initial simplification.
Should be able to generate from table containing either <microstructure> or <texture> and <phase>
This commit is contained in:
parent
b3455c825e
commit
fff377de7f
|
@ -32,34 +32,6 @@ parser.add_option('--microstructure',
|
|||
dest = 'microstructure',
|
||||
type = 'string', metavar = 'string',
|
||||
help = 'microstructure label')
|
||||
parser.add_option('-t', '--tolerance',
|
||||
dest = 'tolerance',
|
||||
type = 'float', metavar = 'float',
|
||||
help = 'angular tolerance for orientation squashing [%default]')
|
||||
parser.add_option('-e', '--eulers',
|
||||
dest = 'eulers',
|
||||
type = 'string', metavar = 'string',
|
||||
help = 'Euler angles label')
|
||||
parser.add_option('-d', '--degrees',
|
||||
dest = 'degrees',
|
||||
action = 'store_true',
|
||||
help = 'all angles are in degrees')
|
||||
parser.add_option('-m', '--matrix',
|
||||
dest = 'matrix',
|
||||
type = 'string', metavar = 'string',
|
||||
help = 'orientation matrix label')
|
||||
parser.add_option('-a',
|
||||
dest='a',
|
||||
type = 'string', metavar = 'string',
|
||||
help = 'crystal frame a vector label')
|
||||
parser.add_option('-b',
|
||||
dest='b',
|
||||
type = 'string', metavar = 'string',
|
||||
help = 'crystal frame b vector label')
|
||||
parser.add_option('-c',
|
||||
dest = 'c',
|
||||
type = 'string', metavar='string',
|
||||
help = 'crystal frame c vector label')
|
||||
parser.add_option('-q', '--quaternion',
|
||||
dest = 'quaternion',
|
||||
type = 'string', metavar='string',
|
||||
|
@ -68,10 +40,7 @@ parser.add_option('--axes',
|
|||
dest = 'axes',
|
||||
type = 'string', nargs = 3, metavar = ' '.join(['string']*3),
|
||||
help = 'orientation coordinate frame in terms of position coordinate frame [same]')
|
||||
parser.add_option('-s', '--symmetry',
|
||||
dest = 'symmetry',
|
||||
action = 'extend', metavar = '<string LIST>',
|
||||
help = 'crystal symmetry of each phase %default {{{}}} '.format(', '.join(damask.Symmetry.lattices[1:])))
|
||||
|
||||
parser.add_option('--homogenization',
|
||||
dest = 'homogenization',
|
||||
type = 'int', metavar = 'int',
|
||||
|
@ -80,9 +49,7 @@ parser.add_option('--crystallite',
|
|||
dest = 'crystallite',
|
||||
type = 'int', metavar = 'int',
|
||||
help = 'crystallite index to be used [%default]')
|
||||
parser.add_option('--verbose',
|
||||
dest = 'verbose', action = 'store_true',
|
||||
help = 'output extra info')
|
||||
|
||||
|
||||
parser.set_defaults(symmetry = [damask.Symmetry.lattices[-1]],
|
||||
tolerance = 0.0,
|
||||
|
@ -95,12 +62,7 @@ parser.set_defaults(symmetry = [damask.Symmetry.lattices[-1]],
|
|||
|
||||
(options,filenames) = parser.parse_args()
|
||||
|
||||
input = [options.eulers is not None,
|
||||
options.a is not None and \
|
||||
options.b is not None and \
|
||||
options.c is not None,
|
||||
options.matrix is not None,
|
||||
options.quaternion is not None,
|
||||
input = [ options.quaternion is not None,
|
||||
options.microstructure is not None,
|
||||
]
|
||||
|
||||
|
@ -109,14 +71,9 @@ if np.sum(input) != 1:
|
|||
if options.axes is not None and not set(options.axes).issubset(set(['x','+x','-x','y','+y','-y','z','+z','-z'])):
|
||||
parser.error('invalid axes {} {} {}.'.format(*options.axes))
|
||||
|
||||
(label,dim,inputtype) = [(options.eulers,3,'eulers'),
|
||||
([options.a,options.b,options.c],[3,3,3],'frame'),
|
||||
(options.matrix,9,'matrix'),
|
||||
(options.quaternion,4,'quaternion'),
|
||||
(label,dim,inputtype) = [(options.quaternion,4,'quaternion'),
|
||||
(options.microstructure,1,'microstructure'),
|
||||
][np.where(input)[0][0]] # select input label that was requested
|
||||
toRadians = math.pi/180.0 if options.degrees else 1.0 # rescale all angles to radians
|
||||
threshold = np.cos(options.tolerance/2.*toRadians) # cosine of (half of) tolerance angle
|
||||
|
||||
# --- loop over input files -------------------------------------------------------------------------
|
||||
|
||||
|
@ -157,10 +114,8 @@ for name in filenames:
|
|||
|
||||
if coordDim == 2:
|
||||
table.data = np.insert(table.data,2,np.zeros(len(table.data)),axis=1) # add zero z coordinate for two-dimensional input
|
||||
if options.verbose: damask.util.croak('extending to 3D...')
|
||||
if options.phase is None:
|
||||
table.data = np.column_stack((table.data,np.ones(len(table.data)))) # add single phase if no phase column given
|
||||
if options.verbose: damask.util.croak('adding dummy phase info...')
|
||||
|
||||
# --------------- figure out size and grid ---------------------------------------------------------
|
||||
|
||||
|
@ -196,17 +151,10 @@ for name in filenames:
|
|||
grain = table.data[:,colOri]
|
||||
nGrains = len(np.unique(grain))
|
||||
|
||||
else:
|
||||
|
||||
if options.verbose: bg = damask.util.backgroundMessage(); bg.start() # start background messaging
|
||||
elif inputtype == 'quaternion':
|
||||
|
||||
colPhase = -1 # column of phase data comes last
|
||||
if options.verbose: bg.set_message('sorting positions...')
|
||||
index = np.lexsort((table.data[:,0],table.data[:,1],table.data[:,2])) # index of position when sorting x fast, z slow
|
||||
if options.verbose: bg.set_message('building KD tree...')
|
||||
KDTree = scipy.spatial.KDTree((table.data[index,:3]-mincorner) / delta) # build KDTree with dX = dY = dZ = 1 and origin 0,0,0
|
||||
|
||||
statistics = {'global': 0, 'local': 0}
|
||||
grain = -np.ones(N,dtype = 'int32') # initialize empty microstructure
|
||||
orientations = [] # orientations
|
||||
multiplicity = [] # orientation multiplicity (number of group members)
|
||||
|
@ -215,87 +163,26 @@ for name in filenames:
|
|||
existingGrains = np.arange(nGrains)
|
||||
myPos = 0 # position (in list) of current grid point
|
||||
|
||||
tick = time.clock()
|
||||
if options.verbose: bg.set_message('assigning grain IDs...')
|
||||
|
||||
for z in range(grid[2]):
|
||||
for y in range(grid[1]):
|
||||
for x in range(grid[0]):
|
||||
if (myPos+1)%(N/500.) < 1:
|
||||
time_delta = (time.clock()-tick) * (N - myPos) / myPos
|
||||
if options.verbose: bg.set_message('(%02i:%02i:%02i) processing point %i of %i (grain count %i)...'
|
||||
%(time_delta//3600,time_delta%3600//60,time_delta%60,myPos,N,nGrains))
|
||||
|
||||
|
||||
myData = table.data[index[myPos]] # read data for current grid point
|
||||
myPhase = int(myData[colPhase])
|
||||
mySym = options.symmetry[min(myPhase,len(options.symmetry))-1] # take last specified option for all with higher index
|
||||
|
||||
if inputtype == 'eulers':
|
||||
o = damask.Orientation(Eulers = myData[colOri:colOri+3]*toRadians,
|
||||
symmetry = mySym)
|
||||
elif inputtype == 'matrix':
|
||||
o = damask.Orientation(matrix = myData[colOri:colOri+9].reshape(3,3),
|
||||
symmetry = mySym)
|
||||
elif inputtype == 'frame':
|
||||
o = damask.Orientation(matrix = np.hstack((myData[colOri[0]:colOri[0]+3],
|
||||
myData[colOri[1]:colOri[1]+3],
|
||||
myData[colOri[2]:colOri[2]+3],
|
||||
)).reshape(3,3),
|
||||
symmetry = mySym)
|
||||
elif inputtype == 'quaternion':
|
||||
o = damask.Orientation(quaternion = myData[colOri:colOri+4],
|
||||
symmetry = mySym)
|
||||
|
||||
o = damask.Rotation(myData[colOri:colOri+4])
|
||||
|
||||
cos_disorientations = -np.ones(1,dtype=float) # largest possible disorientation
|
||||
closest_grain = -1 # invalid neighbor
|
||||
|
||||
if options.tolerance > 0.0: # only try to compress orientations if asked to
|
||||
neighbors = np.array(KDTree.query_ball_point([x,y,z], 3)) # point indices within radius
|
||||
# filter neighbors: skip myself, anyone further ahead (cannot yet have a grain ID), and other phases
|
||||
neighbors = neighbors[(neighbors < myPos) & \
|
||||
(table.data[index[neighbors],colPhase] == myPhase)]
|
||||
grains = np.unique(grain[neighbors]) # unique grain IDs among valid neighbors
|
||||
|
||||
if len(grains) > 0: # check immediate neighborhood first
|
||||
cos_disorientations = np.array([o.disorientation(orientations[grainID],
|
||||
SST = False)[0].quaternion.q \
|
||||
for grainID in grains]) # store disorientation per grainID
|
||||
closest_grain = np.argmax(cos_disorientations) # grain among grains with closest orientation to myself
|
||||
match = 'local'
|
||||
|
||||
if cos_disorientations[closest_grain] < threshold: # orientation not close enough?
|
||||
grains = existingGrains[np.atleast_1d( (np.array(phases) == myPhase ) & \
|
||||
(np.in1d(existingGrains,grains,invert=True)))] # other already identified grains (of my phase)
|
||||
|
||||
if len(grains) > 0:
|
||||
cos_disorientations = np.array([o.disorientation(orientations[grainID],
|
||||
SST = False)[0].quaternion.q \
|
||||
for grainID in grains]) # store disorientation per grainID
|
||||
closest_grain = np.argmax(cos_disorientations) # grain among grains with closest orientation to myself
|
||||
match = 'global'
|
||||
|
||||
if cos_disorientations[closest_grain] >= threshold: # orientation now close enough?
|
||||
grainID = grains[closest_grain]
|
||||
grain[myPos] = grainID # assign myself to that grain ...
|
||||
orientations[grainID] = damask.Orientation.average([orientations[grainID],o],
|
||||
[multiplicity[grainID],1]) # update average orientation of best matching grain
|
||||
multiplicity[grainID] += 1
|
||||
statistics[match] += 1
|
||||
else:
|
||||
grain[myPos] = nGrains # assign new grain to me ...
|
||||
nGrains += 1 # ... and update counter
|
||||
orientations.append(o) # store new orientation for future comparison
|
||||
multiplicity.append(1) # having single occurrence so far
|
||||
phases.append(myPhase) # store phase info for future reporting
|
||||
existingGrains = np.arange(nGrains) # update list of existing grains
|
||||
grain[myPos] = nGrains # assign new grain to me ...
|
||||
nGrains += 1 # ... and update counter
|
||||
orientations.append(o) # store new orientation for future comparison
|
||||
multiplicity.append(1) # having single occurrence so far
|
||||
phases.append(myPhase) # store phase info for future reporting
|
||||
existingGrains = np.arange(nGrains) # update list of existing grains
|
||||
|
||||
myPos += 1
|
||||
|
||||
if options.verbose:
|
||||
bg.stop()
|
||||
bg.join()
|
||||
damask.util.croak("{} seconds total.\n{} local and {} global matches.".\
|
||||
format(time.clock()-tick,statistics['local'],statistics['global']))
|
||||
|
||||
grain += 1 # offset from starting index 0 to 1
|
||||
|
||||
|
|
Loading…
Reference in New Issue