# -*- coding: utf-8 -*-
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"""
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Created on Tue Oct 31 16:12:55 2023
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@author: ZMK
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"""
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import flopy
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import flopy.utils.binaryfile as bf
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import csv
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import Base as base
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import os
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import json
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import ModelPeriod
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import numpy as np
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def get_model_json(model_name):
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period_json=""
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prediction_path = base.model_dir + model_name +"\\prediction.json"
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with open(prediction_path,encoding='utf-8') as f:
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period_json = json.load(f)
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return period_json;
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def get_model_period(model_name):
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period_json=""
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prediction_path = base.model_dir + model_name +"\\prediction.json"
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with open(prediction_path,encoding='utf-8') as f:
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period_json = json.load(f)
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start_time = period_json["start_time"]
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end_time = period_json["end_time"]
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months = ModelPeriod.get_months_in_range_ym(start_time, end_time)
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return months;
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#观测井chart
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def obsChartdata(model_name, row, column):
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row = int(row)-1
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column = int(column)-1
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dir = base.model_dir + model_name + "\\modflow.head"
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head = bf.HeadFile(dir)
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alldata = head.get_alldata()
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period = len(alldata)
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layer = 3
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xdata = []
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ydata = []
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result = {}
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for per in range(period):
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for lay in range(layer):
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if per % 3 == 0 and lay == 0:
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md = (int)(lay / 3 + 1)
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per_array = alldata[per][lay]
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cell_data = (float)(per_array[row][column])
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ydata.append(cell_data)
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period_json= get_model_json(model_name)
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start_time = period_json["start_time"]
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end_time = period_json["end_time"]
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months = ModelPeriod.get_months_in_range_ym(start_time, end_time)
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result = {"y_data": ydata, "x_data": months}
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return result
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def getRowCloumnById(index_id):
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row = 104
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column =114
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count=0
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for i in range(row):
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for j in range(column):
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if index_id == count:
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return (i,j)
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count = count +1
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return ""
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#地下水信息
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def earthWaterChart(model_name, index_id):
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row_column = getRowCloumnById(index_id)
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row = row_column[0]
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column = row_column[1]
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dir = base.model_dir + model_name + "\\modflow.head"
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head = bf.HeadFile(dir)
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alldata = head.get_alldata()
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period = len(alldata)
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layer = 3
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ydata = []
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result = {}
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for per in range(period):
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for lay in range(layer):
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if per % 3 == 0 and lay == 0:
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per_array = alldata[per][lay]
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cell_data = (float)(per_array[row][column])
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ydata.append(cell_data)
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period_json= get_model_json(model_name)
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start_time = period_json["start_time"]
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end_time = period_json["end_time"]
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months = ModelPeriod.get_months_in_range_ym(start_time, end_time)
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result = {"y_data": ydata, "x_data": months}
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return result
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def heatmapdata(model_name,period):
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dir = base.model_dir + model_name + "\\modflow.head"
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head = bf.HeadFile(dir)
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alldata = head.get_alldata()
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index = int(period)*3
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return alldata[index][0]
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#水均衡计算
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def waterEqu(model_name):
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if model_name == '202001_202212':
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water_equ_path = base.prefix + "\\water_equ.json"
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with open(water_equ_path,encoding='utf-8') as f:
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data = json.load(f)
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return data
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else:
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year = model_name[0:4]
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title =[year]
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dict ={"title":title}
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celldata = np.array(base.water_equ2022).tolist()
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predict_json= get_model_json(model_name)
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a1=float(celldata[0])
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a2=float(celldata[1])
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a3=float(celldata[2])
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a4=float(celldata[3])
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b1=float(celldata[4])
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b2=float(celldata[5])
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b3=float(celldata[6])
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if predict_json["rain"]:
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a1= float(predict_json["rain"]["ratio"]) * float(celldata[0])
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a3= float(predict_json["rain"]["ratio"]) * float(celldata[2])
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a4= float(predict_json["rain"]["ratio"]) * float(celldata[3])
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b2= float(predict_json["rain"]["ratio"]) * float(celldata[5])
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b3= float(predict_json["rain"]["ratio"]) * float(celldata[6])
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if predict_json["river"]:
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a2= float(predict_json["river"]["ratio"]) * float(celldata[1])
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if predict_json["mine"]:
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b1= b1
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in_data= a1+a2+a3+a4
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out_data= b1 +b2 + b3
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float_data=[a1,a2,a3,a4,in_data,b1,b2,b3,out_data,in_data-out_data]
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inarray=[]
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inarray.append({"name":"降水入渗量","value":a1})
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inarray.append({"name":"河流入渗量","value":a2})
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inarray.append({"name":"L1侧向补给量","value":a3})
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inarray.append({"name":"L3侧向补给量","value":a4})
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outarray=[]
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outarray.append({"name":"人工开采量","value":b1})
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outarray.append({"name":"L1侧向流出量","value":b2})
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outarray.append({"name":"L3侧向流出量","value":b3})
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pie1={str(year):inarray}
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pie2={str(year):outarray}
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dict["pie1"]=pie1
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dict["pie2"]=pie2
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array2d=[]
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array2d.append([str(year)])
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for i in range(len(float_data)):
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tmp=[]
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tmp.append(str(float_data[i]))
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array2d.append(tmp)
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dict["data"]=array2d
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return dict
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#导出csv文件
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def exportCsV(model_name):
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dir = base.model_dir + model_name + "\\modflow.head"
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out_path = base.model_dir + model_name + "\\output\\"
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if not os.path.exists(out_path):
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os.mkdir(out_path)
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head = bf.HeadFile(dir)
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alldata = head.get_alldata()
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month = len(alldata)
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layer = 3
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for i in range(month):
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for j in range(layer):
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if i % 3 == 0:
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md = (int)(i / 3 + 1)
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filename = out_path + str(md) + '-' + str(j+1) + '.csv'
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f = open(filename, 'w', newline='')
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writer = csv.writer(f)
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for p in alldata[i][j]:
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writer.writerow(p)
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f.close()
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return out_path
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