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DAMASK_EICMD
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using class 

still a very complex script
This commit is contained in:
Martin Diehl 2019-05-26 22:49:05 +02:00
parent 0da39b0c69
commit c8dfba89e5
2 changed files with 76 additions and 102 deletions
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176
processing/pre/geom_fromVoronoiTessellation.py
View File

@ -1,11 +1,14 @@
#!/usr/bin/env python3
# -*- coding: UTF-8 no BOM -*-
import os,sys,math
import numpy as np
import os
import sys
import multiprocessing
from io import StringIO
from optparse import OptionParser,OptionGroup
from scipy import spatial
import numpy as np
from scipy import spatial
import damask
scriptName = os.path.splitext(os.path.basename(__file__))[0]
@ -29,74 +32,74 @@ def meshgrid2(*arrs):
ans.insert(0,arr2)
return tuple(ans)
def findClosestSeed(fargs):
def laguerreTessellation(undeformed, coords, weights, grains, periodic = True, cpus = 2):
def findClosestSeed(fargs):
point, seeds, myWeights = fargs
tmp = np.repeat(point.reshape(3,1), len(seeds), axis=1).T
dist = np.sum((tmp - seeds)**2,axis=1) -myWeights
return np.argmin(dist) # seed point closest to point
copies = \
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'] if periodic else \
np.array([
[ 0, 0, 0 ],
]).astype(float)
repeatweights = np.tile(weights,len(copies)).flatten(order='F') # Laguerre weights (1,2,3,1,2,3,...,1,2,3)
for i,vec in enumerate(copies): # periodic copies of seed points ...
try: seeds = np.append(seeds, coords+vec, axis=0) # ... (1+a,2+a,3+a,...,1+z,2+z,3+z)
except NameError: seeds = coords+vec
def laguerreTessellation(undeformed, coords, weights, grains, periodic = True, cpus = 2):
if (repeatweights == 0.0).all(): # 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,repeatweights] for arg in list(undeformed)]
copies = \
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'] if periodic else \
np.array([
[ 0, 0, 0 ],
]).astype(float)
repeatweights = np.tile(weights,len(copies)).flatten(order='F') # Laguerre weights (1,2,3,1,2,3,...,1,2,3)
for i,vec in enumerate(copies): # periodic copies of seed points ...
try: seeds = np.append(seeds, coords+vec, axis=0) # ... (1+a,2+a,3+a,...,1+z,2+z,3+z)
except NameError: seeds = coords+vec
if (repeatweights == 0.0).all(): # standard Voronoi (no weights, KD tree)
myKDTree = spatial.cKDTree(seeds)
devNull,closestSeeds = myKDTree.query(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:
damask.util.croak('...using {} cpu{}'.format(options.cpus, 's' if options.cpus > 1 else ''))
arguments = [[arg,seeds,repeatweights] 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)
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]]
return grains[closestSeeds%coords.shape[0]]
# --------------------------------------------------------------------
# MAIN
@ -220,10 +223,7 @@ parser.set_defaults(pos = 'pos',
if filenames == []: filenames = [None]
for name in filenames:
try: table = damask.ASCIItable(name = name,
outname = os.path.splitext(name)[0]+'.geom' if name else name,
buffered = False)
except: continue
table = damask.ASCIItable(name = name, readonly = True)
damask.util.report(scriptName,name)
# --- read header ----------------------------------------------------------------------------
@ -281,7 +281,7 @@ for name in filenames:
else table.data[:,table.label_indexrange(options.pos)] - info['origin']
eulers = table.data[:,table.label_indexrange(options.eulers)] if hasEulers \
else np.zeros(3*len(coords))
grains = table.data[:,table.label_indexrange(options.microstructure)].astype('i') if hasGrains \
grains = table.data[:,table.label_indexrange(options.microstructure)].astype(int) if hasGrains \
else 1+np.arange(len(coords))
weights = table.data[:,table.label_indexrange(options.weight)] if hasWeights \
else np.zeros(len(coords))
@ -299,20 +299,8 @@ for name in filenames:
grid = np.vstack(meshgrid2(x, y, z)).reshape(3,-1).T
indices = laguerreTessellation(grid, coords, weights, grains, options.periodic, options.cpus)
# --- write header ------------------------------------------------------------------------
usedGrainIDs = np.intersect1d(grainIDs,indices)
info['microstructures'] = len(usedGrainIDs)
if info['homogenization'] == 0: info['homogenization'] = options.homogenization
damask.util.report_geom(info,['grid','size','origin','homogenization',])
damask.util.croak(['microstructures: {}{}'.format(info['microstructures'],
(' out of {}'.format(NgrainIDs) if NgrainIDs != info['microstructures'] else '')),
])
config_header = []
formatwidth = 1+int(math.log10(NgrainIDs))
formatwidth = 1+int(np.log10(NgrainIDs))
if options.config:
config_header += ['<microstructure>']
@ -331,24 +319,10 @@ for name in filenames:
] + theAxes
config_header += ['<!skip>']
table.labels_clear()
table.info_clear()
table.info_append([
scriptID + ' ' + ' '.join(sys.argv[1:]),
"grid\ta {}\tb {}\tc {}".format(*info['grid']),
"size\tx {}\ty {}\tz {}".format(*info['size']),
"origin\tx {}\ty {}\tz {}".format(*info['origin']),
"homogenization\t{}".format(info['homogenization']),
"microstructures\t{}".format(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()
geom = damask.Geom(indices.reshape(info['grid'],order='F'),info['size'],options.homogenization,comments=config_header)
damask.util.croak(geom)
if name is None:
sys.stdout.write(str(geom.show()))
else:
geom.to_file(os.path.splitext(name)[0]+'.geom')

2
python/damask/geom.py
View File

@ -12,7 +12,7 @@ class Geom():
if len(microstructure.shape) != 3:
raise ValueError('Invalid microstructure shape {}'.format(*microstructure.shape))
elif microstructure.dtype not in ['int','float']:
elif microstructure.dtype not in [int,float]:
raise TypeError('Invalid data type {} for microstructure'.format(microstructure.dtype))
else:
self.microstructure = microstructure