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김선중 1 year ago
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4 changed files with 441 additions and 548 deletions
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  1. +441
    -0
      Analysis/0207_code_reivision/0207_code_reivision.ipynb
  2. +0
    -548
      Analysis/0207_uturn_code_change/0207_uturn_code_change.ipynb
  3. BIN
      Documents/김선중_신호생성(240207).pptx
  4. BIN
      Scripts/__pycache__/preprocess_daily.cpython-38.pyc

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- 0
Analysis/0207_code_reivision/0207_code_reivision.ipynb View File

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{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"41.0\n"
]
}
],
"source": [
"time_data = \"\"\"\n",
"3h\n",
"0.5h\n",
"3h\n",
"2h\n",
"2h\n",
"4h\n",
"3h\n",
"1.5h\n",
"4h\n",
"3.5h\n",
"2.5h\n",
"2h\n",
"3h\n",
"3h\n",
"2h\n",
"1h\n",
"0h\n",
"0.5h\n",
"0.5h\n",
"\"\"\"\n",
"time_list = time_data.strip().split('\\n')\n",
"total_hours = sum(float(time.replace('h', '')) for time in time_list)\n",
"print(total_hours)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1. 데이터를 로드합니다.\n",
"1-1. 네트워크가 로드되었습니다.\n",
"1-2. 테이블들이 로드되었습니다.\n",
"1-3. 네트워크의 모든 clean state requirement들을 체크했습니다.\n",
"1-4. 테이블들의 무결성 검사를 완료했습니다.\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"이동류정보 불러오는 중: 100%|██████████| 17280/17280 [00:51<00:00, 334.89it/s]\n"
]
}
],
"source": [
"import sys\n",
"from datetime import datetime\n",
"sys.path.append('../../Scripts')\n",
"from preprocess_daily import DailyPreprocessor\n",
"self = DailyPreprocessor()\n",
"\n",
"# 1. 데이터 준비\n",
"self.load_data()\n",
"\n",
"self.make_match1()\n",
"self.make_match2()\n",
"self.make_match3()\n",
"self.make_match4()\n",
"self.make_match5()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"u00 True\n",
"u20 False\n",
"u30 True\n",
"u31 True\n",
"u32 True\n",
"u60 True\n"
]
},
{
"ename": "NameError",
"evalue": "name 'pd' is not defined",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[1;32mIn[4], line 55\u001b[0m\n\u001b[0;32m 52\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcoord \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcoord[[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124minter_no\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mphase_no\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mring_type\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mmove_no\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124minc_dir\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mout_dir\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124minc_angle\u001b[39m\u001b[38;5;124m'\u001b[39m,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mout_angle\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124minc_edge\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mout_edge\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mnode_id\u001b[39m\u001b[38;5;124m'\u001b[39m]]\n\u001b[0;32m 54\u001b[0m \u001b[38;5;66;03m# display(coord)\u001b[39;00m\n\u001b[1;32m---> 55\u001b[0m cmatches \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241m.\u001b[39mconcat(cmatches)\n\u001b[0;32m 56\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmatch6 \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mconcat([\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmatch5, cmatches, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcoord])\u001b[38;5;241m.\u001b[39mdrop_duplicates()\u001b[38;5;241m.\u001b[39msort_values(by\u001b[38;5;241m=\u001b[39m[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124minter_no\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mnode_id\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mphase_no\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mring_type\u001b[39m\u001b[38;5;124m'\u001b[39m])\n\u001b[0;32m 57\u001b[0m \u001b[38;5;66;03m# self.match6.to_csv(os.path.join(self.path_intermediates, 'match6.csv'))\u001b[39;00m\n",
"\u001b[1;31mNameError\u001b[0m: name 'pd' is not defined"
]
}
],
"source": [
"# self.node2inter = dict(zip(self.inter_node['node_id'], self.inter_node['inter_no']))\n",
"\n",
"# child_ids = self.inter_node[self.inter_node.inter_type=='child'].node_id.unique()\n",
"# ch2pa = {} # child to parent\n",
"# for child_id in child_ids:\n",
"# parent_no = self.inter_node[self.inter_node.node_id==child_id].inter_no.iloc[0]\n",
"# sub_inter_node = self.inter_node[self.inter_node.inter_no==parent_no]\n",
"# ch2pa[child_id] = sub_inter_node[sub_inter_node.inter_type=='parent'].iloc[0].node_id\n",
"# directions = ['북', '북동', '동', '남동', '남', '남서', '서', '북서'] # 정북기준 시계방향으로 8방향\n",
"\n",
"# # 각 uturn node에 대하여 (inc_edge_id, out_edge_id) 부여\n",
"# cmatches = []\n",
"# for _, row in self.uturn.iterrows():\n",
"# child_id = row.child_id\n",
"# parent_id = row.parent_id\n",
"# direction = row.direction\n",
"# condition = row.condition\n",
"# inc_edge_id = row.inc_edge\n",
"# out_edge_id = row.out_edge\n",
"# # match5에서 parent_id에 해당하는 행들을 가져옴\n",
"# cmatch = self.match5.copy()[self.match5.node_id==parent_id] # match dataframe for a child node\n",
"# cmatch = cmatch.sort_values(by=['phase_no', 'ring_type']).reset_index(drop=True)\n",
"# cmatch['node_id'] = child_id\n",
"# cmatch[['inc_edge', 'out_edge']] = np.nan\n",
"\n",
"# # condition 별로 inc_dire, out_dire_A, out_dire_B를 정함\n",
"# ind = directions.index(direction)\n",
"# if condition == \"좌회전시\":\n",
"# inc_dire = direction\n",
"# out_dire_A = out_dire_B = directions[(ind + 2) % len(directions)]\n",
"# elif condition == \"보행신호시\":\n",
"# inc_dire = directions[(ind + 2) % len(directions)]\n",
"# out_dire_A = directions[(ind - 2) % len(directions)]\n",
"# out_dire_B = directions[(ind - 2) % len(directions)]\n",
"# print(child_id, ((cmatch.inc_dir==inc_dire) & (cmatch.out_dir==out_dire_A)).any())\n",
"# # (inc_dire, out_dire_A, out_dire_B) 별로 inc_edge_id, out_edge_id를 정함\n",
"# cmatch.loc[(cmatch.inc_dir==inc_dire) & (cmatch.out_dir==out_dire_A), ['inc_edge', 'out_edge']] = [inc_edge_id, out_edge_id]\n",
"# cmatch.loc[(cmatch.inc_dir==inc_dire) & (cmatch.out_dir==out_dire_B), ['inc_edge', 'out_edge']] = [inc_edge_id, out_edge_id]\n",
"# if condition == '보행신호시':\n",
"# # 이동류번호가 17(보행신호)이면서 유턴노드방향으로 가는 신호가 없으면 (inc_edge_id, out_edge_id)를 부여한다.\n",
"# cmatch.loc[(cmatch.move_no==17) & (cmatch.out_dir!=direction), ['inc_edge', 'out_edge']] = [inc_edge_id, out_edge_id]\n",
"# # 유턴신호의 이동류번호를 19로 부여한다.\n",
"# cmatch.loc[(cmatch.inc_dir==inc_dire) & (cmatch.out_dir==out_dire_A), 'move_no'] = 19\n",
"# cmatch.loc[(cmatch.inc_dir==inc_dire) & (cmatch.out_dir==out_dire_B), 'move_no'] = 19\n",
"# cmatches.append(cmatch)\n",
"\n",
"# # 각 coordination node에 대하여 (inc_edge_id, out_edge_id) 부여\n",
"# self.coord['inter_no'] = self.coord['parent_id'].map(self.node2inter)\n",
"# self.coord = self.coord.rename(columns={'child_id':'node_id'})\n",
"# self.coord[['inc_dir', 'out_dir', 'inc_angle','out_angle']] = np.nan\n",
"# self.coord['move_no'] = 20\n",
"# self.coord = self.coord[['inter_no', 'phase_no', 'ring_type', 'move_no', 'inc_dir', 'out_dir', 'inc_angle','out_angle', 'inc_edge', 'out_edge', 'node_id']]\n",
"\n",
"# # display(coord)\n",
"# cmatches = pd.concat(cmatches)\n",
"# self.match6 = pd.concat([self.match5, cmatches, self.coord]).drop_duplicates().sort_values(by=['inter_no', 'node_id', 'phase_no', 'ring_type'])\n",
"# # self.match6.to_csv(os.path.join(self.path_intermediates, 'match6.csv'))"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"ename": "AttributeError",
"evalue": "'DailyPreprocessor' object has no attribute 'match6'",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[1;32mIn[5], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmatch6\u001b[49m\n",
"\u001b[1;31mAttributeError\u001b[0m: 'DailyPreprocessor' object has no attribute 'match6'"
]
}
],
"source": [
"self.match6"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"splits 딕셔너리 다시 만들기"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[37 39 55 29 0 0 0 0]\n",
"[37 39 25 59 0 0 0 0]\n",
"[ 37 76 131 160 160 160 160 160]\n",
"[ 37 76 101 160 160 160 160 160]\n",
"[ 37 76 101 131 160]\n",
"[37 39 25 30 29]\n",
"{(1, 1): 37, (2, 2): 39, (3, 3): 25, (3, 4): 55, (4, 4): 29, (4, 5): 59, (5, 5): 0, (6, 6): 0, (7, 7): 0, (8, 8): 0}\n",
"\n",
"[37 39 55 29 0 0 0 0]\n",
"[37 39 25 59 0 0 0 0]\n",
"[ 0 39 55 29 0 0 0 0]\n",
"[ 0 0 55 29 0 0 0 0]\n",
"[ 0 0 30 29 0 0 0 0]\n",
"[ 0 0 30 -1 0 0 0 0]\n",
"[ 0 0 30 -1 -29 0 0 0]\n"
]
}
],
"source": [
"import numpy as np\n",
"row = self.plan.iloc[0]\n",
"# print(row)\n",
"inter_no = row.inter_no\n",
"start_hour = row.start_hour\n",
"start_minute = row.start_minute\n",
"cycle = row.cycle\n",
"\n",
"dura_A = np.array(row[[f'dura_A{j}' for j in range(1, 9)]])\n",
"dura_B = np.array(row[[f'dura_B{j}' for j in range(1, 9)]])\n",
"\n",
"print(np.array(dura_A))\n",
"print(np.array(dura_B))\n",
"\n",
"cums_A = row[[f'dura_A{j}' for j in range(1,9)]].cumsum()\n",
"cums_B = row[[f'dura_B{j}' for j in range(1,9)]].cumsum()\n",
"\n",
"print(np.array(cums_A))\n",
"print(np.array(cums_B))\n",
"\n",
"detailed_cums = []\n",
"combined_row = np.unique(np.concatenate((cums_A,cums_B)))\n",
"print(combined_row)\n",
"detailed_durations = np.concatenate(([combined_row[0]], np.diff(combined_row)))\n",
"\n",
"print(detailed_durations)\n",
"\n",
"desired_dict = {(1, 1): 37, (2, 2): 39, (3, 3): 25, (3, 4): 55, (4, 4): 29, (4, 5): 59, (5, 5): 0, (6, 6): 0, (7, 7): 0, (8, 8): 0}\n",
"print(desired_dict)\n",
"\n",
"print()\n",
"print(dura_A)\n",
"print(dura_B)\n",
"j = 0\n",
"for i in range(len(detailed_durations)):\n",
" dura_A[j] -= detailed_durations[i]\n",
" print(dura_A)\n",
" j += 1"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[37 39 55 29 0 0 0 0]\n",
"[37 39 25 59 0 0 0 0]\n",
"[ 37 76 131 160 160 160 160 160]\n",
"[ 37 76 101 160 160 160 160 160]\n",
"[ 37 76 101 131 160]\n",
"[37 39 25 30 29]\n",
"{(1, 1): 37, (2, 2): 39, (3, 3): 25, (3, 4): 55, (4, 4): 29, (4, 5): 59, (5, 5): 0, (6, 6): 0, (7, 7): 0, (8, 8): 0}\n"
]
}
],
"source": [
"import numpy as np\n",
"row = self.plan.iloc[0]\n",
"inter_no = row.inter_no\n",
"start_hour = row.start_hour\n",
"start_minute = row.start_minute\n",
"cycle = row.cycle\n",
"\n",
"dura_A = row[[f'dura_A{j}' for j in range(1, 9)]]\n",
"dura_B = row[[f'dura_B{j}' for j in range(1, 9)]]\n",
"\n",
"print(np.array(dura_A))\n",
"print(np.array(dura_B))\n",
"\n",
"cums_A = row[[f'dura_A{j}' for j in range(1,9)]].cumsum()\n",
"cums_B = row[[f'dura_B{j}' for j in range(1,9)]].cumsum()\n",
"\n",
"print(np.array(cums_A))\n",
"print(np.array(cums_B))\n",
"\n",
"detailed_cums = []\n",
"combined_row = np.unique(np.concatenate((cums_A,cums_B)))\n",
"print(combined_row)\n",
"detailed_durations = np.concatenate(([combined_row[0]], np.diff(combined_row)))\n",
"\n",
"print(detailed_durations)\n",
"\n",
"duration_dict = {}\n",
"# 두 시리즈의 길이가 같다고 가정합니다.\n",
"for i in range(len(dura_A)):\n",
" # A와 B의 현시시간이 같은 경우\n",
" if dura_A[i] == dura_B[i]:\n",
" duration_dict[(i+1, i+1)] = dura_A[i]\n",
" # A와 B의 현시시간이 다른 경우\n",
" else:\n",
" duration_dict[(i+1, i+1)] = min(dura_A[i], dura_B[i])\n",
" duration_dict[(i+1, i+2)] = max(dura_A[i], dura_B[i])\n",
"\n",
"print(duration_dict)\n",
"# cums_A = row[[f'dura_A{j}' for j in range(1,9)]].cumsum()\n",
"# cums_B = row[[f'dura_B{j}' for j in range(1,9)]].cumsum()\n",
"# print(cums_A)\n",
"# print(cums_B)\n",
"# detailed_cums = []\n",
"# combined_row = np.unique(np.concatenate((cums_A,cums_B)))\n",
"# print(combined_row)\n",
"# detailed_durations = np.concatenate(([combined_row[0]], np.diff(combined_row)))\n",
"# print(detailed_durations)"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [],
"source": [
"# split, isplit : A,B 분리 혹은 통합시 사용될 수 있는 딕셔너리 \n",
"self.splits = {} # splits maps (inter_no, start_hour, start_minute) to split \n",
"for i, row in self.plan.iterrows():\n",
" inter_no = row.inter_no\n",
" start_hour = row.start_hour\n",
" start_minute = row.start_minute\n",
" cycle = row.cycle\n",
" cums_A = row[[f'dura_A{j}' for j in range(1,9)]].cumsum()\n",
" cums_B = row[[f'dura_B{j}' for j in range(1,9)]].cumsum()\n",
" self.splits[(inter_no, start_hour, start_minute)] = {} # split maps (phas_A, phas_B) to k\n",
" k = 0\n",
" for t in range(cycle):\n",
" new_phas_A = len(cums_A[cums_A < t]) + 1\n",
" new_phas_B = len(cums_B[cums_B < t]) + 1\n",
" if k == 0 or ((new_phas_A, new_phas_B) != (phas_A, phas_B)):\n",
" k += 1\n",
" phas_A = new_phas_A\n",
" phas_B = new_phas_B\n",
" self.splits[(inter_no, start_hour, start_minute)][(phas_A, phas_B)] = k\n",
"self.isplits = {} # the inverse of splits\n",
"for i in self.splits:\n",
" self.isplits[i] = {self.splits[i][k]:k for k in self.splits[i]} # isplit maps k to (phas_A, phas_B)\n"
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{(175, 0, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (3, 4): 4, (4, 4): 5},\n",
" (175, 7, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (3, 4): 4, (4, 4): 5},\n",
" (175, 9, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (3, 4): 4, (4, 4): 5},\n",
" (175, 18, 30): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (3, 4): 4, (4, 4): 5},\n",
" (176, 0, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3},\n",
" (176, 7, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3},\n",
" (176, 9, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3},\n",
" (176, 18, 30): {(1, 1): 1, (2, 2): 2, (3, 3): 3},\n",
" (177, 0, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4},\n",
" (177, 7, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4},\n",
" (177, 9, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4},\n",
" (177, 18, 30): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4},\n",
" (178, 0, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4},\n",
" (178, 7, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 3): 4, (4, 4): 5},\n",
" (178, 9, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 3): 4, (4, 4): 5},\n",
" (178, 18, 30): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 3): 4, (4, 4): 5},\n",
" (201, 0, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4, (5, 5): 5},\n",
" (201, 7, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4, (5, 5): 5},\n",
" (201, 9, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4, (5, 5): 5},\n",
" (201, 18, 30): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4, (5, 5): 5},\n",
" (202, 0, 0): {(1, 1): 1, (2, 2): 2},\n",
" (202, 7, 0): {(1, 1): 1, (2, 2): 2},\n",
" (202, 9, 0): {(1, 1): 1, (2, 2): 2},\n",
" (202, 18, 30): {(1, 1): 1, (2, 2): 2},\n",
" (206, 0, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4},\n",
" (206, 7, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4},\n",
" (206, 9, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4},\n",
" (206, 18, 30): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4},\n",
" (210, 0, 0): {(1, 1): 1, (1, 2): 2, (2, 2): 3, (3, 3): 4, (4, 4): 5},\n",
" (210, 7, 0): {(1, 1): 1, (1, 2): 2, (2, 2): 3, (3, 3): 4, (4, 4): 5},\n",
" (210, 9, 0): {(1, 1): 1, (1, 2): 2, (2, 2): 3, (3, 3): 4, (4, 4): 5},\n",
" (210, 18, 30): {(1, 1): 1, (1, 2): 2, (2, 2): 3, (3, 3): 4, (4, 4): 5}}"
]
},
"execution_count": 49,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"self.splits"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "rts",
"language": "python",
"name": "rts"
},
"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
}

+ 0
- 548
Analysis/0207_uturn_code_change/0207_uturn_code_change.ipynb View File

@ -1,548 +0,0 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1. 데이터를 로드합니다.\n",
"1-1. 네트워크가 로드되었습니다.\n",
"1-2. 테이블들이 로드되었습니다.\n",
"1-3. 네트워크의 모든 clean state requirement들을 체크했습니다.\n",
"1-4. 테이블들의 무결성 검사를 완료했습니다.\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"이동류정보 불러오는 중: 100%|██████████| 17280/17280 [00:13<00:00, 1247.47it/s]\n"
]
}
],
"source": [
"import sys\n",
"from datetime import datetime\n",
"sys.path.append('../../Scripts')\n",
"from preprocess_daily import DailyPreprocessor\n",
"self = DailyPreprocessor()\n",
"\n",
"# 1. 데이터 준비\n",
"self.load_data()\n",
"\n",
"self.make_match1()\n",
"self.make_match2()\n",
"self.make_match3()\n",
"self.make_match4()\n",
"self.make_match5()"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"u00 True\n",
"u20 False\n",
"u30 True\n",
"u31 True\n",
"u32 True\n",
"u60 True\n"
]
}
],
"source": [
"self.node2inter = dict(zip(self.inter_node['node_id'], self.inter_node['inter_no']))\n",
"\n",
"child_ids = self.inter_node[self.inter_node.inter_type=='child'].node_id.unique()\n",
"ch2pa = {} # child to parent\n",
"for child_id in child_ids:\n",
" parent_no = self.inter_node[self.inter_node.node_id==child_id].inter_no.iloc[0]\n",
" sub_inter_node = self.inter_node[self.inter_node.inter_no==parent_no]\n",
" ch2pa[child_id] = sub_inter_node[sub_inter_node.inter_type=='parent'].iloc[0].node_id\n",
"directions = ['북', '북동', '동', '남동', '남', '남서', '서', '북서'] # 정북기준 시계방향으로 8방향\n",
"\n",
"# 각 uturn node에 대하여 (inc_edge_id, out_edge_id) 부여\n",
"cmatches = []\n",
"for _, row in self.uturn.iterrows():\n",
" child_id = row.child_id\n",
" parent_id = row.parent_id\n",
" direction = row.direction\n",
" condition = row.condition\n",
" inc_edge_id = row.inc_edge\n",
" out_edge_id = row.out_edge\n",
" # match5에서 parent_id에 해당하는 행들을 가져옴\n",
" cmatch = self.match5.copy()[self.match5.node_id==parent_id] # match dataframe for a child node\n",
" cmatch = cmatch.sort_values(by=['phase_no', 'ring_type']).reset_index(drop=True)\n",
" cmatch['node_id'] = child_id\n",
" cmatch[['inc_edge', 'out_edge']] = np.nan\n",
"\n",
" # condition 별로 inc_dire, out_dire_A, out_dire_B를 정함\n",
" ind = directions.index(direction)\n",
" if condition == \"좌회전시\":\n",
" inc_dire = direction\n",
" out_dire_A = out_dire_B = directions[(ind + 2) % len(directions)]\n",
" elif condition == \"보행신호시\":\n",
" inc_dire = directions[(ind + 2) % len(directions)]\n",
" out_dire_A = directions[(ind - 2) % len(directions)]\n",
" out_dire_B = directions[(ind - 2) % len(directions)]\n",
" print(child_id, ((cmatch.inc_dir==inc_dire) & (cmatch.out_dir==out_dire_A)).any())\n",
" # (inc_dire, out_dire_A, out_dire_B) 별로 inc_edge_id, out_edge_id를 정함\n",
" cmatch.loc[(cmatch.inc_dir==inc_dire) & (cmatch.out_dir==out_dire_A), ['inc_edge', 'out_edge']] = [inc_edge_id, out_edge_id]\n",
" cmatch.loc[(cmatch.inc_dir==inc_dire) & (cmatch.out_dir==out_dire_B), ['inc_edge', 'out_edge']] = [inc_edge_id, out_edge_id]\n",
" if condition == '보행신호시':\n",
" # 이동류번호가 17(보행신호)이면서 유턴노드방향으로 가는 신호가 없으면 (inc_edge_id, out_edge_id)를 부여한다.\n",
" cmatch.loc[(cmatch.move_no==17) & (cmatch.out_dir!=direction), ['inc_edge', 'out_edge']] = [inc_edge_id, out_edge_id]\n",
" # 유턴신호의 이동류번호를 19로 부여한다.\n",
" cmatch.loc[(cmatch.inc_dir==inc_dire) & (cmatch.out_dir==out_dire_A), 'move_no'] = 19\n",
" cmatch.loc[(cmatch.inc_dir==inc_dire) & (cmatch.out_dir==out_dire_B), 'move_no'] = 19\n",
" cmatches.append(cmatch)\n",
"\n",
"# 각 coordination node에 대하여 (inc_edge_id, out_edge_id) 부여\n",
"self.coord['inter_no'] = self.coord['parent_id'].map(self.node2inter)\n",
"self.coord = self.coord.rename(columns={'child_id':'node_id'})\n",
"self.coord[['inc_dir', 'out_dir', 'inc_angle','out_angle']] = np.nan\n",
"self.coord['move_no'] = 20\n",
"self.coord = self.coord[['inter_no', 'phase_no', 'ring_type', 'move_no', 'inc_dir', 'out_dir', 'inc_angle','out_angle', 'inc_edge', 'out_edge', 'node_id']]\n",
"\n",
"# display(coord)\n",
"cmatches = pd.concat(cmatches)\n",
"self.match6 = pd.concat([self.match5, cmatches, self.coord]).drop_duplicates().sort_values(by=['inter_no', 'node_id', 'phase_no', 'ring_type'])\n",
"# self.match6.to_csv(os.path.join(self.path_intermediates, 'match6.csv'))"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>inter_no</th>\n",
" <th>phase_no</th>\n",
" <th>ring_type</th>\n",
" <th>move_no</th>\n",
" <th>inc_dir</th>\n",
" <th>out_dir</th>\n",
" <th>inc_angle</th>\n",
" <th>out_angle</th>\n",
" <th>inc_edge</th>\n",
" <th>out_edge</th>\n",
" <th>node_id</th>\n",
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" <tr>\n",
" <th>0</th>\n",
" <td>175</td>\n",
" <td>1</td>\n",
" <td>A</td>\n",
" <td>8</td>\n",
" <td>남</td>\n",
" <td>북</td>\n",
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" <td>004</td>\n",
" <td>-571542797_02</td>\n",
" <td>571500487_01</td>\n",
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" <td>북</td>\n",
" <td>남</td>\n",
" <td>003</td>\n",
" <td>176</td>\n",
" <td>-571500487_01</td>\n",
" <td>571542797_02</td>\n",
" <td>i0</td>\n",
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" <tr>\n",
" <th>2</th>\n",
" <td>175</td>\n",
" <td>2</td>\n",
" <td>A</td>\n",
" <td>7</td>\n",
" <td>북</td>\n",
" <td>동</td>\n",
" <td>001</td>\n",
" <td>095</td>\n",
" <td>-571500487_01</td>\n",
" <td>571545870_01</td>\n",
" <td>i0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>175</td>\n",
" <td>2</td>\n",
" <td>B</td>\n",
" <td>3</td>\n",
" <td>남</td>\n",
" <td>서</td>\n",
" <td>179</td>\n",
" <td>270</td>\n",
" <td>-571542797_02</td>\n",
" <td>571510153_01</td>\n",
" <td>i0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>175</td>\n",
" <td>3</td>\n",
" <td>A</td>\n",
" <td>6</td>\n",
" <td>동</td>\n",
" <td>서</td>\n",
" <td>090</td>\n",
" <td>270</td>\n",
" <td>571545870_02</td>\n",
" <td>571510153_01</td>\n",
" <td>i0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>210</td>\n",
" <td>2</td>\n",
" <td>B</td>\n",
" <td>2</td>\n",
" <td>서</td>\n",
" <td>동</td>\n",
" <td>270</td>\n",
" <td>090</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>u60</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>210</td>\n",
" <td>3</td>\n",
" <td>A</td>\n",
" <td>7</td>\n",
" <td>북</td>\n",
" <td>동</td>\n",
" <td>359</td>\n",
" <td>090</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>u60</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>210</td>\n",
" <td>3</td>\n",
" <td>B</td>\n",
" <td>4</td>\n",
" <td>북</td>\n",
" <td>남</td>\n",
" <td>000</td>\n",
" <td>180</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>u60</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>210</td>\n",
" <td>4</td>\n",
" <td>A</td>\n",
" <td>8</td>\n",
" <td>남</td>\n",
" <td>북</td>\n",
" <td>180</td>\n",
" <td>000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>u60</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>210</td>\n",
" <td>4</td>\n",
" <td>B</td>\n",
" <td>3</td>\n",
" <td>남</td>\n",
" <td>서</td>\n",
" <td>180</td>\n",
" <td>270</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>u60</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>116 rows × 11 columns</p>\n",
"</div>"
],
"text/plain": [
" inter_no phase_no ring_type move_no inc_dir out_dir inc_angle out_angle \\\n",
"0 175 1 A 8 남 북 179 004 \n",
"1 175 1 B 4 북 남 003 176 \n",
"2 175 2 A 7 북 동 001 095 \n",
"3 175 2 B 3 남 서 179 270 \n",
"4 175 3 A 6 동 서 090 270 \n",
".. ... ... ... ... ... ... ... ... \n",
"3 210 2 B 2 서 동 270 090 \n",
"4 210 3 A 7 북 동 359 090 \n",
"5 210 3 B 4 북 남 000 180 \n",
"6 210 4 A 8 남 북 180 000 \n",
"7 210 4 B 3 남 서 180 270 \n",
"\n",
" inc_edge out_edge node_id \n",
"0 -571542797_02 571500487_01 i0 \n",
"1 -571500487_01 571542797_02 i0 \n",
"2 -571500487_01 571545870_01 i0 \n",
"3 -571542797_02 571510153_01 i0 \n",
"4 571545870_02 571510153_01 i0 \n",
".. ... ... ... \n",
"3 NaN NaN u60 \n",
"4 NaN NaN u60 \n",
"5 NaN NaN u60 \n",
"6 NaN NaN u60 \n",
"7 NaN NaN u60 \n",
"\n",
"[116 rows x 11 columns]"
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"self.match6"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"splits 딕셔너리 다시 만들기"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"dura_A1 37\n",
"dura_A2 39\n",
"dura_A3 55\n",
"dura_A4 29\n",
"dura_A5 0\n",
"dura_A6 0\n",
"dura_A7 0\n",
"dura_A8 0\n",
"Name: 0, dtype: int64\n",
"dura_B1 37\n",
"dura_B2 39\n",
"dura_B3 25\n",
"dura_B4 59\n",
"dura_B5 0\n",
"dura_B6 0\n",
"dura_B7 0\n",
"dura_B8 0\n",
"Name: 0, dtype: int64\n"
]
},
{
"ename": "NameError",
"evalue": "name 'dura_A' is not defined",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[1;32mIn[53], line 11\u001b[0m\n\u001b[0;32m 9\u001b[0m duration_dict \u001b[38;5;241m=\u001b[39m {}\n\u001b[0;32m 10\u001b[0m \u001b[38;5;66;03m# 두 시리즈의 길이가 같다고 가정합니다.\u001b[39;00m\n\u001b[1;32m---> 11\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;28mlen\u001b[39m(\u001b[43mdura_A\u001b[49m)):\n\u001b[0;32m 12\u001b[0m \u001b[38;5;66;03m# A와 B의 현시간이 같은 경우\u001b[39;00m\n\u001b[0;32m 13\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m dura_A[i] \u001b[38;5;241m==\u001b[39m dura_B[i]:\n\u001b[0;32m 14\u001b[0m duration_dict[(i\u001b[38;5;241m+\u001b[39m\u001b[38;5;241m1\u001b[39m, i\u001b[38;5;241m+\u001b[39m\u001b[38;5;241m1\u001b[39m)] \u001b[38;5;241m=\u001b[39m dura_A[i]\n",
"\u001b[1;31mNameError\u001b[0m: name 'dura_A' is not defined"
]
}
],
"source": [
"import numpy as np\n",
"row = self.plan.iloc[0]\n",
"inter_no = row.inter_no\n",
"start_hour = row.start_hour\n",
"start_minute = row.start_minute\n",
"cycle = row.cycle\n",
"print(row[[f'dura_A{j}' for j in range(1,9)]])\n",
"print(row[[f'dura_B{j}' for j in range(1,9)]])\n",
"\n",
"\n",
"dura_A = row[[f'dura_A{j}' for j in range(1, 9)]]\n",
"dura_B = row[[f'dura_B{j}' for j in range(1, 9)]]\n",
"\n",
"duration_dict = {}\n",
"# 두 시리즈의 길이가 같다고 가정합니다.\n",
"for i in range(len(dura_A)):\n",
" # A와 B의 현시간이 같은 경우\n",
" if dura_A[i] == dura_B[i]:\n",
" duration_dict[(i+1, i+1)] = dura_A[i]\n",
" # A와 B의 현시간이 다른 경우\n",
" else:\n",
" duration_dict[(i+1, i+1)] = min(dura_A[i], dura_B[i])\n",
" duration_dict[(i+1, i+2)] = max(dura_A[i], dura_B[i])\n",
"\n",
"print(duration_dict)\n",
"# cums_A = row[[f'dura_A{j}' for j in range(1,9)]].cumsum()\n",
"# cums_B = row[[f'dura_B{j}' for j in range(1,9)]].cumsum()\n",
"# print(cums_A)\n",
"# print(cums_B)\n",
"# detailed_cums = []\n",
"# combined_row = np.unique(np.concatenate((cums_A,cums_B)))\n",
"# print(combined_row)\n",
"# detailed_durations = np.concatenate(([combined_row[0]], np.diff(combined_row)))\n",
"# print(detailed_durations)"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [],
"source": [
"# split, isplit : A,B 분리 혹은 통합시 사용될 수 있는 딕셔너리 \n",
"self.splits = {} # splits maps (inter_no, start_hour, start_minute) to split \n",
"for i, row in self.plan.iterrows():\n",
" inter_no = row.inter_no\n",
" start_hour = row.start_hour\n",
" start_minute = row.start_minute\n",
" cycle = row.cycle\n",
" cums_A = row[[f'dura_A{j}' for j in range(1,9)]].cumsum()\n",
" cums_B = row[[f'dura_B{j}' for j in range(1,9)]].cumsum()\n",
" self.splits[(inter_no, start_hour, start_minute)] = {} # split maps (phas_A, phas_B) to k\n",
" k = 0\n",
" for t in range(cycle):\n",
" new_phas_A = len(cums_A[cums_A < t]) + 1\n",
" new_phas_B = len(cums_B[cums_B < t]) + 1\n",
" if k == 0 or ((new_phas_A, new_phas_B) != (phas_A, phas_B)):\n",
" k += 1\n",
" phas_A = new_phas_A\n",
" phas_B = new_phas_B\n",
" self.splits[(inter_no, start_hour, start_minute)][(phas_A, phas_B)] = k\n",
"self.isplits = {} # the inverse of splits\n",
"for i in self.splits:\n",
" self.isplits[i] = {self.splits[i][k]:k for k in self.splits[i]} # isplit maps k to (phas_A, phas_B)\n"
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{(175, 0, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (3, 4): 4, (4, 4): 5},\n",
" (175, 7, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (3, 4): 4, (4, 4): 5},\n",
" (175, 9, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (3, 4): 4, (4, 4): 5},\n",
" (175, 18, 30): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (3, 4): 4, (4, 4): 5},\n",
" (176, 0, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3},\n",
" (176, 7, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3},\n",
" (176, 9, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3},\n",
" (176, 18, 30): {(1, 1): 1, (2, 2): 2, (3, 3): 3},\n",
" (177, 0, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4},\n",
" (177, 7, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4},\n",
" (177, 9, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4},\n",
" (177, 18, 30): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4},\n",
" (178, 0, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4},\n",
" (178, 7, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 3): 4, (4, 4): 5},\n",
" (178, 9, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 3): 4, (4, 4): 5},\n",
" (178, 18, 30): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 3): 4, (4, 4): 5},\n",
" (201, 0, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4, (5, 5): 5},\n",
" (201, 7, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4, (5, 5): 5},\n",
" (201, 9, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4, (5, 5): 5},\n",
" (201, 18, 30): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4, (5, 5): 5},\n",
" (202, 0, 0): {(1, 1): 1, (2, 2): 2},\n",
" (202, 7, 0): {(1, 1): 1, (2, 2): 2},\n",
" (202, 9, 0): {(1, 1): 1, (2, 2): 2},\n",
" (202, 18, 30): {(1, 1): 1, (2, 2): 2},\n",
" (206, 0, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4},\n",
" (206, 7, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4},\n",
" (206, 9, 0): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4},\n",
" (206, 18, 30): {(1, 1): 1, (2, 2): 2, (3, 3): 3, (4, 4): 4},\n",
" (210, 0, 0): {(1, 1): 1, (1, 2): 2, (2, 2): 3, (3, 3): 4, (4, 4): 5},\n",
" (210, 7, 0): {(1, 1): 1, (1, 2): 2, (2, 2): 3, (3, 3): 4, (4, 4): 5},\n",
" (210, 9, 0): {(1, 1): 1, (1, 2): 2, (2, 2): 3, (3, 3): 4, (4, 4): 5},\n",
" (210, 18, 30): {(1, 1): 1, (1, 2): 2, (2, 2): 3, (3, 3): 4, (4, 4): 5}}"
]
},
"execution_count": 49,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"self.splits"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "rts",
"language": "python",
"name": "rts"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
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"pygments_lexer": "ipython3",
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Documents/김선중_신호생성(240207).pptx View File


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Scripts/__pycache__/preprocess_daily.cpython-38.pyc View File


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