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DAMASK_EICMD
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adoption of recent API change in ASCIItable.

This commit is contained in:
Philip Eisenlohr 2015-08-12 17:47:38 +00:00
parent 3097c87bea
commit 5dad5df588
1 changed files with 27 additions and 20 deletions
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47
processing/pre/seeds_fromRandom.py
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@ -57,7 +57,11 @@ group = OptionGroup(parser, "Laguerre Tessellation Options",
group.add_option('-w', '--weights',
action = 'store_true',
dest = 'weights',
help = 'assign random weigts (normal distribution) to seed points for Laguerre tessellation [%default]')
help = 'assign random weigts to seed points for Laguerre tessellation [%default]')
group.add_option('--max',
dest = 'max',
type = 'float', metavar = 'float',
help = 'max of uniform distribution for weights [%default]')
group.add_option('--mean',
dest = 'mean',
type = 'float', metavar = 'float',
@ -93,8 +97,9 @@ parser.set_defaults(randomSeed = None,
grid = (16,16,16),
N = 20,
weights = False,
mean = 0.0,
sigma = 0.1,
max = 0.0,
mean = 0.2,
sigma = 0.05,
microstructure = 1,
selective = False,
force = False,
@ -114,13 +119,15 @@ random.seed(options.randomSeed)
# --- loop over output files -------------------------------------------------------------------------
if filenames == []: filenames = ['STDIN']
if filenames == []: filenames = [None]
for name in filenames:
table = damask.ASCIItable(name = name, outname = None,
buffered = False, writeonly = True)
table.croak('\033[1m'+scriptName+'\033[0m'+(': '+name if name != 'STDIN' else ''))
try:
table = damask.ASCIItable(outname = name,
buffered = False)
except:
continue
table.croak('\033[1m'+scriptName+'\033[0m'+(': '+name if name else ''))
# --- sanity checks -------------------------------------------------------------------------
@ -172,21 +179,21 @@ for name in filenames:
if i%(options.N/100.) < 1: table.croak('.',False)
table.croak('')
seeds = np.transpose(seeds) # prepare shape for stacking
seeds = seeds.T # prepare shape for stacking
if options.weights:
seeds = np.transpose(np.vstack((seeds,
grainEuler,
np.arange(options.microstructure,
options.microstructure + options.N),
np.random.normal(loc=options.mean, scale=options.sigma, size=options.N),
)))
if options.max > 0.0:
weights = [np.random.uniform(low = 0, high = options.max, size = options.N)]
else:
weights = [np.random.normal(loc = options.mean, scale = options.sigma, size = options.N)]
else:
seeds = np.transpose(np.vstack((seeds,
grainEuler,
np.arange(options.microstructure,
options.microstructure + options.N),
)))
weights = []
seeds = np.transpose(np.vstack(tuple([seeds,
grainEuler,
np.arange(options.microstructure,
options.microstructure + options.N),
] + weights
)))
# ------------------------------------------ assemble header ---------------------------------------