342 lines
15 KiB
Python
Executable File
342 lines
15 KiB
Python
Executable File
#!/usr/bin/env python
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# -*- coding: UTF-8 no BOM -*-
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import os,sys,math
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import numpy as np
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import multiprocessing
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from optparse import OptionParser
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from scipy import spatial
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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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def meshgrid2(*arrs):
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"""code inspired by http://stackoverflow.com/questions/1827489/numpy-meshgrid-in-3d"""
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arrs = tuple(reversed(arrs))
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arrs = tuple(arrs)
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lens = np.array(map(len, arrs))
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dim = len(arrs)
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ans = []
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for i, arr in enumerate(arrs):
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slc = np.ones(dim,'i')
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slc[i] = lens[i]
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arr2 = np.asarray(arr).reshape(slc)
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for j, sz in enumerate(lens):
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if j != i:
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arr2 = arr2.repeat(sz, axis=j)
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ans.insert(0,arr2)
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return tuple(ans)
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def findClosestSeed(fargs):
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point, seeds, weightssquared = fargs
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tmp = np.repeat(point.reshape(3,1), len(seeds), axis=1).T
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dist = np.sum((tmp - seeds)*(tmp - seeds),axis=1) - weightssquared
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return np.argmin(dist) # seed point closest to point
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def laguerreTessellation(undeformed, coords, weights, grains, nonperiodic = False, cpus = 2):
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copies = \
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np.array([
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[ 0, 0, 0 ],
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]).astype(float) if nonperiodic else \
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np.array([
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[ -1,-1,-1 ],
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[ 0,-1,-1 ],
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[ 1,-1,-1 ],
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[ -1, 0,-1 ],
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[ 0, 0,-1 ],
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[ 1, 0,-1 ],
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[ -1, 1,-1 ],
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[ 0, 1,-1 ],
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[ 1, 1,-1 ],
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[ -1,-1, 0 ],
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[ 0,-1, 0 ],
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[ 1,-1, 0 ],
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[ -1, 0, 0 ],
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[ 0, 0, 0 ],
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[ 1, 0, 0 ],
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[ -1, 1, 0 ],
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[ 0, 1, 0 ],
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[ 1, 1, 0 ],
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[ -1,-1, 1 ],
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[ 0,-1, 1 ],
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[ 1,-1, 1 ],
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[ -1, 0, 1 ],
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[ 0, 0, 1 ],
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[ 1, 0, 1 ],
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[ -1, 1, 1 ],
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[ 0, 1, 1 ],
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[ 1, 1, 1 ],
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]).astype(float)*info['size']
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squaredweights = np.power(np.tile(weights,len(copies)),2) # Laguerre weights (squared, size N*n)
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for i,vec in enumerate(copies): # periodic copies of seed points (size N*n)
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try: seeds = np.append(seeds, coords+vec, axis=0)
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except NameError: seeds = coords+vec
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if all(squaredweights == 0.0): # standard Voronoi (no weights, KD tree)
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myKDTree = spatial.cKDTree(seeds)
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devNull,closestSeeds = myKDTree.query(undeformed)
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else:
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damask.util.croak('...using {} cpu{}'.format(options.cpus, 's' if options.cpus > 1 else ''))
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arguments = [[arg] + [seeds,squaredweights] for arg in list(undeformed)]
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if cpus > 1: # use multithreading
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pool = multiprocessing.Pool(processes = cpus) # initialize workers
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result = pool.map_async(findClosestSeed, arguments) # evaluate function in parallel
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pool.close()
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pool.join()
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closestSeeds = np.array(result.get()).flatten()
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else:
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closestSeeds = np.zeros(len(arguments),dtype='i')
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for i,arg in enumerate(arguments):
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closestSeeds[i] = findClosestSeed(arg)
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# closestSeed is modulo number of original seed points (i.e. excluding periodic copies)
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return grains[closestSeeds%coords.shape[0]]
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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 options [file[s]]', description = """
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Generate geometry description and material configuration by standard Voronoi tessellation of given seeds file.
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""", version = scriptID)
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parser.add_option('-g', '--grid',
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dest = 'grid',
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type = 'int', nargs = 3, metavar = ' '.join(['int']*3),
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help = 'a,b,c grid of hexahedral box [auto]')
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parser.add_option('-s', '--size',
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dest = 'size',
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type = 'float', nargs = 3, metavar=' '.join(['float']*3),
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help = 'x,y,z size of hexahedral box [auto]')
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parser.add_option('-o', '--origin',
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dest = 'origin',
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type = 'float', nargs = 3, metavar=' '.join(['float']*3),
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help = 'offset from old to new origin of grid')
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parser.add_option('-p', '--position',
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dest = 'position',
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type = 'string', metavar = 'string',
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help = 'column label for seed positions [%default]')
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parser.add_option('-w', '--weight',
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dest = 'weight',
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type = 'string', metavar = 'string',
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help = 'column label for seed weights [%default]')
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parser.add_option('-m', '--microstructure',
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dest = 'microstructure',
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type = 'string', metavar = 'string',
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help = 'column label for seed microstructures [%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 = 'column label for seed Euler angles [%default]')
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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')
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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('--phase',
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dest = 'phase',
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type = 'int', metavar = 'int',
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help = 'phase index to be used [%default]')
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parser.add_option('-r', '--rnd',
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dest = 'randomSeed',
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type = 'int', metavar='int',
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help = 'seed of random number generator for second phase distribution [%default]')
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parser.add_option('--secondphase',
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dest = 'secondphase',
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type = 'float', metavar= 'float',
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help = 'volume fraction of randomly distribute second phase [%default]')
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parser.add_option('-l', '--laguerre',
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dest = 'laguerre',
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action = 'store_true',
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help = 'use Laguerre (weighted Voronoi) tessellation')
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parser.add_option('--cpus',
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dest = 'cpus',
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type = 'int', metavar = 'int',
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help = 'number of parallel processes to use for Laguerre tessellation [%default]')
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parser.add_option('--nonperiodic',
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dest = 'nonperiodic',
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action = 'store_true',
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help = 'use nonperiodic tessellation')
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parser.set_defaults(position = 'pos',
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weight = 'weight',
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microstructure = 'microstructure',
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eulers = 'eulerangles',
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homogenization = 1,
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crystallite = 1,
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phase = 1,
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secondphase = 0.0,
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cpus = 2,
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laguerre = False,
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nonperiodic = False,
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randomSeed = None,
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)
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(options,filenames) = parser.parse_args()
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if options.secondphase > 1.0 or options.secondphase < 0.0:
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parser.error('volume fraction of second phase ({}) out of bounds.'.format(options.secondphase))
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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 header ----------------------------------------------------------------------------
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table.head_read()
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info,extra_header = table.head_getGeom()
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if options.grid is not None: info['grid'] = options.grid
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if options.size is not None: info['size'] = options.size
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if options.origin is not None: info['origin'] = options.origin
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# ------------------------------------------ sanity checks ---------------------------------------
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remarks = []
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errors = []
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labels = []
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hasGrains = table.label_dimension(options.microstructure) == 1
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hasEulers = table.label_dimension(options.eulers) == 3
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hasWeights = table.label_dimension(options.weight) == 1 and options.laguerre
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if np.any(info['grid'] < 1): errors.append('invalid grid a b c.')
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if np.any(info['size'] <= 0.0) \
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and np.all(info['grid'] < 1): errors.append('invalid size x y z.')
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else:
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for i in xrange(3):
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if info['size'][i] <= 0.0: # any invalid size?
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info['size'][i] = float(info['grid'][i])/max(info['grid']) # normalize to grid
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remarks.append('rescaling size {} to {}...'.format({0:'x',1:'y',2:'z'}[i],info['size'][i]))
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if table.label_dimension(options.position) != 3:
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errors.append('position columns "{}" have dimension {}.'.format(options.position,
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table.label_dimension(options.position)))
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else:
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labels += [options.position]
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if not hasEulers: remarks.append('missing seed orientations...')
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else: labels += [options.eulers]
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if not hasGrains: remarks.append('missing seed microstructure indices...')
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else: labels += [options.microstructure]
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if options.laguerre and not hasWeights: remarks.append('missing seed weights...')
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else: labels += [options.weight]
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if remarks != []: damask.util.croak(remarks)
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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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# ------------------------------------------ read seeds ---------------------------------------
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table.data_readArray(labels)
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coords = table.data[:,table.label_index(options.position):table.label_index(options.position)+3]\
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* info['size']
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eulers = table.data[:,table.label_index(options.eulers ):table.label_index(options.eulers )+3]\
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if hasEulers else np.zeros(3*len(coords))
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grains = table.data[:,table.label_index(options.microstructure)].astype('i')\
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if hasGrains else 1+np.arange(len(coords))
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weights = table.data[:,table.label_index(options.weight)]\
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if hasWeights else np.zeros(len(coords))
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grainIDs = np.unique(grains).astype('i')
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NgrainIDs = len(grainIDs)
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# --- tessellate microstructure ------------------------------------------------------------
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x = (np.arange(info['grid'][0])+0.5)*info['size'][0]/info['grid'][0]
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y = (np.arange(info['grid'][1])+0.5)*info['size'][1]/info['grid'][1]
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z = (np.arange(info['grid'][2])+0.5)*info['size'][2]/info['grid'][2]
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damask.util.croak('tessellating...')
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grid = np.vstack(meshgrid2(x, y, z)).reshape(3,-1).T
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indices = laguerreTessellation(grid, coords, weights, grains, options.nonperiodic, options.cpus)
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# --- write header ------------------------------------------------------------------------
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usedGrainIDs = np.intersect1d(grainIDs,indices)
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info['microstructures'] = len(usedGrainIDs)
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if info['homogenization'] == 0: info['homogenization'] = options.homogenization
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damask.util.croak(['grid a b c: %s'%(' x '.join(map(str,info['grid']))),
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'size x y z: %s'%(' x '.join(map(str,info['size']))),
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'origin x y z: %s'%(' : '.join(map(str,info['origin']))),
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'homogenization: %i'%info['homogenization'],
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'microstructures: %i%s'%(info['microstructures'],
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(' out of %i'%NgrainIDs if NgrainIDs != info['microstructures'] else '')),
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])
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config_header = []
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formatwidth = 1+int(math.log10(NgrainIDs))
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phase = options.phase * np.ones(NgrainIDs,'i')
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if int(options.secondphase*info['microstructures']) > 0:
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phase[0:int(options.secondphase*info['microstructures'])] += 1 # alter fraction 'options.secondphase' of used grainIDs
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randomSeed = options.randomSeed if options.randomSeed \
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else int(os.urandom(4).encode('hex'), 16) # random seed for second phase
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np.random.seed(randomSeed)
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np.random.shuffle(phase)
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config_header += ['# random seed (phase shuffling): {}'.format(randomSeed)]
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config_header += ['<microstructure>']
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for i,ID in enumerate(grainIDs):
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config_header += ['[Grain%s]'%(str(ID).zfill(formatwidth)),
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'crystallite %i'%options.crystallite,
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'(constituent)\tphase %i\ttexture %s\tfraction 1.0'%(phase[i],str(ID).rjust(formatwidth)),
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]
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if hasEulers:
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config_header += ['<texture>']
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for ID in grainIDs:
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eulerID = np.nonzero(grains == ID)[0][0] # find first occurrence of this grain id
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config_header += ['[Grain%s]'%(str(ID).zfill(formatwidth)),
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'(gauss)\tphi1 %g\tPhi %g\tphi2 %g\tscatter 0.0\tfraction 1.0'%tuple(eulers[eulerID])
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]
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if options.axes is not None: config_header.append('axes\t%s %s %s'%tuple(options.axes))
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table.labels_clear()
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table.info_clear()
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table.info_append([
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scriptID + ' ' + ' '.join(sys.argv[1:]),
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"grid\ta {grid[0]}\tb {grid[1]}\tc {grid[2]}".format(grid=info['grid']),
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"size\tx {size[0]}\ty {size[1]}\tz {size[2]}".format(size=info['size']),
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"origin\tx {origin[0]}\ty {origin[1]}\tz {origin[2]}".format(origin=info['origin']),
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"homogenization\t{homog}".format(homog=info['homogenization']),
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"microstructures\t{microstructures}".format(microstructures=info['microstructures']),
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config_header,
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])
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table.head_write()
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# --- write microstructure information ------------------------------------------------------------
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table.data = indices.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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