#!/usr/bin/env python # -*- coding: UTF-8 no BOM -*- import os,sys,string import numpy as np from optparse import OptionParser import damask scriptID = string.replace('$Id$','\n','\\n') scriptName = os.path.splitext(scriptID.split()[1])[0] # -------------------------------------------------------------------- # MAIN # -------------------------------------------------------------------- parser = OptionParser(option_class=damask.extendableOption, usage='%prog options file[s]', description = """ Add column containing debug information. Operates on periodic ordered three-dimensional data sets. """, version = scriptID) parser.add_option('--no-shape','-s', dest='noShape', action='store_false', help='do not calcuate shape mismatch [%default]') parser.add_option('--no-volume','-v', dest='noVolume', action='store_false', help='do not calculate volume mismatch [%default]') parser.add_option('-c','--coordinates', dest='coords', metavar='string', help='column heading for coordinates [%default]') parser.add_option('-f','--defgrad', dest='defgrad', metavar='string ', help='column heading for coordinates [%defgrad]') parser.set_defaults(noVolume = False) parser.set_defaults(noShape = False) parser.set_defaults(coords = 'ip') parser.set_defaults(defgrad = 'f') (options,filenames) = parser.parse_args() datainfo = { # list of requested labels per datatype 'defgrad': {'len':9, 'label':[]}, } datainfo['defgrad']['label'].append(options.defgrad) # ------------------------------------------ setup file handles ------------------------------------ files = [] for name in filenames: if os.path.exists(name): files.append({'name':name, 'input':open(name), 'output':open(name+'_tmp','w'), 'croak':sys.stderr}) #--- loop over input files ------------------------------------------------------------------------- for file in files: file['croak'].write('\033[1m'+scriptName+'\033[0m: '+file['name']+'\n') table = damask.ASCIItable(file['input'],file['output'],False) # make unbuffered ASCII_table table.head_read() # read ASCII header info table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:])) # --------------- figure out size and grid --------------------------------------------------------- try: locationCol = table.labels.index('1_%s'%options.coords) # columns containing location data except ValueError: try: locationCol = table.labels.index('%s.x'%options.coords) # columns containing location data (legacy naming scheme) except ValueError: file['croak'].write('no coordinate data (1_%s/%s.x) found...\n'%(options.coords,options.coords)) continue coords = [{},{},{}] while table.data_read(): # read next data line of ASCII table for j in xrange(3): coords[j][str(table.data[locationCol+j])] = True # remember coordinate along x,y,z grid = np.array([len(coords[0]),\ len(coords[1]),\ len(coords[2]),],'i') # grid is number of distinct coordinates found size = grid/np.maximum(np.ones(3,'d'),grid-1.0)* \ np.array([max(map(float,coords[0].keys()))-min(map(float,coords[0].keys())),\ max(map(float,coords[1].keys()))-min(map(float,coords[1].keys())),\ max(map(float,coords[2].keys()))-min(map(float,coords[2].keys())),\ ],'d') # size from bounding box, corrected for cell-centeredness for i, points in enumerate(grid): if points == 1: options.packing[i] = 1 options.shift[i] = 0 mask = np.ones(3,dtype=bool) mask[i]=0 size[i] = min(size[mask]/grid[mask]) # third spacing equal to smaller of other spacing N = grid.prod() # --------------- figure out columns to process --------------------------------------------------- key = '1_%s'%datainfo['defgrad']['label'][0] if key not in table.labels: file['croak'].write('column %s not found...\n'%key) continue else: column = table.labels.index(key) # remember columns of requested data # ------------------------------------------ assemble header --------------------------------------- if not options.noShape: table.labels_append(['shapeMismatch(%s)' %options.defgrad]) if not options.noVolume: table.labels_append(['volMismatch(%s)'%options.defgrad]) table.head_write() # ------------------------------------------ read deformation gradient field ----------------------- table.data_rewind() F = np.zeros(N*9,'d').reshape([3,3]+list(grid)) idx = 0 while table.data_read(): (x,y,z) = damask.util.gridLocation(idx,grid) # figure out (x,y,z) position from line count idx += 1 F[0:3,0:3,x,y,z] = np.array(map(float,table.data[column:column+9]),'d').reshape(3,3) Favg = damask.core.math.tensorAvg(F) centres = damask.core.mesh.deformedCoordsFFT(size,F,Favg,[1.0,1.0,1.0]) nodes = damask.core.mesh.nodesAroundCentres(size,Favg,centres) if not options.noShape: shapeMismatch = damask.core.mesh.shapeMismatch( size,F,nodes,centres) if not options.noVolume: volumeMismatch = damask.core.mesh.volumeMismatch(size,F,nodes) # ------------------------------------------ process data ------------------------------------------ table.data_rewind() idx = 0 outputAlive = True while outputAlive and table.data_read(): # read next data line of ASCII table (x,y,z) = damask.util.gridLocation(idx,grid) # figure out (x,y,z) position from line count idx += 1 if not options.noShape: table.data_append( shapeMismatch[x,y,z]) if not options.noVolume: table.data_append(volumeMismatch[x,y,z]) outputAlive = table.data_write() # output processed line # ------------------------------------------ output result --------------------------------------- outputAlive and table.output_flush() # just in case of buffered ASCII table table.input_close() # close input ASCII table table.output_close() # close output ASCII table os.rename(file['name']+'_tmp',file['name']) # overwrite old one with tmp new