = row[[f'dura_B{j}' for j in range(1,9)]] - durs_A = [getattr(row, f'dura_A{j}') for j in range(1, 9)] - durs_B = [getattr(row, f'dura_B{j}') for j in range(1, 9)] - durations = [] - for j in range(1, len(self.isplit)+1): - ja = self.isplit[j][0] - jb = self.isplit[j][1] - if ja == jb: - durations.append(min(durs_A[ja-1], durs_B[jb-1])) - else: - durations.append(abs(durs_A[ja-1] - durs_B[ja-1])) - new_rows = pd.DataFrame({'inter_no':[inter_no] * len(durations), 'start_unix':[start_unix] * len(durations), - 'phas_A':phas_As, 'phas_B':phas_Bs, 'duration':durations}) - self.hrhists.append(new_rows) - self.hrhists = pd.concat(self.hrhists) - # self.hrhists = self.hrhists.sort_values(by = ['start_unix', 'inter_no', 'phas_A', 'phas_B']).reset_index(drop=True) - - # 3. 이동λ₯˜μ •λ³΄ μ „μ²˜λ¦¬ - def process_movement(self): - print("3. 이동λ₯˜μ •λ³΄ ν…Œμ΄λΈ”μ„ λ³€ν™˜ν•©λ‹ˆλ‹€.") - self.make_movement() - self.time31 = datetime.now() - self.update_movement() - self.time32 = datetime.now() - - # 3-1. movement - def make_movement(self): - # - μ•„λž˜ 절차λ₯Ό 5μ΄ˆλ§ˆλ‹€ 반볡 - for fsec in range(self.present_time - 300, self.present_time + 1, 5): # fsec : unix time by Five SECond - # 1. μƒνƒœ ν…Œμ΄λΈ” μ‘°νšŒν•΄μ„œ 전체 데이터쀑 ν•„μš”λ°μ΄ν„°(ꡐ차둜번호, A링 ν˜„μ‹œλ²ˆν˜Έ, A링 이동λ₯˜λ²ˆν˜Έ, B링 ν˜„μ‹œλ²ˆν˜Έ, B링 이동λ₯˜λ²ˆν˜Έ)만 μˆ˜μ§‘ : A - move = pd.read_csv(os.path.join(self.path_tables, 'move', f'move_{fsec}.csv'), index_col=0) - # 2. 이λ ₯ ν…Œμ΄λΈ” μ‘°νšŒν•΄μ„œ κ΅μ°¨λ‘œλ³„λ‘œ μœ λ‹‰μŠ€μ‹œκ°„ μ΅œλŒ€μΈ 데이터(ꡐ차둜번호, μ’…λ£Œμœ λ‹‰μŠ€νƒ€μž„)만 μˆ˜μ§‘ : B - recent_histories = [group.iloc[-1:] for _, group in self.history[self.history['end_unix'] < fsec].groupby('inter_no')] # κ΅μ°¨λ‘œλ³„λ‘œ μœ λ‹‰μŠ€μ‹œκ°„μ΄ μ΅œλŒ€μΈ ν–‰λ“€ - - # print([group for _, group in self.history[self.history['end_unix'] < fsec].groupby('inter_no')]) - if not recent_histories: - rhistory = pd.DataFrame({'inter_no':[], 'end_unix':[]}) # recent history - else: - rhistory = pd.concat(recent_histories) - recent_unix = rhistory[['inter_no', 'end_unix']] - # 3. μƒνƒœ ν…Œμ΄λΈ” μ‘°νšŒμ •λ³΄(A)와 이λ ₯ ν…Œμ΄λΈ” μ‘°νšŒμ •λ³΄(B) 쑰인(ν‚€κ°’ : ꡐ차둜번호) : C - move = pd.merge(move, recent_unix, how='left', on='inter_no') - move['end_unix'] = move['end_unix'].fillna(0).astype(int) - # 4. C데이터 ν”„λ ˆμž„μ— μ‹ κ·œ 컬럼(μ‹œμž‘ μœ λ‹‰μŠ€νƒ€μž„) 생성 ν›„ μ’…λ£Œμœ λ‹‰μŠ€ νƒ€μž„ κ°’ μž…λ ₯, μ’…λ£Œ μœ λ‹‰μŠ€ νƒ€μž„ 컬럼 제거 - move = move.rename(columns = {'end_unix':'start_unix'}) - # 5. 이동λ₯˜ 이λ ₯정보 READ - # - CSV 파일둜 μ„œλ²„μ— μ €μž₯된 이동λ₯˜μ •λ³΄λ₯Ό μ½μ–΄μ˜΄(파일이 μ—†λŠ” κ²½μš°μ—λŠ” 데이터가 μ—†λŠ” ν”„λ ˆμž„ D 생성) - try: - if isinstance(movement, pd.DataFrame): # movementκ°€ μ‘΄μž¬ν•  경우 κ·Έκ±Έ κ·ΈλŒ€λ‘œ 씀. - pass - else: - movement = pd.DataFrame() - except NameError: # movementκ°€ μ‘΄μž¬ν•˜μ§€ μ•ŠλŠ” 경우 생성 - movement = pd.DataFrame() - # 6. 이동λ₯˜ 이λ ₯정보 λ°μ΄ν„°ν…Œμ΄λΈ”(D)에 C데이터 add - movement = pd.concat([movement, move]) - # 7. D데이터 ν”„λ ˆμž„μ—μ„œ 쀑볡데이터 제거(ꡐ차둜번호, μ‹œμž‘ μœ λ‹‰μŠ€νƒ€μž„, A링 ν˜„μ‹œλ²ˆν˜Έ, B링 ν˜„μ‹œλ²ˆν˜Έ 같은 행은 제거) - movement = movement.drop_duplicates(['inter_no','phas_A','phas_B','start_unix']) - # 8. D데이터 보관 μ‹œκ°„ κΈ°μ€€μ‹œκ°„μ„ μ‹œμž‘ μœ λ‹‰μŠ€ νƒ€μž„μ˜ μ΅œλŒ€κ°’ - self.subtractor // 2을 κ°’μœΌλ‘œ μ‚°μΆœν•˜κ³ , 보관 μ‹œκ°„ κΈ°μ€€μ‹œκ°„λ³΄λ‹€ μž‘μ€ μ‹œμž‘ μœ λ‹‰μŠ€ νƒ€μž„μ„ 가진 행은 λͺ¨λ‘ 제거(1μ‹œκ°„ λ°μ΄ν„°λ§Œ 보관) - movement = movement[movement.start_unix > fsec - self.subtractor // 2] - # movement = movement.sort_values(by=['start_unix','inter_no','phas_A','phas_B']).reset_index(drop=True) - self.movement = pd.read_csv(os.path.join(self.path_intermediates, 'movement', f'movement_{self.present_time}.csv'), index_col=0) - - # 3-2. movement_updated - def update_movement(self): - # 쀑볡을 μ œκ±°ν•˜κ³  (inter_no, start_unix) μŒμ„ λ§Œλ“­λ‹ˆλ‹€. - hrhists_inter_unix = set(self.hrhists[['inter_no', 'start_unix']].drop_duplicates().itertuples(index=False, name=None)) - movement_inter_unix = set(self.movement[['inter_no', 'start_unix']].drop_duplicates().itertuples(index=False, name=None)) - - # hrhistsμ—λŠ” μžˆμ§€λ§Œ movementμ—λŠ” μ—†λŠ” (inter_no, start_unix) μŒμ„ μ°ΎμŠ΅λ‹ˆλ‹€. - missing_in_movement = hrhists_inter_unix - movement_inter_unix - - # μƒˆλ‘œμš΄ 행듀을 μƒμ„±ν•©λ‹ˆλ‹€. - new_rows = [] - if missing_in_movement: - for inter_no, start_unix in missing_in_movement: - # match1μ—μ„œ ν•΄λ‹Ή inter_no의 데이터λ₯Ό μ°ΎμŠ΅λ‹ˆλ‹€. - new_row = self.match1[self.match1['inter_no'] == inter_no].copy() - # start_unix 값을 μ„€μ •ν•©λ‹ˆλ‹€. - new_row['start_unix'] = start_unix - new_rows.append(new_row) - - # μƒˆλ‘œμš΄ λ°μ΄ν„°ν”„λ ˆμž„μ„ μƒμ„±ν•˜κ³  κΈ°μ‘΄ movement λ°μ΄ν„°ν”„λ ˆμž„κ³Ό ν•©μΉ©λ‹ˆλ‹€. - new_movement = pd.concat(new_rows, ignore_index=True) - self.movement_updated = pd.concat([self.movement, new_movement], ignore_index=True) - else: - self.movement_updated = self.movement - - # 4. ν†΅ν•©ν…Œμ΄λΈ” 생성 - def make_histids(self): - print("4. 톡합 ν…Œμ΄λΈ”μ„ μƒμ„±ν•©λ‹ˆλ‹€.") - self.merge_dfs() - self.time41 = datetime.now() - # self.attach_children() - # self.time42 = datetime.now() - - # 4-1. histid - def merge_dfs(self): - # movements and durations - movedur = pd.merge(self.hrhists, self.movement_updated, how='inner', on=['inter_no', 'start_unix', 'phas_A', 'phas_B']) - # movedur = movedur.sort_values(by=['start_unix', 'inter_no', 'phas_A','phas_B']) - movedur = movedur[['inter_no', 'start_unix', 'phas_A', 'phas_B', 'move_A', 'move_B', 'duration']] - - # matching DataFrame에 λŒ€ν•΄ multi-index μ„€μ • - self.matching.set_index(['inter_no', 'move_no'], inplace=True) - self.matching.sort_index(inplace=True) - - for row in movedur.itertuples(index=True): - inter_no = row.inter_no - start_unix = row.start_unix - move_A = row.move_A - move_B = row.move_B - - # incoming and outgoing edges A - if move_A in [17, 18]: - inc_edge_A = np.nan - out_edge_A = np.nan - else: - match_A = self.matching.loc[(inter_no, move_A)] - inc_edge_A = match_A.inc_edge.values[0] - out_edge_A = match_A.out_edge.values[0] - movedur.at[row.Index, 'inc_edge_A'] = inc_edge_A - movedur.at[row.Index, 'out_edge_A'] = out_edge_A - - # incoming and outgoing edges B - if move_B in [17, 18]: - inc_edge_B = np.nan - out_edge_B = np.nan - else: - match_B = self.matching.loc[(inter_no, move_B)] - inc_edge_B = match_B.inc_edge.values[0] - out_edge_B = match_B.out_edge.values[0] - movedur.at[row.Index, 'inc_edge_B'] = inc_edge_B - movedur.at[row.Index, 'out_edge_B'] = out_edge_B - - # 이동λ₯˜ 컬럼 제거 - movedur = movedur.drop(['move_A', 'move_B'], axis=1) - - self.histid = movedur.copy() # history with edge ids (incoming and outgoing edge ids) - self.histid['node_id'] = self.histid['inter_no'].map(self.inter2node) - self.histid = self.histid[['inter_no', 'node_id', 'start_unix', 'phas_A', 'phas_B', 'duration', 'inc_edge_A', 'out_edge_A', 'inc_edge_B', 'out_edge_B']] - histid_start = self.present_time - 600 - self.histid = self.histid[self.histid.start_unix > histid_start] - - # 4-2. histids - def attach_children(self): - ''' - μžμ‹κ΅μ°¨λ‘œμ— λŒ€ν•œ μ§„μž…Β·μ§„μΆœ 엣지 정보λ₯Ό λΆ™μ—¬μ£ΌλŠ” ν•¨μˆ˜ - - input : - (1) histid - - 각 κ΅μ°¨λ‘œμ— λŒ€ν•œ (μ‹œμž‘μœ λ‹‰μŠ€, Aν˜„μ‹œ, Bν˜„μ‹œ)별 ν˜„μ‹œμ‹œκ°„, μ§„μž…Β·μ§„μΆœμ—£μ§€ - - λΆ€λͺ¨κ΅μ°¨λ‘œ(주ꡐ차둜)에 λŒ€ν•΄μ„œλ§Œ 값이 μ§€μ •λ˜μ–΄ 있음 - (2) match6 - - (ν˜„μ‹œ, 링)별 μ§„μž…Β·μ§„μΆœμ—£μ§€ - - μžμ‹κ΅μ°¨λ‘œ(μœ ν„΄ 및 μ—°λ™κ΅μ°¨λ‘œ)에 λŒ€ν•΄μ„œλ„ 값이 μ§€μ •λ˜μ–΄ 있음 - (3) parent_ids : λΆ€λͺ¨κ΅μ°¨λ‘œ λͺ©λ‘ - (4) pa2ch : 각 λΆ€λͺ¨κ΅μ°¨λ‘œidλ₯Ό λΆ€λͺ¨κ΅μ°¨λ‘œκ°€ ν¬ν•¨ν•˜κ³  μžˆλŠ” μžμ‹κ΅μ°¨λ‘œλ“€μ˜ idλ“€μ˜ 리슀트둜 λŒ€μ‘μ‹œν‚€λŠ” λ”•μ…”λ„ˆλ¦¬ - - output : histids - - λͺ¨λ“ (λΆ€λͺ¨ 및 μžμ‹) κ΅μ°¨λ‘œμ— λŒ€ν•œ μ‹œμž‘μœ λ‹‰μŠ€ (μ‹œμž‘μœ λ‹‰μŠ€, Aν˜„μ‹œ, Bν˜„μ‹œ)별 ν˜„μ‹œμ‹œκ°„, μ§„μž…Β·μ§„μΆœμ—£μ§€ - ''' - new_histids = [] - for parent_id in self.parent_ids: - for child_id in self.pa2ch[parent_id]: - new_histid = self.histid.copy()[self.histid.node_id==parent_id] - new_histid[['inc_edge_A', 'out_edge_A', 'inc_edge_B', 'out_edge_B']] = np.nan - for i, row in new_histid.iterrows(): - phas_A = row.phas_A - phas_B = row.phas_B - new_match = self.match6[self.match6.node_id==child_id] - Arow = new_match[(new_match.phase_no==phas_A) & (new_match.ring_type=='A')] - if ~ Arow[['inc_edge', 'out_edge']].isna().all().all(): - inc_edge = Arow.iloc[0].inc_edge - out_edge = Arow.iloc[0].out_edge - new_histid.loc[i, ['inc_edge_A', 'out_edge_A']] = [inc_edge, out_edge] - Brow = new_match[(new_match.phase_no==phas_B) & (new_match.ring_type=='B')] - if ~ Brow[['inc_edge', 'out_edge']].isna().all().all(): - inc_edge = Brow.iloc[0].inc_edge - out_edge = Brow.iloc[0].out_edge - new_histid.loc[i, ['inc_edge_B', 'out_edge_B']] = [inc_edge, out_edge] - new_histid.loc[i, 'node_id'] = child_id - new_histids.append(new_histid) - new_histids = pd.concat(new_histids) - self.histids = pd.concat([self.histid.copy(), new_histids]) - self.histids = self.histids.sort_values(by=['start_unix', 'node_id', 'phas_A', 'phas_B']).reset_index(drop=True) - - # 5. μ‹ ν˜Έ 생성 - def get_signals(self): - print("5. μ‹ ν˜Έλ₯Ό μƒμ„±ν•©λ‹ˆλ‹€.") - self.initialize_states() - self.time51 = datetime.now() - self.assign_signals() - self.time52 = datetime.now() - self.set_timepoints() - self.time53 = datetime.now() - self.assign_red_yellow() - self.time54 = datetime.now() - self.make_tl_file() - self.time55 = datetime.now() - - # 5-1. μ‹ ν˜Έμ΄ˆκΈ°ν™” - def initialize_states(self): - ''' - μ‹ ν˜Έ μ΄ˆκΈ°ν™” - - input : - (1) net : λ„€νŠΈμ›Œν¬ - (2) nodes : λ…Έλ“œ λͺ©λ‘ - (3) histids : λͺ¨λ“  κ΅μ°¨λ‘œμ— λŒ€ν•œ μ‹œμž‘μœ λ‹‰μŠ€ (μ‹œμž‘μœ λ‹‰μŠ€, Aν˜„μ‹œ, Bν˜„μ‹œ)별 ν˜„μ‹œμ‹œκ°„, μ§„μž…Β·μ§„μΆœμ—£μ§€ - - output : node2init - - 각 λ…Έλ“œλ₯Ό μ΄ˆκΈ°ν™”λœ μ‹ ν˜Έλ‘œ λ§΅ν•‘ν•˜λŠ” λ”•μ…”λ„ˆλ¦¬ - - μ΄ˆκΈ°ν™”λœ μ‹ ν˜Έλž€, μš°νšŒμ „μ„ g둜 λ‚˜λ¨Έμ§€λŠ” r둜 μ§€μ •ν•œ μ‹ ν˜Έλ₯Ό 말함. - ''' - self.node2init = {} - for node in self.nodes: - node_id = node.getID() - conns = [(c.getJunctionIndex(), c) for c in node.getConnections()] - conns = [c for c in conns if c[0] >= 0] - conns = sorted(conns, key=lambda x: x[0]) - state = [] - for i, ci in conns: - if ci.getTLLinkIndex() < 0: - continue - are_foes = False - for j, cj in conns: - if ci.getTo() == cj.getTo(): - continue - if node.areFoes(i, j): - are_foes = True - break - state.append('r' if are_foes else 'g') - self.node2init[node_id] = state - - # μ–΄λ–€ 연결과도 상좩이 μΌμ–΄λ‚˜μ§€λŠ” μ•Šμ§€λ§Œ, μ‹ ν˜Έκ°€ λΆ€μ—¬λ˜μ–΄ μžˆλŠ” κ²½μš°μ—λŠ” r을 λΆ€μ—¬ - for _, row in self.histids.iterrows(): - node_id = row['node_id'] - inc_edge_A = row.inc_edge_A - inc_edge_B = row.inc_edge_B - out_edge_A = row.out_edge_A - out_edge_B = row.out_edge_B - - if pd.isna(inc_edge_A) or pd.isna(out_edge_A): - pass - else: - inc_edge_A = self.net.getEdge(inc_edge_A) - out_edge_A = self.net.getEdge(out_edge_A) - for conn in inc_edge_A.getConnections(out_edge_A): - index = conn.getTLLinkIndex() - if index >= 0: - self.node2init[node_id][index] = 'r' - - if pd.isna(inc_edge_B) or pd.isna(out_edge_B): - pass - else: - inc_edge_B = self.net.getEdge(inc_edge_B) - out_edge_B = self.net.getEdge(out_edge_B) - for conn in inc_edge_B.getConnections(out_edge_B): - index = conn.getTLLinkIndex() - if index >= 0: - self.node2init[node_id][index] = 'r' - - # 5-2. λ…Ήμƒ‰μ‹ ν˜Έ λΆ€μ—¬ - def assign_signals(self): - ''' - μ§„μž…Β·μ§„μΆœμ—£μ§€λ₯Ό μ‹ ν˜Έλ¬Έμžμ—΄λ‘œ λ°°μ • - - input : - (1) histids : λͺ¨λ“  κ΅μ°¨λ‘œμ— λŒ€ν•œ (μ‹œμž‘μœ λ‹‰μŠ€, Aν˜„μ‹œ, Bν˜„μ‹œ)별 ν˜„μ‹œμ‹œκ°„, μ§„μž…Β·μ§„μΆœμ—£μ§€ - (2) node2init : 각 λ…Έλ“œλ₯Ό μ΄ˆκΈ°ν™”λœ μ‹ ν˜Έλ‘œ λ§΅ν•‘ν•˜λŠ” λ”•μ…”λ„ˆλ¦¬ - (3) net : λ„€νŠΈμ›Œν¬ - - output : sigtable - - λͺ¨λ“  κ΅μ°¨λ‘œμ— λŒ€ν•œ (μ‹œμž‘μœ λ‹‰μŠ€, Aν˜„μ‹œ, Bν˜„μ‹œ)별 ν˜„μ‹œμ‹œκ°„, μ‹ ν˜Έλ¬Έμžμ—΄ - - 황색 및 μ μƒ‰μ‹ ν˜ΈλŠ” 아직 λ°˜μ˜λ˜μ§€ μ•Šμ•˜μŒ. - ''' - self.sigtable = self.histids.copy() - self.sigtable['init_state'] = self.sigtable['node_id'].map(self.node2init) - self.sigtable['state'] = self.sigtable['init_state'].map(lambda x:''.join(x)) - for row in self.sigtable.itertuples(index=True): - node_id = row.node_id - inc_edge_A = row.inc_edge_A - inc_edge_B = row.inc_edge_B - out_edge_A = row.out_edge_A - out_edge_B = row.out_edge_B - state = copy.deepcopy(self.node2init)[node_id] - if pd.isna(inc_edge_A) or pd.isna(out_edge_A): - pass - else: - inc_edge_A = self.net.getEdge(inc_edge_A) - out_edge_A = self.net.getEdge(out_edge_A) - for conn in inc_edge_A.getConnections(out_edge_A): - index = conn.getTLLinkIndex() - if index >= 0: - state[index] = 'G' - self.sigtable.at[row.Index, 'state'] = ''.join(state) - - if pd.isna(inc_edge_B) or pd.isna(out_edge_B): - pass - else: - inc_edge_B = self.net.getEdge(inc_edge_B) - out_edge_B = self.net.getEdge(out_edge_B) - for conn in inc_edge_B.getConnections(out_edge_B): - index = conn.getTLLinkIndex() - if index >= 0: - state[index] = 'G' - self.sigtable.at[row.Index, 'state'] = ''.join(state) - self.sigtable = self.sigtable.dropna(subset='state') - self.sigtable = self.sigtable.reset_index(drop=True) - self.sigtable['phase_sumo'] = self.sigtable.groupby(['node_id', 'start_unix']).cumcount() - self.sigtable = self.sigtable[['node_id', 'start_unix', 'phase_sumo', 'duration', 'state']] - # self.sigtable = self.sigtable.sort_values(by=['start_unix', 'node_id']) - self.sigtable['start_dt'] = self.sigtable['start_unix'].apply(lambda x:datetime.fromtimestamp(x)) - - # 5-3. μ‹ ν˜Έ 파일의 μ‹œμž‘ 및 μ’…λ£Œμ‹œκ° μ„€μ • - def set_timepoints(self): - self.offsets = {} - self.Sigtable = [] - sim_start = self.present_time - 300 - for node_id, group in self.sigtable.groupby('node_id'): - lsbs = group[group['start_unix'] < sim_start]['start_unix'].max() # the last start_unix before sim_start - self.offsets[node_id] = lsbs - sim_start - group = group[group.start_unix >= lsbs] - start_unixes = np.array(group.start_unix) - start_unixes = np.sort(np.unique(start_unixes))[:self.node2num_cycles[node_id]] - - group = group[group.start_unix.isin(start_unixes)] - self.Sigtable.append(group) - self.Sigtable = pd.concat(self.Sigtable) - - # 5-4. 적색 및 ν™©μƒ‰μ‹ ν˜Έ λΆ€μ—¬ - def assign_red_yellow(self): - ''' - 적색, ν™©μƒ‰μ‹ ν˜Έλ₯Ό λ°˜μ˜ν•œ μ‹ ν˜Έλ¬Έμžμ—΄ λ°°μ • - - input : Sigtable - - λͺ¨λ“  κ΅μ°¨λ‘œμ— λŒ€ν•œ (μ‹œμž‘μœ λ‹‰μŠ€, μ„ΈλΆ€ν˜„μ‹œλ²ˆν˜Έ)별 ν˜„μ‹œμ‹œκ°„, μ‹ ν˜Έλ¬Έμžμ—΄, μ§„μž…Β·μ§„μΆœμ—£μ§€ - * μ„ΈλΆ€ν˜„μ‹œλž€ μ˜€λ²„λž©μ„ λ°˜μ˜ν•œ ν˜„μ‹œλ²ˆν˜Έλ₯Ό λœ»ν•¨. - - output : SIGTABLE - - λͺ¨λ“  κ΅μ°¨λ‘œμ— λŒ€ν•œ (μ‹œμž‘μœ λ‹‰μŠ€, λ…Ήν™©μ μ„ΈλΆ€ν˜„μ‹œλ²ˆν˜Έ)별 ν˜„μ‹œμ‹œκ°„, (ν™©Β·μ μƒ‰μ‹ ν˜Έκ°€ ν¬ν•¨λœ) μ‹ ν˜Έλ¬Έμžμ—΄ - * λ…Ήν™©μ μ„ΈλΆ€ν˜„μ‹œλ²ˆν˜Έλž€ μ„ΈλΆ€ν˜„μ‹œλ²ˆν˜Έμ— r, g, y μ˜΅μ…˜κΉŒμ§€ ν¬ν•¨λœ ν˜„μ‹œλ²ˆν˜Έλ₯Ό λœ»ν•¨. - ''' - self.SIGTABLE = [] - for _, group in self.Sigtable.groupby('node_id'): - new_rows_list = [] - for i in range(1, len(group)): - prev_row = group.iloc[i-1:i].copy() - next_row = group.iloc[i:i+1].copy() - new_rows = pd.concat([prev_row, prev_row, next_row]).reset_index(drop=True) - new_rows.loc[0, 'phase_sumo'] = str(prev_row.phase_sumo.iloc[0]) + '_g' - new_rows.loc[0, 'duration'] = new_rows.loc[0, 'duration'] - 5 - new_rows.loc[1, 'phase_sumo'] = str(prev_row.phase_sumo.iloc[0]) + '_y' - new_rows.loc[1, 'duration'] = 4 - yellow_state = '' - red_state = '' - for a, b in zip(prev_row.state.iloc[0], next_row.state.iloc[0]): - if a == 'G' and b == 'r': - yellow_state += 'y' - red_state += 'r' - else: - yellow_state += a - red_state += a - new_rows.loc[2, 'phase_sumo'] = str(next_row.phase_sumo.iloc[0]) + '__r' - new_rows.loc[2, 'duration'] = 1 - new_rows.loc[1, 'state'] = yellow_state - new_rows.loc[2, 'state'] = red_state - new_rows_list.append(new_rows) - next_row['phase_sumo'] = str(next_row.phase_sumo.iloc[0]) + '_g' - next_row['duration'] -= 5 - new_rows_list.append(next_row) - new_rows = pd.concat(new_rows_list) - self.SIGTABLE.append(new_rows) - self.SIGTABLE = pd.concat(self.SIGTABLE).sort_values(by=['node_id', 'start_unix', 'phase_sumo']) - - # 5-5. μ‹ ν˜ΈνŒŒμΌ 생성 - def make_tl_file(self): - strings = ['\n'] - for node_id, group in self.SIGTABLE.groupby('node_id'): - strings.append(f' \n') - for row in group.itertuples(index=True): - duration = row.duration - state = row.state - strings.append(f' \n') - strings.append(' \n') - strings.append('') - strings = ''.join(strings) - # μ €μž₯ - self.path_output = os.path.join(self.path_results, f'sn_{self.present_time}.add.xml') - with open(self.path_output, 'w') as f: - f.write(strings) - - # 6. μ΄μŠˆμ‚¬ν•­ μ €μž₯ - def write_issues(self): - print('6. μ΄μŠˆμ‚¬ν•­μ„ μ €μž₯ν•©λ‹ˆλ‹€.') - path_issues = os.path.join(self.path_results, "issues_generate_signals.txt") - with open(path_issues, "w", encoding="utf-8") as file: - for item in self.issues: - file.write(item + "\n") - if self.issues: - print("데이터 처리 쀑 λ°œμƒν•œ νŠΉμ΄μ‚¬ν•­μ€ λ‹€μŒκ³Ό κ°™μŠ΅λ‹ˆλ‹€. :") - for review in self.issues: - print(review) - - def main(self): - self.time0 = datetime.now() - # 1. 데이터 μ€€λΉ„ - self.prepare_data() - self.time1 = datetime.now() - # 2. μ‹ ν˜Έμ΄λ ₯ μ „μ²˜λ¦¬ - self.process_history() - self.time2 = datetime.now() - # 3. 이동λ₯˜μ •λ³΄ μ „μ²˜λ¦¬ - self.process_movement() - self.time3 = datetime.now() - # 4. ν†΅ν•©ν…Œμ΄λΈ” 생성 - self.make_histids() - self.time4 = datetime.now() - # # 5. μ‹ ν˜Έ 생성 - # self.get_signals() - # self.time5 = datetime.now() - # # 6. μ΄μŠˆμ‚¬ν•­ μ €μž₯ - # self.write_issues() - # self.time6 = datetime.now() - - print('(1)', self.time1 - self.time0) - print('(1-1)', self.time11 - self.time0) - print('(1-2)', self.time12 - self.time11) - print('(1-3)', self.time13 - self.time12) - print('(1-4)', self.time14 - self.time13) - print('(1-5)', self.time15 - self.time14) - print('(2)', self.time2 - self.time1) - print('(2-1)', self.time21 - self.time1) - print('(2-2)', self.time22 - self.time21) - print('(2-3)', self.time23 - self.time22) - print('(3)', self.time3 - self.time2) - print('(3-1)', self.time31 - self.time2) - print('(3-2)', self.time32 - self.time31) - print('(4)', self.time4 - self.time3) - print('(4-1)', self.time41 - self.time3) - # print('(4-2)', self.time42 - self.time41) - # print('(5)', self.time5 - self.time4) - # print('(5-1)', self.time51 - self.time4) - # print('(5-2)', self.time52 - self.time51) - # print('(5-3)', self.time53 - self.time52) - # print('(5-4)', self.time54 - self.time53) - # print('(5-5)', self.time55 - self.time54) - # print('(6)', self.time6 - self.time5) - print('total time :', self.time41 - self.time0) - -if __name__ == '__main__': - self = SignalGenerator() - self.main() - # self.path_unit = os.path.join(self.path_root, 'Analysis', '0207_unit_test') - # self.hrhists.to_csv(os.path.join(self.path_unit, 'hrhists.csv')) - # self.histids.to_csv(os.path.join(self.path_unit, 'histids.csv')) - # self.sigtable.to_csv(os.path.join(self.path_unit, 'sigtable.csv')) - # self.Sigtable.to_csv(os.path.join(self.path_unit, 'ssigtable.csv')) - # print("elapsed time :", datetime.now() - starting_time) \ No newline at end of file

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