298 lines
16 KiB
Python
Executable File
298 lines
16 KiB
Python
Executable File
#!/usr/bin/env python
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# -*- coding: UTF-8 no BOM -*-
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import os,sys,string,re,math,numpy,itertools
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import damask
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from optparse import OptionParser, OptionGroup, Option, SUPPRESS_HELP
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from scipy import ndimage
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from multiprocessing import Pool
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scriptID = '$Id$'
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scriptName = scriptID.split()[1]
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#--------------------------------------------------------------------------------------------------
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class extendedOption(Option):
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#--------------------------------------------------------------------------------------------------
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# used for definition of new option parser action 'extend', which enables to take multiple option arguments
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# taken from online tutorial http://docs.python.org/library/optparse.html
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ACTIONS = Option.ACTIONS + ("extend",)
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STORE_ACTIONS = Option.STORE_ACTIONS + ("extend",)
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TYPED_ACTIONS = Option.TYPED_ACTIONS + ("extend",)
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ALWAYS_TYPED_ACTIONS = Option.ALWAYS_TYPED_ACTIONS + ("extend",)
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def take_action(self, action, dest, opt, value, values, parser):
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if action == "extend":
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lvalue = value.split(",")
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values.ensure_value(dest, []).extend(lvalue)
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else:
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Option.take_action(self, action, dest, opt, value, values, parser)
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def grainCoarsenLocal(microLocal,ix,iy,iz,window):
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interfacialEnergy = lambda A,B: 1.0
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struc = ndimage.generate_binary_structure(3,3)
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winner = numpy.where(numpy.in1d(microLocal,options.black).reshape(microLocal.shape),
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microLocal,0) # zero out non-blacklisted microstructures
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diffusedMax = (winner > 0).astype(float) # concentration of immutable microstructures
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boundingSlice = ndimage.measurements.find_objects(microLocal) # bounding boxes of each distinct microstructure region
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diffused = {}
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for grain in set(numpy.unique(microLocal)) - set(options.black) - (set([0])): # all microstructures except immutable ones
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mini = [max(0, boundingSlice[grain-1][i].start - window) for i in range(3)] # upper right of expanded bounding box
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maxi = [min(microLocal.shape[i], boundingSlice[grain-1][i].stop + window) for i in range(3)] # lower left of expanded bounding box
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microWindow = microLocal[mini[0]:maxi[0],mini[1]:maxi[1],mini[2]:maxi[2]]
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grainCharFunc = microWindow==grain
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neighbours = set(numpy.unique(microWindow[ndimage.morphology.binary_dilation(grainCharFunc,structure=struc)]))\
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- set([grain]) - set(options.black) # who is on my boundary?
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try: # has grain been diffused previously?
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diff = diffused[grain].copy() # yes: use previously diffused grain
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except:
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diffused[grain] = ndimage.filters.gaussian_filter((grainCharFunc).astype(float),options.d) # no: diffuse grain with unit speed
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diff = diffused[grain].copy()
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if len(neighbours) == 1:
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speed = interfacialEnergy(grain,neighbours.pop()) # speed proportional to interfacial energy between me and neighbour
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diff = speed*diff + (1.-speed)*(grainCharFunc) # rescale diffused microstructure by speed
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else:
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tiny = 0.001
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numerator = numpy.zeros(microWindow.shape)
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denominator = numpy.zeros(microWindow.shape)
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weights = {grain: diff + tiny}
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for i in neighbours:
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miniI = [max(0, boundingSlice[i-1][j].start - window) for j in range(3)] # bounding box of neighbour
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maxiI = [min(microLocal.shape[j], boundingSlice[i-1][j].stop + window) for j in range(3)]
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miniCommon = [max(mini[j], boundingSlice[i-1][j].start - window) for j in range(3)] # intersection of mine and neighbouring bounding box
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maxiCommon = [min(maxi[j], boundingSlice[i-1][j].stop + window) for j in range(3)]
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weights[i] = tiny*numpy.ones(microWindow.shape)
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try: # has neighbouring grain been diffused previously?
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weights[i][miniCommon[0] - mini[0]:maxiCommon[0] - mini[0],\
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miniCommon[1] - mini[1]:maxiCommon[1] - mini[1],\
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miniCommon[2] - mini[2]:maxiCommon[2] - mini[2]] = diffused[i][miniCommon[0] - miniI[0]:maxiCommon[0] - miniI[0],\
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miniCommon[1] - miniI[1]:maxiCommon[1] - miniI[1],\
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miniCommon[2] - miniI[2]:maxiCommon[2] - miniI[2]] + tiny
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except: # no: diffuse neighbouring grain with unit speed
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diffused[i] = ndimage.filters.gaussian_filter((microLocal[miniI[0]:maxiI[0],\
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miniI[1]:maxiI[1],\
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miniI[2]:maxiI[2]]==i).astype(float),options.d)
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weights[i][miniCommon[0] - mini[0]:maxiCommon[0] - mini[0],\
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miniCommon[1] - mini[1]:maxiCommon[1] - mini[1],\
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miniCommon[2] - mini[2]:maxiCommon[2] - mini[2]] = diffused[i][miniCommon[0] - miniI[0]:maxiCommon[0] - miniI[0],\
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miniCommon[1] - miniI[1]:maxiCommon[1] - miniI[1],\
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miniCommon[2] - miniI[2]:maxiCommon[2] - miniI[2]] + tiny
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for grainA,grainB in itertools.combinations(neighbours,2): # combinations of possible triple junctions
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speed = interfacialEnergy(grain,grainA) +\
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interfacialEnergy(grain,grainB) -\
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interfacialEnergy(grainA,grainB) # speed of the triple junction
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weight = weights[grainA] * weights[grainB]
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if numpy.any(weight > 0.01): # strongly interacting triple junction?
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weight *= weights[grain]
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numerator += weight*(speed*diff + (1.-speed)*(grainCharFunc))
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denominator += weight
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diff = numerator/denominator # weighted sum of strongly interacting triple junctions
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winner[mini[0]:maxi[0],\
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mini[1]:maxi[1],\
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mini[2]:maxi[2]][diff > diffusedMax[mini[0]:maxi[0],\
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mini[1]:maxi[1],\
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mini[2]:maxi[2]]] = grain # remember me ...
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diffusedMax[mini[0]:maxi[0],\
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mini[1]:maxi[1],\
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mini[2]:maxi[2]] = numpy.maximum(diff,diffusedMax[mini[0]:maxi[0],\
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mini[1]:maxi[1],\
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mini[2]:maxi[2]]) # ... and my concentration
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return [winner[window:-window,window:-window,window:-window],ix,iy,iz]
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def log_result(result):
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ix = result[1]; iy = result[2]; iz = result[3]
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microstructure[ix*stride[0]:(ix+1)*stride[0],iy*stride[1]:(iy+1)*stride[1],iz*stride[2]:(iz+1)*stride[2]] = \
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result[0]
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#--------------------------------------------------------------------------------------------------
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# MAIN
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#--------------------------------------------------------------------------------------------------
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synonyms = {
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'grid': ['resolution'],
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'size': ['dimension'],
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}
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identifiers = {
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'grid': ['a','b','c'],
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'size': ['x','y','z'],
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'origin': ['x','y','z'],
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}
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mappings = {
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'grid': lambda x: int(x),
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'size': lambda x: float(x),
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'origin': lambda x: float(x),
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'homogenization': lambda x: int(x),
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'microstructures': lambda x: int(x),
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}
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parser = OptionParser(option_class=extendedOption, usage='%prog options [file[s]]', description = """
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Smoothens out interface roughness by simulated curvature flow.
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This is achieved by the diffusion of each initially sharply bounded grain volume within the periodic domain
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up to a given distance 'd' voxels.
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The final geometry is assembled by selecting at each voxel that grain index for which the concentration remains largest.
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""" + string.replace(scriptID,'\n','\\n')
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)
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parser.add_option('-d', '--distance', dest='d', type='int', \
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help='diffusion distance in voxels [%default]', metavar='float')
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parser.add_option('-N', '--smooth', dest='N', type='int', \
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help='N for curvature flow [%default]')
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parser.add_option('-p', '--processors', dest='p', type='int', nargs = 3, \
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help='number of threads in x,y,z direction')
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parser.add_option('-b', '--black', dest='black', action='extend', type='string', \
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help='indices of stationary microstructures', metavar='<LIST>')
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parser.set_defaults(d = 1)
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parser.set_defaults(N = 1)
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parser.set_defaults(p = [1,1,1])
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parser.set_defaults(black = [])
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(options, filenames) = parser.parse_args()
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options.black = map(int,options.black)
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#--- setup file handles --------------------------------------------------------------------------
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files = []
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if filenames == []:
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files.append({'name':'STDIN',
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'input':sys.stdin,
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'output':sys.stdout,
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'croak':sys.stderr,
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})
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else:
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for name in filenames:
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if os.path.exists(name):
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files.append({'name':name,
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'input':open(name),
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'output':open(name+'_tmp','w'),
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'croak':sys.stdout,
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})
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#--- loop over input files ------------------------------------------------------------------------
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for file in files:
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if file['name'] != 'STDIN': file['croak'].write('\033[1m'+scriptName+'\033[0m: '+file['name']+'\n')
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else: file['croak'].write('\033[1m'+scriptName+'\033[0m\n')
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theTable = damask.ASCIItable(file['input'],file['output'],labels=False)
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theTable.head_read()
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#--- interpret header ----------------------------------------------------------------------------
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info = {
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'grid': numpy.zeros(3,'i'),
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'size': numpy.zeros(3,'d'),
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'origin': numpy.zeros(3,'d'),
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'homogenization': 0,
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'microstructures': 0,
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}
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newInfo = {
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'microstructures': 0,
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}
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extra_header = []
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for header in theTable.info:
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headitems = map(str.lower,header.split())
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if len(headitems) == 0: continue
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for synonym,alternatives in synonyms.iteritems():
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if headitems[0] in alternatives: headitems[0] = synonym
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if headitems[0] in mappings.keys():
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if headitems[0] in identifiers.keys():
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for i in xrange(len(identifiers[headitems[0]])):
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info[headitems[0]][i] = \
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mappings[headitems[0]](headitems[headitems.index(identifiers[headitems[0]][i])+1])
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else:
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info[headitems[0]] = mappings[headitems[0]](headitems[1])
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else:
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extra_header.append(header)
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file['croak'].write('grid a b c: %s\n'%(' x '.join(map(str,info['grid']))) + \
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'size x y z: %s\n'%(' x '.join(map(str,info['size']))) + \
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'origin x y z: %s\n'%(' : '.join(map(str,info['origin']))) + \
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'homogenization: %i\n'%info['homogenization'] + \
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'microstructures: %i\n'%info['microstructures'])
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if numpy.any(info['grid'] < 1):
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file['croak'].write('invalid grid a b c.\n')
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continue
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if numpy.any(info['size'] <= 0.0):
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file['croak'].write('invalid size x y z.\n')
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continue
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#--- read data ------------------------------------------------------------------------------------
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microstructure = numpy.zeros(info['grid'].prod(),'i')
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i = 0
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theTable.data_rewind()
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while theTable.data_read():
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items = theTable.data
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if len(items) > 2:
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if items[1].lower() == 'of': items = [int(items[2])]*int(items[0])
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elif items[1].lower() == 'to': items = xrange(int(items[0]),1+int(items[2]))
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else: items = map(int,items)
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else: items = map(int,items)
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s = len(items)
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microstructure[i:i+s] = items
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i += s
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#--- do work -------------------------------------------------------------------------------------
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microstructure = microstructure.reshape(info['grid'],order='F')
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#--- domain decomposition -------------------------------------------------------------------------
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numProc = int(options.p[0]*options.p[1]*options.p[2])
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stride = info['grid']/options.p
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if numpy.any(numpy.floor(stride) != stride):
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file['croak'].write('invalid domain decomposition.\n')
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continue
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#--- initialize helper data -----------------------------------------------------------------------
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window = 4*options.d
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for smoothIter in xrange(options.N):
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extendedMicro = numpy.tile(microstructure,[3,3,3])
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extendedMicro = extendedMicro[(info['grid'][0]-window):-(info['grid'][0]-window),
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(info['grid'][1]-window):-(info['grid'][1]-window),
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(info['grid'][2]-window):-(info['grid'][2]-window)]
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pool = Pool(processes=numProc)
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for iz in xrange(options.p[2]):
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for iy in xrange(options.p[1]):
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for ix in xrange(options.p[0]):
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pool.apply_async(grainCoarsenLocal,(extendedMicro[ix*stride[0]:(ix+1)*stride[0]+2*window,\
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iy*stride[1]:(iy+1)*stride[1]+2*window,\
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iz*stride[2]:(iz+1)*stride[2]+2*window],\
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ix,iy,iz,window), callback=log_result)
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pool.close()
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pool.join()
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# --- assemble header -----------------------------------------------------------------------------
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newInfo['microstructures'] = microstructure.max()
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#--- report ---------------------------------------------------------------------------------------
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if (newInfo['microstructures'] != info['microstructures']):
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file['croak'].write('--> microstructures: %i\n'%newInfo['microstructures'])
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#--- write header ---------------------------------------------------------------------------------
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theTable.labels_clear()
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theTable.info_clear()
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theTable.info_append(extra_header+[
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scriptID,
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"grid\ta %i\tb %i\tc %i"%(info['grid'][0],info['grid'][1],info['grid'][2],),
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"size\tx %f\ty %f\tz %f"%(info['size'][0],info['size'][1],info['size'][2],),
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"origin\tx %f\ty %f\tz %f"%(info['origin'][0],info['origin'][1],info['origin'][2],),
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"homogenization\t%i"%info['homogenization'],
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"microstructures\t%i"%(newInfo['microstructures']),
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])
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theTable.head_write()
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theTable.output_flush()
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# --- write microstructure information ------------------------------------------------------------
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formatwidth = int(math.floor(math.log10(microstructure.max())+1))
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theTable.data = microstructure.reshape((info['grid'][0],info['grid'][1]*info['grid'][2]),order='F').transpose()
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theTable.data_writeArray('%%%ii'%(formatwidth))
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#--- output finalization --------------------------------------------------------------------------
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if file['name'] != 'STDIN':
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file['input'].close()
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file['output'].close()
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os.rename(file['name']+'_tmp',file['name'])
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