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| | | @author: ZMK |
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| | | """ |
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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 subprocess |
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| | | import re |
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| | | import ModelPeriod |
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| | | import numpy as np |
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| | | import AchiveReport |
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| | | |
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| | | |
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| | | #添加modle |
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| | | def addModelJson(model_name,start_time,end_time,remark): |
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| | | |
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| | | context="" |
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| | | prediction_path = base.prefix + "\\model_list.json" |
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| | | with open(prediction_path,encoding='utf-8') as f: |
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| | | context = json.load(f) |
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| | | array=[] |
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| | | for item in context: |
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| | | array.append(item) |
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| | | |
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| | | dicts={"model_name":model_name, |
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| | | "start_time":start_time,"end_time":end_time,"remark":remark} |
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| | | array.append(dicts) |
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| | | |
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| | | with open(prediction_path, "w",encoding='utf-8') as outfile: |
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| | | json.dump(array, outfile,ensure_ascii=False) |
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| | | return "保存完毕！"; |
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| | | |
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| | | #删除model |
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| | | def removeModelJson(model_name): |
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| | | context="" |
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| | | prediction_path = base.prefix + "\\model_list.json" |
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| | | with open(prediction_path,encoding='utf-8') as f: |
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| | | context = json.load(f) |
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| | | array=[] |
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| | | for item in context: |
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| | | if item["model_name"] != model_name: |
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| | | array.append(item) |
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| | | |
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| | | with open(prediction_path, "w",encoding='utf-8') as outfile: |
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| | | json.dump(array, outfile,ensure_ascii=False) |
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| | | |
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| | | return "删除模型完毕！"; |
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| | | |
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| | | |
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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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| | | |
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| | | period_json = json.load(f) |
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| | | return period_json; |
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| | | |
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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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| | | |
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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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| | | |
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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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| | | |
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| | | def is_cloned_model(model_name): |
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| | | paths = base.model_dir + model_name + "\\water_bal.txt" |
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| | | if os.path.exists(paths): |
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| | | return False |
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| | | return True |
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| | | |
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| | | |
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| | | #观测井chart |
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| | | def obsChartdata(model_name, row, column): |
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| | | def obsChartdata(wellId,model_name, row, column): |
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| | | |
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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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| | | |
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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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| | | |
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| | | layer = 3 |
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| | | |
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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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| | | |
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| | | cell_data = (float)(per_array[row][column]) |
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| | | ydata.append(cell_data) |
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| | | |
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| | | period_json= get_model_json(model_name) |
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| | | |
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| | | dir="" |
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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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| | | xmonths = ModelPeriod.get_months_in_range_ym(start_time, end_time) |
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| | | |
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| | | months = ModelPeriod.get_months_in_range_ym(start_time, end_time) |
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| | | |
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| | | result = {"y_data": ydata, "x_data": months} |
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| | | if model_name == base.not_allowed_model: |
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| | | dir = base.baseModel2 + "\\modflow.head" |
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| | | else: |
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| | | dir = base.model_dir + model_name + "\\modflow.head" |
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| | | cloned = is_cloned_model(model_name) |
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| | | if cloned ==True: |
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| | | return {"y_data": [],"y_data2":[],"x_data":xmonths } |
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| | | |
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| | | head = bf.HeadFile(dir) |
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| | | alldata = head.get_alldata() |
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| | | |
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| | | #周期数 |
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| | | months = int(len(alldata)/3) |
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| | | ydata= [] |
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| | | result = {} |
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| | | for month in range(months): |
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| | | z1= alldata[int(month+1)*3-1,0,:,:] |
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| | | cell_data = float(z1[row][column]) |
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| | | ydata.append(round(cell_data,2)) |
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| | | |
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| | | y_data2=[] |
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| | | if model_name == base.not_allowed_model: |
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| | | array_data = np.loadtxt(base.obswell_data_path, dtype=str,encoding='utf-8') |
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| | | y_data2= getObsData(wellId,array_data) |
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| | | |
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| | | result = {"y_data": ydata,"y_data2":y_data2,"x_data": xmonths} |
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| | | return result |
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| | | |
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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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| | | def getObsData(wellId,array_data): |
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| | | result =[] |
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| | | new_list =[] |
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| | | for item in array_data: |
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| | | if item[0]==wellId: |
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| | | result.append(item[3]) |
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| | | for i in range(0,len(result),3): |
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| | | data =( float(result[i]) +float(result[i+1])+float(result[i+2]))/3 |
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| | | data = round(data,2) |
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| | | new_list.append(data) |
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| | | |
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| | | return new_list; |
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| | | |
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| | | |
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| | | def getRowCloumnById(index_id): |
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| | | row,column,count = 104,114,0 |
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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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| | |
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| | | #地下水信息 |
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| | | def earthWaterChart(model_name, index_id): |
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| | | |
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| | | row_column = getRowCloumnById(index_id) |
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| | | |
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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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| | | |
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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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| | | |
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| | | layer = 3 |
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| | | |
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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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| | | |
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| | | per_array = alldata[per][lay] |
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| | | |
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| | | cell_data = (float)(per_array[row][column]) |
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| | | ydata.append(cell_data) |
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| | | |
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| | | period_json= get_model_json(model_name) |
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| | | |
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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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| | | xmonths = ModelPeriod.get_months_in_range_ym(start_time, end_time) |
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| | | dir = "" |
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| | | if model_name == base.not_allowed_model: |
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| | | dir = base.baseModel2 + "\\modflow.head" |
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| | | else: |
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| | | dir = base.model_dir + model_name + "\\modflow.head" |
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| | | cloned = is_cloned_model(model_name) |
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| | | if cloned ==True: |
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| | | return {"y_data": [],"x_data":xmonths } |
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| | | |
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| | | months = ModelPeriod.get_months_in_range_ym(start_time, end_time) |
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| | | head = bf.HeadFile(dir) |
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| | | alldata = head.get_alldata() |
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| | | |
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| | | #周期数 |
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| | | months = int(len(alldata)/3) |
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| | | ydata= [] |
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| | | result = {} |
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| | | for month in range(months): |
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| | | z1= alldata[int(month+1)*3-1,0,:,:] |
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| | | cell_data = float(z1[row][column]) |
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| | | ydata.append(round(cell_data,2)) |
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| | | |
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| | | result = {"y_data": ydata, "x_data": months} |
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| | | result = {"y_data": ydata, "x_data": xmonths} |
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| | | return result |
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| | | |
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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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| | | |
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| | | head = bf.HeadFile(dir) |
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| | | |
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| | | alldata = head.get_alldata() |
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| | | |
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| | | |
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| | | index = int(period)*3 |
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| | | return alldata[index][0] |
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| | | |
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| | | |
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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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| | | |
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| | | celldata = np.array(base.water_equ2022).tolist() |
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| | | |
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| | | predict_json= get_model_json(model_name) |
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| | | |
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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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| | | |
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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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| | | |
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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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| | | |
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| | | if predict_json["mine"]: |
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| | | b1= b1 |
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| | | |
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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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| | | |
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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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| | | |
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| | | dict["pie1"]=pie1 |
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| | | dict["pie2"]=pie2 |
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| | | |
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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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| | | |
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| | | |
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| | | #导出csv文件 |
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| | | def exportCsV(model_name): |
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| | | |
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| | |
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| | | if not os.path.exists(out_path): |
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| | | os.mkdir(out_path) |
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| | | |
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| | | head = bf.HeadFile(dir) |
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| | | |
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| | | # z1= alldata[int(per1)*3,0,:,:] |
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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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| | | |
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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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| | | months = int(len(alldata)/3) |
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| | | layers = 3 |
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| | | #例如 0-36月 |
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| | | for month in range(months): |
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| | | for layer in range (layers): |
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| | | z_last= alldata[(month+1)*3-1,layer,:,:] |
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| | | |
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| | | filename = out_path + str(month+1) + '-' + str(layer+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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| | | |
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| | | for p in z_last: |
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| | | writer.writerow(p) |
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| | | f.close() |
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| | | |
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| | | |
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| | | return out_path |
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| | | |
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| | | |
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| | | #水均衡计算 |
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| | | def waterEqu(model_name): |
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| | | if model_name == base.not_allowed_model: |
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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 |
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| | | title =[year] |
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| | | dict ={"title":title} |
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| | | |
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| | | jx = get_model_json(model_name) |
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| | | dict["start_time"]=jx["start_time"] |
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| | | dict["end_time"]=jx["end_time"] |
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| | | |
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| | | paths=base.model_dir + model_name +"\\water_bal.txt" |
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| | | wat = water_balance(model_name, paths) |
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| | | |
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| | | in_data= round(wat[0]+ wat[1]+ wat[2]+ wat[3] , 4) |
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| | | out_data= round(wat[4] + wat[5] + wat[6], 4) |
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| | | inout = round(in_data-out_data, 4) |
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| | | float_data=[wat[0],wat[1],wat[2],wat[3],in_data, |
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| | | wat[4],wat[5], wat[6],out_data,inout] |
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| | | |
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| | | inarray=[] |
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| | | inarray.append({"name":"降水入渗量","value":wat[0]}) |
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| | | inarray.append({"name":"河流入渗量","value":wat[1]}) |
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| | | inarray.append({"name":"一层侧向补给量","value":wat[2]}) |
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| | | inarray.append({"name":"三层侧向补给量","value":wat[3]}) |
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| | | outarray=[] |
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| | | outarray.append({"name":"人工开采量","value":wat[4]}) |
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| | | outarray.append({"name":"一层侧向流出量","value":wat[5]}) |
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| | | outarray.append({"name":"三层侧向流出量","value":wat[6]}) |
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| | | pie1={str(year):inarray} |
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| | | pie2={str(year):outarray} |
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| | | |
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| | | dict["pie1"]=pie1 |
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| | | dict["pie2"]=pie2 |
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| | | |
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| | | array2d=[] |
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| | | array2d.append(["数据（亿立方米）"]) |
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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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| | | |
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| | | |
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| | | |
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| | | def run_zonebudget_bal(model_name): |
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| | | # 定义exe文件的路径和参数 |
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| | | exe_path = base.ZoneBudget64Exe |
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| | | txt_path = base.model_dir + model_name + "\\water_bal.txt\n" |
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| | | cell_path = base.model_dir + model_name + "\\modflow.flow\n" |
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| | | process = subprocess.Popen([exe_path], stdin=subprocess.PIPE,shell = True) |
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| | | process.stdin.write(txt_path.encode()) # 输入参数1 |
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| | | process.stdin.write(cell_path.encode()) |
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| | | process.stdin.write(b"title\n") |
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| | | process.stdin.write(base.water_bal_zones.encode()) |
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| | | process.stdin.write(b"A\n") |
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| | | output, _ = process.communicate() |
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| | | print(output) |
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| | | |
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| | | |
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| | | def run_zonebudget_res(model_name): |
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| | | # 定义exe文件的路径和参数 |
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| | | exe_path = base.ZoneBudget64Exe |
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| | | txt_path = base.model_dir + model_name + "\\water_res.txt\n" |
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| | | cell_path = base.model_dir + model_name + "\\modflow.flow\n" |
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| | | process = subprocess.Popen([exe_path], stdin=subprocess.PIPE,shell = True) |
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| | | process.stdin.write(txt_path.encode()) # 输入参数1 |
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| | | process.stdin.write(cell_path.encode()) |
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| | | process.stdin.write(b"title\n") |
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| | | process.stdin.write(base.water_res_zones.encode()) |
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| | | process.stdin.write(b"A\n") |
|---|
| | | output, _ = process.communicate() |
|---|
| | | print(output) |
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| | | |
|---|
| | | 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] |
|---|
