355 lines
19 KiB
Python
Executable File
355 lines
19 KiB
Python
Executable File
#!/usr/bin/env python2.7
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# -*- coding: UTF-8 no BOM -*-
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import os,sys,math,types,time
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import scipy.spatial, numpy as np
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from optparse import OptionParser
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import damask
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scriptName = os.path.splitext(os.path.basename(__file__))[0]
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scriptID = ' '.join([scriptName,damask.version])
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# --------------------------------------------------------------------
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# MAIN
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# --------------------------------------------------------------------
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parser = OptionParser(option_class=damask.extendableOption, usage='%prog option(s) [ASCIItable(s)]', description = """
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Generate geometry description and material configuration from position, phase, and orientation (or microstructure) data.
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""", version = scriptID)
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parser.add_option('--coordinates',
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dest = 'pos',
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type = 'string', metavar = 'string',
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help = 'coordinates label (%default)')
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parser.add_option('--phase',
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dest = 'phase',
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type = 'string', metavar = 'string',
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help = 'phase label')
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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 = 'angles are given in degrees [%default]')
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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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help = 'quaternion label')
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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 %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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help = 'homogenization index to be used [%default]')
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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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degrees = False,
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homogenization = 1,
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crystallite = 1,
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verbose = False,
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pos = 'pos',
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)
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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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options.microstructure is not None,
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]
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if np.sum(input) != 1:
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parser.error('need either microstructure label or exactly one orientation input format.')
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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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(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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if filenames == []: filenames = [None]
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for name in filenames:
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try:
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table = damask.ASCIItable(name = name,
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outname = os.path.splitext(name)[-2]+'.geom' if name else name,
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buffered = False)
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except: continue
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damask.util.report(scriptName,name)
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# ------------------------------------------ read head ---------------------------------------
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table.head_read() # read ASCII header info
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# ------------------------------------------ sanity checks ---------------------------------------
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coordDim = table.label_dimension(options.pos)
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errors = []
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if not 3 >= coordDim >= 2:
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errors.append('coordinates "{}" need to have two or three dimensions.'.format(options.pos))
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if not np.all(table.label_dimension(label) == dim):
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errors.append('input "{}" needs to have dimension {}.'.format(label,dim))
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if options.phase and table.label_dimension(options.phase) != 1:
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errors.append('phase column "{}" is not scalar.'.format(options.phase))
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if errors != []:
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damask.util.croak(errors)
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table.close(dismiss = True)
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continue
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table.data_readArray([options.pos] \
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+ ([label] if isinstance(label, types.StringTypes) else label) \
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+ ([options.phase] if options.phase else []))
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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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coords = [np.unique(table.data[:,i]) for i in range(3)]
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mincorner = np.array(map(min,coords))
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maxcorner = np.array(map(max,coords))
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grid = np.array(map(len,coords),'i')
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size = grid/np.maximum(np.ones(3,'d'), grid-1.0) * (maxcorner-mincorner) # size from edge to edge = dim * n/(n-1)
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size = np.where(grid > 1, size, min(size[grid > 1]/grid[grid > 1])) # spacing for grid==1 set to smallest among other spacings
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delta = size/np.maximum(np.ones(3,'d'), grid)
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origin = mincorner - 0.5*delta # shift from cell center to corner
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N = grid.prod()
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if N != len(table.data):
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errors.append('data count {} does not match grid {}.'.format(len(table.data),' x '.join(map(repr,grid))))
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if np.any(np.abs(np.log10((coords[0][1:]-coords[0][:-1])/delta[0])) > 0.01) \
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or np.any(np.abs(np.log10((coords[1][1:]-coords[1][:-1])/delta[1])) > 0.01) \
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or np.any(np.abs(np.log10((coords[2][1:]-coords[2][:-1])/delta[2])) > 0.01):
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errors.append('regular grid spacing {} violated.'.format(' x '.join(map(repr,delta))))
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if errors != []:
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damask.util.croak(errors)
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table.close(dismiss = True)
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continue
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# ------------------------------------------ process data ------------------------------------------
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colOri = table.label_index(label)+(3-coordDim) # column(s) of orientation data followed by 3 coordinates
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if inputtype == 'microstructure':
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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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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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phases = [] # phase info
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nGrains = 0 # counter for detected grains
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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).transpose(),
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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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cos_disorientations = -np.ones(1,dtype='f') # 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.w \
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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.w \
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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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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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# --- generate header ----------------------------------------------------------------------------
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info = {
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'grid': grid,
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'size': size,
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'origin': origin,
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'microstructures': nGrains,
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'homogenization': options.homogenization,
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}
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damask.util.croak(['grid a b c: {}'.format(' x '.join(map(str,info['grid']))),
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'size x y z: {}'.format(' x '.join(map(str,info['size']))),
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'origin x y z: {}'.format(' : '.join(map(str,info['origin']))),
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'homogenization: {}'.format(info['homogenization']),
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'microstructures: {}'.format(info['microstructures']),
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])
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# --- write header ---------------------------------------------------------------------------------
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formatwidth = 1+int(math.log10(info['microstructures']))
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if inputtype == 'microstructure':
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config_header = []
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else:
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config_header = ['<microstructure>']
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for i,phase in enumerate(phases):
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config_header += ['[Grain%s]'%(str(i+1).zfill(formatwidth)),
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'crystallite %i'%options.crystallite,
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'(constituent)\tphase %i\ttexture %s\tfraction 1.0'%(phase,str(i+1).rjust(formatwidth)),
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]
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config_header += ['<texture>']
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for i,orientation in enumerate(orientations):
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config_header += ['[Grain%s]'%(str(i+1).zfill(formatwidth)),
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'axes\t%s %s %s'%tuple(options.axes) if options.axes is not None else '',
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'(gauss)\tphi1 %g\tPhi %g\tphi2 %g\tscatter 0.0\tfraction 1.0'%tuple(orientation.asEulers(degrees = True)),
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]
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table.labels_clear()
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table.info_clear()
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table.info_append([scriptID + ' ' + ' '.join(sys.argv[1:])])
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table.head_putGeom(info)
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table.info_append(config_header)
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table.head_write()
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# --- write microstructure information ------------------------------------------------------------
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table.data = grain.reshape(info['grid'][1]*info['grid'][2],info['grid'][0])
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table.data_writeArray('%%%ii'%(formatwidth),delimiter=' ')
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#--- output finalization --------------------------------------------------------------------------
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table.close()
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