# -*- coding: utf-8 -*-
"""
Created on Fri Oct 20 16:15:23 2023

@author: ZMK
"""

import numpy as np
import shutil
import os


# 生成的流场图文件
flow_file ="D:\\javaCode\\xishan\\xishan\\xishan\\xinshanFlow\\"

prefix ='C:\\Users\\86134\\Desktop\\xsModel2\\'

ZoneBudget64Exe= prefix + "zonebuget\\ZoneBudget64.exe"

water_bal_zones = prefix +"zonebuget\\water_bal.zones\n"
water_res_zones = prefix +"zonebuget\\water_res.zones\n"

water_lsh_path = prefix + "water_lsh.ini"
water_yhy_path = prefix + "water_yhy.ini"
water_dbw_path = prefix + "water_dbw.ini"


baseModel = prefix + 'verifyModel\\'
baseModel2 = prefix + 'verifyModel2\\'

predictModel= prefix + 'predictModel\\'

predictParamModel= prefix + 'predictParamModel\\'

muiltyModel =  prefix + 'muiltyModel\\'

model_dir = prefix + '0612Model\\'

obswellpath = prefix + '监测井.ini'
obswell_data_path=  prefix + 'water_obs_data.ini'

obs_well = np.loadtxt(obswellpath, dtype=str,encoding='utf-8')

district_path = prefix +"区县.ini"

district= np.loadtxt(district_path, dtype=str,encoding='utf-8')

pumpwellpath = prefix +'抽水井.ini'

pump_well = np.loadtxt(pumpwellpath, dtype=str,encoding='utf-8')

period_path = prefix  +"period.json"

areapath = prefix + '分区.ini'
area_array = np.loadtxt(areapath, dtype=str,encoding='utf-8')

#水均衡路径
water_equ_path = prefix + 'water_equ.ini'
water_equ = np.loadtxt(water_equ_path, dtype=str,encoding='utf-8')

water_equ_path2022 = prefix + 'water_equ2022.ini'
water_equ2022 = np.loadtxt(water_equ_path2022, dtype=str,encoding='utf-8')

#地表高程数据
dis_top_path = prefix + 'md_dis_top.ini'

#分区的储水系数
lpf_path =  prefix + 'md_lpf.ini'
md_lpf =  np.loadtxt(lpf_path, dtype=str,encoding='utf-8')

# #玉泉山矩阵数据
yqs_path=  prefix + '玉泉山泉划分.ini'
xs_yqs_matrix =  np.loadtxt(yqs_path, dtype=str,encoding='utf-8')

# #山区平原区矩阵
xs_mp_path = prefix + '山区平原区划分.ini'
xs_mp_matrix =  np.loadtxt(xs_mp_path, dtype=str,encoding='utf-8')

           
model_config ='D:\\javaCode\\xishan\\objclipdig\\ModelFlow_xishan\\config.ini'

model3d_path='D:/javaCode/xishan/xishan/xishan/output2/'

modeldata_csv_path ="C:/Users/86134/Desktop/xsModel2/0612Model/"

exe_path = 'D:/javaCode/xishan/objclipdig/ModelFlow_xishan/ModelFlow_xishan.exe'


#调动 exe 程序
def callModelexe():
    os.system(exe_path)


#更新模型的exe配置
def updateModelConfig(model_name):
    conf = np.loadtxt(model_config, dtype=str,encoding='utf-8')
    outpath = "outpath=" + model3d_path + model_name
    csvpath = "csvpath=" + modeldata_csv_path + model_name +"/output"
    conf[1]=outpath
    conf[2]=csvpath
    np.savetxt(model_config,conf, newline='\n', fmt='%s' , encoding='utf-8')



def getPumpWellName(row,column):
  
    for index, r, c,ids, qu ,name in pump_well:
        if r==row and c == column:
            return name
    
    return "NONE"


#获取矩阵分组的字典结构
def getAreas():
    arr = np.loadtxt(areapath, dtype=int)
    dict ={}
    for i in range(len(arr)):
        for j in range(len(arr[i])):  
            zb = str(arr[i][j])
            if arr[i][j] == -9999:         
                continue        
            if zb not in dict:
                dict[zb] = [(i,j)]         
            else:
                dict[zb].append((i,j))  
    return dict


def getAreaDictFirstIndex():
    arr = np.loadtxt(areapath, dtype=int)
    dict ={}
    for i in range(len(arr)):
        for j in range(len(arr[i])):           
            if arr[i][j] == -9999:         
                continue        
            if arr[i][j] not in dict:
                dict[arr[i][j]] = [(i,j)]         
             
    return dict
    

#获取分组小标字典数据
def getAreaDictIndexArray():
    arr = np.loadtxt(areapath, dtype=int)
    dict_array={}
    for i in range(len(arr)):
        for j in range(len(arr[i])):  
            zb= str(arr[i][j])
            if arr[i][j] == -9999:         
                continue        
            if zb not in dict_array:
                array= []
                index = getCellIdByRC(i+1,j+1)
                array.append(index)    
                dict_array[zb] = array                              
            else:            
                index = getCellIdByRC(i+1,j+1)
                dict_array[zb].append(index)
            
    return dict_array


def getCellIdByRC(rowVal, columnVal):   
    return (rowVal - 1) * 114 + columnVal - 1;