# -*- coding: utf-8 -*-

import pandas as pd
import numpy as np
import itertools, json, warnings, time
warnings.filterwarnings('ignore', category=Warning)
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 minKCal(flows, maxPipe, minSpeed, maxSpeed, minRate):
    flows.sort()
    minFlow = (np.pi * np.power(maxPipe / 1000.0, 2.0) / 4.0) * 3600.0 * minSpeed - np.sum(flows) * minRate
    maxFlow = (np.pi * np.power(maxPipe / 1000.0, 2.0) / 4.0) * 3600.0 * maxSpeed - np.sum(flows) * minRate
    flows = flows * (1 - minRate)
    minK, maxK = 0, 0
    while minFlow > 0.0 and minK < len(flows):
        minFlow -= flows[len(flows) - 1 - minK]
        if minFlow > 0.0:
            minK += 1
    while maxFlow > 0.0 and maxK < len(flows):
        maxFlow -= flows[maxK]
        if maxFlow > 0.0:
            maxK += 1
    return min(minK + 1, len(flows)), min(maxK + 1, len(flows))

def maxKCal(flows, maxPipe, avgSpeed, minRate):
    flows.sort()
    mFlow = (np.pi * np.power(maxPipe / 1000.0, 2.0) / 4.0) * 3600.0 * avgSpeed - np.sum(flows) * minRate
    mflows = flows * (1 - minRate)
    maxK = 0
    while mFlow > 0.0 and maxK < len(mflows):
        mFlow -= mflows[maxK]
        maxK += 1
    return min(maxK, len(flows))


def CombCal(fileName, minSpeed, maxSpeed, avgSpeed, minRate,df=None):
    if df is None:
        df = pd.read_csv(fileName, encoding='utf-8')
    df['面积m2'] = (np.pi * np.power(df['管径D(mm)'] / 1000.0, 2.0) / 4.0) * 3600.0
    valves = [minRate, 1.0]

    maxK = maxKCal(df['风量Q(m3/h)'].values.copy(), df['管径D(mm)'].values[-1], avgSpeed, minRate)

    mm_arr, qq_arr = [[minRate], [1.0]], []
    m_arr, q_arr = [], []
    for ar in mm_arr:
        if np.count_nonzero(np.array(ar) == 1.0) == 0:
            m_arr.append(ar)
            m_flow = np.dot(ar, df['风量Q(m3/h)'][:len(ar)].values)
            q_arr.append(m_flow)
        else:
            m_flow = np.dot(ar, df['风量Q(m3/h)'][:len(ar)].values)
            m_Speed = m_flow / df['面积m2'][len(ar)-1]
            if m_Speed > minSpeed and m_Speed < maxSpeed:
                m_arr.append(ar)
                q_arr.append(m_flow)

    for k in range(1, len(df)):
        mm_arr = m_arr
        qq_arr = q_arr
        m_arr = []
        q_arr = []
        m_count = 0
        for valve in valves:
            for i in range(len(mm_arr)):
                ar = mm_arr[i].copy()
                ar.append(valve)
                m_nonzero = np.count_nonzero(np.array(ar) == 1.0)
                if m_nonzero == 0 and len(ar) < maxK:
                    m_arr.append(ar)
                    q_arr.append(qq_arr[i] + minRate * df['风量Q(m3/h)'][len(ar)-1])
                else:
                    if m_nonzero <= maxK:
                        m_flow = qq_arr[i] + valve * df['风量Q(m3/h)'][len(ar)-1]
                        m_Speed = m_flow / df['面积m2'][len(ar) - 1]
                        if m_Speed > minSpeed and m_Speed < maxSpeed:
                            m_arr.append(ar)
                            q_arr.append(m_flow)
                            if m_nonzero == maxK:
                                m_count += 1
        # print(f'{k}:{len(m_arr)}:{m_Speed}:{m_count}')

    res = {}
    for ar in m_arr:
        if np.count_nonzero(np.array(ar) == 1.0) > 0:
            df['开度'] = ar
            df['支管风量'] = df['开度'] * df['风量Q(m3/h)']
            df['总管风量'] = df['支管风量'].cumsum()
            df['总管风速'] = df['总管风量'] / df['面积m2']
            m_Flow = df['总管风量'][len(df) - 1]
            m_minSpeed = df['总管风速'][(df['开度'] == 1.0).idxmax():].min()
            m_maxSpeed = df['总管风速'][(df['开度'] == 1.0).idxmax():].max()
            m_name = df['编号'][df['开度'] == 1.0].values
            res[str(set(m_name))] = {
                "mainFlow": m_Flow,
                "minSpeed": np.round(m_minSpeed, 2),
                "maxSpeed": np.round(m_maxSpeed, 2),
                "setNames": str(list(m_name))
            }

    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 recommend_v2(design_plan_id,prod_pipe_list,pipe_id,force_update):
    output_dir = './calculated/v2'
    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'],avgSpeed=common_config['avgSpeed'],df=df)
            # 复制comb.json文件到./calculated/<parentId>.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/<pipe_id>.json文件
    with open(f'./{output_dir}/{pipe_id}.json', 'r', encoding='utf-8') as json_file:
        res = json.load(json_file)
        ids_set = {pipe['id'] for index, pipe in enumerate(prod_pipe_list) if pipe['valveOpening'] == 100}
        df =  CombSelect(ids_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