diff --git a/Scripts/__pycache__/generate_signals.cpython-312.pyc b/Scripts/__pycache__/generate_signals.cpython-312.pyc index be7fc7a60..c1e4b41ab 100644 Binary files a/Scripts/__pycache__/generate_signals.cpython-312.pyc and b/Scripts/__pycache__/generate_signals.cpython-312.pyc differ diff --git a/Scripts/__pycache__/preprocess_daily.cpython-312.pyc b/Scripts/__pycache__/preprocess_daily.cpython-312.pyc index 5405eacb0..9d8021a63 100644 Binary files a/Scripts/__pycache__/preprocess_daily.cpython-312.pyc and b/Scripts/__pycache__/preprocess_daily.cpython-312.pyc differ diff --git a/Scripts/generate_signals.py b/Scripts/generate_signals.py index bd4b42a01..c2ef0426a 100644 --- a/Scripts/generate_signals.py +++ b/Scripts/generate_signals.py @@ -307,6 +307,19 @@ class SignalGenerator(): inter_no = self.node2inter[parent_id] self.pa2ch[parent_id] = list(self.inter_node[(self.inter_node.inter_no==inter_no) & (self.inter_node.inter_type=='child')].node_id) + # 유효한 노드들만을 다시 id 목록 정의 + # (history 기준으로 유효함을 설정했으나, 추후 더 조건이 필요할 수 있음) + valid_parent_ids = [self.inter2node[inter_no] for inter_no in set(self.history.inter_no)] + invalid_parent_ids = [parent_id for parent_id in self.parent_ids if not parent_id in valid_parent_ids ] + invalid_child_ids = [] + for parent_id in invalid_parent_ids: + invalid_child_ids.extend(self.pa2ch[parent_id]) + self.parent_ids = sorted(set(self.parent_ids) - set(invalid_parent_ids)) + self.node_ids = sorted(set(self.node_ids) - set(invalid_parent_ids)) + self.child_ids = sorted(set(self.child_ids) - set(invalid_child_ids)) + self.uturn_ids = sorted(set(self.uturn_ids) - set(invalid_child_ids)) + self.coord_ids = sorted(set(self.coord_ids) - set(invalid_child_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() 함수를 사용해 파일 내용을 Python 딕셔너리로 불러옵니다. @@ -748,7 +761,18 @@ class SignalGenerator(): self.sigtable = [] sim_start = self.present_time - self.sim_timespan for node_id, group in self.histids.groupby('node_id'): - lsbs = group[group['start_unix'] < sim_start]['start_unix'].max() # the last start_unix before sim_start + series = group[group['start_unix'] < sim_start]['start_unix'] + # lsbs : the last start_unix before sim_start + if len(series): + lsbs = series.max() + else: + min_start_unix = int(group['start_unix'].min()) + inter_no = self.node2inter[node_id] + _, prow = self.load_prow(inter_no, min_start_unix) + cycle = prow.iloc[0]['cycle'] + lsbs = min_start_unix + while lsbs > sim_start: + lsbs -= cycle self.offsets[node_id] = lsbs - sim_start group = group[group.start_unix >= lsbs] start_unixes = np.array(group.start_unix) @@ -857,6 +881,14 @@ class SignalGenerator(): # 5-2-3 helper function of 5-2 def cumulate(self, sig, alph): + + sig[f'phas_{alph}'] = sig[f'phas_{alph}'].astype(int) + # 만약 현시번호가 1로 일정하면 2현시를 가상으로 추가 + if (sig[f'phas_{alph}']==1).all(): + sig_dup = sig.copy() + sig_dup[f'phas_{alph}'] = 2 + sig = pd.concat([sig, sig_dup]).sort_values(by=['start_unix', f'phas_{alph}']) + csig = [] # cumulated sig pre = pd.Series({f'phas_{alph}':None}) diff --git a/Scripts/preprocess_daily.py b/Scripts/preprocess_daily.py index 9575920be..4fda29ee3 100644 --- a/Scripts/preprocess_daily.py +++ b/Scripts/preprocess_daily.py @@ -23,6 +23,7 @@ class DailyPreprocessor(): 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_network = os.path.join(self.path_root, *self.paths['network']) self.path_scripts = os.path.join(self.path_root, *self.paths['scripts']) # 이슈사항 목록 @@ -40,7 +41,7 @@ class DailyPreprocessor(): # 1-1. 네트워크 불러오기 def load_networks(self): - self.net = sumolib.net.readNet(os.path.join(self.path_networks, self.file_net)) + self.net = sumolib.net.readNet(self.path_network) print("1-1. 네트워크가 로드되었습니다.") # 1-2. 테이블 불러오기 @@ -734,7 +735,7 @@ class DailyPreprocessor(): all_redsigns = (cmatch.move_no==18) & ~ out_true # 보행신호시/좌회전시 진입/진출 엣지id 배정 - cmatch[['inc_edge_id', 'out_edge_id']] = np.nan + cmatch[['inc_edge_id', 'out_edge_id']] = None if condition == "보행신호시": cmatch.loc[pedes_flag, ['inc_edge_id', 'out_edge_id']] = [inc_edge_id, out_edge_id] elif condition == "좌회전시": diff --git a/analysis/0725_main_test/4_use_class_pd.ipynb b/analysis/0725_main_test/4_use_class_pd.ipynb index e175d74fd..2f9c414c8 100644 --- a/analysis/0725_main_test/4_use_class_pd.ipynb +++ b/analysis/0725_main_test/4_use_class_pd.ipynb @@ -25,7 +25,7 @@ "metadata": {}, "outputs": [], "source": [ - "self = DailyPreprocessor(config_name='test_0731',\n", + "self = DailyPreprocessor(config_name = 'test_0731',\n", " file_net = 'new_sungnam_network_internal_target_0721.net.xml')" ] }, @@ -69,29 +69,24 @@ "cell_type": "code", "execution_count": 5, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1-5. 테이블을 표준화했습니다.\n" + ] + } + ], "source": [ - "# self.angle" + "# 1-5. 테이블 표준화\n", + "self.standardize()" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, - "outputs": [], - "source": [ - "# angle_A = self.angle[self.angle.ring_type=='A']\n", - "# angle_B = self.angle[self.angle.ring_type=='B']\n", - "# isa2move_A = dict(zip(zip(angle_A.inter_no, angle_A.STOS_NO, angle_A.phase_no), angle_A.move_no))\n", - "# isa2move_B = dict(zip(zip(angle_B.inter_no, angle_B.STOS_NO, angle_B.phase_no), angle_B.move_no))\n", - "# isa2move = {'A':isa2move_A, 'B':isa2move_B}\n", - "# isa2move" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, "outputs": [ { "name": "stdout", @@ -108,20 +103,7 @@ }, { "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "self.parent_ids = sorted(self.inter_node[self.inter_node.inter_type=='parent'].node_id.unique())\n", - "self.child_ids = sorted(self.inter_node[self.inter_node.inter_type=='child'].node_id.unique())\n", - "self.uturn_ids = sorted(self.uturn.child_id.unique())\n", - "self.coord_ids = sorted(self.coord.child_id.unique())\n", - "self.node_ids = self.parent_ids + self.child_id" - ] - }, - { - "cell_type": "code", - "execution_count": 10, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -139,7 +121,148 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "self.make_match1()\n", + "self.make_match2()\n", + "self.make_match3()\n", + "self.make_match4()\n", + "self.make_match5()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "self.uturn = pd.merge(self.uturn, self.u_condition, on='child_id')\n", + "\n", + "# p2inc_edge2angle : node_id to inc_edge2angle\n", + "p2inc_edge2angle = dict()\n", + "# p2out_edge2angle : node_id to out_edge2angle\n", + "p2out_edge2angle = dict()\n", + "# p2inc_angle2edge : node_id to inc_angle2edge\n", + "p2inc_angle2edge = dict()\n", + "# p2out_angle2edge : node_id to out_angle2edge\n", + "p2out_angle2edge = dict()\n", + "for node_id in self.parent_ids:\n", + " m5 = self.match5[self.match5.node_id==node_id]\n", + " m5 = m5.dropna(subset=['inc_edge_id', 'out_edge_id'])\n", + " # inc_edge2angle : inc_edge_id to inc_angle\n", + " inc_edge2angle = dict(zip(m5.inc_edge_id, m5.inc_angle.astype(int)))\n", + " p2inc_edge2angle[node_id] = inc_edge2angle\n", + " # out_edge2angle : out_edge_id to out_angle\n", + " out_edge2angle = dict(zip(m5.out_edge_id, m5.out_angle.astype(int)))\n", + " p2out_edge2angle[node_id] = out_edge2angle\n", + " # inc_angle2edge : inc_angle to inc_edge_id\n", + " inc_angle2edge = dict(zip(m5.inc_angle.astype(int), m5.inc_edge_id))\n", + " p2inc_angle2edge[node_id] = inc_angle2edge\n", + " # out_angle2edge : out_angle to out_edge_id\n", + " out_angle2edge = dict(zip(m5.out_angle.astype(int), m5.out_edge_id))\n", + " p2out_angle2edge[node_id] = out_angle2edge\n", + "# 각 uturn node에 대하여 (inc_edge_id, out_edge_id) 부여\n", + "cmatches = []\n", + "row = self.uturn.iloc[0]\n", + "parent_id = row.parent_id\n", + "child_id = row.child_id\n", + "condition = row.condition\n", + "inc_edge_id = row.inc_edge_id\n", + "out_edge_id = row.out_edge_id\n", + "print(type(inc_edge_id))\n", + "adj_inc_edge_id = row.adj_inc_edge_id\n", + "adj_out_edge_id = row.adj_out_edge_id\n", + "\n", + "# match5에서 부모노드id에 해당하는 행들을 가져옴 (cmatch)\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['node_type'] = 'u_turn'\n", + "\n", + "# 진입엣지 각도\n", + "inc_angle = p2inc_edge2angle[parent_id][adj_inc_edge_id]\n", + "\n", + "# 이격각도\n", + "self.angle_separation = 10\n", + "\n", + "# 진입로 각도 목록\n", + "inc_angles = cmatch.dropna(subset=['inc_angle', 'out_angle']).inc_angle.astype(int).unique()\n", + "inc_angles = np.sort(inc_angles)\n", + "inc_angles = list(inc_angles - 360) + list(inc_angles) + list(inc_angles + 360)\n", + "inc_angles = np.array(inc_angles)\n", + "\n", + "# 보행신호시의 진입로 각도\n", + "inc_angles_left = inc_angles[inc_angles >= inc_angle + self.angle_separation]\n", + "inc_angle_pedes = np.sort(inc_angles_left)[0] % 360\n", + "\n", + "# 보행신호시의 진입로 엣지id\n", + "inc_angle2edge = p2inc_angle2edge[parent_id]\n", + "inc_edge_id_pedes = inc_angle2edge[inc_angle_pedes]\n", + "\n", + "# 진출로 각도 목록\n", + "out_angles = cmatch.dropna(subset=['inc_angle', 'out_angle']).out_angle.astype(int).unique()\n", + "out_angles = np.sort(out_angles)\n", + "out_angles = list(out_angles - 360) + list(out_angles) + list(out_angles + 360)\n", + "out_angles = np.array(out_angles)\n", + "\n", + "# 보행신호시의 진출로 각도\n", + "out_angles_right = out_angles[out_angles <= inc_angle - self.angle_separation]\n", + "out_angle_pedes = np.sort(out_angles_right)[-1] % 360\n", + "\n", + "# 보행신호시의 진출로 엣지id\n", + "out_angle2edge = p2out_angle2edge[parent_id]\n", + "out_edge_id_pedes = out_angle2edge[out_angle_pedes]\n", + "\n", + "# 진입엣지/진출엣지 포함 조건\n", + "inc_true = (cmatch.inc_edge_id==adj_inc_edge_id)\n", + "out_true = (cmatch.out_edge_id==adj_out_edge_id)\n", + "\n", + "# 보행신호시 조건\n", + "pedes_flag = (cmatch.inc_edge_id==inc_edge_id_pedes) & (cmatch.out_edge_id==out_edge_id_pedes)\n", + "\n", + "# 좌회전시 조건\n", + "right_flag = inc_true & (cmatch.turn_type=='left')\n", + "\n", + "# 보행신호이동류(17) 조건\n", + "crosswalk_on = (cmatch.move_no==17) & ~ out_true\n", + "\n", + "# 신호없음이동류(18) 조건\n", + "all_redsigns = (cmatch.move_no==18) & ~ out_true" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "print(type(inc_edge_id))\n", + "print(type(out_edge_id))\n", + "print(cmatch[['inc_edge_id', 'out_edge_id']].info())" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "print(inc_edge_id, out_edge_id)\n", + "# 보행신호시/좌회전시 진입/진출 엣지id 배정\n", + "cmatch[['inc_edge_id', 'out_edge_id']] = None\n", + "if condition == \"보행신호시\":\n", + " cmatch.loc[pedes_flag, ['inc_edge_id', 'out_edge_id']] = [inc_edge_id, out_edge_id]\n", + "elif condition == \"좌회전시\":\n", + " cmatch.loc[right_flag, ['inc_edge_id', 'out_edge_id']] = [inc_edge_id, out_edge_id]\n", + "\n", + "uturn_not_assigned = cmatch[['inc_edge_id','out_edge_id']].isna().any(axis=1).all()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -152,36 +275,6 @@ "2-4. 직진 및 좌회전(G)을 배정했습니다.\n", "2-5. node2num_cycles.json를 저장했습니다.\n" ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "c:\\github\\siggen\\scripts\\preprocess_daily.py:741: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '519797' has dtype incompatible with float64, please explicitly cast to a compatible dtype first.\n", - " cmatch.loc[right_flag, ['inc_edge_id', 'out_edge_id']] = [inc_edge_id, out_edge_id]\n", - "c:\\github\\siggen\\scripts\\preprocess_daily.py:741: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '519796' has dtype incompatible with float64, please explicitly cast to a compatible dtype first.\n", - " cmatch.loc[right_flag, ['inc_edge_id', 'out_edge_id']] = [inc_edge_id, out_edge_id]\n", - "c:\\github\\siggen\\scripts\\preprocess_daily.py:741: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '519799' has dtype incompatible with float64, please explicitly cast to a compatible dtype first.\n", - " cmatch.loc[right_flag, ['inc_edge_id', 'out_edge_id']] = [inc_edge_id, out_edge_id]\n", - "c:\\github\\siggen\\scripts\\preprocess_daily.py:741: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '519798' has dtype incompatible with float64, please explicitly cast to a compatible dtype first.\n", - " cmatch.loc[right_flag, ['inc_edge_id', 'out_edge_id']] = [inc_edge_id, out_edge_id]\n", - "c:\\github\\siggen\\scripts\\preprocess_daily.py:741: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '519801' has dtype incompatible with float64, please explicitly cast to a compatible dtype first.\n", - " cmatch.loc[right_flag, ['inc_edge_id', 'out_edge_id']] = [inc_edge_id, out_edge_id]\n", - "c:\\github\\siggen\\scripts\\preprocess_daily.py:741: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '519800' has dtype incompatible with float64, please explicitly cast to a compatible dtype first.\n", - " cmatch.loc[right_flag, ['inc_edge_id', 'out_edge_id']] = [inc_edge_id, out_edge_id]\n", - "c:\\github\\siggen\\scripts\\preprocess_daily.py:741: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '519873' has dtype incompatible with float64, please explicitly cast to a compatible dtype first.\n", - " cmatch.loc[right_flag, ['inc_edge_id', 'out_edge_id']] = [inc_edge_id, out_edge_id]\n", - "c:\\github\\siggen\\scripts\\preprocess_daily.py:741: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '519874' has dtype incompatible with float64, please explicitly cast to a compatible dtype first.\n", - " cmatch.loc[right_flag, ['inc_edge_id', 'out_edge_id']] = [inc_edge_id, out_edge_id]\n", - "c:\\github\\siggen\\scripts\\preprocess_daily.py:741: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '516929' has dtype incompatible with float64, please explicitly cast to a compatible dtype first.\n", - " cmatch.loc[right_flag, ['inc_edge_id', 'out_edge_id']] = [inc_edge_id, out_edge_id]\n", - "c:\\github\\siggen\\scripts\\preprocess_daily.py:741: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '517055' has dtype incompatible with float64, please explicitly cast to a compatible dtype first.\n", - " cmatch.loc[right_flag, ['inc_edge_id', 'out_edge_id']] = [inc_edge_id, out_edge_id]\n", - "c:\\github\\siggen\\scripts\\preprocess_daily.py:741: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '519834' has dtype incompatible with float64, please explicitly cast to a compatible dtype first.\n", - " cmatch.loc[right_flag, ['inc_edge_id', 'out_edge_id']] = [inc_edge_id, out_edge_id]\n", - "c:\\github\\siggen\\scripts\\preprocess_daily.py:741: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '519833' has dtype incompatible with float64, please explicitly cast to a compatible dtype first.\n", - " cmatch.loc[right_flag, ['inc_edge_id', 'out_edge_id']] = [inc_edge_id, out_edge_id]\n" - ] } ], "source": [ @@ -200,17 +293,9 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "3. 이슈사항을 저장합니다.\n" - ] - } - ], + "outputs": [], "source": [ "self.write_issues()" ] diff --git a/analysis/0725_main_test/6_use_class_gs.ipynb b/analysis/0725_main_test/6_use_class_gs.ipynb index 11655f98c..09d38c1c6 100644 --- a/analysis/0725_main_test/6_use_class_gs.ipynb +++ b/analysis/0725_main_test/6_use_class_gs.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -20,7 +20,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -44,7 +44,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -58,7 +58,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -75,7 +75,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -92,7 +92,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -117,7 +117,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -137,7 +137,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -154,123 +154,165 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "# valid_parent_ids = [self.inter2node[inter_no] for inter_no in set(self.history.inter_no)]\n", + "# invalid_parent_ids = [parent_id for parent_id in self.parent_ids if not parent_id in valid_parent_ids ]\n", + "# print(sorted(self.parent_ids))\n", + "# print(sorted(valid_parent_ids))\n", + "# print(sorted(invalid_parent_ids))\n", + "# invalid_child_ids = []\n", + "# for parent_id in invalid_parent_ids:\n", + "# invalid_child_ids.extend(self.pa2ch[parent_id])\n", + "# print(sorted(invalid_child_ids))\n", + "\n", + "# print()\n", + "# print()\n", + "# self.parent_ids = sorted(set(self.parent_ids) - set(invalid_parent_ids))\n", + "# self.node_ids = sorted(set(self.node_ids) - set(invalid_parent_ids))\n", + "# self.child_ids = sorted(set(self.child_ids) - set(invalid_child_ids))\n", + "# self.uturn_ids = sorted(set(self.uturn_ids) - set(invalid_child_ids))\n", + "# self.coord_ids = sorted(set(self.coord_ids) - set(invalid_child_ids))\n", + "# print(self.parent_ids)\n", + "# print(self.node_ids)\n", + "# print(self.child_ids)\n", + "# print(self.uturn_ids)\n", + "# print(self.coord_ids)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "2. 신호이력 테이블을 변환합니다.\n" - ] + "data": { + "text/plain": [ + "[436, 437, 442, 443, 455, 456, 457]" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "self.process_history()" + "sorted(inter_no for inter_no in set(self.history.inter_no))" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 12, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2. 신호이력 테이블을 변환합니다.\n" + ] + }, + { + "data": { + "text/plain": [ + "[436, 437, 442, 443, 455, 456, 457]" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "phases = pd.read_csv(os.path.join(self.path_tables, 'TL_IF_SIGL.csv'))\n", - "phases = phases.drop(columns=['FRST_REG_DT', 'RINGA_FLOW', 'RINGB_FLOW'])\n", - "phases = phases.rename(columns={\n", - " 'PHASE_DT':'start_unix','CRSRD_ID':'inter_no',\n", - " 'RINGA_PHASE':'phas_A', 'RINGB_PHASE':'phas_B',\n", - " 'MAP_MODE':'STOS_NO'\n", - " })\n", - "isp2move_A = self.isp2move['A']\n", - "isp2move_B = self.isp2move['B']\n", - "phases['move_A'] = phases.apply(\n", - " lambda row: int(isp2move_A.get((row.inter_no, row.STOS_NO, row.phas_A), -1)), axis=1)\n", - "phases['move_B'] = phases.apply(\n", - " lambda row: int(isp2move_B.get((row.inter_no, row.STOS_NO, row.phas_B), -1)), axis=1)\n", - "phases['start_unix'] = phases['start_unix'].apply(lambda x:int(datetime.strptime(x, '%Y-%m-%d %H:%M:%S').timestamp()))\n", - "phases = phases[phases.inter_no.isin(self.inter_nos)].reset_index(drop=True)\n", - "phases = phases.drop(columns='STOS_NO')\n", - "\n", - "# - 아래 절차를 5초마다 반복\n", - "fsecs = list(range(self.present_time - self.sim_timespan, self.present_time + 1, 5))\n", - "for fsec in range(self.present_time - self.sim_timespan, self.present_time + 1, 5): # fsec : unix time by Five SECond\n", - " # 1. 상태 테이블 조회해서 전체 데이터중 필요데이터(교차로번호, A링 현시번호, A링 이동류번호, B링 현시번호, B링 이동류번호)만 수집 : A\n", - " moves = [group.iloc[-1:] for _, group in phases[phases.start_unix <= fsec].groupby('inter_no')]\n", - " if not moves:\n", - " move = pd.DataFrame({'start_unix':[], 'inter_no':[], 'phas_A':[], 'phas_B':[], 'move_A':[], 'move_B':[]})\n", - " pass\n", - " else:\n", - " move = pd.concat(moves)\n", - " move = move.drop(columns='start_unix')\n", - " # move = pd.read_csv(os.path.join(self.path_tables, 'move', f'move_{fsec}.csv'))\n", - " # 2. 이력 테이블 조회해서 교차로별로 유닉스시간 최대인 데이터(교차로번호, 종료유닉스타임)만 수집 : B\n", - " recent_histories = [group.iloc[-1:] for _, group in self.history[self.history['end_unix'] < fsec].groupby('inter_no')] # 교차로별로 유닉스시간이 최대인 행들\n", - "\n", - " if not recent_histories:\n", - " rhistory = pd.DataFrame({'inter_no':[], 'end_unix':[]}) # recent history\n", - " else:\n", - " rhistory = pd.concat(recent_histories)\n", - " recent_unix = rhistory[['inter_no', 'end_unix']]\n", - " # 3. 상태 테이블 조회정보(A)와 이력 테이블 조회정보(B) 조인(키값 : 교차로번호) : C\n", - " move = pd.merge(move, recent_unix, how='left', on='inter_no')\n", - " # move['end_unix'] = move['end_unix'].fillna(0).astype(int)\n", - " # 4. C데이터 프레임에 신규 컬럼(시작 유닉스타임) 생성 후 종료유닉스 타임 값 입력, 종료 유닉스 타임 컬럼 제거\n", - " move = move.rename(columns = {'end_unix':'start_unix'})\n", - " # 5. 이동류 이력정보 READ\n", - " # - CSV 파일로 서버에 저장된 이동류정보를 읽어옴(파일이 없는 경우에는 데이터가 없는 프레임 D 생성)\n", - " try:\n", - " movement # movement가 존재할 경우 그걸 그대로 씀.\n", - " except NameError: # movement가 존재하지 않는 경우 생성\n", - " movement = pd.DataFrame()\n", - " # 6. 이동류 이력정보 데이터테이블(D)에 C데이터 add\n", - " movement = pd.concat([movement, move])\n", - " # 7. D데이터 프레임에서 중복데이터 제거(교차로번호, 시작 유닉스타임, A링 현시번호, B링 현시번호 같은 행은 제거)\n", - " movement = movement.drop_duplicates(['inter_no','phas_A','phas_B','start_unix'])\n", - " # # 8. D데이터 보관 시간 기준시간을 시작 유닉스 타임의 최대값 - self.subtractor // 2을 값으로 산출하고, 보관 시간 기준시간보다 작은 시작 유닉스 타임을 가진 행은 모두 제거(1시간 데이터만 보관)\n", - " movement = movement[movement.start_unix > fsec - self.subtractor // 2]\n", - "movement['start_unix'] = movement['start_unix'].astype(int)\n", - "self.movement = movement.reset_index(drop=True)\n", - "display(self.movement.head())" + "self.process_history()\n", + "sorted(inter_no for inter_no in set(self.rhistory.inter_no))" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[436, 437, 442, 443, 455, 456, 457]" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "self.update_movement()" + "sorted(inter_no for inter_no in set(self.rhists.inter_no))" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[436, 437, 442, 443, 455, 456, 457]" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# 4-1\n", - "self.merge_dfs()" + "sorted(inter_no for inter_no in set(self.hrhists.inter_no))" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "3. 이동류정보 테이블을 변환합니다.\n" + ] + }, + { + "data": { + "text/plain": [ + "[436, 437, 438, 442, 443, 444, 455, 456, 457, 458]" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# 4-2\n", - "self.assign_signals()" + "self.process_movement()\n", + "sorted(inter_no for inter_no in set(self.movement.inter_no))" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "4. 통합 테이블을 생성합니다.\n" + ] + } + ], "source": [ - "# 4-3\n", - "self.attach_children()" + "self.make_histids()" ] }, { @@ -280,170 +322,2890 @@ "outputs": [ { "data": { - "text/html": [ - "
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Use obj.ffill() or obj.bfill() instead.\n", + " SIG[['phas_A', 'state_A']] = SIG[['phas_A', 'state_A']].fillna(method='ffill')\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:826: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + " SIG[['phas_B', 'state_B']] = SIG[['phas_B', 'state_B']].fillna(method='ffill')\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:825: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + " SIG[['phas_A', 'state_A']] = SIG[['phas_A', 'state_A']].fillna(method='ffill')\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:826: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + " SIG[['phas_B', 'state_B']] = SIG[['phas_B', 'state_B']].fillna(method='ffill')\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:825: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + " SIG[['phas_A', 'state_A']] = SIG[['phas_A', 'state_A']].fillna(method='ffill')\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:826: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + " SIG[['phas_B', 'state_B']] = SIG[['phas_B', 'state_B']].fillna(method='ffill')\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:825: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + " SIG[['phas_A', 'state_A']] = SIG[['phas_A', 'state_A']].fillna(method='ffill')\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:826: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + " SIG[['phas_B', 'state_B']] = SIG[['phas_B', 'state_B']].fillna(method='ffill')\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:825: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + " SIG[['phas_A', 'state_A']] = SIG[['phas_A', 'state_A']].fillna(method='ffill')\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:826: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + " SIG[['phas_B', 'state_B']] = SIG[['phas_B', 'state_B']].fillna(method='ffill')\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:825: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + " SIG[['phas_A', 'state_A']] = SIG[['phas_A', 'state_A']].fillna(method='ffill')\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:826: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + " SIG[['phas_B', 'state_B']] = SIG[['phas_B', 'state_B']].fillna(method='ffill')\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:825: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + " SIG[['phas_A', 'state_A']] = SIG[['phas_A', 'state_A']].fillna(method='ffill')\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:826: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + " SIG[['phas_B', 'state_B']] = SIG[['phas_B', 'state_B']].fillna(method='ffill')\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:825: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + " SIG[['phas_A', 'state_A']] = SIG[['phas_A', 'state_A']].fillna(method='ffill')\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:826: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + " SIG[['phas_B', 'state_B']] = SIG[['phas_B', 'state_B']].fillna(method='ffill')\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:825: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + " SIG[['phas_A', 'state_A']] = SIG[['phas_A', 'state_A']].fillna(method='ffill')\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:826: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + " SIG[['phas_B', 'state_B']] = SIG[['phas_B', 'state_B']].fillna(method='ffill')\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:825: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + " SIG[['phas_A', 'state_A']] = SIG[['phas_A', 'state_A']].fillna(method='ffill')\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:826: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + " SIG[['phas_B', 'state_B']] = SIG[['phas_B', 'state_B']].fillna(method='ffill')\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:825: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + " SIG[['phas_A', 'state_A']] = SIG[['phas_A', 'state_A']].fillna(method='ffill')\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:826: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + " SIG[['phas_B', 'state_B']] = SIG[['phas_B', 'state_B']].fillna(method='ffill')\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:825: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + " SIG[['phas_A', 'state_A']] = SIG[['phas_A', 'state_A']].fillna(method='ffill')\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:826: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + " SIG[['phas_B', 'state_B']] = SIG[['phas_B', 'state_B']].fillna(method='ffill')\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:825: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + " SIG[['phas_A', 'state_A']] = SIG[['phas_A', 'state_A']].fillna(method='ffill')\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:826: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + " SIG[['phas_B', 'state_B']] = SIG[['phas_B', 'state_B']].fillna(method='ffill')\n" + ] + } + ], + "source": [ + "self.assign_red_yellow()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "455" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "self.node2inter[self.node_ids[11]]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " start_time phas_A state_A start_unix\n", + "0 0 1g GGrr 1722383976\n", + "1 59 1y GGrr 1722383976\n", + "2 63 2r GGrr 1722384066\n", + "3 63 2g GGrr 1722384066\n", + "4 122 2y GGrr 1722384066\n", + "5 126 1r GGrr 1722384067\n", + "6 126 1g GGrr 1722384067\n", + "7 185 1y GGrr 1722384067\n", + "8 189 2r GGrr 1722384155\n", + "9 189 2g GGrr 1722384155\n", + "10 248 2y GGrr 1722384155\n", + "11 252 1r GGrr 1722384156\n", + "12 252 1g GGrr 1722384156\n", + "13 311 1y GGrr 1722384156" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# csig_A = self.cumulate(sig_A, 'A')\n", + "sig = sig_A\n", + "alph = 'A'\n", + "csig = [] # cumulated sig\n", + "pre = pd.Series({f'phas_{alph}':None})\n", + "\n", + "sig[f'phas_{alph}'] = sig[f'phas_{alph}'].astype(int)\n", + "# 만약 현시번호가 1로 일정하면 2현시를 가상으로 추가\n", + "if (sig[f'phas_{alph}']==1).all():\n", + " sig_dup = sig.copy() \n", + " sig_dup[f'phas_{alph}'] = 2\n", + " sig = pd.concat([sig, sig_dup]).sort_values(by=['start_unix', f'phas_{alph}'])\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(self.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(self.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", + "csig\n" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "109901\n" + ] + }, + { + "data": { + "text/html": [ + "
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\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mA\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[0;32m 30\u001b[0m csig_B \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcumulate(sig_B, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mB\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m 31\u001b[0m display(csig_A)\n", + "File \u001b[1;32mc:\\github\\siggen\\scripts\\generate_signals.py:942\u001b[0m, in \u001b[0;36mSignalGenerator.cumulate\u001b[1;34m(self, sig, alph)\u001b[0m\n\u001b[0;32m 940\u001b[0m sig_[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mstart_unix\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m start_unix\n\u001b[0;32m 941\u001b[0m csig\u001b[38;5;241m.\u001b[39mappend(sig_)\n\u001b[1;32m--> 942\u001b[0m csig \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconcat\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcsig\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39mreset_index(drop\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[0;32m 943\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m csig\n", + "File \u001b[1;32mc:\\github\\siggen\\siggen_env\\Lib\\site-packages\\pandas\\core\\reshape\\concat.py:382\u001b[0m, in \u001b[0;36mconcat\u001b[1;34m(objs, axis, join, ignore_index, keys, levels, names, verify_integrity, sort, copy)\u001b[0m\n\u001b[0;32m 379\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m copy \u001b[38;5;129;01mand\u001b[39;00m using_copy_on_write():\n\u001b[0;32m 380\u001b[0m copy \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m--> 382\u001b[0m op \u001b[38;5;241m=\u001b[39m \u001b[43m_Concatenator\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 383\u001b[0m \u001b[43m \u001b[49m\u001b[43mobjs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 384\u001b[0m \u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maxis\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 385\u001b[0m \u001b[43m \u001b[49m\u001b[43mignore_index\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mignore_index\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 386\u001b[0m \u001b[43m \u001b[49m\u001b[43mjoin\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mjoin\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 387\u001b[0m \u001b[43m \u001b[49m\u001b[43mkeys\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mkeys\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 388\u001b[0m \u001b[43m \u001b[49m\u001b[43mlevels\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlevels\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 389\u001b[0m \u001b[43m \u001b[49m\u001b[43mnames\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnames\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 390\u001b[0m \u001b[43m \u001b[49m\u001b[43mverify_integrity\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mverify_integrity\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 391\u001b[0m \u001b[43m \u001b[49m\u001b[43mcopy\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcopy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 392\u001b[0m \u001b[43m \u001b[49m\u001b[43msort\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msort\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 393\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 395\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m op\u001b[38;5;241m.\u001b[39mget_result()\n", + "File \u001b[1;32mc:\\github\\siggen\\siggen_env\\Lib\\site-packages\\pandas\\core\\reshape\\concat.py:445\u001b[0m, in \u001b[0;36m_Concatenator.__init__\u001b[1;34m(self, objs, axis, join, keys, levels, names, ignore_index, verify_integrity, copy, sort)\u001b[0m\n\u001b[0;32m 442\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mverify_integrity \u001b[38;5;241m=\u001b[39m verify_integrity\n\u001b[0;32m 443\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcopy \u001b[38;5;241m=\u001b[39m copy\n\u001b[1;32m--> 445\u001b[0m objs, keys \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_clean_keys_and_objs\u001b[49m\u001b[43m(\u001b[49m\u001b[43mobjs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkeys\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 447\u001b[0m \u001b[38;5;66;03m# figure out what our result ndim is going to be\u001b[39;00m\n\u001b[0;32m 448\u001b[0m ndims \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_get_ndims(objs)\n", + "File \u001b[1;32mc:\\github\\siggen\\siggen_env\\Lib\\site-packages\\pandas\\core\\reshape\\concat.py:507\u001b[0m, in \u001b[0;36m_Concatenator._clean_keys_and_objs\u001b[1;34m(self, objs, keys)\u001b[0m\n\u001b[0;32m 504\u001b[0m objs_list \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(objs)\n\u001b[0;32m 506\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(objs_list) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m--> 507\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mNo objects to concatenate\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m 509\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m keys \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m 510\u001b[0m objs_list \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(com\u001b[38;5;241m.\u001b[39mnot_none(\u001b[38;5;241m*\u001b[39mobjs_list))\n", + "\u001b[1;31mValueError\u001b[0m: No objects to concatenate" + ] + } + ], + "source": [ + "self.SIGTABLE = []\n", + "node_id = self.node_ids[11]\n", + "print(node_id)\n", + "sig = self.sigtable.query('node_id==@node_id')\n", + "display(sig)\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", + " # 황색 및 적색시간 컬럼 생성\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", + "display(sig)\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", + "display(sig)\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", + "display(sig_A)\n", + "display(sig_B)\n", + "\n", + "csig_A = self.cumulate(sig_A, 'A')\n", + "csig_B = self.cumulate(sig_B, 'B')\n", + "display(csig_A)\n", + "display(csig_B)\n", + "\n", + "SIG = pd.merge(csig_A, csig_B, on=['start_time', 'start_unix'], how='outer')\n", + "display(SIG[:40])\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", + "display(SIG[:40])\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\"예상되지 않은 조합 발생: a={a}, b={b}\")\n", + " SIG.at[row.Index, 'state'] = state\n", + "display(SIG[:40])\n", + "SIG = SIG[SIG.duration!=0]\n", + "SIG = SIG.drop(columns=['start_time', 'state_A', 'state_B'])\n", + "display(SIG[:40])\n", + "self.SIGTABLE.append(SIG)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1722384300\n", + "300\n" + ] + } + ], + "source": [ + "self.offsets = {}\n", + "self.sigtable = []\n", + "sim_start = self.present_time - self.sim_timespan\n", + "print(self.present_time)\n", + "print(self.sim_timespan)" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1722383877" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "node_id = '106231'\n", + "group = self.histids[self.histids.node_id==node_id]\n", + "min_start_unix = int(group['start_unix'].min())\n", + "min_start_unix" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1722384007 1722384000 200\n", + "True\n", + " hello \n", + "1722384007\n" + ] + } + ], + "source": [ + "node_id = '107587'\n", + "group = self.histids[self.histids.node_id==node_id]\n", + "series = group[group['start_unix'] < sim_start]['start_unix']\n", + "min_start_unix = int(group['start_unix'].min())\n", + "inter_no = self.node2inter[node_id]\n", + "_, prow = self.load_prow(inter_no, min_start_unix)\n", + "cycle = prow.iloc[0]['cycle']\n", + "lsbs = min_start_unix\n", + "print(lsbs, sim_start, cycle)\n", + "print(lsbs > sim_start)\n", + "print(type(lsbs), 'hello', type(sim_start))\n", + "while lsbs > sim_start:\n", + " lsbs -= cycle\n", + "print(min_start_unix)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "self.offsets = {}\n", + "self.sigtable = []\n", + "sim_start = self.present_time - self.sim_timespan\n", + "for node_id, group in self.histids.groupby('node_id'):\n", + " series = group[group['start_unix'] < sim_start]['start_unix']\n", + " # lsbs : the last start_unix before sim_start\n", + " if len(series):\n", + " lsbs = series.max()\n", + " else:\n", + " min_start_unix = int(group['start_unix'].min())\n", + " inter_no = self.node2inter[node_id]\n", + " _, prow = self.load_prow(inter_no, min_start_unix)\n", + " cycle = prow.iloc[0]['cycle']\n", + " lsbs = min_start_unix\n", + " while lsbs > sim_start:\n", + " lsbs -= cycle\n", + " self.offsets[node_id] = lsbs - sim_start\n", + " group = group[group.start_unix >= lsbs]\n", + " start_unixes = np.array(group.start_unix)\n", + " start_unixes = np.sort(np.unique(start_unixes))[:self.node2num_cycles[node_id]]\n", + "\n", + " group = group[group.start_unix.isin(start_unixes)]\n", + " self.sigtable.append(group)\n", + "self.sigtable = pd.concat(self.sigtable).reset_index(drop=True)\n", + "self.sigtable['phase_sumo'] = self.sigtable.groupby(['node_id', 'start_unix']).cumcount()" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[436, 437, 442, 443, 455, 456, 457]" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sorted(inter_no for inter_no in set(self.sigtable.inter_no))" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['106231',\n", + " '106234',\n", + " '106332',\n", + " '107587',\n", + " '108769',\n", + " '109295',\n", + " '109296',\n", + " '109297',\n", + " '109313',\n", + " '109333',\n", + " '109836',\n", + " '109901',\n", + " '109986']" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sorted(node_id for node_id in set(self.sigtable.node_id))" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [], + "source": [ + "# 5-1\n", + "self.set_timepoints()" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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inter_nonode_idstart_unixphas_Aphas_Bmove_Amove_Bdurationstate_Astate_Bphase_sumo
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"112 443 108769 1722384502 2 2 5 2 25 \n", - "113 443 108769 1722384502 3 3 7 18 50 \n", - "114 456 106231 1722384507 1 1 5 2 15 \n", - "115 456 106231 1722384507 2 2 6 2 28 \n", - "116 456 106231 1722384507 3 3 7 7 12 \n", - "117 456 106231 1722384507 4 4 17 17 35 \n", - "118 455 109901 1722384516 1 1 6 2 63 \n", - "119 457 106234 1722384592 1 1 6 2 45 \n", - "120 457 106234 1722384592 2 2 5 1 20 \n", - "121 457 106234 1722384592 3 3 17 17 40 \n", - "122 457 106234 1722384592 4 4 8 3 40 \n", - "123 457 106234 1722384592 5 5 7 4 35 \n", - "124 456 106231 1722384597 1 1 5 2 15 \n", - "125 456 106231 1722384597 2 2 6 2 28 \n", - "126 456 106231 1722384597 3 3 7 7 12 \n", - "127 456 106231 1722384597 4 4 17 17 35 \n", - "128 455 109901 1722384606 1 1 6 2 63 \n", - "129 436 109836 1722384636 1 1 5 2 50 \n", - "130 436 109836 1722384636 2 2 8 3 85 \n", - "131 436 109836 1722384636 3 3 7 4 35 \n", - "132 436 109836 1722384636 4 4 6 1 30 \n", - "133 456 106231 1722384687 1 1 5 2 15 \n", - "134 456 106231 1722384687 2 2 6 2 28 \n", - "135 456 106231 1722384687 3 3 7 7 12 \n", - "136 456 106231 1722384687 4 4 17 17 35 \n", - "137 455 109901 1722384696 1 1 6 2 63 \n", - "138 442 106332 1722384697 1 1 6 1 35 \n", - "139 442 106332 1722384697 2 2 6 2 27 \n", - "140 442 106332 1722384697 3 3 5 2 30 \n", - "141 442 106332 1722384697 4 4 7 4 47 \n", - "142 442 106332 1722384697 5 5 8 3 45 \n", - "143 442 106332 1722384697 6 6 8 3 16 \n", - "144 457 106234 1722384700 1 1 6 2 27 \n", - "145 457 106234 1722384700 2 2 5 1 12 \n", - "146 457 106234 1722384700 3 3 17 17 24 \n", - "147 457 106234 1722384700 4 4 8 3 24 \n", - "148 457 106234 1722384700 5 5 7 4 21 \n", - "149 443 108769 1722384700 1 1 6 2 124 \n", - "150 443 108769 1722384700 2 2 5 2 25 \n", - "151 443 108769 1722384700 3 3 7 18 49 \n", - "152 437 109986 1722384700 1 1 6 2 71 \n", - "153 437 109986 1722384700 2 2 5 1 28 \n", - "154 437 109986 1722384700 3 3 8 3 58 \n", - "155 437 109986 1722384700 4 4 7 4 43 \n", - "\n", - " state_A state_B \n", - "0 gGGGrgrrrrgrrrrgrrr grrrrgrrrrgGGGrgrrr \n", - "1 grrrrgrrrrgrrrGgrrr grrrGgrrrrgrrrrgrrr \n", - "2 grrrrgrrrrgrrrrgrrr grrrrgrrrrgrrrrgrrr \n", - "3 grrrrgGGrrgrrrrgrrr grrrrgrrGGgrrrrgrrr \n", - "4 grrrrgrrrrgrrrrgrrG grrrrgrrrrgrrrrgGGr \n", - "5 grgrrrrG grgrrGGr \n", - "6 grgGGrrr grgrrGGr \n", - "7 gGgrrrrr gGgrrrrr \n", - "8 grgrrrrr grgrrrrr \n", - "9 GGrr rrGG \n", - "10 gGGGrrrrrrgrrgrrrrrrrrgrrrr grrrrGGrrrgrrgrrrrrrrrgrrrr \n", - "11 gGGGrrrrrrgrrgrrrrrrrrgrrrr grrrrrrrrrgrrgrGGGGGrrgrrrr \n", - "12 grrrrrrrrrgrrgrrrrrrGGgrrrr grrrrrrrrrgrrgrGGGGGrrgrrrr \n", - "13 grrrrrrrrrgrrgrrrrrrrrgrrrG grrrrrrrrrgrrgrrrrrrrrgGGGr \n", - "14 grrrrrrGGrgrrgrrrrrrrrgrrrr grrrrrrrrGgrrgrrrrrrrrgrrrr \n", - "15 grrrrrrGGrgrrgrrrrrrrrgrrrr grrrrrrrrGgrrgrrrrrrrrgrrrr \n", - "16 gGGGGGrrrrrrgrr grrrrrGGGGGrgrr \n", - "17 grrrrrrrrrrGgrr grrrrrGGGGGrgrr \n", - "18 grrrrrrrrrrrgGG grrrrrrrrrrrgrr \n", - "19 grgrrrrG grgrrGGr \n", - "20 grgGGrrr grgrrGGr \n", - "21 gGgrrrrr grgrrrrr \n", - "22 grgrrrrr grgrrrrr \n", - "23 grgrrrrG grgrrGGr \n", - "24 grgGGrrr grgrrGGr \n", - "25 gGgrrrrr gGgrrrrr \n", - "26 grgrrrrr grgrrrrr \n", - "27 GGrr rrGG \n", - "28 GGrr rrGG \n", - "29 rrrr rrrr \n", - "30 gGGGGrgrrgrrrrrgrr grrrrrgrrgGGGGrgrr \n", - "31 grrrrrgrrgrrrrGgrr grrrrGgrrgrrrrrgrr \n", - "32 grrrrrgGrgrrrrrgrr grrrrrgrGgrrrrrgrr \n", - "33 grrrrrgrrgrrrrrgrG grrrrrgrrgrrrrrgGr \n", - "34 grrrrgrrgrGgrr grrrrgrrgGrgrr \n", - "35 grrrrgGrgrrgrr grrrrgrGgrrgrr \n", - "36 grrrrgrrgrrgrG grrrrgrrgrrgGr \n", - "37 gGGGrgrrgrrgrr grrrGgrrgrrgrr \n", - "38 gGGGrgrrrrgrrrrgrrr grrrrgrrrrgGGGrgrrr \n", - "39 grrrrgrrrrgrrrGgrrr grrrGgrrrrgrrrrgrrr \n", - "40 grrrrgrrrrgrrrrgrrr grrrrgrrrrgrrrrgrrr \n", - "41 grrrrgGGrrgrrrrgrrr grrrrgrrGGgrrrrgrrr \n", - "42 grrrrgrrrrgrrrrgrrG grrrrgrrrrgrrrrgGGr \n", - "43 grgrrrrG grgrrGGr \n", - "44 grgGGrrr grgrrGGr \n", - "45 gGgrrrrr gGgrrrrr \n", - "46 grgrrrrr grgrrrrr \n", - "47 grgrrrrG grgrrGGr \n", - "48 grgGGrrr grgrrGGr \n", - "49 gGgrrrrr gGgrrrrr \n", - "50 grgrrrrr grgrrrrr \n", - "51 GGrr rrGG \n", - "52 GGrr rrGG \n", - "53 gGGGrrrrrrgrrgrrrrrrrrgrrrr grrrrGGrrrgrrgrrrrrrrrgrrrr \n", - "54 gGGGrrrrrrgrrgrrrrrrrrgrrrr grrrrrrrrrgrrgrGGGGGrrgrrrr \n", - "55 grrrrrrrrrgrrgrrrrrrGGgrrrr grrrrrrrrrgrrgrGGGGGrrgrrrr \n", - "56 grrrrrrrrrgrrgrrrrrrrrgrrrG grrrrrrrrrgrrgrrrrrrrrgGGGr \n", - "57 grrrrrrGGrgrrgrrrrrrrrgrrrr grrrrrrrrGgrrgrrrrrrrrgrrrr \n", - "58 grrrrrrGGrgrrgrrrrrrrrgrrrr grrrrrrrrGgrrgrrrrrrrrgrrrr \n", - "59 gGGGGGrrrrrrgrr grrrrrGGGGGrgrr \n", - "60 grrrrrrrrrrGgrr grrrrrGGGGGrgrr \n", - "61 grrrrrrrrrrrgGG grrrrrrrrrrrgrr \n", - "62 grgrrrrG grgrrGGr \n", - "63 grgrrrrG grgrrGGr \n", - "64 grgGGrrr grgrrGGr \n", - "65 grgGGrrr grgrrGGr \n", - "66 gGgrrrrr gGgrrrrr \n", - "67 gGgrrrrr gGgrrrrr \n", - "68 grgrrrrr grgrrrrr \n", - "69 grgrrrrr grgrrrrr \n", - "70 GGrr rrGG \n", - "71 GGrr rrGG \n", - "72 gGGGrgrrrrgrrrrgrrr grrrrgrrrrgGGGrgrrr \n", - "73 grrrrgrrrrgrrrGgrrr grrrGgrrrrgrrrrgrrr \n", - "74 grrrrgrrrrgrrrrgrrr grrrrgrrrrgrrrrgrrr \n", - "75 grrrrgrrgrGgrr grrrrgrrgGrgrr \n", - "76 grrrrgGrgrrgrr grrrrgrGgrrgrr \n", - "77 grgrrrrG grgrrGGr \n", - "78 grgGGrrr grgrrGGr \n", - "79 gGgrrrrr gGgrrrrr \n", - "80 grgrrrrr grgrrrrr \n", - "81 GGrr rrGG \n", - "82 gGGGrrrrrrgrrgrrrrrrrrgrrrr grrrrGGrrrgrrgrrrrrrrrgrrrr \n", - "83 gGGGGGrrrrrrgrr grrrrrGGGGGrgrr \n", - "84 grrrrrrrrrrGgrr grrrrrGGGGGrgrr \n", - "85 grrrrrrrrrrrgGG grrrrrrrrrrrgrr \n", - "86 grgrrrrG grgrrGGr \n", - "87 grgGGrrr grgrrGGr \n", - "88 gGgrrrrr gGgrrrrr \n", - "89 grgrrrrr grgrrrrr \n", - "90 GGrr rrGG \n", - "91 gGGGrgrrrrgrrrrgrrr grrrrgrrrrgGGGrgrrr \n", - "92 grrrrgrrrrgrrrGgrrr grrrGgrrrrgrrrrgrrr \n", - "93 grrrrgrrrrgrrrrgrrr grrrrgrrrrgrrrrgrrr \n", - "94 grrrrgGGrrgrrrrgrrr grrrrgrrGGgrrrrgrrr \n", - "95 grrrrgrrrrgrrrrgrrG grrrrgrrrrgrrrrgGGr \n", - "96 grgrrrrG grgrrGGr \n", - "97 grgGGrrr grgrrGGr \n", - "98 gGgrrrrr gGgrrrrr \n", - "99 grgrrrrr grgrrrrr \n", - "100 GGrr rrGG \n", - "101 grrrrgrrgrGgrr grrrrgrrgGrgrr \n", - "102 grrrrgGrgrrgrr grrrrgrGgrrgrr \n", - "103 grrrrgrrgrrgrG grrrrgrrgrrgGr \n", - "104 gGGGrgrrgrrgrr grrrGgrrgrrgrr \n", - "105 gGGGrrrrrrgrrgrrrrrrrrgrrrr grrrrGGrrrgrrgrrrrrrrrgrrrr \n", - "106 gGGGrrrrrrgrrgrrrrrrrrgrrrr grrrrrrrrrgrrgrGGGGGrrgrrrr \n", - "107 grrrrrrrrrgrrgrrrrrrGGgrrrr grrrrrrrrrgrrgrGGGGGrrgrrrr \n", - "108 grrrrrrrrrgrrgrrrrrrrrgrrrG grrrrrrrrrgrrgrrrrrrrrgGGGr \n", - "109 grrrrrrGGrgrrgrrrrrrrrgrrrr grrrrrrrrGgrrgrrrrrrrrgrrrr \n", - "110 grrrrrrGGrgrrgrrrrrrrrgrrrr grrrrrrrrGgrrgrrrrrrrrgrrrr \n", - "111 gGGGGGrrrrrrgrr grrrrrGGGGGrgrr \n", - "112 grrrrrrrrrrGgrr grrrrrGGGGGrgrr \n", - "113 grrrrrrrrrrrgGG grrrrrrrrrrrgrr \n", - "114 grgrrrrG grgrrGGr \n", - "115 grgGGrrr grgrrGGr \n", - "116 gGgrrrrr gGgrrrrr \n", - "117 grgrrrrr grgrrrrr \n", - "118 GGrr rrGG \n", - "119 gGGGrgrrrrgrrrrgrrr grrrrgrrrrgGGGrgrrr \n", - "120 grrrrgrrrrgrrrGgrrr grrrGgrrrrgrrrrgrrr \n", - "121 grrrrgrrrrgrrrrgrrr grrrrgrrrrgrrrrgrrr \n", - "122 grrrrgGGrrgrrrrgrrr grrrrgrrGGgrrrrgrrr \n", - "123 grrrrgrrrrgrrrrgrrG grrrrgrrrrgrrrrgGGr \n", - "124 grgrrrrG grgrrGGr \n", - "125 grgGGrrr grgrrGGr \n", - "126 gGgrrrrr gGgrrrrr \n", - "127 grgrrrrr grgrrrrr \n", - "128 GGrr rrGG \n", - "129 grrrrgrrgrGgrr grrrrgrrgGrgrr \n", - "130 grrrrgGrgrrgrr grrrrgrGgrrgrr \n", - "131 grrrrgrrgrrgrG grrrrgrrgrrgGr \n", - "132 gGGGrgrrgrrgrr grrrGgrrgrrgrr \n", - "133 grgrrrrG grgrrGGr \n", - "134 grgGGrrr grgrrGGr \n", - "135 gGgrrrrr gGgrrrrr \n", - "136 grgrrrrr grgrrrrr \n", - "137 GGrr rrGG \n", - "138 gGGGrrrrrrgrrgrrrrrrrrgrrrr grrrrGGrrrgrrgrrrrrrrrgrrrr \n", - "139 gGGGrrrrrrgrrgrrrrrrrrgrrrr grrrrrrrrrgrrgrGGGGGrrgrrrr \n", - "140 grrrrrrrrrgrrgrrrrrrGGgrrrr grrrrrrrrrgrrgrGGGGGrrgrrrr \n", - "141 grrrrrrrrrgrrgrrrrrrrrgrrrG grrrrrrrrrgrrgrrrrrrrrgGGGr \n", - "142 grrrrrrGGrgrrgrrrrrrrrgrrrr grrrrrrrrGgrrgrrrrrrrrgrrrr \n", - "143 grrrrrrGGrgrrgrrrrrrrrgrrrr grrrrrrrrGgrrgrrrrrrrrgrrrr \n", - "144 gGGGrgrrrrgrrrrgrrr grrrrgrrrrgGGGrgrrr \n", - "145 grrrrgrrrrgrrrGgrrr grrrGgrrrrgrrrrgrrr \n", - "146 grrrrgrrrrgrrrrgrrr grrrrgrrrrgrrrrgrrr \n", - "147 grrrrgGGrrgrrrrgrrr grrrrgrrGGgrrrrgrrr \n", - "148 grrrrgrrrrgrrrrgrrG grrrrgrrrrgrrrrgGGr \n", - "149 gGGGGGrrrrrrgrr grrrrrGGGGGrgrr \n", - "150 grrrrrrrrrrGgrr grrrrrGGGGGrgrr \n", - "151 grrrrrrrrrrrgGG grrrrrrrrrrrgrr \n", - "152 gGGGGrgrrgrrrrrgrr grrrrrgrrgGGGGrgrr \n", - "153 grrrrrgrrgrrrrGgrr grrrrGgrrgrrrrrgrr \n", - "154 grrrrrgGrgrrrrrgrr grrrrrgrGgrrrrrgrr \n", - "155 grrrrrgrrgrrrrrgrG grrrrrgrrgrrrrrgGr " + "136 443 109333 1722383902 1 1 6 2 125 \n", + "137 443 109333 1722383902 2 2 5 2 25 \n", + "138 443 109333 1722383902 3 3 7 18 50 \n", + "139 443 109333 1722384102 1 1 6 2 125 \n", + "140 443 109333 1722384102 2 2 5 2 25 \n", + "141 443 109333 1722384102 3 3 7 18 50 \n", + "142 443 109333 1722384302 1 1 6 2 125 \n", + "143 443 109333 1722384302 2 2 5 2 25 \n", + "144 443 109333 1722384302 3 3 7 18 50 \n", + "\n", + " state_A state_B phase_sumo \n", + "136 GGGGGGGGGGGr GGGGGGGGGGGr 0 \n", + "137 GGGGGGGGGGGG GGGGGGGGGGGr 1 \n", + "138 GGGGGGGGGGGr GGGGGGGGGGGr 2 \n", + "139 GGGGGGGGGGGr GGGGGGGGGGGr 0 \n", + "140 GGGGGGGGGGGG GGGGGGGGGGGr 1 \n", + "141 GGGGGGGGGGGr GGGGGGGGGGGr 2 \n", + "142 GGGGGGGGGGGr GGGGGGGGGGGr 0 \n", + "143 GGGGGGGGGGGG GGGGGGGGGGGr 1 \n", + "144 GGGGGGGGGGGr GGGGGGGGGGGr 2 " ] }, "metadata": {}, @@ -2667,104 +5850,51 @@ } ], "source": [ - "with pd.option_context('display.max_rows', None, 'display.max_columns', None):\n", - " display(self.histids)" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [], - "source": [ - "# 5-1\n", - "self.set_timepoints()" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "['106231',\n", - " '106234',\n", - " '106238',\n", - " '106332',\n", - " '106350',\n", - " '108769',\n", - " '109836',\n", - " '109901',\n", - " '109986']" - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "self.node_ids" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "['107587', '109295', '109296', '109297', '109313', '109333']" - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "self.uturn_ids" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "9" - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "len(self.parent_ids)" + "self.SIGTABLE = []\n", + "for node_id in self.node_ids:\n", + " sig = self.sigtable.query('node_id==@node_id')\n", + " display(sig)\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", + " try:\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", + " except:\n", + " print(node_id)\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 = self.cumulate(sig_A, 'A')\n", + " # csig_B = self.cumulate(sig_B, 'B')\n" ] }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 30, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "c:\\github\\siggen\\scripts\\generate_signals.py:801: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:818: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", " SIG[['phas_A', 'state_A']] = SIG[['phas_A', 'state_A']].fillna(method='ffill')\n", - "c:\\github\\siggen\\scripts\\generate_signals.py:802: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:819: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", " SIG[['phas_B', 'state_B']] = SIG[['phas_B', 'state_B']].fillna(method='ffill')\n", - "c:\\github\\siggen\\scripts\\generate_signals.py:801: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:818: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", " SIG[['phas_A', 'state_A']] = SIG[['phas_A', 'state_A']].fillna(method='ffill')\n", - "c:\\github\\siggen\\scripts\\generate_signals.py:802: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + "c:\\github\\siggen\\scripts\\generate_signals.py:819: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", " SIG[['phas_B', 'state_B']] = SIG[['phas_B', 'state_B']].fillna(method='ffill')\n" ] }, @@ -2775,8 +5905,8 @@ "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mKeyError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[1;32mIn[19], line 2\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;66;03m# 5-2. 적색 및 황색신호 부여\u001b[39;00m\n\u001b[1;32m----> 2\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43massign_red_yellow\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[1;32mc:\\github\\siggen\\scripts\\generate_signals.py:789\u001b[0m, in \u001b[0;36mSignalGenerator.assign_red_yellow\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 787\u001b[0m yellow_B \u001b[38;5;241m=\u001b[39m prow[\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124myellow_B\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mphas_B\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m]\n\u001b[0;32m 788\u001b[0m sig\u001b[38;5;241m.\u001b[39mloc[i, [\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mred_A\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mred_B\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124myellow_A\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124myellow_B\u001b[39m\u001b[38;5;124m'\u001b[39m]] \u001b[38;5;241m=\u001b[39m red_A, red_B, yellow_A, yellow_B\n\u001b[1;32m--> 789\u001b[0m sig \u001b[38;5;241m=\u001b[39m \u001b[43msig\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mastype\u001b[49m\u001b[43m(\u001b[49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mred_A\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mint\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mred_B\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mint\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43myellow_A\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mint\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43myellow_B\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mint\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m 790\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mphas_A\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[38;5;28;43mstr\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mphas_B\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[38;5;28;43mstr\u001b[39;49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 791\u001b[0m sig \u001b[38;5;241m=\u001b[39m sig\u001b[38;5;241m.\u001b[39mdrop([\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mmove_A\u001b[39m\u001b[38;5;124m'\u001b[39m,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mmove_B\u001b[39m\u001b[38;5;124m'\u001b[39m], axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m)\n\u001b[0;32m 793\u001b[0m sig_A \u001b[38;5;241m=\u001b[39m sig[[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mstart_unix\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mphas_A\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mduration\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mstate_A\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mred_A\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124myellow_A\u001b[39m\u001b[38;5;124m'\u001b[39m]]\u001b[38;5;241m.\u001b[39mreset_index(drop\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n", + "Cell \u001b[1;32mIn[30], line 2\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;66;03m# 5-2. 적색 및 황색신호 부여\u001b[39;00m\n\u001b[1;32m----> 2\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43massign_red_yellow\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[1;32mc:\\github\\siggen\\scripts\\generate_signals.py:806\u001b[0m, in \u001b[0;36mSignalGenerator.assign_red_yellow\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 804\u001b[0m yellow_B \u001b[38;5;241m=\u001b[39m prow[\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124myellow_B\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mphas_B\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m]\n\u001b[0;32m 805\u001b[0m sig\u001b[38;5;241m.\u001b[39mloc[i, [\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mred_A\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mred_B\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124myellow_A\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124myellow_B\u001b[39m\u001b[38;5;124m'\u001b[39m]] \u001b[38;5;241m=\u001b[39m red_A, red_B, yellow_A, yellow_B\n\u001b[1;32m--> 806\u001b[0m sig \u001b[38;5;241m=\u001b[39m \u001b[43msig\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mastype\u001b[49m\u001b[43m(\u001b[49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mred_A\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mint\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mred_B\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mint\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43myellow_A\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mint\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43myellow_B\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mint\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m 807\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mphas_A\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[38;5;28;43mstr\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mphas_B\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[38;5;28;43mstr\u001b[39;49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 808\u001b[0m sig \u001b[38;5;241m=\u001b[39m sig\u001b[38;5;241m.\u001b[39mdrop([\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mmove_A\u001b[39m\u001b[38;5;124m'\u001b[39m,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mmove_B\u001b[39m\u001b[38;5;124m'\u001b[39m], axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m)\n\u001b[0;32m 810\u001b[0m sig_A \u001b[38;5;241m=\u001b[39m sig[[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mstart_unix\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mphas_A\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mduration\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mstate_A\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mred_A\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124myellow_A\u001b[39m\u001b[38;5;124m'\u001b[39m]]\u001b[38;5;241m.\u001b[39mreset_index(drop\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n", "File \u001b[1;32mc:\\github\\siggen\\siggen_env\\Lib\\site-packages\\pandas\\core\\generic.py:6605\u001b[0m, in \u001b[0;36mNDFrame.astype\u001b[1;34m(self, dtype, copy, errors)\u001b[0m\n\u001b[0;32m 6603\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m col_name \u001b[38;5;129;01min\u001b[39;00m dtype_ser\u001b[38;5;241m.\u001b[39mindex:\n\u001b[0;32m 6604\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m col_name \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m:\n\u001b[1;32m-> 6605\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(\n\u001b[0;32m 6606\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mOnly a column name can be used for the \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 6607\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mkey in a dtype mappings argument. \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 6608\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mcol_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m not found in columns.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 6609\u001b[0m )\n\u001b[0;32m 6611\u001b[0m dtype_ser \u001b[38;5;241m=\u001b[39m dtype_ser\u001b[38;5;241m.\u001b[39mreindex(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcolumns, fill_value\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, copy\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[0;32m 6613\u001b[0m results \u001b[38;5;241m=\u001b[39m []\n", "\u001b[1;31mKeyError\u001b[0m: \"Only a column name can be used for the key in a dtype mappings argument. 'red_A' not found in columns.\"" ] diff --git a/configs/config_test_0731.json b/configs/config_test_0731.json index 1284a1b5e..a9b021315 100644 --- a/configs/config_test_0731.json +++ b/configs/config_test_0731.json @@ -9,5 +9,6 @@ "results":["test_0731", "results"], "tables":["test_0731", "data","tables"], "networks":["test_0731", "data", "networks"], + "network":["test_0731", "data", "networks", "new_sungnam_network_internal_target_0721.net.xml"], "scripts": ["scripts"]} } \ No newline at end of file diff --git a/test_0731/results/sn_1722384300.add.xml b/test_0731/results/sn_1722384300.add.xml new file mode 100644 index 000000000..3130f9cb6 --- /dev/null +++ b/test_0731/results/sn_1722384300.add.xml @@ -0,0 +1,315 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + \ No newline at end of file