# HG changeset patch # User mb2013 # Date 1384949738 18000 # Node ID 7c2cca12ab39ba9b9a0e196c6e1da23a5e26e3e8 # Parent 8cd5f40c928e2fb473eb4c2ec771fe96dde9385d Uploaded diff -r 8cd5f40c928e -r 7c2cca12ab39 converter_dta_to_csv.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/converter_dta_to_csv.py Wed Nov 20 07:15:38 2013 -0500 @@ -0,0 +1,44 @@ +#Converter of dta to csv +#M.Baak +#9-10-2013 +#last update: 13-11-2013 + + +import sys +import os + +file_name = sys.argv[1] +file_outputname = sys.argv[2] +file_outputname2 = sys.argv[3] + +def convert_dta(file_name,file_outputname): + + read_file = open(file_name, 'r') #open file + a = len(read_file.readlines()) + read_file2 = open(file_name, 'r') # open file second time + output = open(file_outputname,'w') #output file + output2 = open(file_outputname2, 'w') + + numberlandmarks = 0 + header = "" + + #for loop, coordinates, number of landmarks and name of sample will be stored in csv format + for x in range(0,a): + b = read_file2.readline().strip() + split_tabs = b.split(' ') + number_columns = len(split_tabs) + if x == 0: + header += b.replace(' ', '_') #name of sample + if number_columns == 3: #coordinates + output.write("%f,%f,%f\n"%(float(split_tabs[0]),float(split_tabs[1]),float(split_tabs[2]))) + numberlandmarks += 1 # number of landmarks + + output2.write("%s\n"%(header[1:-4])) # writing header to output file + + output.close() + +convert_dta(file_name,file_outputname) + + + +