diff --git a/app/comm.py b/app/comm.py index af2d1a5..273314a 100644 --- a/app/comm.py +++ b/app/comm.py @@ -1153,3 +1153,43 @@ def get_green_waves_cross_list(start_seq, cross_num, artery_coss_list): green_waves_list.append(artery_coss_list[index]) return green_waves_list + + +def tplist_2_tpinterval(tp_list): + if len(tp_list) == 0: + return [] + + result = [ + {'tp_start': tp_list[0], 'tp_end': '23:59'} + ] + + for i in range(1, len(tp_list)): + if tp_list[i] == '23:59': + continue + result[-1]['tp_end'] = tp_list[i] + result.append({'tp_start': tp_list[i], 'tp_end': '23:59'}) + + return result + + +def time_intersection_minutes(time1: str, time2: str) -> int: + """计算两个时间段的交集分钟数""" + + def to_minutes(t: str) -> int: + h, m = map(int, t.split(':')) + return h * 60 + m + + # 解析时间段 + start1, end1 = map(to_minutes, time1.split('-')) + start2, end2 = map(to_minutes, time2.split('-')) + + # 计算交集 + intersection_start = max(start1, start2) + intersection_end = min(end1, end2) + + # 如果没有交集，返回0 + if intersection_start >= intersection_end: + return 0 + + # 返回交集分钟数 + return intersection_end - intersection_start diff --git a/app/cross_eva_views.py b/app/cross_eva_views.py index 70f663b..0d2892c 100644 --- a/app/cross_eva_views.py +++ b/app/cross_eva_views.py @@ -88,6 +88,7 @@ from app.views_task import * from app.views_workstation import * from app.monitor_views import * from app.compare_views import * +from app.flow_views import * if __name__ == '__main__': pass \ No newline at end of file diff --git a/app/db_cross_delay.py b/app/db_cross_delay.py index 8643047..04fc1ca 100644 --- a/app/db_cross_delay.py +++ b/app/db_cross_delay.py @@ -158,4 +158,30 @@ class CrossDbHelper(TableDbHelperBase): sql = f""" select * from traffic_{nodeid}.csr_data where key = '{key}' and crossid = '{crossid}' """ - return self.do_select(sql) \ No newline at end of file + return self.do_select(sql) + + def query_cross_flow_usable_date_sql(self, nodeid, crossid): + conn, cursor = self.connect() + try: + sql = f"""select distinct day from traffic_{nodeid}.cross_flowdata where crossid = %s """ + print(cursor.mogrify(sql, (crossid))) + cursor.execute(sql, (crossid)) + result = cursor.fetchall() + return result, None + except Exception as error: + return None, error + finally: + self.close(conn, cursor) + + def query_cross_flowdata(self, nodeid, crossid, date_list): + conn, cursor = self.connect() + try: + sql = f"""select crossid,`day`,data from traffic_{nodeid}.cross_flowdata where crossid = %s and `day` in %s""" + print(cursor.mogrify(sql, (crossid, date_list))) + cursor.execute(sql, (crossid, date_list)) + result = cursor.fetchall() + return result, None + except Exception as error: + return None, error + finally: + self.close(conn, cursor) diff --git a/app/flow_views.py b/app/flow_views.py new file mode 100644 index 0000000..4f61e51 --- /dev/null +++ b/app/flow_views.py @@ -0,0 +1,26 @@ +# -*- coding: utf-8 -*- +# @Author: Owl +# @Date: 2025/11/10 18:12 +# @Description: +import json +import logging + +import requests +from flask import Flask, request + +from app.cross_eva_views import app +from app.flow_worker import cross_flow_usable_date, cross_flow_tp_divide, auto_match_phase + + +@app.route('/api/cross_flow_usable_date', methods=['GET']) +def cross_flow_usable_date_route(): + return cross_flow_usable_date(dict(request.args)) + + +@app.route('/api/cross_flow_tp_divide', methods=['POST']) +def cross_flow_tp_divide_route(): + return cross_flow_tp_divide(request.json) + +@app.route('/api/auto_match_phase', methods=['POST']) +def auto_match_phase_route(): + return auto_match_phase(request.json) \ No newline at end of file diff --git a/app/flow_worker.py b/app/flow_worker.py new file mode 100644 index 0000000..f3665b3 --- /dev/null +++ b/app/flow_worker.py @@ -0,0 +1,541 @@ +import copy +import io +import json +from io import BytesIO + +from app.common_worker import * +from app.eva_common import * +from openpyxl import Workbook +from openpyxl.styles import Alignment +from datetime import datetime + +# 查询可用路口列表 +from proto.phase_grpc import QueryCrossRunningPhase +from flask import send_file + +# 一天内的一刻时段个数 +QUARTER_COUNT = 96 + + +# 查询路口可用时段 +def cross_flow_usable_date(params): + crossid = check_param(params, 'crossid') + if not crossid: + return json.dumps(make_common_res(1, '缺少crossid， 请刷新后重试')) + nodeid = check_param(params, 'nodeid') + if not nodeid: + return json.dumps(make_common_res(2, '缺少nodeid， 请刷新后重试')) + area_id = check_param(params, 'area_id') + if not area_id: + return json.dumps(make_common_res(3, '缺少area_id， 请刷新后重试')) + userid = check_param(params, 'userid') + if not userid: + return json.dumps(make_common_res(4, '缺少userid， 请刷新后重试')) + area_list = db_user.query_areaid_list(userid) + if not area_list or len(area_list) < 1: + return json.dumps(make_common_res(5, '用户信息异常')) + area_list = map(int, area_list) + if not str(area_id).lstrip('-').isdigit() or int(area_id) not in area_list: + return json.dumps(make_common_res(5, '辖区id异常，请检查后重试')) + + row_list, error = db_cross.query_cross_flow_usable_date_sql(nodeid, crossid) + if error: + return json.dumps(make_common_res(5, f"{error}")) + res = make_common_res(0, 'ok') + res['data'] = [] + if len(row_list) <= 0: + return json.dumps(res, ensure_ascii=False) + date_list = [row['day'] for row in row_list] + res = make_common_res(0, 'ok') + res['data'] = date_list + return json.dumps(res, ensure_ascii=False) + + +def cross_flow_tp_divide(params): + crossid = check_param(params, 'crossid') + if not crossid: + return json.dumps(make_common_res(1, '缺少crossid， 请刷新后重试')) + nodeid = check_param(params, 'nodeid') + if not nodeid: + return json.dumps(make_common_res(2, '缺少nodeid， 请刷新后重试')) + area_id = check_param(params, 'area_id') + if not area_id: + return json.dumps(make_common_res(3, '缺少area_id， 请刷新后重试')) + userid = check_param(params, 'userid') + if not userid: + return json.dumps(make_common_res(4, '缺少userid， 请刷新后重试')) + area_list = db_user.query_areaid_list(userid) + if not area_list or len(area_list) < 1: + return json.dumps(make_common_res(5, '用户信息异常')) + area_list = map(int, area_list) + if not str(area_id).lstrip('-').isdigit() or int(area_id) not in area_list: + return json.dumps(make_common_res(5, '辖区id异常，请检查后重试')) + date_list = check_param(params, 'date_list') + if not date_list or len(date_list) == 0: + return json.dumps(make_common_res(2, '缺少date_list， 请刷新后重试')) + date_type = check_param(params, 'date_type') + if not date_type: + return json.dumps(make_common_res(2, '缺少date_type， 请刷新后重试')) + + week_days = [1, 2, 3, 4, 5, 6, 7] + if date_type == 'workday': + week_days = [1, 2, 3, 4, 5] + if date_type == 'weekend': + week_days = [6, 7] + + search_date_list = [] + search_week_day_map = {} + for item_date in date_list: + date_time = datetime.strptime(str(item_date), '%Y%m%d') + date_weekday = date_time.weekday() + 1 + if date_weekday in week_days: + search_week_day_map[date_weekday] = True + search_date_list.append(item_date) + + res = make_common_res(0, 'ok') + res['data'] = { + 'flow_data': [], + 'recommend_tp': [], + 'schedule_info': [] + } + + if len(search_date_list) == 0: + return json.dumps(res, ensure_ascii=False) + + flow_data, error = db_cross.query_cross_flowdata(str(nodeid), crossid, search_date_list) + if error: + return json.dumps(make_common_res(2, f"{error}")) + + if len(flow_data) <= 0: + return json.dumps(res, ensure_ascii=False) + + flow_data_pb_list = [] + for item_flow_data in flow_data: + item_flow_pb = pb.xl_cross_flowdata_t() + item_flow_pb.ParseFromString(item_flow_data['data']) + flow_data_pb_list.append(item_flow_pb) + + merged_flow = merge_cross_flow(flow_data_pb_list) + if not merged_flow: + return json.dumps(res, ensure_ascii=False) + hm_idx_list, flow_list = do_cross_tp_divide(merged_flow.flows) + if not flow_list or len(flow_list) == 0: + return json.dumps(res, ensure_ascii=False) + tp_list = trans_to_tp_list(hm_idx_list) + + recommend_tp = {} + if tp_list and len(tp_list) > 0: + for item_tp_list in tp_list: + res['data']['recommend_tp'].append(item_tp_list[0]) + recommend_tp[item_tp_list[0]] = 1 + + current_time = datetime.strptime("00:00", "%H:%M") + for i in range(0, len(flow_list)): + time_str = current_time.strftime("%H:%M") + res['data']['flow_data'].append({ + "flow": round(flow_list[i], 2), + "tp": time_str, + "recommend": recommend_tp.get(time_str, 0) + }) + current_time += timedelta(minutes=15) + + #查询配时方案 + tps, error = db_phasetable.query_cross_tps_by_crossid(int(nodeid), crossid) + if error: + return json.dumps(make_common_res(2, f"{error}"), ensure_ascii=False) + + if len(tps) <= 0: + return res + + tps_map = {} + for item_tps in tps: + if item_tps['weekday'] not in tps_map: + tps_map[item_tps['weekday']] = { + 'tp': [], + 'scheduleid': item_tps['scheduleid'], + } + tps_map[item_tps['weekday']]['tp'].append(item_tps['tp_start']) + + search_week_day = list(search_week_day_map.keys()) + for weeks, tp_value in tps_map.items(): + weeks_list = list(map(int, weeks.split(','))) + intersection = list(set(search_week_day) & set(weeks_list)) + if len(intersection) == 0: + continue + plans, error = db_phasetable.day_schedule_by_xlcrossid(int(nodeid), crossid, tp_value['scheduleid']) + if error: + return json.dumps(make_common_res(2, f"{error}"), ensure_ascii=False) + + week_name = [] + if weeks == '1,2,3,4,5,6,7': + week_name = ['全周'] + if weeks == '1,2,3,4,5': + week_name = ['工作日'] + if weeks == '6,7': + week_name = ['周末'] + if len(week_name) == 0: + week_slice = weeks.split(',') + for item_week in week_slice: + week_name.append(g_week_day[int(item_week)]) + + item_data = { + 'scheduleid': tp_value['scheduleid'], + 'schedule_week': weeks, + 'schedule_name': ','.join(week_name), + 'tps': [], + } + + plans_map = {} + for item_plan in plans: + plans_map[item_plan['tp_start']] = item_plan + + if len(tp_value['tp']) > 0: + tp_interval = tplist_2_tpinterval(tp_value['tp']) + for item_tp_interval in tp_interval: + if item_tp_interval['tp_start'] in plans_map: + item_data['tps'].append({ + 'tp_start': item_tp_interval['tp_start'], + 'tp_end': item_tp_interval['tp_end'], + 'plan_name': plans_map[item_tp_interval['tp_start']]['name'], + 'plan_id': plans_map[item_tp_interval['tp_start']]['planid'], + }) + res['data']['schedule_info'].append(item_data) + + return json.dumps(res, ensure_ascii=False) + + +def merge_cross_flow(crossflow_list: list[pb.xl_cross_flowdata_t]): + """将多个xl_cross_flowdata_t数据合并为一个 + :param crossflow_list: 数组 + :return: 合并后的pb消息 + """ + avg_flow = pb.xl_cross_flowdata_t() + if len(crossflow_list) == 0: + return None + if len(crossflow_list) == 1: + return crossflow_list[0] + avg_flow.crossid = crossflow_list[0].crossid + for i in range(0, QUARTER_COUNT): + avg_flow.flows.append(0) + for item in crossflow_list: + flows = item.flows + for i in range(0, len(flows)): + avg_flow.flows[i] += flows[i] + return avg_flow + + +def get_cross_tp_divide(orig_flow_list: list[float]) -> list[str]: + """输入路口流量数据，执行时段划分 + :param orig_flow_list: 原始流量数组，约定包含96个元素 + :return: list[str], 时段列表 + """ + # (1)执行时段划分 + hm_idx_list, flow_list = do_cross_tp_divide(orig_flow_list) + # (2)生成时段序列， tp_list的数据结构: [["00:00","06:30"],["06:30","07:30"],["07:30","08:30"]] + tp_list = trans_to_tp_list(hm_idx_list) + return tp_list + + +def do_cross_tp_divide(orig_flow_list: list[float]): + """ + 输入一个路口的flow数据，执行时段划分。返回：1个划分结果 和 标准流量数据序列 + :param crossflow: + :return: hm_idx_list, std_flow_list + """ + # 对原始流量进行平滑处理 + smooth_flow_list = get_smoothed_flow(orig_flow_list) + # 计算相对流量 + std_flow_list = get_normlize_flow(smooth_flow_list) + # 执行时段划分 + idx_list = _split_tps_by_fallhead(std_flow_list) + return idx_list, std_flow_list + + +def get_smoothed_flow(flow_list: list[float]) -> list[float]: + """ + 对原始流量数组进行平滑处理，采用邻域平均法 + :param flow_list: [float] + :return: [float] + """ + # 计算平均流量 + avg_flow = sum(flow_list) / len(flow_list) + # 根据不同的平均流量，设置不同的权重 + # print(f'avg_flow: {avg_flow}') + center_w = 0.6 + left_w = 0.2 + right_w = 0.2 + if avg_flow < 10: + center_w = 0.4 + left_w = 0.3 + right_w = 0.3 + # print(f'center_w: {center_w}, left_w: {left_w}, right_w: {right_w}') + smoothed_flow_list = [] + max_idx = len(flow_list) - 1 + for i in range(0, len(flow_list)): + sum_value = 0 + sum_w = 0 + sum_w += center_w + sum_value += flow_list[i] * center_w + if i + 1 >= 0 and i + 1 <= max_idx: + sum_w += right_w + sum_value += flow_list[i + 1] * right_w + if i - 1 >= 0 and i - 1 <= max_idx: + sum_w += left_w + sum_value += flow_list[i - 1] * left_w + smoothed_flow = sum_value / sum_w + smoothed_flow_list.append(smoothed_flow) + return smoothed_flow_list + + +def get_normlize_flow(flow_list: list[float]) -> list[float]: + """ + 对原始流量数组进行归一化，以最大流量作为100，对其他流量进行等比缩放 + :param flow_list: [float] + :return: [float] + """ + max_flow = 0 + for flow in flow_list: + if flow > max_flow: + max_flow = flow + norm_flow_list = [] + for flow in flow_list: + norm_flow = flow / max_flow * 100 if max_flow != 0 else 0 + norm_flow_list.append(norm_flow) + return norm_flow_list + + +def _split_tps_by_fallhead(std_flow_list, max_tp_num=8): + """ + 根据相邻时段的流量落差来划分时段, 返回用于切分时段的刻钟时段的序号的数组 + :param std_flow_list: 标准流量序列 + :param max_tp_num: 最大时段个数 + :return: [hm_idx] + """ + min_tp_num = 5 # 最小时段个数 + # 低流量阈值 + low_flow_limit = 40 + # (1)计算所有相邻刻钟的相对流量落差 + fallhead_map = {} + """包含 QUARTER_COUNT-1 个元素 {idx => drop}, 表示idx-1与idx之间的落差""" + for i in range(1, QUARTER_COUNT): + drop = _calc_drop(std_flow_list, i) + # 如果两侧的流量都低于该阈值，就不再考虑落差，一律设定为0 + if std_flow_list[i] <= low_flow_limit and std_flow_list[i - 1] <= low_flow_limit: + drop = 0 + fallhead_map[i] = drop + # (2)按落差降序排序 + drop_info_list = sorted(fallhead_map.items(), key=lambda item: item[1], reverse=True) + # print(drop_info_list) + # (3) 提取落差最大的部分分界点 + top_drop_idx_list = [] + for info in drop_info_list: + idx = info[0] + drop = info[1] + if drop < 5: # 落差低于5%不再分割 + break + top_drop_idx_list.append(idx) + # 如果落差不太差，且已经满足max_tp_num，则不再分割 + if drop < 15 and len(top_drop_idx_list) >= max_tp_num - 1: + break + # 梳理得到顺序排序的分界点 + split_idx_list = sorted(top_drop_idx_list) + boundary_list = [0] # + for idx in split_idx_list: + boundary_list.append(idx) + boundary_list.append(QUARTER_COUNT) + # 刻钟独立时段合并 + # drop_limit_cannot_merge = 30 # 落差大于这个阈值，即使是单个刻钟时段，则不能合并 + drop_limit_cannot_merge = 50 # 落差大于这个阈值，即使是单个刻钟时段，则不能合并 + tp_num = len(boundary_list) - 1 # 当前时段个数 + for i in range(1, len(boundary_list)): + if tp_num <= min_tp_num: + break + half_num = boundary_list[i] - boundary_list[i - 1] + if half_num == 1: # 只有1个刻钟，则考虑合并到左侧或右侧 + if i == 1: + # 只能合并到右侧 + right_drop = fallhead_map[boundary_list[i]] + if right_drop <= drop_limit_cannot_merge: + boundary_list[i] = -1 + tp_num -= 1 + elif i == len(boundary_list) - 1: + # 只能合并到左侧 + left_drop = fallhead_map[boundary_list[i - 1]] + if left_drop <= drop_limit_cannot_merge: + boundary_list[i - 1] = -1 + else: + left_drop = fallhead_map[boundary_list[i - 1]] + right_drop = fallhead_map[boundary_list[i]] + if left_drop <= right_drop and left_drop <= drop_limit_cannot_merge: + # 合并到左侧 + boundary_list[i - 1] = -1 + tp_num -= 1 + elif right_drop < left_drop and right_drop <= drop_limit_cannot_merge: + boundary_list[i] = -1 + tp_num -= 1 + # 合并落差小的相邻时段，以满足最大时段要求 + if tp_num > max_tp_num: + need_reduce_tp_num = tp_num - max_tp_num + idx_to_index = {} + for i in range(0, len(boundary_list)): + if boundary_list[i] > 0: + idx_to_index[boundary_list[i]] = i + top_drop_idx_list.reverse() + kill_tp_num = 0 + for i in range(0, len(top_drop_idx_list)): + idx = top_drop_idx_list[i] + if idx in idx_to_index: + index = idx_to_index[idx] + boundary_list[index] = -1 + kill_tp_num += 1 + if kill_tp_num >= need_reduce_tp_num: + break + # 梳理最终的分界点 + hm_idx_list = [] + for i in range(0, len(boundary_list)): + if boundary_list[i] < 0: + continue + hm_idx_list.append(boundary_list[i]) + return hm_idx_list + + +def _calc_drop(flow_list, i): + """ + 计算流量序列中，第i个流量与前一个流量的落差 + :param flow_list: 流量数组 + :param i: + :return: + """ + drop = abs(flow_list[i] - flow_list[i - 1]) + # 计算落差折减系数，当相对流量整体偏高，进行折减 + factor = (flow_list[i] + flow_list[i - 1]) / 100 + if factor < 1.0: + factor = 1.0 + # 适当折减 + drop = drop / factor + return drop + + +def trans_to_tp_list(hm_idx_list: list[int]) -> list[str]: + """将刻钟序号数组，转化为时段数组 + :param hm_idx_list: 刻钟序号构成的数组，用于表示时段划分结果 + :return: 时段字符串数组 + """ + hm_list = [] + for hm_idx in hm_idx_list: + num = hm_idx * 15 + h = num // 60 + m = num % 60 + hm = '%02d:%02d' % (h, m) + hm_list.append(hm) + tp_list = [] + for i in range(1, len(hm_list)): + tp_list.append([hm_list[i - 1], hm_list[i]]) + return tp_list + + +def auto_match_phase(params): + crossid = check_param(params, 'crossid') + if not crossid: + return json.dumps(make_common_res(1, '缺少crossid， 请刷新后重试')) + nodeid = check_param(params, 'nodeid') + if not nodeid: + return json.dumps(make_common_res(2, '缺少nodeid， 请刷新后重试')) + area_id = check_param(params, 'area_id') + if not area_id: + return json.dumps(make_common_res(3, '缺少area_id， 请刷新后重试')) + userid = check_param(params, 'userid') + if not userid: + return json.dumps(make_common_res(4, '缺少userid， 请刷新后重试')) + area_list = db_user.query_areaid_list(userid) + if not area_list or len(area_list) < 1: + return json.dumps(make_common_res(5, '用户信息异常')) + area_list = map(int, area_list) + if not str(area_id).lstrip('-').isdigit() or int(area_id) not in area_list: + return json.dumps(make_common_res(5, '辖区id异常，请检查后重试')) + scheduleid = check_param(params, 'scheduleid') + if not scheduleid: + return json.dumps(make_common_res(2, '缺少scheduleid， 请刷新后重试')) + recommend_tp = check_param(params, 'recommend_tp') + if not recommend_tp or len(recommend_tp) == 0: + return json.dumps(make_common_res(2, '缺少recommend_tp， 请刷新后重试')) + + cross_phase_info, error = db_phasetable.query_cross_runing_phasetable(int(nodeid), crossid) + if error: + return json.dumps(make_common_res(2, f"{error}")) + + scheduleid = int(scheduleid) + + res = make_common_res(0, 'ok') + res['data'] = { + 'scheduleid': scheduleid, + 'plans': [] + } + + if len(cross_phase_info) == 0: + return json.dumps(res, ensure_ascii=False) + + cross_phase_info_map = {} + for item_cross_phase_info in cross_phase_info: + if scheduleid != item_cross_phase_info['scheduleid']: + continue + if item_cross_phase_info['tp_start'] not in cross_phase_info_map: + cross_phase_info_map[item_cross_phase_info['tp_start']] = { + 'tp_start': item_cross_phase_info['tp_start'], + 'control_mode': item_cross_phase_info['control_mode'], + 'coord_phaseid': item_cross_phase_info['coord_phaseid'], + 'cycle': item_cross_phase_info['cycle'], + 'name': item_cross_phase_info['name'], + 'offset': item_cross_phase_info['offset'], + 'planid': item_cross_phase_info['planid'], + 'stages': [], + } + cross_phase_info_map[item_cross_phase_info['tp_start']]['stages'].append({ + 'stageid': item_cross_phase_info['stageid'], + 'stage_name': item_cross_phase_info['stage_name'], + 'allred': item_cross_phase_info['allred'], + 'green': item_cross_phase_info['green'], + 'max_green': item_cross_phase_info['max_green'], + 'min_green': item_cross_phase_info['min_green'], + 'phaseids': item_cross_phase_info['phases'], + 'redyellow': item_cross_phase_info['redyellow'], + 'stage_duration': item_cross_phase_info['stage_duration'], + 'yellow': item_cross_phase_info['yellow'], + }) + + phase_tps_list = tplist_2_tpinterval(list(cross_phase_info_map.keys())) + for item_phase_tps_list in phase_tps_list: + cross_phase_info_map[item_phase_tps_list['tp_start']]['tp_end'] = item_phase_tps_list['tp_end'] + + recommend_tp_interval = tplist_2_tpinterval(recommend_tp) + for item_recommend_tp_interval in recommend_tp_interval: + max_calc_diff_minute = 0 + max_max_calc_diff_minute = None + for _, item_cross_phase_info_map in cross_phase_info_map.items(): + if (item_recommend_tp_interval['tp_end'] > item_cross_phase_info_map['tp_start'] + and item_cross_phase_info_map['tp_end'] > item_recommend_tp_interval['tp_start']): + calc_diff_minute = time_intersection_minutes( + f"{item_recommend_tp_interval['tp_start']}-{item_recommend_tp_interval['tp_end']}", + f"{item_cross_phase_info_map['tp_start']}-{item_cross_phase_info_map['tp_end']}") + if calc_diff_minute > max_calc_diff_minute: + max_calc_diff_minute = calc_diff_minute + max_max_calc_diff_minute = copy.deepcopy(item_cross_phase_info_map) + + if not max_max_calc_diff_minute: + continue + + max_max_calc_diff_minute['tp_start'] = item_recommend_tp_interval['tp_start'] + max_max_calc_diff_minute['tp_end'] = item_recommend_tp_interval['tp_end'] + if len(res['data']['plans']) == 0: + res['data']['plans'].append(max_max_calc_diff_minute) + continue + + if (res['data']['plans'][-1]['tp_end'] == max_max_calc_diff_minute['tp_start'] + and res['data']['plans'][-1]['planid'] == max_max_calc_diff_minute['planid']): + res['data']['plans'][-1]['tp_end'] = max_max_calc_diff_minute['tp_end'] + continue + + res['data']['plans'].append(max_max_calc_diff_minute) + + + return json.dumps(res, ensure_ascii=False) diff --git a/app/global_source.py b/app/global_source.py index 418df11..400ede0 100644 --- a/app/global_source.py +++ b/app/global_source.py @@ -106,6 +106,7 @@ g_valid_daytypes = {'today', 'hisday', 'workdayofweek', 'weekendofweek'} g_valid_tps = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 100, 200, 300, 400, 500, 600, 1000} g_tp_list = [100, 200, 300, 400, 500, 600, 1000] +g_week_day = {1: '周一', 2: '周二', 3: '周三', 4: '周四', 5: '周五', 6: '周六', 7: '周日'} g_crossname_inverted_index = defaultdict(lambda: defaultdict(list)) diff --git a/app/phase_db_func.py b/app/phase_db_func.py index 5698ef4..f2fcbca 100644 --- a/app/phase_db_func.py +++ b/app/phase_db_func.py @@ -735,6 +735,101 @@ class PhaseTableDbHelper(TableDbHelperBase): except Exception as error: self.close(conn, cursor) return None, error + + def query_cross_tps_by_crossid(self, citycode, crossid): + conn, cursor = self.connect() + try: + sql = f'''select * from {self.DB_Name}.cross_tps where citycode = %s and crossid = %s order by weekday , tp_start asc''' + cursor.execute(sql, (citycode, crossid)) + # 获取所有查询结果 + result = cursor.fetchall() + return result, None + except Exception as e: + return None, e + finally: + self.close(conn, cursor) + + def day_schedule_by_xlcrossid(self, citycode, xlcrossid, scheduleid): + + conn, cursor = self.connect() + try: + sql_query = f'''select ds.scheduleid, + ds.crossid, + ds.control_mode, + ds.tp_start, + ds.planid, + ps.name, + ds.nodeid + from cross_mapping as cm + join day_schedule as ds on ds.crossid = cm.jj_crossid and ds.nodeid = cm.nodeid + left join plan_stage as ps on ps.crossid = cm.jj_crossid and ps.nodeid = cm.nodeid and ps.planid = ds.planid + where cm.xl_crossid = %s + and cm.nodeid = %s + and ds.scheduleid = %s + group by ds.scheduleid,ds.crossid,ds.nodeid,ds.control_mode,ds.tp_start,ds.planid,ps.name + order by ds.tp_start asc''' + print(cursor.mogrify(sql_query, (xlcrossid, citycode, scheduleid))) + cursor.execute(sql_query, (xlcrossid, citycode, scheduleid)) + # 获取所有查询结果 + result = cursor.fetchall() + return result, None + except Exception as e: + return None, e + finally: + self.close(conn, cursor) + + def query_cross_runing_phasetable(self, citycode, crossid): + conn, cursor = self.connect() + try: + sql = f'''select t1.*, + group_concat(t2.name) as phase_name, -- 相位名称 + IFNULL(max(t2.min_green), 0) min_green, -- 最小绿 + IFNULL(max(t2.max_green), 0) max_green -- 最大绿 + from ( + select cm.nodeid, -- 城市ID + cm.xl_crossid, -- 路口ID + cm.jj_crossid, + ct.scheduleid, -- 日计划号 + ct.weekday, + ds.tp_start, -- 开始时段 + ds.control_mode, -- 控制模式 + ds.planid, -- 方案ID + ps.name, -- 方案名称 + ps.cycle, -- 周期 + ps.coord_phaseid, -- 协调阶段号 + ps.offset, -- 绝对相位差 + ps.stageid, -- 阶段号 + ps.stage_duration, -- 阶段时长 + ps.stage_seq, -- 阶段排序 + s.name stage_name, -- 阶段名称 + s.green, -- 绿灯时长 + s.redyellow, -- 红黄时长 + s.yellow, -- 黄灯时长 + s.allred, -- 全红时长 + s.phases -- 相位ID + from {self.DB_Name}.cross_mapping as cm + join {self.DB_Name}.cross_tps as ct on ct.crossid = cm.xl_crossid and ct.citycode = cm.nodeid + join {self.DB_Name}.day_schedule as ds on ds.crossid = cm.jj_crossid and cm.nodeid = ds.nodeid and ds.scheduleid = ct.scheduleid + left join {self.DB_Name}.plan_stage as ps on ds.crossid = ps.crossid and ps.nodeid = ds.nodeid and ps.planid = ds.planid + left join {self.DB_Name}.stage as s on s.crossid = ps.crossid and s.nodeid = ps.nodeid and s.stageid = ps.stageid + where cm.xl_crossid = %s and cm.nodeid = %s + group by cm.nodeid, cm.xl_crossid, ct.scheduleid, ct.weekday, ds.tp_start, ds.control_mode, ds.planid, + ps.name,ps.cycle, ps.coord_phaseid, ps.offset, ps.stageid, ps.stage_duration, ps.stage_seq, + s.name, s.green, s.redyellow, s.yellow, s.allred, s.phases + ) as t1 left join {self.DB_Name}.phase as t2 ON FIND_IN_SET(t2.phaseid, t1.phases) > 0 and t2.crossid = t1.jj_crossid and t2.nodeid = t1.nodeid + group by t1.nodeid, t1.xl_crossid, t1.scheduleid, t1.weekday, t1.tp_start, t1.control_mode, t1.planid, + t1.name, t1.cycle, t1.coord_phaseid, t1.offset, t1.stageid, t1.stage_duration, t1.stage_seq, + t1.stage_name, t1.green, t1.redyellow, t1.yellow, t1.allred, t1.phases + order by t1.weekday, t1.tp_start, t1.stage_seq asc''' + print(cursor.mogrify(sql, (crossid, citycode))) + cursor.execute(sql, (crossid, citycode)) + # 获取所有查询结果 + result = cursor.fetchall() + return result, None + except Exception as e: + return None, e + finally: + self.close(conn, cursor) # if __name__ == '__main__': # tt_5min = get_latest_5min_timestamp() # print(tt_5min) diff --git a/proto/xlcomm.proto b/proto/xlcomm.proto index d0a2e6c..2b02c7c 100644 --- a/proto/xlcomm.proto +++ b/proto/xlcomm.proto @@ -592,6 +592,12 @@ message xl_cross_flowdata_t int32 daynum = 3; // 统计日期 }; +message xl_cross_flowdata_bkt_t +{ + repeated xl_cross_flowdata_t bkt = 1; // 路口流量数据集合 + int32 citycode = 2; // 城市编码 +}; + ///////////////////////////////////////////////////////////////////////////////// diff --git a/proto/xlcomm_pb2.py b/proto/xlcomm_pb2.py index 0b8649a..7627785 100644 --- a/proto/xlcomm_pb2.py +++ b/proto/xlcomm_pb2.py @@ -15,7 +15,7 @@ import proto.traj_pb2 as traj__pb2 import proto.map_match_pb2 as map__match__pb2 -DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\x0cxlcomm.proto\x12\x05xlsyn\x1a\ntraj.proto\x1a\x0fmap_match.proto\"\x95\x01\n\x13rtt_tlink_diverge_t\x12\x12\n\ndist2cross\x18\x01 \x01(\x05\x12\x14\n\x0cout_xlink_id\x18\x02 \x01(\x04\x12\x11\n\teta_speed\x18\x03 \x01(\x05\x12\x13\n\x0b\x64ist2branch\x18\x04 \x01(\x05\x12\x12\n\nout_linkid\x18\x05 \x01(\x04\x12\x18\n\x10refine_eta_speed\x18\x06 \x01(\x05\"o\n\x11rtt_flow_status_t\x12\x14\n\x0cout_xlink_id\x18\x01 \x01(\x04\x12\x0e\n\x06status\x18\x02 \x01(\x05\x12\r\n\x05speed\x18\x03 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_SAMPLE_TAG_T._serialized_end=11902 _RTT_TLINK_DIVERGE_T._serialized_start=53 _RTT_TLINK_DIVERGE_T._serialized_end=202 _RTT_FLOW_STATUS_T._serialized_start=204 @@ -107,20 +107,22 @@ if _descriptor._USE_C_DESCRIPTORS == False: _XL_CROSS_REPORT_T._serialized_end=8281 _XL_CROSS_FLOWDATA_T._serialized_start=8283 _XL_CROSS_FLOWDATA_T._serialized_end=8352 - _RTT_TLINK_HTS_ITEM_T._serialized_start=8355 - _RTT_TLINK_HTS_ITEM_T._serialized_end=8494 - _RTT_TLINK_HTS_BKT_T._serialized_start=8496 - _RTT_TLINK_HTS_BKT_T._serialized_end=8563 - _RTT_LINK_CAR_FLOW_T._serialized_start=8565 - _RTT_LINK_CAR_FLOW_T._serialized_end=8674 - _RTT_LINK_CAR_FLOW_BKT_T._serialized_start=8676 - _RTT_LINK_CAR_FLOW_BKT_T._serialized_end=8747 - _RTT_SPEED_ODD_POINT_T._serialized_start=8750 - _RTT_SPEED_ODD_POINT_T._serialized_end=8972 - _RTT_RG_SINGLE_SLICE_T._serialized_start=8974 - _RTT_RG_SINGLE_SLICE_T._serialized_end=9077 - _RTT_RG_SLICES_T._serialized_start=9080 - _RTT_RG_SLICES_T._serialized_end=9237 - _RTT_RG_SLICES_BKT_T._serialized_start=9239 - _RTT_RG_SLICES_BKT_T._serialized_end=9297 + _XL_CROSS_FLOWDATA_BKT_T._serialized_start=8354 + _XL_CROSS_FLOWDATA_BKT_T._serialized_end=8438 + _RTT_TLINK_HTS_ITEM_T._serialized_start=8441 + _RTT_TLINK_HTS_ITEM_T._serialized_end=8580 + _RTT_TLINK_HTS_BKT_T._serialized_start=8582 + _RTT_TLINK_HTS_BKT_T._serialized_end=8649 + _RTT_LINK_CAR_FLOW_T._serialized_start=8651 + _RTT_LINK_CAR_FLOW_T._serialized_end=8760 + _RTT_LINK_CAR_FLOW_BKT_T._serialized_start=8762 + _RTT_LINK_CAR_FLOW_BKT_T._serialized_end=8833 + _RTT_SPEED_ODD_POINT_T._serialized_start=8836 + _RTT_SPEED_ODD_POINT_T._serialized_end=9058 + _RTT_RG_SINGLE_SLICE_T._serialized_start=9060 + _RTT_RG_SINGLE_SLICE_T._serialized_end=9163 + _RTT_RG_SLICES_T._serialized_start=9166 + _RTT_RG_SLICES_T._serialized_end=9323 + _RTT_RG_SLICES_BKT_T._serialized_start=9325 + _RTT_RG_SLICES_BKT_T._serialized_end=9383 # @@protoc_insertion_point(module_scope)