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pkpm_postprocessing_open.py
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181 lines (153 loc) · 6.73 KB
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#-*- coding: utf-8 -*-
import numpy as np
import re
import linecache
import pandas as pd
#---------------------------------------------------------------------------
#分割文本
def fileParse(inputfile):
fp = open(inputfile, 'r',encoding='utf-8')
number =[]
lineNumber = 1
keyword = '地震波各时刻' ##输入你要切分的关键字
outfilename = 'user_out' ##输出文件名,如out.txt则写out即可,后续输出的文件是out0.txt,out1.txt...
outfilepath_list=[]
for eachLine in fp:
m = re.search(keyword, eachLine) ##查询关键字
# print (eachLine)
if m is not None:
number.append(lineNumber) #将关键字的行号记录在number中
print (number)
lineNumber = lineNumber + 1
number.append(2*number[-1]-number[-2])
size = int(len(number))
for i in range(0,size-1):
start = number[i]
end = number[i+1]
destLines = linecache.getlines(inputfile)[start-1:end-2] #将行号为start-2到end-1的文件内容截取出来
outpath=outfilename + str(i)+'.txt'
fp_w = open(outpath,'w') #将截取出的内容保存在输出文件中
outfilepath_list.append(outpath)
for key in destLines:
fp_w.write(key)
fp_w.close()
return outfilepath_list
#---------------------------------------------------------------------------
#从文本中获取数据并分别输出到文件
def Getdata(path):
# data_list=[]
# i=0
# for file_url in file_list:
# data = np.loadtxt(path,skiprows=10,encoding='gb2312')
file_input=open(path,'r')
file_test=open('test.out','w')
datalist_disp=[]
datalist_force=[]
for eachline in file_input:
linelist=eachline.split()
# file_test.write(str(linelist))
if len(linelist)!=0 and len(linelist)!=4:
if linelist[0].isdigit():
if '/' in linelist[5]:
datalist_disp.append(linelist)
else:
datalist_force.append(linelist)
floor_number=int(len(datalist_disp)/4)
# print(len(datalist_force))
# for i in datalist_force:
# file_test.write(str(datalist_force))
#位移和内力数据分别分方向存储为列表
displist_x1,displist_x2,displist_y1,displist_y2=datalist_disp[0:floor_number],datalist_disp[floor_number:2*floor_number],datalist_disp[2*floor_number:3*floor_number],datalist_disp[3*floor_number:4*floor_number+1]
forlist_x1,forlist_x2,forlist_y1,forlist_y2=datalist_force[0:floor_number],datalist_force[floor_number:2*floor_number],datalist_force[2*floor_number:3*floor_number],datalist_force[3*floor_number:4*floor_number+1]
#结果文件数组初始化
array_x1_dis1=np.zeros(floor_number)
array_x1_dis2=np.zeros(floor_number)
array_y1_dis1=np.zeros(floor_number)
array_y1_dis2=np.zeros(floor_number)
array_x1_for1=np.zeros(floor_number)
array_x1_for2=np.zeros(floor_number)
array_y1_for1=np.zeros(floor_number)
array_y1_for2=np.zeros(floor_number)
output_list=[array_x1_dis1,array_y1_dis1,array_x1_dis2,array_y1_dis2,array_x1_for1,array_y1_for1,array_x1_for2,array_y1_for2]
for i,val in enumerate(displist_x1):
array_x1_dis1[i]=(val[3])
array_x1_dis2[i]=(eval(val[5]))
for i,val in enumerate(displist_y1):
array_y1_dis1[i]=(val[3])
array_y1_dis2[i]=(eval(val[5]))
for i,val in enumerate(forlist_x1):
# print(val)
array_x1_for1[i]=(val[2])
array_x1_for2[i]=(eval(val[4]))
for i,val in enumerate(forlist_y1):
array_y1_for1[i]=(val[2])
array_y1_for2[i]=(eval(val[4]))
#创建或打开文本文件
# file_x1_dis1=open(path[0:-4]+'.x1dis1','w')
# file_x1_dis2=open(path[0:-4]+'.x1dis2','w')
# file_y1_dis1=open(path[0:-4]+'.y1dis1','w')
# file_y1_dis2=open(path[0:-4]+'.y1dis2','w')
# file_x1_for1=open(path[0:-4]+'.x1for1','w')
# file_x1_for2=open(path[0:-4]+'.x1for2','w')
# file_y1_for1=open(path[0:-4]+'.y1for1','w')
# file_y1_for2=open(path[0:-4]+'.y1for2','w')
#输出到文本文件
# for i in displist_x1:
# file_x1_dis1.write(i[3]+'\n')
# file_x1_dis2.write(str(eval(i[5]))+'\n')
# for i in displist_y1:
# file_y1_dis1.write(i[3]+'\n')
# file_y1_dis2.write(str(eval(i[5]))+'\n')
# for i in forlist_x1:
# file_x1_for1.write(i[2]+'\n')
# file_x1_for2.write(str(eval(i[4]))+'\n')
# for i in forlist_y1:
# file_y1_for1.write(i[2]+'\n')
# file_y1_for2.write(str(eval(i[4]))+'\n')
#仅供测试
# file_x2_dis1=open(path[0:-4]+'.x2dis1','w')
# for i in displist_x2:
# file_x2_dis1.write(i[3]+'\n')
# file_y2_dis1=open(path[0:-4]+'.y2dis1','w')
# for i in displist_y2:
# file_y2_dis1.write(i[3]+'\n')
return output_list
def ToExcel(datalist,ExcelName='pkpm_output.xlsx',SheetName='计算结果'):
writer = pd.ExcelWriter(ExcelName)
# x = np.array([x]).T
# y = np.array([y]).T
for i ,j in enumerate(datalist):
data_col = pd.DataFrame(j)
# # change the index and column name
# data_df.columns = ['A','B','C','D','E','F','G','H','I','J']
# data_df.index = ['a','b','c','d','e','f','g','h','i','j']
# ExcelName='Save_Excel.xlsx'
data_col.to_excel(writer,SheetName,float_format='%.8f', columns=None, header=False, index=False, startrow=0, startcol=i, engine='xlsxwriter', merge_cells=True, encoding=None, inf_rep='inf', verbose=True) # float_format 控制精度
# ###########################################################################
if __name__ == "__main__":
result=[]
x_dis1=[]
y_dis1=[]
x_dis2=[]
y_dis2=[]
x_for1=[]
y_for1=[]
x_for2=[]
y_for2=[]
excel_data=[x_dis1,y_dis1,x_dis2,y_dis2,x_for1,y_for1,x_for2,y_for2]
originfile='WDYNA.OUT'
inputfile_list=fileParse(originfile)
for i,j in enumerate(inputfile_list):
result.append(Getdata(j))
x_dis1.append(Getdata(j)[0])
y_dis1.append(Getdata(j)[1])
x_dis2.append(Getdata(j)[2])
y_dis2.append(Getdata(j)[3])
x_for1.append(Getdata(j)[4])
y_for1.append(Getdata(j)[5])
x_for2.append(Getdata(j)[6])
y_for2.append(Getdata(j)[7])
for i,j in enumerate(excel_data):
ToExcel(j,'pkpm_output%s.xlsx'%i)
for i,j in enumerate(result):
print("地震波%s基底剪力:x方向%s y方向%s"%(i,j[4].max(),j[5].max()))