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DAMASK_EICMD
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DAMASK_EICMD/processing/pre/geom_stretchInterfaces.py

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#!/usr/bin/env python
# -*- coding: UTF-8 no BOM -*-
import os,sys,string,re,math,numpy
from optparse import OptionParser, OptionGroup, Option, SUPPRESS_HELP
from scipy import ndimage
#--------------------------------------------------------------------------------------------------
class extendedOption(Option):
#--------------------------------------------------------------------------------------------------
# used for definition of new option parser action 'extend', which enables to take multiple option arguments
# taken from online tutorial http://docs.python.org/library/optparse.html
ACTIONS = Option.ACTIONS + ("extend",)
STORE_ACTIONS = Option.STORE_ACTIONS + ("extend",)
TYPED_ACTIONS = Option.TYPED_ACTIONS + ("extend",)
ALWAYS_TYPED_ACTIONS = Option.ALWAYS_TYPED_ACTIONS + ("extend",)
def take_action(self, action, dest, opt, value, values, parser):
if action == "extend":
lvalue = value.split(",")
values.ensure_value(dest, []).extend(lvalue)
else:
Option.take_action(self, action, dest, opt, value, values, parser)
#--------------------------------------------------------------------------------------------------
# MAIN
#--------------------------------------------------------------------------------------------------
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),
}
parser = OptionParser(option_class=extendedOption, 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 for a given time,
i.e. up to a diffusion distance of sqrt(t) voxels.
The final geometry is assembled by selecting at each voxel that grain index for which the concentration is largest.
""" + string.replace('$Id$','\n','\\n')
)
parser.add_option('-t', '--time', dest='t', type='int', \
help='time for curvature flow [%default]')
parser.add_option('-N', '--smooth', dest='N', type='int', \
help='number of steps for curvature flow [%default]')
parser.add_option('-b', '--black', dest='black', action='extend', type='string', \
help='indices of stationary microstructures', metavar='<LIST>')
parser.add_option('-2', '--twodimensional', dest='twoD', action='store_true', \
help='output geom file with two-dimensional data arrangement [%default]')
parser.set_defaults(t = 1)
parser.set_defaults(N = 1)
parser.set_defaults(black = [])
parser.set_defaults(twoD = False)
(options, filenames) = parser.parse_args()
options.black = map(int,options.black)
#--- 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(file['name']+'\n')
firstline = file['input'].readline()
m = re.search('(\d+)\s*head', firstline.lower())
if m:
headerlines = int(m.group(1))
headers = [file['input'].readline() for i in range(headerlines)]
else:
headerlines = 1
headers = firstline
content = file['input'].readlines()
file['input'].close()
#--- interprete header ----------------------------------------------------------------------------
info = {
'grid': numpy.zeros(3,'i'),
'size': numpy.zeros(3,'d'),
'origin': numpy.zeros(3,'d'),
'microstructures': 0,
'homogenization': 0,
}
new_header = []
for header in headers:
headitems = map(str.lower,header.split())
if headitems[0] == 'resolution': headitems[0] = 'grid'
if headitems[0] == 'dimension': headitems[0] = 'size'
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])
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 numpy.any(info['grid'] < 1):
file['croak'].write('invalid grid a b c.\n')
sys.exit()
if numpy.any(info['size'] <= 0.0):
file['croak'].write('invalid size x y z.\n')
sys.exit()
#--- read data ------------------------------------------------------------------------------------
microstructure = numpy.zeros(info['grid'],'i')
i = 0
for line in content:
items = line.split()
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)
for item in items:
microstructure[i%info['grid'][0],
(i/info['grid'][0])%info['grid'][1],
i/info['grid'][0] /info['grid'][1]] = item
i += 1
#--- initialize helper data -----------------------------------------------------------------------
diffusionWindow = int(math.ceil(4.0*numpy.sqrt(options.t)))
for smoothIter in xrange(options.N):
extendedMicro = numpy.zeros(2*diffusionWindow+info['grid']).astype(int)
extendedMicro[:info['grid'][0],:info['grid'][1],:info['grid'][2]] = \
numpy.roll(numpy.roll(numpy.roll(microstructure,shift=diffusionWindow,axis=0),\
shift=diffusionWindow,axis=1),shift=diffusionWindow,axis=2)
extendedMicro[-info['grid'][0]:,:info['grid'][1],:info['grid'][2]] = \
numpy.roll(numpy.roll(numpy.roll(microstructure,shift=-diffusionWindow,axis=0),\
shift=diffusionWindow,axis=1),shift=diffusionWindow,axis=2)
extendedMicro[:info['grid'][0],-info['grid'][1]:,:info['grid'][2]] = \
numpy.roll(numpy.roll(numpy.roll(microstructure,shift=diffusionWindow,axis=0),\
shift=-diffusionWindow,axis=1),shift=diffusionWindow,axis=2)
extendedMicro[-info['grid'][0]:,-info['grid'][1]:,:info['grid'][2]] = \
numpy.roll(numpy.roll(numpy.roll(microstructure,shift=-diffusionWindow,axis=0),\
shift=-diffusionWindow,axis=1),shift=diffusionWindow,axis=2)
extendedMicro[:info['grid'][0],:info['grid'][1],-info['grid'][2]:] = \
numpy.roll(numpy.roll(numpy.roll(microstructure,shift=diffusionWindow,axis=0),\
shift=diffusionWindow,axis=1),shift=-diffusionWindow,axis=2)
extendedMicro[-info['grid'][0]:,:info['grid'][1],-info['grid'][2]:] = \
numpy.roll(numpy.roll(numpy.roll(microstructure,shift=-diffusionWindow,axis=0),\
shift=diffusionWindow,axis=1),shift=-diffusionWindow,axis=2)
extendedMicro[:info['grid'][0],-info['grid'][1]:,-info['grid'][2]:] = \
numpy.roll(numpy.roll(numpy.roll(microstructure,shift=diffusionWindow,axis=0),\
shift=-diffusionWindow,axis=1),shift=-diffusionWindow,axis=2)
extendedMicro[-info['grid'][0]:,-info['grid'][1]:,-info['grid'][2]:] = \
numpy.roll(numpy.roll(numpy.roll(microstructure,shift=-diffusionWindow,axis=0),\
shift=-diffusionWindow,axis=1),shift=-diffusionWindow,axis=2)
winner = numpy.zeros(extendedMicro.shape).astype(int)
winner[diffusionWindow:-diffusionWindow,diffusionWindow:-diffusionWindow,diffusionWindow:-diffusionWindow] =\
numpy.where(numpy.reshape(numpy.in1d(microstructure,options.black),microstructure.shape),\
microstructure,0)
diffusedMax = numpy.zeros(extendedMicro.shape)
boundingSlice = ndimage.measurements.find_objects(microstructure)
microList = set(numpy.unique(microstructure)).difference(set(options.black).union(set([0])))
#--- diffuse each grain separately ----------------------------------------------------------------
for grain in microList:
xMin = boundingSlice[grain-1][0].start; xMax = boundingSlice[grain-1][0].stop + 2*diffusionWindow
yMin = boundingSlice[grain-1][1].start; yMax = boundingSlice[grain-1][1].stop + 2*diffusionWindow
zMin = boundingSlice[grain-1][2].start; zMax = boundingSlice[grain-1][2].stop + 2*diffusionWindow
diffused = ndimage.filters.gaussian_filter((extendedMicro[xMin:xMax,yMin:yMax,zMin:zMax] == grain).astype(float),\
numpy.sqrt(options.t))
isMax = diffused > diffusedMax[xMin:xMax,yMin:yMax,zMin:zMax]
winner[xMin:xMax,yMin:yMax,zMin:zMax][isMax] = grain
diffusedMax[xMin:xMax,yMin:yMax,zMin:zMax] = numpy.where(isMax,diffused,diffusedMax[xMin:xMax,yMin:yMax,zMin:zMax])
microstructure = winner[diffusionWindow:-diffusionWindow,diffusionWindow:-diffusionWindow,diffusionWindow:-diffusionWindow]
# --- assemble header -----------------------------------------------------------------------------
formatwidth = int(math.floor(math.log10(microstructure.max())+1))
new_header.append('$Id$\n')
new_header.append("grid\ta %i\tb %i\tc %i\n"%(
info['grid'][0],info['grid'][1],info['grid'][2]))
new_header.append("size\tx %f\ty %f\tz %f\n"%(
info['size'][0],info['size'][1],info['size'][2]))
new_header.append("origin\tx %f\ty %f\tz %f\n"%(
info['origin'][0],info['origin'][1],info['origin'][2]))
new_header.append("homogenization\t%i\n"%info['homogenization'])
new_header.append("microstructures\t%i\n"%info['microstructures'])
file['output'].write('%i\theader\n'%(len(new_header))+''.join(new_header))
# --- write microstructure information ------------------------------------------------------------
for z in xrange(info['grid'][2]):
for y in xrange(info['grid'][1]):
file['output'].write({True:' ',False:'\n'}[options.twoD].join(map(lambda x: \
('%%%ii'%formatwidth)%x, microstructure[:,y,z])) + '\n')
#--- output finalization --------------------------------------------------------------------------
if file['name'] != 'STDIN':
file['output'].close()
os.rename(file['name']+'_tmp',file['name'])
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