#!/usr/bin/env python # -*- coding: UTF-8 no BOM -*- import os,sys,string,math import numpy as np from optparse import OptionParser import damask scriptName = os.path.splitext(os.path.basename(__file__))[0] scriptID = ' '.join([scriptName,damask.version]) #-------------------------------------------------------------------------------------------------- def deformedCoordsFFT(F,undeformed=False): #-------------------------------------------------------------------------------------------------- wgt = 1.0/grid.prod() integrator = np.array([0.+1.j,0.+1.j,0.+1.j],'c16') * size/ 2.0 / math.pi step = size/grid F_fourier = np.fft.rfftn(F,axes=(0,1,2)) coords_fourier = np.zeros(F_fourier.shape[0:4],'c16') if undeformed: Favg=np.eye(3) else: Favg=np.real(F_fourier[0,0,0,:,:])*wgt #-------------------------------------------------------------------------------------------------- # integration in Fourier space k_s = np.zeros([3],'i') for i in xrange(grid[2]): k_s[2] = i if(i > grid[2]//2 ): k_s[2] = k_s[2] - grid[2] for j in xrange(grid[1]): k_s[1] = j if(j > grid[1]//2 ): k_s[1] = k_s[1] - grid[1] for k in xrange(grid[0]//2+1): k_s[0] = k for m in xrange(3): coords_fourier[i,j,k,m] = sum(F_fourier[i,j,k,m,0:3]*k_s*integrator) if (any(k_s != 0)): coords_fourier[i,j,k,0:3] /= -sum(k_s*k_s) #-------------------------------------------------------------------------------------------------- # add average to scaled fluctuation and put (0,0,0) on (0,0,0) coords = np.fft.irfftn(coords_fourier,F.shape[0:3],axes=(0,1,2)) offset_coords = np.dot(F[0,0,0,:,:],step/2.0) - scaling*coords[0,0,0,0:3] for z in xrange(grid[2]): for y in xrange(grid[1]): for x in xrange(grid[0]): coords[z,y,x,0:3] = scaling*coords[z,y,x,0:3] \ + offset_coords \ + np.dot(Favg,step*np.array([x,y,z])) return coords # -------------------------------------------------------------------- # MAIN # -------------------------------------------------------------------- parser = OptionParser(option_class=damask.extendableOption, usage='%prog options file[s]', description = """ Add deformed configuration of given initial coordinates. Operates on periodic three-dimensional x,y,z-ordered data sets. """, version = scriptID) parser.add_option('-f', '--defgrad',dest='defgrad', metavar = 'string', help='heading of deformation gradient columns [%default]') parser.add_option('--reference', dest='undeformed', action='store_true', help='map results to reference (undeformed) average configuration [%default]') parser.add_option('--scaling', dest='scaling', action='extend', metavar = '', help='scaling of fluctuation') parser.add_option('-u', '--unitlength', dest='unitlength', type='float', metavar = 'float', help='set unit length for 2D model [%default]') parser.add_option('--coordinates', dest='coords', metavar='string', help='column heading for coordinates [%default]') parser.set_defaults(defgrad = 'f') parser.set_defaults(coords = 'ipinitialcoord') parser.set_defaults(scaling = []) parser.set_defaults(undeformed = False) parser.set_defaults(unitlength = 0.0) (options,filenames) = parser.parse_args() options.scaling += [1.0 for i in xrange(max(0,3-len(options.scaling)))] scaling = map(float, options.scaling) # --- loop over input files ------------------------------------------------------------------------- if filenames == []: filenames = [None] for name in filenames: try: table = damask.ASCIItable(name = name, buffered = False) except: continue damask.util.report(scriptName,name) # ------------------------------------------ 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 != []: damask.util.croak(remarks) if errors != []: damask.util.croak(errors) table.close(dismiss = True) continue # --------------- figure out size and grid --------------------------------------------------------- table.data_readArray() coords = [np.unique(table.data[:,colCoord+i]) for i in xrange(3)] mincorner = np.array(map(min,coords)) maxcorner = np.array(map(max,coords)) grid = np.array(map(len,coords),'i') size = grid/np.maximum(np.ones(3,'d'), grid-1.0) * (maxcorner-mincorner) # size from edge to edge = dim * n/(n-1) 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() if N != len(table.data): errors.append('data count {} does not match grid {}x{}x{}.'.format(N,*grid)) if errors != []: damask.util.croak(errors) table.close(dismiss = True) continue # ------------------------------------------ assemble header --------------------------------------- table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:])) for coord in xrange(3): label = '{}_{}_{}'.format(coord+1,options.defgrad,options.coords) if np.any(scaling) != 1.0: label+='_{}_{}_{}'.format(scaling) if options.undeformed: label+='_undeformed' table.labels_append([label]) # extend ASCII header with new labels table.head_write() # ------------------------------------------ read deformation gradient field ----------------------- centroids = deformedCoordsFFT(table.data[:,colF:colF+9].reshape(grid[2],grid[1],grid[0],3,3), options.undeformed) # ------------------------------------------ process data ------------------------------------------ table.data_rewind() for z in xrange(grid[2]): for y in xrange(grid[1]): for x in xrange(grid[0]): table.data_read() table.data_append(list(centroids[z,y,x,:])) table.data_write() # ------------------------------------------ output finalization ----------------------------------- table.close() # close ASCII tables