#!/usr/bin/env python # -*- coding: UTF-8 no BOM -*- import os,sys,string,re,math,itertools import numpy as np from optparse import OptionParser from scipy import ndimage from multiprocessing import Pool import damask scriptID = string.replace('$Id$','\n','\\n') scriptName = scriptID.split()[1][:-3] #-------------------------------------------------------------------------------------------------- # MAIN #-------------------------------------------------------------------------------------------------- synonyms = { 'grid': ['resolution'], 'size': ['dimension'], } identifiers = { 'grid': ['a','b','c'], 'size': ['x','y','z'], 'origin': ['x','y','z'], } mappings = { 'grid': lambda x: int(x), 'size': lambda x: float(x), 'origin': lambda x: float(x), 'homogenization': lambda x: int(x), 'microstructures': lambda x: int(x), } parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """ Smoothens out interface roughness by simulated curvature flow. This is achieved by the diffusion of each initially sharply bounded grain volume within the periodic domain up to a given distance 'd' voxels. The final geometry is assembled by selecting at each voxel that grain index for which the concentration remains largest. """ + string.replace(scriptID,'\n','\\n') ) parser.add_option('-d', '--distance', dest='d', type='int', metavar='int', help='diffusion distance in voxels [%default]') parser.add_option('-N', '--smooth', dest='N', type='int', metavar='int', help='N for curvature flow [%default]') parser.add_option('-r', '--renumber', dest='renumber', action='store_true', help='renumber microstructure indices from 1...N [%default]') parser.add_option('-i', '--immutable', action='extend', dest='immutable', metavar = '', help='list of immutable microstructures') parser.set_defaults(d = 1) parser.set_defaults(N = 1) parser.set_defaults(renumber = False) parser.set_defaults(immutable = []) (options, filenames) = parser.parse_args() options.immutable = map(int,options.immutable) #--- setup file handles -------------------------------------------------------------------------- files = [] if filenames == []: files.append({'name':'STDIN', 'input':sys.stdin, 'output':sys.stdout, 'croak':sys.stderr, }) else: for name in filenames: if os.path.exists(name): files.append({'name':name, 'input':open(name), 'output':open(name+'_tmp','w'), 'croak':sys.stdout, }) #--- loop over input files ------------------------------------------------------------------------ for file in files: if file['name'] != 'STDIN': file['croak'].write('\033[1m'+scriptName+'\033[0m: '+file['name']+'\n') else: file['croak'].write('\033[1m'+scriptName+'\033[0m\n') theTable = damask.ASCIItable(file['input'],file['output'],labels = False,buffered = False) theTable.head_read() #--- interpret header ---------------------------------------------------------------------------- info = { 'grid': np.zeros(3,'i'), 'size': np.zeros(3,'d'), 'origin': np.zeros(3,'d'), 'homogenization': 0, 'microstructures': 0, } newInfo = { 'microstructures': 0, } extra_header = [] for header in theTable.info: headitems = map(str.lower,header.split()) if len(headitems) == 0: continue for synonym,alternatives in synonyms.iteritems(): if headitems[0] in alternatives: headitems[0] = synonym if headitems[0] in mappings.keys(): if headitems[0] in identifiers.keys(): for i in xrange(len(identifiers[headitems[0]])): info[headitems[0]][i] = \ mappings[headitems[0]](headitems[headitems.index(identifiers[headitems[0]][i])+1]) else: info[headitems[0]] = mappings[headitems[0]](headitems[1]) else: extra_header.append(header) file['croak'].write('grid a b c: %s\n'%(' x '.join(map(str,info['grid']))) + \ 'size x y z: %s\n'%(' x '.join(map(str,info['size']))) + \ 'origin x y z: %s\n'%(' : '.join(map(str,info['origin']))) + \ 'homogenization: %i\n'%info['homogenization'] + \ 'microstructures: %i\n'%info['microstructures']) if np.any(info['grid'] < 1): file['croak'].write('invalid grid a b c.\n') continue if np.any(info['size'] <= 0.0): file['croak'].write('invalid size x y z.\n') continue #--- read data ------------------------------------------------------------------------------------ microstructure = np.zeros(np.prod(info['grid']),'i') # 2D structures do not work i = 0 while theTable.data_read(): # read next data line of ASCII table items = theTable.data if len(items) > 2: if items[1].lower() == 'of': items = [int(items[2])]*int(items[0]) elif items[1].lower() == 'to': items = xrange(int(items[0]),1+int(items[2])) else: items = map(int,items) else: items = map(int,items) s = len(items) microstructure[i:i+s] = items i += s #--- reshape, if 2D make copy --------------------------------------------------------------------- microstructure = np.tile(microstructure.reshape(info['grid'],order='F'), np.where(info['grid'] == 1, 2,1)) # make one copy along dimensions with grid == 1 grid = np.array(microstructure.shape) #--- initialize support data ----------------------------------------------------------------------- periodic_microstructure = np.tile(microstructure,(3,3,3))[grid[0]/2:-grid[0]/2, grid[1]/2:-grid[1]/2, grid[2]/2:-grid[2]/2] # periodically extend the microstructure microstructure_original = np.copy(microstructure) # store a copy the initial microstructure to find locations of immutable indices X,Y,Z = np.mgrid[0:grid[0],0:grid[1],0:grid[2]] gauss = np.exp(-(X*X + Y*Y + Z*Z)/(2.0*options.d*options.d))/math.pow(2.0*np.pi*options.d*options.d,1.5) gauss[:,:,grid[2]/2::] = gauss[:,:,round(grid[2]/2.)-1::-1] # trying to cope with uneven (odd) grid size gauss[:,grid[1]/2::,:] = gauss[:,round(grid[1]/2.)-1::-1,:] gauss[grid[0]/2::,:,:] = gauss[round(grid[0]/2.)-1::-1,:,:] gauss = np.fft.rfftn(gauss) interfacialEnergy = lambda A,B: (A*B != 0)*(A != B)*1.0 struc = ndimage.generate_binary_structure(3,1) # 3D von Neumann neighborhood for smoothIter in xrange(options.N): boundary = np.zeros(microstructure.shape) for i in (-1,0,1): for j in (-1,0,1): for k in (-1,0,1): interfaceEnergy = np.maximum(boundary, interfacialEnergy(microstructure,np.roll(np.roll(np.roll( microstructure,i,axis=0), j,axis=1), k,axis=2))) # assign interfacial energy to all voxels that have a differing neighbor (in Moore neighborhood) periodic_interfaceEnergy = np.tile(interfaceEnergy,(3,3,3))[grid[0]/2:-grid[0]/2, grid[1]/2:-grid[1]/2, grid[2]/2:-grid[2]/2] # periodically extend interfacial energy array by half a grid size in positive and negative directions index = ndimage.morphology.distance_transform_edt(periodic_interfaceEnergy == 0., # transform bulk volume (i.e. where interfacial energy is zero) return_distances = False, return_indices = True) # want array index of nearest voxel on periodically extended boundary # boundaryExt = boundaryExt[index[0].flatten(),index[1].flatten(),index[2].flatten()].reshape(boundaryExt.shape) # fill bulk with energy of nearest interface | question PE: what "flatten" for? periodic_bulkEnergy = periodic_interfaceEnergy[index[0], index[1], index[2]].reshape(2*grid) # fill bulk with energy of nearest interface diffusedEnergy = np.fft.irfftn(np.fft.rfftn(np.where(ndimage.morphology.binary_dilation(interfaceEnergy > 0., structure = struc, iterations = options.d/2 + 1), # fat boundary | question PE: why 2d - 1? I would argue for d/2 + 1 !! periodic_bulkEnergy[grid[0]/2:-grid[0]/2, # retain filled energy on fat boundary... grid[1]/2:-grid[1]/2, grid[2]/2:-grid[2]/2], # ...and zero everywhere else 0.)\ )*gauss) periodic_diffusedEnergy = np.tile(diffusedEnergy,(3,3,3))[grid[0]/2:-grid[0]/2, grid[1]/2:-grid[1]/2, grid[2]/2:-grid[2]/2] # periodically extend the smoothed bulk energy index = ndimage.morphology.distance_transform_edt(periodic_diffusedEnergy >= 0.5, # transform voxels close to interface region | question PE: what motivates 1/2 (could be any small number, or)? return_distances = False, return_indices = True) # want index of closest bulk grain microstructure = periodic_microstructure[index[0], index[1], index[2]].reshape(2*grid)[grid[0]/2:-grid[0]/2, grid[1]/2:-grid[1]/2, grid[2]/2:-grid[2]/2] # extent grains into interface region immutable = np.zeros(microstructure.shape, dtype=bool) for micro in options.immutable: immutable += np.logical_or(microstructure == micro, microstructure_original == micro) # find locations where immutable microstructures have been or are now microstructure = np.where(immutable, microstructure_original,microstructure) # undo any changes involving immutable microstructures # --- renumber to sequence 1...Ngrains if requested ------------------------------------------------ # http://stackoverflow.com/questions/10741346/np-frequency-counts-for-unique-values-in-an-array if options.renumber: newID = 0 for microstructureID,count in enumerate(np.bincount(microstructure.flatten())): if count != 0: newID += 1 microstructure = np.where(microstructure == microstructureID, newID, microstructure) # --- assemble header ----------------------------------------------------------------------------- newInfo['microstructures'] = microstructure[0:info['grid'][0],0:info['grid'][1],0:info['grid'][2]].max() #--- report --------------------------------------------------------------------------------------- if (newInfo['microstructures'] != info['microstructures']): file['croak'].write('--> microstructures: %i\n'%newInfo['microstructures']) #--- write header --------------------------------------------------------------------------------- theTable.labels_clear() theTable.info_clear() theTable.info_append(extra_header+[ scriptID+ ' ' + ' '.join(sys.argv[1:]), "grid\ta %i\tb %i\tc %i"%(info['grid'][0],info['grid'][1],info['grid'][2],), "size\tx %f\ty %f\tz %f"%(info['size'][0],info['size'][1],info['size'][2],), "origin\tx %f\ty %f\tz %f"%(info['origin'][0],info['origin'][1],info['origin'][2],), "homogenization\t%i"%info['homogenization'], "microstructures\t%i"%(newInfo['microstructures']), ]) theTable.head_write() # --- write microstructure information ------------------------------------------------------------ formatwidth = int(math.floor(math.log10(microstructure.max())+1)) theTable.data = microstructure[0:info['grid'][0],0:info['grid'][1],0:info['grid'][2]].reshape(np.prod(info['grid']),order='F').transpose() # question PE: this assumes that only the Z dimension can be 1! theTable.data_writeArray('%%%ii'%(formatwidth),delimiter=' ') #--- output finalization -------------------------------------------------------------------------- if file['name'] != 'STDIN': theTable.__IO__['in'].close() theTable.__IO__['out'].close() os.rename(file['name']+'_tmp',file['name'])