#!/usr/bin/env python3 # -*- coding: UTF-8 no BOM -*- import os import numpy as np import argparse import damask scriptName = os.path.splitext(os.path.basename(__file__))[0] scriptID = ' '.join([scriptName,damask.version]) # -------------------------------------------------------------------- # MAIN # -------------------------------------------------------------------- parser = argparse.ArgumentParser() #ToDo: We need to decide on a way of handling arguments of variable lentght #https://stackoverflow.com/questions/15459997/passing-integer-lists-to-python #parser.add_argument('--version', action='version', version='%(prog)s {}'.format(scriptID)) parser.add_argument('filenames', nargs='+', help='DADF5 files') parser.add_argument('-d','--dir', dest='dir',default='postProc',metavar='string', help='name of subdirectory to hold output') options = parser.parse_args() options.labels = ['Fe','Fp','xi_sl'] # --- loop over input files ------------------------------------------------------------------------ for filename in options.filenames: results = damask.DADF5(filename) if not results.structured: continue delta = results.size/results.grid*0.5 x, y, z = np.meshgrid(np.linspace(delta[2],results.size[2]-delta[2],results.grid[2]), np.linspace(delta[1],results.size[1]-delta[1],results.grid[1]), np.linspace(delta[0],results.size[0]-delta[0],results.grid[0]), indexing = 'ij') coords = np.concatenate((z[:,:,:,None],y[:,:,:,None],x[:,:,:,None]),axis = 3) for i,inc in enumerate(results.increments): print('Output step {}/{}'.format(i+1,len(results.increments))) header = '1 header\n' data = np.array([inc['inc'] for j in range(np.product(results.grid))]).reshape([np.product(results.grid),1]) header+= 'inc' data = np.concatenate((data,np.array([j+1 for j in range(np.product(results.grid))]).reshape([np.product(results.grid),1])),1) header+=' node' coords = coords.reshape([np.product(results.grid),3]) data = np.concatenate((data,coords),1) header+=' 1_pos 2_pos 3_pos' results.active['increments'] = [inc] for label in options.labels: for o in results.c_output_types: results.active['c_output_types'] = [o] for c in results.constituents: results.active['constituents'] = [c] x = results.get_dataset_location(label) if len(x) == 0: continue label = x[0].split('/')[-1] array = results.read_dataset(x,0) d = np.product(np.shape(array)[1:]) array = np.reshape(array,[np.product(results.grid),d]) data = np.concatenate((data,array),1) header+= ''.join([' {}_{}'.format(j+1,label) for j in range(d)]) dirname = os.path.abspath(os.path.join(os.path.dirname(filename),options.dir)) try: os.mkdir(dirname) except FileExistsError: pass file_out = '{}_inc{:04d}.txt'.format(filename.split('.')[0],i) np.savetxt(os.path.join(dirname,file_out),data,header=header,comments='')