#!/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(s) containing the shape and volume mismatch resulting from given deformation gradient. Operates on periodic three-dimensional x,y,z-ordered data sets. """, version = scriptID) parser.add_option('-c','--coordinates', dest = 'coords', type = 'string', metavar = 'string', help = 'column heading of coordinates [%default]') parser.add_option('-f','--defgrad', dest = 'defgrad', type = 'string', metavar = 'string ', help = 'column heading of deformation gradient [%default]') parser.add_option('--no-shape','-s', dest = 'shape', action = 'store_false', help = 'omit shape mismatch') parser.add_option('--no-volume','-v', dest = 'volume', action = 'store_false', help = 'omit volume mismatch') parser.set_defaults(coords = 'ipinitialcoord', defgrad = 'f', shape = True, volume = True, ) (options,filenames) = parser.parse_args() # --- loop over input files ------------------------------------------------------------------------- if filenames == []: filenames = ['STDIN'] for name in filenames: if not (name == 'STDIN' or os.path.exists(name)): continue table = damask.ASCIItable(name = name, outname = name+'_tmp', buffered = False) table.croak('\033[1m'+scriptName+'\033[0m'+(': '+name if name != 'STDIN' else '')) # ------------------------------------------ read header ------------------------------------------ table.head_read() # ------------------------------------------ sanity checks ---------------------------------------- errors = [] remarks = [] if table.label_dimension(options.coords) != 3: errors.append('coordinates {} are not a vector.'.format(options.coords)) else: colCoord = table.label_index(options.coords) if table.label_dimension(options.defgrad) != 9: errors.append('deformation gradient {} is not a tensor.'.format(options.defgrad)) else: colF = table.label_index(options.defgrad) if remarks != []: table.croak(remarks) if errors != []: table.croak(errors) table.close(dismiss = True) continue # ------------------------------------------ assemble header -------------------------------------- table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:])) if options.shape: table.labels_append('shapeMismatch({})'.format(options.defgrad)) if options.volume: table.labels_append('volMismatch({})'.format(options.defgrad)) table.head_write() # --------------- figure out size and grid --------------------------------------------------------- table.data_readArray() coords = [{},{},{}] for i in xrange(len(table.data)): for j in xrange(3): coords[j][str(table.data[i,colCoord+j])] = True grid = np.array(map(len,coords),'i') 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 size = np.where(grid > 1, size, min(size[grid > 1]/grid[grid > 1])) # spacing for grid==1 equal to smallest among other spacings N = grid.prod() # ------------------------------------------ process deformation gradient -------------------------- F = table.data[:,colF:colF+9].transpose().reshape([3,3]+list(options.dimension),order='F') 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) stack = [table.data] if options.shape: stack.append(damask.core.mesh.shapeMismatch( size,F,nodes,centres)) if options.volume: stack.append(damask.core.mesh.volumeMismatch(size,F,nodes)) # ------------------------------------------ output result ----------------------------------------- if len(stack) > 1: table.data = np.hstack(tuple(stack)) table.data_writeArray('%.12g') # ------------------------------------------ output finalization ----------------------------------- table.close() # close ASCII tables if name != 'STDIN': os.rename(name+'_tmp',name) # overwrite old one with tmp new