#!/usr/bin/env python
# -*- coding: UTF-8 no BOM -*-
import os,sys,math
import numpy as np
from optparse import OptionParser
from scipy import ndimage
import damask
scriptName = os.path.splitext(os.path.basename(__file__))[0]
scriptID = ' '.join([scriptName,damask.version])
#--------------------------------------------------------------------------------------------------
# MAIN
#--------------------------------------------------------------------------------------------------
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.
""", version = scriptID)
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 = '<LIST>',
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)
# --- loop over input files -------------------------------------------------------------------------
if filenames == []: filenames = [None]
for name in filenames:
try:
table = damask.ASCIItable(name = name,
buffered = False, labeled = False)
except: continue
damask.util.report(scriptName,name)
# --- interpret header ----------------------------------------------------------------------------
table.head_read()
info,extra_header = table.head_getGeom()
damask.util.croak(['grid a b c: %s'%(' x '.join(map(str,info['grid']))),
'size x y z: %s'%(' x '.join(map(str,info['size']))),
'origin x y z: %s'%(' : '.join(map(str,info['origin']))),
'homogenization: %i'%info['homogenization'],
'microstructures: %i'%info['microstructures'],
])
errors = []
if np.any(info['grid'] < 1): errors.append('invalid grid a b c.')
if np.any(info['size'] <= 0.0): errors.append('invalid size x y z.')
if errors != []:
damask.util.croak(errors)
table.close(dismiss = True)
continue
# --- read data ------------------------------------------------------------------------------------
microstructure = np.tile(np.array(table.microstructure_read(info['grid']),'i').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
# store a copy the initial microstructure to find locations of immutable indices
microstructure_original = np.copy(microstructure)
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):
# assign interfacial energy to all voxels that have a differing neighbor (in Moore neighborhood)
interfaceEnergy = np.maximum(boundary,
interfacialEnergy(microstructure,np.roll(np.roll(np.roll(
microstructure,i,axis=0), j,axis=1), k,axis=2)))
# periodically extend interfacial energy array by half a grid size in positive and negative directions
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]
# transform bulk volume (i.e. where interfacial energy is zero)
index = ndimage.morphology.distance_transform_edt(periodic_interfaceEnergy == 0.,
return_distances = False,
return_indices = True)
# want array index of nearest voxel on periodically extended boundary
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 | 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
# transform voxels close to interface region | question PE: what motivates 1/2 (could be any small number, or)?
index = ndimage.morphology.distance_transform_edt(periodic_diffusedEnergy >= 0.5,
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)
# find locations where immutable microstructures have been or are now
for micro in options.immutable:
immutable += np.logical_or(microstructure == micro, microstructure_original == micro)
# undo any changes involving immutable microstructures
microstructure = np.where(immutable, microstructure_original,microstructure)
# --- 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)
newInfo = {'microstructures': 0,}
newInfo['microstructures'] = microstructure.max()
# --- report ---------------------------------------------------------------------------------------
remarks = []
if (newInfo['microstructures'] != info['microstructures']): remarks.append('--> microstructures: %i'%newInfo['microstructures'])
if remarks != []: damask.util.croak(remarks)
# --- write header ---------------------------------------------------------------------------------
table.labels_clear()
table.info_clear()
table.info_append(extra_header+[
scriptID + ' ' + ' '.join(sys.argv[1:]),
"grid\ta {grid[0]}\tb {grid[1]}\tc {grid[2]}".format(grid=info['grid']),
"size\tx {size[0]}\ty {size[1]}\tz {size[2]}".format(size=info['size']),
"origin\tx {origin[0]}\ty {origin[1]}\tz {origin[2]}".format(origin=info['origin']),
"homogenization\t{homog}".format(homog=info['homogenization']),
"microstructures\t{microstructures}".format(microstructures=newInfo['microstructures']),
])
table.head_write()
# --- write microstructure information ------------------------------------------------------------
formatwidth = int(math.floor(math.log10(microstructure.max())+1))
table.data = microstructure.reshape((info['grid'][0],info['grid'][1]*info['grid'][2]),order='F').transpose()
table.data_writeArray('%%%ii'%(formatwidth),delimiter = ' ')
# --- output finalization --------------------------------------------------------------------------
table.close()