343 lines
14 KiB
Python
Executable File
343 lines
14 KiB
Python
Executable File
#!/usr/bin/env python2
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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,OptionGroup
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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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repeatweights = np.repeat(weights,len(copies),axis=1).flatten(order='F') # Laguerre weights (1,2,3,1,2,3,...,1,2,3)
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for i,vec in enumerate(copies): # periodic copies of seed points ...
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try: seeds = np.append(seeds, coords+vec, axis=0) # ... (1+a,2+a,3+a,...,1+z,2+z,3+z)
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except NameError: seeds = coords+vec
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if (repeatweights == 0.0).all(): # 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,repeatweights] 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 option(s) [seedfile(s)]', description = """
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Generate geometry description and material configuration by tessellation of given seeds file.
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""", version = scriptID)
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group = OptionGroup(parser, "Tessellation","")
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group.add_option('-l',
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'--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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group.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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group.add_option('--nonperiodic',
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dest = 'nonperiodic',
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action = 'store_true',
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help = 'nonperiodic tessellation')
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parser.add_option_group(group)
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group = OptionGroup(parser, "Geometry","")
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group.add_option('-g',
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'--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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group.add_option('-s',
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'--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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group.add_option('-o',
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'--origin',
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dest = 'origin',
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type = 'float', nargs = 3, metavar=' '.join(['float']*3),
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help = 'origin of grid')
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parser.add_option_group(group)
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group = OptionGroup(parser, "Seeds","")
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group.add_option('-p',
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'--pos', '--seedposition',
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dest = 'pos',
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type = 'string', metavar = 'string',
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help = 'label of coordinates [%default]')
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group.add_option('-w',
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'--weight',
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dest = 'weight',
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type = 'string', metavar = 'string',
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help = 'label of weights [%default]')
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group.add_option('-m',
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'--microstructure',
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dest = 'microstructure',
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type = 'string', metavar = 'string',
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help = 'label of microstructures [%default]')
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group.add_option('-e',
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'--eulers',
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dest = 'eulers',
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type = 'string', metavar = 'string',
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help = 'label of Euler angles [%default]')
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group.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_group(group)
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group = OptionGroup(parser, "Configuration","")
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group.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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group.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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group.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_group(group)
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parser.set_defaults(pos = 'pos',
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weight = 'weight',
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microstructure = 'microstructure',
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eulers = 'euler',
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homogenization = 1,
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crystallite = 1,
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phase = 1,
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cpus = 2,
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laguerre = False,
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nonperiodic = False,
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)
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(options,filenames) = parser.parse_args()
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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: table = damask.ASCIItable(name = name,
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outname = os.path.splitext(name)[0]+'.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.pos) != 3:
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errors.append('seed positions "{}" have dimension {}.'.format(options.pos,
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table.label_dimension(options.pos)))
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else:
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labels += [options.pos]
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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_indexrange(options.pos)] * info['size']
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eulers = table.data[:,table.label_indexrange(options.eulers)] if hasEulers \
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else np.zeros(3*len(coords))
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grains = table.data[:,table.label_indexrange(options.microstructure)].astype('i') if hasGrains \
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else 1+np.arange(len(coords))
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weights = table.data[:,table.label_indexrange(options.weight)] if hasWeights \
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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.report_geom(info,['grid','size','origin','homogenization',])
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damask.util.croak(['microstructures: {}{}'.format(info['microstructures'],
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(' out of {}'.format(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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config_header += ['<microstructure>']
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for i,ID in enumerate(grainIDs):
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config_header += ['[Grain{}]'.format(str(ID).zfill(formatwidth)),
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'crystallite {}'.format(options.crystallite),
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'(constituent)\tphase {}\ttexture {}\tfraction 1.0'.format(options.phase,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{}]'.format(str(ID).zfill(formatwidth)),
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'(gauss)\tphi1 {:g}\tPhi {:g}\tphi2 {:g}\tscatter 0.0\tfraction 1.0'.format(*eulers[eulerID])
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]
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if options.axes is not None: config_header.append('axes\t{} {} {}'.format(*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 {}\tb {}\tc {}".format(*info['grid']),
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"size\tx {}\ty {}\tz {}".format(*info['size']),
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"origin\tx {}\ty {}\tz {}".format(*info['origin']),
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"homogenization\t{}".format(info['homogenization']),
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"microstructures\t{}".format(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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