DAMASK_EICMD/processing/pre/geom_grainGrowth.py

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#!/usr/bin/env python
# -*- coding: UTF-8 no BOM -*-
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import os,sys,string,re,math,itertools
import numpy as np
from optparse import OptionParser
from scipy import ndimage
from multiprocessing import Pool
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import damask
scriptID = '$Id$'
scriptName = scriptID.split()[1]
#--------------------------------------------------------------------------------------------------
# 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),
}
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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',
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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', type='string', 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()
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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 = {
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'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'])
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if np.any(info['grid'] < 1):
file['croak'].write('invalid grid a b c.\n')
continue
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if np.any(info['size'] <= 0.0):
file['croak'].write('invalid size x y z.\n')
continue
#--- read data ------------------------------------------------------------------------------------
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microstructure = np.zeros(np.prod([2 if i == 1 else i for i in 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 ---------------------------------------------------------------------
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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 -----------------------------------------------------------------------
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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
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microstructure_original = np.copy(microstructure) # store a copy the initial microstructure to find locations of immutable indices
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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,:,:]
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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):
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boundary = np.zeros(microstructure.shape)
for i in (-1,0,1):
for j in (-1,0,1):
for k in (-1,0,1):
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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)
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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
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# 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
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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)
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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
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immutable = np.zeros(microstructure.shape, dtype=bool)
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for micro in options.immutable:
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immutable += np.logical_or(microstructure == micro, microstructure_original == micro) # find locations where immutable microstructures have been or are now
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microstructure = np.where(immutable, microstructure_original,microstructure) # undo any changes involving immutable microstructures
# --- renumber to sequence 1...Ngrains if requested ------------------------------------------------
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# http://stackoverflow.com/questions/10741346/np-frequency-counts-for-unique-values-in-an-array
if options.renumber:
newID = 0
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for microstructureID,count in enumerate(np.bincount(microstructure.flatten())):
if count != 0:
newID += 1
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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+[
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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))
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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':
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theTable.__IO__['in'].close()
theTable.__IO__['out'].close()
os.rename(file['name']+'_tmp',file['name'])