# -*- coding: utf-8 -*- import pandas as pd import numpy as np import itertools, json from config import load_common_config from utils.mysql import get_all_pipe_by_design_plan_id from utils.dust import group_pipes ,get_pipes_diameter import os def CombCal(fileName, minSpeed, maxSpeed, minRate,df): if df is None: df = pd.read_csv(fileName, encoding='utf-8') res = {} for k in range(1, len(df)+1): for combs in itertools.combinations(range(len(df)), k): m_minSpeed, m_maxSpeed = maxSpeed, -1.0 * minSpeed m_Flow = df['风量Q(m3/h)'][0:combs[0]].sum() * minRate for i in range(combs[0], len(df)): if i in combs: m_Flow += df['风量Q(m3/h)'][i] else: m_Flow += df['风量Q(m3/h)'][i] * minRate m_Speed = m_Flow / (np.pi * np.power(df['管径D(mm)'][i] / 1000.0, 2.0) / 4.0) / 3600.0 if m_Speed <= minSpeed or m_Speed >= maxSpeed: break else: m_minSpeed = min(m_minSpeed, m_Speed) m_maxSpeed = max(m_maxSpeed, m_Speed) if m_Speed > minSpeed and m_Speed < maxSpeed: res[str(set(combs))] = { "mainFlow": m_Flow, "minSpeed": np.round(m_minSpeed, 2), "maxSpeed": np.round(m_maxSpeed, 2), "setNames": str(list(df['编号'][list(combs)].values)) } with open('comb.json', 'w', encoding='utf-8') as json_file: json.dump(res, json_file, indent=2) def CombSelect(S_Comb,file_path='comb.json'): _Res = pd.read_json(file_path, encoding='utf-8') S_Col = [] S_Count = 0 for col in _Res.columns: if eval(col) & S_Comb == S_Comb: if S_Count == 0: S_Count = len(eval(col)) if S_Count + 1 < len(eval(col)): break S_Col.append(col) return _Res[S_Col].T.sort_values(by=['mainFlow', 'minSpeed', 'maxSpeed'], ascending=[True, True, True]) def main(): CombCal(minSpeed=15, maxSpeed=1000, minRate=0.1) def recommend_v1(design_plan_id,prod_pipe_list,pipe_id,force_update): output_dir = './calculated/v1' if not os.path.exists(os.path.join(output_dir, f'{pipe_id}.json')) or force_update: common_config = load_common_config() all_pipes = get_all_pipe_by_design_plan_id(design_plan_id) groups = group_pipes(all_pipes) for parentId, pipes in groups.items(): pipes = get_pipes_diameter(pipes,design_plan_id) data = [] for pipe in pipes: data.append([float(pipe['flow']),float(pipe['diameter']), pipe['id']]) # flow(风量Q(m3/h)) diameter(管径D(mm)) id(编号) df = pd.DataFrame(data, columns=['风量Q(m3/h)', '管径D(mm)', '编号']) CombCal(fileName='',minSpeed=common_config['minSpeed'], maxSpeed=common_config['maxSpeed'], minRate=common_config['minRate'],df=df) # 复制comb.json文件到./calculated/.json with open('comb.json', 'r', encoding='utf-8') as json_file: res = json.load(json_file) os.makedirs(output_dir, exist_ok=True) # 如果目录不存在则创建 with open(f'{output_dir}/{parentId}.json', 'w', encoding='utf-8') as json_file: json.dump(res, json_file, indent=2) # 读取./calculated/.json文件 with open(f'{output_dir}/{pipe_id}.json', 'r', encoding='utf-8') as json_file: res = json.load(json_file) index_set = {index for index, pipe in enumerate(prod_pipe_list) if pipe['valveOpening'] == 100} df = CombSelect(index_set,file_path=f'{output_dir}/{pipe_id}.json') # 把df转换为json格式 df = df.to_dict(orient='records') return df