# -*- coding: utf-8 -*-
"""
Created on Tue Oct 31 16:12:55 2023

@author: ZMK
"""

import flopy.utils.binaryfile as bf
import csv
import Base as base
import os
import json
import subprocess
import re
import ModelPeriod
import numpy as np
import AchiveReport

#添加modle
def addModelJson(model_name,start_time,end_time,remark):
  
      context=""
      prediction_path = base.prefix + "\\model_list.json"
      with open(prediction_path,encoding='utf-8') as f:
             context = json.load(f)   
      array=[]
      for item in context:
             array.append(item) 
             
      dicts={"model_name":model_name,
              "start_time":start_time,"end_time":end_time,"remark":remark} 
      array.append(dicts)
      
      with open(prediction_path, "w",encoding='utf-8') as outfile:
          json.dump(array, outfile,ensure_ascii=False)
      return "保存完毕！"; 
    
#删除model
def removeModelJson(model_name):
      context=""
      prediction_path = base.prefix + "\\model_list.json"
      with open(prediction_path,encoding='utf-8') as f:
             context = json.load(f)   
      array=[]
      for item in context:
          if item["model_name"] != model_name:
              array.append(item) 
              
      with open(prediction_path, "w",encoding='utf-8') as outfile:
          json.dump(array, outfile,ensure_ascii=False)
          
      return "删除模型完毕！"; 
    

def get_model_json(model_name):
      period_json=""
      prediction_path = base.model_dir + model_name +"\\prediction.json"
      with open(prediction_path,encoding='utf-8') as f:
             period_json = json.load(f)    
      return period_json; 
  
def get_model_period(model_name):
     period_json= get_model_json(model_name)     
     start_time = period_json["start_time"]
     end_time = period_json["end_time"]    
     months = ModelPeriod.get_months_in_range_ym(start_time, end_time)
     return months; 
    
def is_cloned_model(model_name):
    paths = base.model_dir + model_name + "\\water_bal.txt"
    if os.path.exists(paths):
        return False
    return True
    

#观测井chart
def obsChartdata(wellId,model_name, row, column):
    
      row = int(row)-1
      column = int(column)-1
      dir=""    
      period_json= get_model_json(model_name)    
      start_time = period_json["start_time"]
      end_time = period_json["end_time"]
      xmonths = ModelPeriod.get_months_in_range_ym(start_time, end_time)
      
      if model_name == base.not_allowed_model:
          dir = base.baseModel2  + "\\modflow.head"
      else:
          dir = base.model_dir + model_name + "\\modflow.head"
          cloned = is_cloned_model(model_name)
          if cloned ==True:
              return  {"y_data": [],"y_data2":[],"x_data":xmonths }
          
      head = bf.HeadFile(dir)
      alldata = head.get_alldata()
      
      #周期数
      months = int(len(alldata)/3)
      ydata= []
      result = {}
      for month in range(months):
          z1= alldata[int(month+1)*3-1,0,:,:]
          cell_data = float(z1[row][column])
          ydata.append(round(cell_data,2))
    
      y_data2=[]
      if model_name == base.not_allowed_model:
          array_data =  np.loadtxt(base.obswell_data_path, dtype=str,encoding='utf-8')
          y_data2= getObsData(wellId,array_data)
          
      result = {"y_data": ydata,"y_data2":y_data2,"x_data": xmonths}
      return result

def getObsData(wellId,array_data):
    result =[]
    new_list =[]
    for item in array_data:
        if item[0]==wellId:
            result.append(item[3])
    for i in range(0,len(result),3):
        data =( float(result[i]) +float(result[i+1])+float(result[i+2]))/3
        data = round(data,2)
        new_list.append(data)
        
    return new_list;
    
    
def getRowCloumnById(index_id):
    row,column,count = 104,114,0
    for  i in range(row):
        for j in range(column):
            if index_id == count:
                return (i,j)
            count = count +1
    return ""        
            
    
    
#地下水信息
def earthWaterChart(model_name, index_id):
    
      row_column =  getRowCloumnById(index_id)  
      row = row_column[0]
      column = row_column[1]
      
      period_json= get_model_json(model_name)    
      start_time = period_json["start_time"]
      end_time = period_json["end_time"]
      xmonths = ModelPeriod.get_months_in_range_ym(start_time, end_time)
      dir = ""
      if model_name == base.not_allowed_model:
          dir = base.baseModel2  + "\\modflow.head"
      else:
          dir = base.model_dir + model_name + "\\modflow.head"
          cloned = is_cloned_model(model_name)
          if cloned ==True:
              return  {"y_data": [],"x_data":xmonths }
      
      head = bf.HeadFile(dir)
      alldata = head.get_alldata()
      
      #周期数
      months = int(len(alldata)/3)
      ydata= []
      result = {}
      for month in range(months):
          z1= alldata[int(month+1)*3-1,0,:,:]
          cell_data = float(z1[row][column])
          ydata.append(round(cell_data,2))

      result = {"y_data": ydata, "x_data": xmonths}
      return result
   
    
#导出csv文件
def exportCsV(model_name):
    
    dir = base.model_dir + model_name + "\\modflow.head"
    out_path = base.model_dir + model_name + "\\output\\"
    if not os.path.exists(out_path):
         os.mkdir(out_path)  
    
    # z1= alldata[int(per1)*3,0,:,:]
    head = bf.HeadFile(dir) 
    alldata = head.get_alldata()
    months = int(len(alldata)/3)  
    layers = 3
    #例如 0-36月
    for month in range(months):
        for layer in range (layers):
            z_last= alldata[(month+1)*3-1,layer,:,:]
            
            filename = out_path + str(month+1) + '-' + str(layer+1) + '.csv'
            f = open(filename, 'w', newline='')
            writer = csv.writer(f)
           
            for p in z_last:
               writer.writerow(p)
            f.close()
            
    return out_path
 
    
#水均衡计算
def waterEqu(model_name):
    if model_name == base.not_allowed_model:  
        water_equ_path = base.prefix + "\\water_equ.json"
        with open(water_equ_path,encoding='utf-8') as f:
             data = json.load(f)
             return data       
    else:
        year = model_name
        title =[year]
        dict ={"title":title}
        
        jx = get_model_json(model_name)
        dict["start_time"]=jx["start_time"]
        dict["end_time"]=jx["end_time"]
        
        paths=base.model_dir + model_name +"\\water_bal.txt"
        wat = water_balance(model_name, paths)
        
        in_data= round(wat[0]+ wat[1]+ wat[2]+ wat[3] , 4)
        out_data= round(wat[4] + wat[5] +  wat[6], 4)
        inout = round(in_data-out_data, 4)
        float_data=[wat[0],wat[1],wat[2],wat[3],in_data,
                     wat[4],wat[5], wat[6],out_data,inout]
        
        inarray=[]
        inarray.append({"name":"降水入渗量","value":wat[0]})
        inarray.append({"name":"河流入渗量","value":wat[1]})
        inarray.append({"name":"一层侧向补给量","value":wat[2]})
        inarray.append({"name":"三层侧向补给量","value":wat[3]})
        outarray=[]
        outarray.append({"name":"人工开采量","value":wat[4]})
        outarray.append({"name":"一层侧向流出量","value":wat[5]})
        outarray.append({"name":"三层侧向流出量","value":wat[6]})
        pie1={str(year):inarray}
        pie2={str(year):outarray}
        
        dict["pie1"]=pie1
        dict["pie2"]=pie2
        
        array2d=[]
        array2d.append(["数据（亿立方米）"])
        for i in range(len(float_data)):
            tmp=[]
            tmp.append(str(float_data[i]))
            array2d.append(tmp)
        dict["data"]=array2d
        return dict        



def run_zonebudget_bal(model_name):
    # 定义exe文件的路径和参数  
    exe_path = base.ZoneBudget64Exe
    txt_path = base.model_dir + model_name + "\\water_bal.txt\n"
    cell_path = base.model_dir + model_name + "\\modflow.flow\n"
    process = subprocess.Popen([exe_path], stdin=subprocess.PIPE,shell = True) 
    process.stdin.write(txt_path.encode())  # 输入参数1  
    process.stdin.write(cell_path.encode()) 
    process.stdin.write(b"title\n") 
    process.stdin.write(base.water_bal_zones.encode()) 
    process.stdin.write(b"A\n")
    output, _ = process.communicate()
    print(output)


def run_zonebudget_res(model_name):
    # 定义exe文件的路径和参数  
    exe_path = base.ZoneBudget64Exe
    txt_path = base.model_dir + model_name + "\\water_res.txt\n"
    cell_path = base.model_dir + model_name + "\\modflow.flow\n"
    process = subprocess.Popen([exe_path], stdin=subprocess.PIPE,shell = True) 
    process.stdin.write(txt_path.encode())  # 输入参数1  
    process.stdin.write(cell_path.encode()) 
    process.stdin.write(b"title\n") 
    process.stdin.write(base.water_res_zones.encode()) 
    process.stdin.write(b"A\n")
    output, _ = process.communicate()
    print(output)

def reg_find_int(text):
    numbers = re.findall(r'\d+', text)
    return numbers


def read_txt(path):
    data =[]
    with open(path, 'r') as file:
        lines = file.readlines()   
        for line in lines:
           data.append(line)
    return data  
   
#解析水均衡数据 
def water_balance(model_name,paths):
    data= read_txt(paths)  
    lens = len(data) 
    index = 0 
    segment=[]
    dicts={}
    flag = 0
    title=""
    while index < lens:
        strs = data[index].strip()
        if strs.startswith("Flow Budget for Zone"):
            segment=[]
            flag = 1
            title=strs
        if strs.startswith("Percent Discrepancy"):
            segment.append(strs) 
            numbers = reg_find_int(title)
            key = ','.join(numbers)
            dicts[key]=segment
            flag = 0       
        if flag ==1 :
            segment.append(strs)
        index=index+1
        
    recharge = 0  
    for key in dicts:
        array = dicts[key]
        temp=[]
        for item in array:
            if item.startswith("RECHARGE") :
                strs = item.replace(" ", "").replace("RECHARGE=", "")
                temp.append(float(strs))
                
        recharge += (temp[0]-temp[1])
    
    #河流入渗量（正）	所有应力期，for Zone 3的WELLS项相加
    zone3 = 0
    for key in dicts:
        if key.startswith("3,"):
            array = dicts[key]
            temp=[]
            for item in array:
                 if item.startswith("WELLS") :
                     strs = item.replace(" ", "").replace("WELLS=", "")
                     temp.append(float(strs))
       
            zone3 += (temp[0]-temp[1])
             
    #L1侧向补给量（正）	所有应力期，for Zone 4的IN-WELLS项相加
    Zone4_in_well=0
    for key in dicts:
        if key.startswith("4,"):
            array = dicts[key]
            for item in array:
                 if item.startswith("WELLS") :
                     strs = item.replace(" ", "").replace("WELLS=", "")
                     data = float(strs)
                     Zone4_in_well +=data
                     break
    
    #L3侧向补给量（正）	所有应力期，for Zone 8的IN-WELLS项相加
    Zone8_in_well =0 
    for key in dicts:
        if key.startswith("8,"):
            array = dicts[key]
            for item in array:
                 if item.startswith("WELLS") :
                     strs = item.replace(" ", "").replace("WELLS=", "")
                     data = float(strs)
                     Zone8_in_well +=data
                     break   
    
    #人工开采量（负）	所有应力期，for Zone 5的OUT-WELLS项相加
    zone5out =0
    for key in dicts:
        if key.startswith("5,"):
            array = dicts[key]
            for item in array:
                 if item.startswith("WELLS") :
                     strs = item.replace(" ", "").replace("WELLS=", "")
                     data = float(strs)
                     zone5out +=data 
     
      #L1侧向流出量（负）	所有应力期，for Zone 4的OUT-WELLS项相加  
    Zone4_out_well=0  
    for key in dicts:
        if key.startswith("4,"):
            array = dicts[key]
            for item in array:
                 if item.startswith("WELLS") :
                     strs = item.replace(" ", "").replace("WELLS=", "")
                     data = float(strs)
                     Zone4_out_well +=data
     
    # L3=L3侧向流出量（负）
    L3=0.0
    result =[recharge,zone3,Zone4_in_well,Zone8_in_well,zone5out,Zone4_out_well,L3]
    for i in range(len(result)):
        # 每行数据实际上计算 的是 一个step , 1个step =10天
        result[i]= round(result[i]/100000000*10, 4)
    
    return result


#解析水资源量数据 
def water_res(model_name,paths):
    data= read_txt(paths) 
    lens = len(data)
    index = 0
    segment=[]
    dicts={}
    flag = 0
    title=""
    while index < lens:
        strs = data[index].strip()
        if strs.startswith("Flow Budget for Zone"):
            segment=[]
            flag = 1
            title=strs
        if strs.startswith("Percent Discrepancy"):
            segment.append(strs) 
            numbers = reg_find_int(title)
            key = ','.join(numbers)
            dicts[key]=segment
            flag = 0       
        if flag ==1 :
            segment.append(strs)
        index=index+1
        
    # 大气降水	for zone1里所有的recharge项相加（包括in和out）
    zone1_rechage = 0
    
    for key in dicts:
       if key.startswith("1,"):
          array = dicts[key]
          temp=[]
          for item in array:
              if item.startswith("RECHARGE") :
                  strs = item.replace(" ", "").replace("RECHARGE=", "")
                  temp.append(float(strs))
                
          zone1_rechage += (temp[0]-temp[1])
    
    #永定河渗漏	for zone1里所有的zone2项相加（包括in和out）
    zone1_well = 0
    for key in dicts:
        if key.startswith("1,"):
            array = dicts[key]
            indata,outdata= 0,0
            for item in array:
                 if item.startswith("Zone   2 to   1") :
                     strs = item.replace(" ", "").replace("Zone2to1=", "")
                     indata = float(strs)
                     
                 if item.startswith("Zone   1 to   2") :
                     strs = item.replace(" ", "").replace("Zone1to2=", "")
                     outdata = float(strs)
       
            zone1_well += (indata-outdata)
           
    #侧向流入	For zone7 里所有的zone8项相加（包括in和out）
    zone7=0
    for key in dicts:
        if key.startswith("7,"):
            array = dicts[key]
            indata,outdata= 0,0
            for item in array:
                 if item.startswith("Zone   8 to   7") :
                     strs = item.replace(" ", "").replace("Zone8to7=", "")
                     indata = float(strs)
                   
                 if item.startswith("Zone   7 to   8") :
                     strs = item.replace(" ", "").replace("Zone7to8=", "")
                     outdata = float(strs)
                    
            zone7 += (indata-outdata)
    
    #越流排泄	For zone6 里所有的zone7项相加（包括in和out）
    zone6 =0 
    for key in dicts:
        if key.startswith("6,"):
            array = dicts[key]
            indata,outdata= 0,0
            for item in array:
                 if item.startswith("Zone   7 to   6") :
                     strs = item.replace(" ", "").replace("Zone7to6=", "")
                     indata = float(strs)
                     
                 if item.startswith("Zone   6 to   7") :
                     strs = item.replace(" ", "").replace("Zone6to7=", "")
                     outdata = float(strs)
            zone6 += (indata-outdata)
    
    result =[zone1_rechage,zone1_well,zone7,zone6]
    for i in range(len(result)):
        result[i]= round(result[i]/100000000*10,4)
    return result


 #解析水资源量数据 
def water_res_month(model_name,paths,per):
    data= read_txt(paths) 
    lens = len(data)
    index = 0
    segment=[]
    dicts={}
    flag = 0
    title=""
    while index < lens:
        strs = data[index].strip()
        if strs.startswith("Flow Budget for Zone"):
            segment=[]
            flag = 1
            title=strs
        if strs.startswith("Percent Discrepancy"):
            segment.append(strs) 
            numbers = reg_find_int(title)
            key = ','.join(numbers)
            dicts[key]=segment
            flag = 0       
        if flag ==1 :
            segment.append(strs)
        index=index+1
        
    # 大气降水	for zone1里所有的recharge项相加（包括in和out）
    zone1_rechage = 0
    zone1_keys=[ "1,1,"+str(per+1),"1,2,"+str(per+1),"1,3,"+str(per+1)]
    for key in zone1_keys:
          array = dicts[key]
          temp=[]
          for item in array:
              if item.startswith("RECHARGE") :
                  strs = item.replace(" ", "").replace("RECHARGE=", "")
                  temp.append(float(strs))   
          zone1_rechage += (temp[0]-temp[1])
          
    #永定河渗漏	for zone1里所有的zone2项相加（包括in和out）
    zone1_well = 0
    zone1_well_keys=["1,1,"+str(per+1),"1,2,"+str(per+1),"1,3,"+str(per+1)]
    for key in zone1_well_keys:
            array = dicts[key]
            indata,outdata= 0,0
            for item in array:
                 if item.startswith("Zone   2 to   1") :
                     strs = item.replace(" ", "").replace("Zone2to1=", "")
                     indata = float(strs)
                     
                 if item.startswith("Zone   1 to   2") :
                     strs = item.replace(" ", "").replace("Zone1to2=", "")
                     outdata = float(strs)
       
            zone1_well += (indata-outdata)
           
    #侧向流入	For zone7 里所有的zone8项相加（包括in和out）
    zone7=0
    zone7_keys=["7,1,"+str(per+1),"7,2,"+str(per+1),"7,3,"+str(per+1)]
    for key in zone7_keys:
            array = dicts[key]
            indata,outdata= 0,0
            for item in array:
                 if item.startswith("Zone   8 to   7") :
                     strs = item.replace(" ", "").replace("Zone8to7=", "")
                     indata = float(strs)
                     
                 if item.startswith("Zone   7 to   8") :
                     strs = item.replace(" ", "").replace("Zone7to8=", "")
                     outdata = float(strs)
            zone7 += (indata-outdata)
  
    #越流排泄	For zone6 里所有的zone7项相加（包括in和out）
    zone6 =0 
    zone6_keys=["6,1,"+str(per+1),"6,2,"+str(per+1),"6,3,"+str(per+1)]
    for key in zone6_keys:
            array = dicts[key]
            indata,outdata= 0,0
            for item in array:
                 if item.startswith("Zone   7 to   6") :
                     strs = item.replace(" ", "").replace("Zone7to6=", "")
                     indata = float(strs)
                     
                 if item.startswith("Zone   6 to   7") :
                     strs = item.replace(" ", "").replace("Zone6to7=", "")
                     outdata = float(strs)
            zone6 += (indata-outdata)
 
    result =[zone1_rechage,zone1_well,zone7,zone6]
    for i in range(len(result)):
        result[i]= round(result[i]/100000000*10, 4)
    
    return result  

#多模型的水位
def water_depth(model_name):
    name_array = model_name.split(",")
    
    yhyMatrix = np.loadtxt(base.water_yhy_path, dtype=str,encoding='utf-8')
    lshMatrix  = np.loadtxt(base.water_lsh_path, dtype=str,encoding='utf-8')
    dbwMatrix =  np.loadtxt(base.water_dbw_path, dtype=str,encoding='utf-8')
    
    res ={} 
    #颐和园，莲石湖，东北旺的水平线和多模型的多折线值 
    yhydata=[]
    base1={"name":"地表高程","data":[52]*12}
    yhydata.append(base1)
    
    lshdata=[]
    base2={"name":"地表高程","data":[80]*12}
    lshdata.append(base2)
    
    dbwdata=[]
    base3={"name":"地表高程","data":[49]*12}
    dbwdata.append(base3)
    
    months = ModelPeriod.get_months_in_range_ym("2023-01","2023-12")
    
    for i in range(len(name_array)):
        if name_array[i] != '':
 
             index = muiltyModelIndex(name_array[i])
             array1 = get_column(yhyMatrix,index)
             array2 = get_column(lshMatrix,index)
             array3 = get_column(dbwMatrix,index)
                
             yhydata.append({"name":name_array[i],"data":convertColumnData(array1)})
             lshdata.append({"name":name_array[i],"data":convertColumnData(array2)})
             dbwdata.append({"name":name_array[i],"data":convertColumnData(array3)})
            
    rchMatrix = np.loadtxt(base.prefix + "base_water.ini", dtype=str,encoding='utf-8')
    riverMatrix = np.loadtxt(base.prefix + "base_river.ini", dtype=str,encoding='utf-8')
    pumpMatrix = np.loadtxt(base.prefix + "base_mining.ini", dtype=str,encoding='utf-8')
    
    rchdata=[]
    rch_base1 = rchMatrix[1]
    rch_base1_float =[]
    for i in range (0,len(rch_base1)):
         float_data =  round(float(rch_base1[i])/9,2)
         rch_base1_float.append(float_data)
    
    rchdata.append({"name":"基准值","data":rch_base1_float})
    
    riverdata=[]
    riverdata.append({"name":"基准值","data":riverMatrix.astype(float).tolist()})
    
    pumpdata=[]
    pumpX=pumpMatrix[1]
    pump_float=[]
    for i in range (0,len(pumpX)):
         float_data =  round(float(pumpX[i]),2)
         pump_float.append(float_data)
    
    pumpdata.append({"name":"基准值","data":pump_float})     
       
    res["xAxis"]  = months
    res["yhy_line"]  = yhydata
    res["lsh_line"]  = lshdata
    res["dbw_line"]  = dbwdata
    
    
    for i in range(len(name_array)):
        if name_array[i] != '':
            rchdata.append(rchBaseResult(rchMatrix,name_array[i]))
            riverdata.append(riverBaseResult(riverMatrix, name_array[i]))
            pumpdata.append(pumpBaseResult(pumpMatrix, name_array[i]))
            
    res["rch_line"]  = rchdata
    res["river_line"]  = riverdata
    res["pump_line"]  = pumpdata     
    
    yqsdata=[]
    pyqdata=[]
    sqdata=[]
    for i in range(len(name_array)):
         if name_array[i] != '':
             paths = base.muiltyModel + name_array[i] + "\\modflow.head"
             resdata = AchiveReport.getXs3LineChart(paths)    
             pyqdata.append({"name":name_array[i],"data":resdata["pyq"]})
             sqdata.append({"name":name_array[i],"data":resdata["sq"]})
             yqsdata.append({"name":name_array[i],"data":resdata["yqs"]})
             
    res["yqs_line"]  = yqsdata  
    res["sq_line"]  = sqdata 
    res["pyq_line"]  = pyqdata            

    return res 

#小场景水位 和变幅
def xs_depth(model_name):
    res={}
    line1,line2=[],[]
    paths = base.model_dir + model_name + "\\modflow.head"
    if model_name == base.not_allowed_model:
        paths = base.baseModel2 + "\\modflow.head"
    
    resdata = AchiveReport.getXs3LineChart(paths)    
    line1.append({"name":"平原区","data":roundArray(resdata["pyq"])})
    line1.append({"name":"山区","data":roundArray(resdata["sq"])})
    line1.append({"name":"玉泉山地区","data":roundArray(resdata["yqs"])})
    res["depth"]  = line1  
    
    line2.append({"name":"平原区","data":xs_bf(resdata["pyq"])})
    line2.append({"name":"山区","data":xs_bf(resdata["sq"])})
    line2.append({"name":"玉泉山地区","data":xs_bf(resdata["yqs"])})
    res["bf"]  = line2          
    return res 

def xs_bf(array):
    newlist=[]
    newlist.append(0)
    lens = len(array)-1
    for i in range(0,lens):
        x = array[i+1]-array[i]
        newlist.append(round(x,2))
    return newlist

def roundArray(array):
    newlist=[]
    for item in array:
        item = round(item,2)
        newlist.append(item)
    return newlist

#rch 基准数据
def rchBaseResult(rchMatrix,sp):
    rchDict ={}   
    rch_base1 = rchMatrix[1]
    rch_base2 = rchMatrix[2]
    rch_base3 = rchMatrix[3]    
    trump = getmuiltyModelparam(sp)
    
    types = trump[0]
    rch_x = trump[1]
    
    if types ==1:
        temp = muiltyArray(rch_base1,rch_x)
        for i in range(0,len(temp)):
            temp[i] =round(temp[i]/9,2)    
        rchDict={"name":sp,"data":temp}
    if types ==2:
        temp = muiltyArray(rch_base2,rch_x)
        for i in range(0,len(temp)):
            temp[i] =round(temp[i]/9,2) 
        rchDict={"name":sp,"data":temp}    
    if types ==3:
        temp = muiltyArray(rch_base3,rch_x)
        for i in range(0,len(temp)):
            temp[i] =round(temp[i]/9,2) 
        rchDict={"name":sp,"data":temp}
    
    return rchDict

#河流基准 数据
def riverBaseResult(riverMatrix,sp):   
    trump = getmuiltyModelparam(sp)  
    river_x = trump[2]
    riverDict={"name":sp,"data":muiltyArray(riverMatrix,river_x)}
    return riverDict


#抽水井基准数据
def pumpBaseResult(pumpMatrix,sp):
    trump = getmuiltyModelparam(sp)
    pump_x =trump[3]
    pumpDict={"name":sp,"data":muiltyArray(pumpMatrix[1],pump_x)}
    return pumpDict
    

def muiltyArray(array,scale):
    result =[]
    for item in array:
        x= round(float(item) * scale,2)
        result.append(x)
    return result


def convertColumnData(array):
    result =[]
    new_list=[]
    for i in range(len(array)):
        if i!= 0:         
             data =  transToNum(array[i])
             result.append(data) 
    for index in range(len(result)):
        if index % 3 == 0:
            new_list.append(result[index])     
    return new_list   

def transToNum(str):
    data = 0
    try:
        data=  round(float(str),2) 
        return data
    except ValueError():
        return 0    
  
     
 #获取预测场景的下标值， 需要从ini 文件中按照列进行读取
def muiltyModelIndex(name):
    models= muiltyModelList()
    indexs = models.index(name)
    return indexs

#预测模型列表
def  muiltyModelList():
    models=["SP0-0","SP1-1","SP1-2","SP1-3","SP2-1","SP2-2","SP2-3","SP3-1",
            "SP3-2","SP3-4","SP3-5","SP3-6","SP3-7","SP4-1","SP4-7"]
    return models
    
   

#Np获取某一列的值
def get_column(matrix, column_number):
    column = matrix[:, column_number]
    return column

#元组中 1=降雨类型  2=倍数 3,河流倍数 4,抽水井倍数
def getmuiltyModelparam(sp):
    dicts={
        "SP0-0":(1,1,1,1),
        "SP1-1":(2,1,1,1),
        "SP1-2":(3,1,1,1),
        "SP1-3":(3,1.2,1,1),     
        "SP2-1":(1,1,2,1),
        "SP2-2":(1,1,5,1),
        "SP2-3":(1,1,10,1),     
        "SP3-1":(1,1,1,0.25),
        "SP3-2":(1,1,1,0.5),
        "SP3-4":(1,1,1,0),    
        "SP3-5":(1,1,1,0.4),
        "SP3-6":(1,1,1,0.3),
        "SP3-7":(1,1,1,0.6),
        
        "SP4-1":(1,1,2,0.5),
        "SP4-7":(3,1.2,10,0)}
    return dicts[sp]