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DAMASK_EICMD
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polishing of variable names, comments, and some of the programming structure.

This commit is contained in:
Philip Eisenlohr 2014-06-07 18:13:29 +00:00
parent fec50e424e
commit 72e9c512bd
1 changed files with 73 additions and 62 deletions
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135
processing/pre/geom_grainGrowth.py
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@ -57,22 +57,23 @@ The final geometry is assembled by selecting at each voxel that grain index for
""" + string.replace(scriptID,'\n','\\n') """ + string.replace(scriptID,'\n','\\n')
) )
parser.add_option('-d', '--distance', dest='d', type='int', metavar='int', \ parser.add_option('-d', '--distance', dest='d', type='int', metavar='int',
help='diffusion distance in voxels [%default]') help='diffusion distance in voxels [%default]')
parser.add_option('-N', '--smooth', dest='N', type='int', metavar='int', \ parser.add_option('-N', '--smooth', dest='N', type='int', metavar='int',
help='N for curvature flow [%default]') help='N for curvature flow [%default]')
parser.add_option('-r', '--renumber', dest='renumber', action='store_true', \ parser.add_option('-r', '--renumber', dest='renumber', action='store_true',
help='renumber microstructure indices from 1...N [%default]') help='renumber microstructure indices from 1...N [%default]')
parser.add_option('-i', '--immutable', action='extend', dest='immutable', type='string', \ parser.add_option('-i', '--immutable', action='extend', dest='immutable', type='string', metavar = '<LIST>',
help='immutable microstructures') help='list of immutable microstructures')
parser.set_defaults(d = 1) parser.set_defaults(d = 1)
parser.set_defaults(N = 1) parser.set_defaults(N = 1)
parser.set_defaults(renumber = False) parser.set_defaults(renumber = False)
parser.set_defaults(immutable = [0]) parser.set_defaults(immutable = [])
(options, filenames) = parser.parse_args() (options, filenames) = parser.parse_args()
options.immutable = map(int,options.immutable)
#--- setup file handles -------------------------------------------------------------------------- #--- setup file handles --------------------------------------------------------------------------
files = [] files = []
@ -157,73 +158,83 @@ for file in files:
i += s i += s
#--- reshape, if 2D make copy --------------------------------------------------------------------- #--- reshape, if 2D make copy ---------------------------------------------------------------------
expandedGrid = numpy.array([2 if i == 1 else i for i in info['grid']],'i')
nMicrostuctures = numpy.prod(expandedGrid)
if nMicrostuctures > info['grid'].prod():
microstructure[info['grid'].prod():nMicrostuctures] = microstructure[0:info['grid'].prod()]
microstructure = microstructure.reshape([2 if i == 1 else i for i in info['grid']],order='F')
grid = numpy.array([2 if i == 1 else i for i in info['grid']],'i')
microstructure = numpy.tile(microstructure.reshape(info['grid'],order='F'),
numpy.where(info['grid'] == 1, 2,1)) # make one copy along dimensions with grid == 1
grid = numpy.array(microstructure.shape)
#--- initialize support data -----------------------------------------------------------------------
#--- initialize helper data ----------------------------------------------------------------------- periodic_microstructure = numpy.tile(microstructure,(3,3,3))[grid[0]/2:-grid[0]/2,
X,Y,Z = numpy.mgrid[0:expandedGrid[0],0:expandedGrid[1],0:expandedGrid[2]] grid[1]/2:-grid[1]/2,
gauss = numpy.exp(-(X*X+Y*Y+Z*Z)/(2.0*options.d*options.d))/math.pow(2.0*numpy.pi*options.d*options.d,1.5) grid[2]/2:-grid[2]/2] # periodically extend the microstructure
gauss[:,:,(expandedGrid[2])/2::] = gauss[:,:,(expandedGrid[2])/2-1::-1] microstructure_original = numpy.copy(microstructure) # store a copy the initial microstructure to find locations of immutable indices
gauss[:,(expandedGrid[1])/2::,:] = gauss[:,(expandedGrid[1])/2-1::-1,:]
gauss[(expandedGrid[0])/2::,:,:] = gauss[(expandedGrid[0])/2-1::-1,:,:] X,Y,Z = numpy.mgrid[0:grid[0],0:grid[1],0:grid[2]]
gauss = numpy.exp(-(X*X + Y*Y + Z*Z)/(2.0*options.d*options.d))/math.pow(2.0*numpy.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 = numpy.fft.rfftn(gauss) gauss = numpy.fft.rfftn(gauss)
interfacialEnergy = lambda A,B: (A*B != 0)*(A != B)*1.0 interfacialEnergy = lambda A,B: (A*B != 0)*(A != B)*1.0
struc = ndimage.generate_binary_structure(3,1) struc = ndimage.generate_binary_structure(3,1) # 3D von Neumann neighborhood
microstructure_original = numpy.copy(microstructure)
for smoothIter in xrange(options.N): for smoothIter in xrange(options.N):
boundary = numpy.zeros(microstructure.shape) boundary = numpy.zeros(microstructure.shape)
for i in range(3): for i in (-1,0,1):
for j in range(3): for j in (-1,0,1):
for k in range(3): for k in (-1,0,1):
boundary = numpy.maximum(boundary, interfaceEnergy = numpy.maximum(boundary,
interfacialEnergy(microstructure,numpy.roll(numpy.roll(numpy.roll( interfacialEnergy(microstructure,numpy.roll(numpy.roll(numpy.roll(
microstructure,i-1,axis=0),j-1,axis=1),k-1,axis=2))) microstructure,i,axis=0), j,axis=1), k,axis=2))) # assign interfacial energy to all voxels that have a differing neighbor (in Moore neighborhood)
boundaryExt = numpy.tile(boundary,(3,3,3)) periodic_interfaceEnergy = numpy.tile(interfaceEnergy,(3,3,3))[grid[0]/2:-grid[0]/2,
boundaryExt = boundaryExt[(expandedGrid[0])/2:-(expandedGrid[0])/2, grid[1]/2:-grid[1]/2,
(expandedGrid[1])/2:-(expandedGrid[1])/2, grid[2]/2:-grid[2]/2] # periodically extend interfacial energy array by half a grid size in positive and negative directions
(expandedGrid[2])/2:-(expandedGrid[2])/2] index = ndimage.morphology.distance_transform_edt(periodic_interfaceEnergy == 0., # transform bulk volume (i.e. where interfacial energy is zero)
index = ndimage.morphology.distance_transform_edt(boundaryExt == 0.,return_distances = False,return_indices = True) # array index of nearest voxel on periodically extended boundary return_distances = False,
boundaryExt = boundaryExt[index[0].flatten(),index[1].flatten(),index[2].flatten()].reshape(boundaryExt.shape) # fill bulk with energy of nearest interface return_indices = True) # want array index of nearest voxel on periodically extended boundary
boundary = numpy.fft.irfftn(numpy.fft.rfftn(numpy.where(ndimage.morphology.binary_dilation(boundary > 0., # 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?
structure = struc, periodic_bulkEnergy = periodic_interfaceEnergy[index[0],
iterations = 2*options.d-1), # fat boundary index[1],
boundaryExt[(expandedGrid[0])/2:-(expandedGrid[0])/2, # retain filled energy on fat boundary index[2]].reshape(2*grid) # fill bulk with energy of nearest interface
(expandedGrid[1])/2:-(expandedGrid[1])/2, diffusedEnergy = numpy.fft.irfftn(numpy.fft.rfftn(numpy.where(ndimage.morphology.binary_dilation(interfaceEnergy > 0.,
(expandedGrid[2])/2:-(expandedGrid[2])/2], structure = struc,
0.))*gauss) # zero everywhere else iterations = options.d/2 + 1), # fat boundary | question PE: why 2d - 1? I would argue for d/2 + 1 !!
boundaryExt = numpy.tile(boundary,(3,3,3)) periodic_bulkEnergy[grid[0]/2:-grid[0]/2, # retain filled energy on fat boundary...
boundaryExt = boundaryExt[(expandedGrid[0])/2:-(expandedGrid[0])/2, grid[1]/2:-grid[1]/2,
(expandedGrid[1])/2:-(expandedGrid[1])/2, grid[2]/2:-grid[2]/2], # ...and zero everywhere else
(expandedGrid[2])/2:-(expandedGrid[2])/2] 0.)\
microstructureExt = numpy.tile(microstructure,(3,3,3)) )*gauss)
microstructureExt = microstructureExt[(expandedGrid[0])/2:-(expandedGrid[0])/2, periodic_diffusedEnergy = numpy.tile(diffusedEnergy,(3,3,3))[grid[0]/2:-grid[0]/2,
(expandedGrid[1])/2:-(expandedGrid[1])/2, grid[1]/2:-grid[1]/2,
(expandedGrid[2])/2:-(expandedGrid[2])/2] grid[2]/2:-grid[2]/2] # periodically extend the smoothed bulk energy
index = ndimage.morphology.distance_transform_edt(boundaryExt >= 0.5,return_distances=False,return_indices=True) 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)?
microstructureExt = microstructureExt[index[0].flatten(),index[1].flatten(),index[2].flatten()].reshape(microstructureExt.shape) return_distances = False,
microstructure = microstructureExt[(expandedGrid[0])/2:-(expandedGrid[0])/2, return_indices = True) # want index of closest bulk grain
(expandedGrid[1])/2:-(expandedGrid[1])/2, microstructure = periodic_microstructure[index[0],
(expandedGrid[2])/2:-(expandedGrid[2])/2] 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 = numpy.zeros(microstructure.shape, dtype=bool) immutable = numpy.zeros(microstructure.shape, dtype=bool)
for micro in options.immutable: for micro in options.immutable:
immutable = numpy.logical_or(immutable, numpy.logical_or(microstructure == int(micro), microstructure_original == int(micro))) immutable += numpy.logical_or(microstructure == micro, microstructure_original == micro) # find locations where immutable microstructures have been or are now
microstructure = numpy.where(immutable, microstructure_original,microstructure) microstructure = numpy.where(immutable, microstructure_original,microstructure) # undo any changes involving immutable microstructures
# --- renumber to sequence 1...Ngrains if requested ------------------------------------------------ # --- renumber to sequence 1...Ngrains if requested ------------------------------------------------
# http://stackoverflow.com/questions/10741346/numpy-frequency-counts-for-unique-values-in-an-array # http://stackoverflow.com/questions/10741346/numpy-frequency-counts-for-unique-values-in-an-array
if options.renumber: if options.renumber:
newID=0 newID = 0
for microstructureID,count in enumerate(numpy.bincount(microstructure.reshape(info['grid'].prod()))): for microstructureID,count in enumerate(numpy.bincount(microstructure.flatten())):
if count != 0: if count != 0:
newID+=1 newID += 1
microstructure=numpy.where(microstructure==microstructureID,newID,microstructure).reshape(microstructure.shape) microstructure = numpy.where(microstructure == microstructureID, newID, microstructure)
# --- assemble header ----------------------------------------------------------------------------- # --- assemble header -----------------------------------------------------------------------------
newInfo['microstructures'] = microstructure[0:info['grid'][0],0:info['grid'][1],0:info['grid'][2]].max() newInfo['microstructures'] = microstructure[0:info['grid'][0],0:info['grid'][1],0:info['grid'][2]].max()
@ -246,11 +257,11 @@ for file in files:
# --- write microstructure information ------------------------------------------------------------ # --- write microstructure information ------------------------------------------------------------
formatwidth = int(math.floor(math.log10(microstructure.max())+1)) 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(numpy.prod(info['grid']),order='F').transpose() theTable.data = microstructure[0:info['grid'][0],0:info['grid'][1],0:info['grid'][2]].reshape(numpy.prod(info['grid']),order='F').transpose() # question PE: this assumes that only the Z dimension can be 1!
theTable.data_writeArray('%%%ii'%(formatwidth),delimiter=' ') theTable.data_writeArray('%%%ii'%(formatwidth),delimiter=' ')
#--- output finalization -------------------------------------------------------------------------- #--- output finalization --------------------------------------------------------------------------
if file['name'] != 'STDIN': if file['name'] != 'STDIN':
file['input'].close() theTable.input_close()
file['output'].close() theTable.output_close()
os.rename(file['name']+'_tmp',file['name']) os.rename(file['name']+'_tmp',file['name'])