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