# 获取数据
from LIB.BACKEND import DBManager

import os
import pandas as pd
import numpy as np
import bisect
import datetime
# import matplotlib.pyplot as plt

#参数输入
Capacity = 53.6
PackFullChrgVolt=69.99
CellFullChrgVolt=3.37
CellVoltNums=20
CellTempNums=4
FullChrgSoc=98
CellVoltPort=[3.357,3.358,3.359,3.36,3.361]
PeakSoc=57
# #40Ah-OCV
# LookTab_SOC = [0, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100]
# LookTab_OCV = [3.3159, 3.4502, 3.4904, 3.5277, 3.5590, 3.5888, 3.6146, 3.6312, 3.6467, 3.6642, 3.6865, 3.7171, 3.7617,
#                3.8031, 3.8440, 3.8888, 3.9376, 3.9891, 4.0451, 4.1068, 4.1830]
#55Ah-OCV
LookTab_SOC = [0,  10,  20,  30,  40,  50,  60,  70,  80,  90,  100]
LookTab_OCV = [3.1820, 3.2250, 3.2730, 3.2840, 3.2860, 3.2920, 3.3210, 3.3260, 3.3270, 3.3270, 3.3640]

# 获取数据时间段
def cal_LFPLeakCurrent(sn, end_time, start_time):
    end_time = end_time
    strat_time = start_time

    sn = sn
    st = strat_time
    et = end_time

    dbManager = DBManager.DBManager()
    df_data = dbManager.get_data(sn=sn, start_time=st, end_time=et, data_groups=['bms'])
    df_bms = df_data['bms']

    #寻找电压最大值
    packcrnt=df_bms['总电流[A]']
    SOC=df_bms['SOC[%]']
    bmsstat=df_bms['充电状态']
    time= pd.to_datetime(df_bms['时间戳'], format='%Y-%m-%d %H:%M:%S')

    #第一步：筛选充电数据
    ChgStart=[]
    ChgEnd=[]
    for i in range(3, len(time) - 3):
        if i==3 and bmsstat[i]==2 and bmsstat[i+1]==2 and bmsstat[i+2]==2:
            ChgStart.append(i)
        elif bmsstat[i-2]!=2 and bmsstat[i-1]!=2 and bmsstat[i]==2:
            ChgStart.append(i)
        elif bmsstat[i-1]==2 and bmsstat[i]!=2 and bmsstat[i+1]!=2:
            ChgEnd.append(i)
        elif i == (len(time) - 4) and bmsstat[len(bmsstat)-1] == 2 and bmsstat[len(bmsstat)-2] == 2:
            ChgEnd.append(len(time)-1)

    #第二步：筛选充电起始Soc<45%，且单体最小电压>3.37V的数据
    ChgStartValid=[]
    ChgEndValid=[]
    if ChgStart:
        for i in range(len(ChgEnd)):
            #寻找最小电压值
            cellvolt = []
            for j in range(1, CellVoltNums+1):
                s = str(j)
                volt = df_bms['单体电压' + s]/1000
                cellvolt.append(max(volt[ChgStart[i]:ChgEnd[i]]))
            if min(cellvolt)>CellFullChrgVolt and SOC[ChgStart[i]]<40 and (ChgEnd[i]-ChgStart[i])>10:
                if ((time[ChgEnd[i]]-time[ChgStart[i]]).total_seconds())/(ChgEnd[i]-ChgStart[i])<30:
                    ChgStartValid.append(ChgStart[i])
                    ChgEndValid.append(ChgEnd[i])

    #第三步：计算充电每个单体到达3.368V的Ah差
    #定义寻找电压3.368V的数据点
    def data_search(data1,data2,data3,data4):
        Soc=0
        for m in range(1,len(data1)):
            t=(data2[m]-data2[m-1]).total_seconds()
            Soc=Soc-data3[m]*t/(3600*Capacity)
            if data1[m]>data4:
                DetaT=(data2[m]-data2[0]).total_seconds()
                return Soc,m
                break
    
    if ChgStartValid:
        df_DetaTime=pd.DataFrame()
        df_DetaTime1=pd.DataFrame()
        df_detatime=pd.DataFrame()
        for i in range(len(ChgStartValid)):
            DetaSoc1=[]
            DetaSoc2 = []
            DetaSoc=[]
            a=list(range(5))
            b=list(range(5))
            #计算1-10号电芯到达特定电压值得时间和SOC
            for j in range(1, CellVoltNums-9):
                s = str(j)
                cellvolt = df_bms['单体电压' + s]/1000
                cellvolt=list(cellvolt[ChgStartValid[i]:ChgEndValid[i]])
                Time=list(time[ChgStartValid[i]:ChgEndValid[i]])
                Packcrnt=list(packcrnt[ChgStartValid[i]:ChgEndValid[i]])
                for k in range(len(CellVoltPort)):
                    a[k],b[k]=data_search(cellvolt,Time,Packcrnt,CellVoltPort[k])
                DetaSoc1.append(np.mean(a))  #计算到达3.368V的时长
                # DetaT.append((Time[b]-Time[0]).total_seconds())

            #计算1-10号电芯到达特定电压值的平均Soc
            Socmean1=(sum(DetaSoc1)-max(DetaSoc1)-min(DetaSoc1))/(len(DetaSoc1)-2)
            # Tmean=np.mean(DetaT)

            ##计算11-20号电芯到达特定电压值得时间和SOC
            for j in range(11, CellVoltNums+1):
                s = str(j)
                cellvolt = df_bms['单体电压' + s]/1000
                cellvolt=list(cellvolt[ChgStartValid[i]:ChgEndValid[i]])
                Time=list(time[ChgStartValid[i]:ChgEndValid[i]])
                Packcrnt=list(packcrnt[ChgStartValid[i]:ChgEndValid[i]])
                for k in range(len(CellVoltPort)):
                    a[k],b[k]=data_search(cellvolt,Time,Packcrnt,CellVoltPort[k])
                DetaSoc2.append(np.mean(a))  #计算到达3.368V的时长

            #计算11-20号电芯到达特定电压值的平均Soc
            Socmean2=(sum(DetaSoc2)-max(DetaSoc2)-min(DetaSoc2))/(len(DetaSoc2)-2)

            #计算每个电芯的Soc差

            DetaSoc3=DetaSoc1+DetaSoc2
            for j in range(len(DetaSoc3)):
                if j<10:
                    Socmean=Socmean1
                else:
                    Socmean=Socmean2
                DetaSoc.append(DetaSoc3[j]-Socmean)
                # DetaSoc.append((DetaT[j]-Tmean)*9.5/(Capacity*3600))
            df_DetaTime[time[ChgStartValid[i]]]=DetaSoc
        #漏电流计算
        column=[]
        time1=[]
        sn1=[]

        for index, row in df_DetaTime.iteritems():
            column.append(index) #提取列名称

        for  i in range(1,len(column)):#计算漏电流值
            df_DetaTime1[column[i]] = df_DetaTime.apply(lambda x: (x[column[i-1]] -  x[column[i]])*1000*Capacity*3600/((column[i]-column[i-1]).total_seconds()), axis=1)
            time1.append(column[i])
            sn1.append(sn)
        df_detatime['time']=time1
        df_detatime['sn']=sn1

        for i in range(CellVoltNums):
            cell=[]
            for j in range(1,len(column)):
                cell.append(df_DetaTime1[column[j]][i])
            df_detatime['cell'+str(i+1)]=cell
        return df_detatime
    return pd.DataFrame()