diff --git a/Analysis/0207_code_reivision/0207_code_reivision.ipynb b/Analysis/0207_code_reivision/0207_code_reivision.ipynb new file mode 100644 index 000000000..02d34e398 --- /dev/null +++ b/Analysis/0207_code_reivision/0207_code_reivision.ipynb @@ -0,0 +1,441 @@ +{ + "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 +} diff --git a/Analysis/0207_uturn_code_change/0207_uturn_code_change.ipynb b/Analysis/0207_uturn_code_change/0207_uturn_code_change.ipynb deleted file mode 100644 index 615b0654d..000000000 --- a/Analysis/0207_uturn_code_change/0207_uturn_code_change.ipynb +++ /dev/null @@ -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": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
inter_nophase_noring_typemove_noinc_dirout_dirinc_angleout_angleinc_edgeout_edgenode_id
01751A8남북179004-571542797_02571500487_01i0
11751B4북남003176-571500487_01571542797_02i0
21752A7북동001095-571500487_01571545870_01i0
31752B3남서179270-571542797_02571510153_01i0
41753A6동서090270571545870_02571510153_01i0
....................................
32102B2서동270090NaNNaNu60
42103A7북동359090NaNNaNu60
52103B4북남000180NaNNaNu60
62104A8남북180000NaNNaNu60
72104B3남서180270NaNNaNu60
\n", - "

116 rows × 11 columns

\n", - "
" - ], - "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", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.10" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/Documents/김선중_신호생성(240207).pptx b/Documents/김선중_신호생성(240207).pptx index c96317a82..4e9aaa696 100644 Binary files a/Documents/김선중_신호생성(240207).pptx and b/Documents/김선중_신호생성(240207).pptx differ diff --git a/Scripts/__pycache__/preprocess_daily.cpython-38.pyc b/Scripts/__pycache__/preprocess_daily.cpython-38.pyc index 5ec61e524..6694b8dc9 100644 Binary files a/Scripts/__pycache__/preprocess_daily.cpython-38.pyc and b/Scripts/__pycache__/preprocess_daily.cpython-38.pyc differ