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