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DAMASK_EICMD
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fixed bug in asciitable when updating labels for readArray, fixed checking for euler angels presence in tessellation, improved help

This commit is contained in:
Martin Diehl 2015-05-14 17:07:50 +00:00
parent 7ea350b90e
commit fa1368204d
4 changed files with 63 additions and 77 deletions
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14
lib/damask/asciitable.py
View File

@ -258,12 +258,14 @@ class ASCIItable():
read whole data of all (given) labels as numpy array
'''
if labels == []: indices = range(self.__IO__['validReadSize']) # use all columns
else:
indices = self.labels_index(labels) # use specified columns
dictionary = dict(zip(indices, labels))
self.labels_index = range(len(dictionary))
self.labels = [dictionary[label] for label in sorted(dictionary)]
if labels != []: # read only some labels
indices = self.labels_index(labels) # get indices to read
tempDict = dict(zip(indices, labels)) # column <> label connections
self.labels = [tempDict[label] for label in sorted(tempDict)] # sort labels to reflect order from np.readtxt
self.__IO__['validReadSize'] = len(labels)
else:
indices = range(self.__IO__['validReadSize']) # use all columns
try:
self.data_rewind() # try to wind back to start of data
except:

12
processing/pre/geom_check.py
View File

@ -40,19 +40,11 @@ parser.set_defaults(data = True)
#--- setup file handles --------------------------------------------------------------------------
files = []
if filenames == []:
files.append({'name':'STDIN',
'input':sys.stdin,
'output':sys.stdout,
'croak':sys.stderr,
})
files.append({'name':'STDIN', 'input':sys.stdin, 'output':sys.stdout, 'croak':sys.stderr, })
else:
for name in filenames:
if os.path.exists(name):
files.append({'name':name,
'input':open(name),
'output':sys.stdout,
'croak':sys.stdout,
})
files.append({'name':name, 'input':open(name), 'output':sys.stdout, 'croak':sys.stdout, })
#--- loop over input files ------------------------------------------------------------------------
for file in files:

82
processing/pre/geom_fromVoronoiTessellation.py
View File

@ -31,43 +31,43 @@ def meshgrid2(*arrs):
return tuple(ans)
def laguerreTessellation(undeformed, coords):
bestdist = np.ones(len(undeformed)) * np.finfo('d').max
bestseed = np.zeros(len(undeformed))
bestdist = np.ones(len(undeformed)) * np.finfo('d').max
bestseed = np.zeros(len(undeformed))
for i,seed in enumerate(coords):
for copy in np.array([[1, 0, 0, ],
[0, 1, 0, ],
[0, 0, 1, ],
[-1, 0, 0, ],
[0, -1, 0, ],
[0, 0, -1, ],
[1, 1, 0, ],
[1, 0, 1, ],
[0, 1, 1, ],
[-1, 1, 0, ],
[-1, 0, 1, ],
[0, -1, 1, ],
[-1, -1, 0, ],
[-1, 0, -1, ],
[0, -1, -1, ],
[1, -1, 0, ],
[1, 0, -1, ],
[0, 1, -1, ],
[1, 1, 1, ],
[-1, 1, 1, ],
[1, -1, 1, ],
[1, 1, -1, ],
[-1, -1, -1, ],
[1, -1, -1, ],
[-1, 1, -1, ],
[-1, -1, 1, ]]).astype(float):
for i,seed in enumerate(coords):
for copy in np.array([[1, 0, 0, ],
[0, 1, 0, ],
[0, 0, 1, ],
[-1, 0, 0, ],
[0, -1, 0, ],
[0, 0, -1, ],
[1, 1, 0, ],
[1, 0, 1, ],
[0, 1, 1, ],
[-1, 1, 0, ],
[-1, 0, 1, ],
[0, -1, 1, ],
[-1, -1, 0, ],
[-1, 0, -1, ],
[0, -1, -1, ],
[1, -1, 0, ],
[1, 0, -1, ],
[0, 1, -1, ],
[1, 1, 1, ],
[-1, 1, 1, ],
[1, -1, 1, ],
[1, 1, -1, ],
[-1, -1, -1, ],
[1, -1, -1, ],
[-1, 1, -1, ],
[-1, -1, 1, ]]).astype(float):
diff = undeformed - np.repeat((seed+info['size']*copy).reshape(3,1),len(undeformed),axis=1).T
dist = np.sum(diff*diff,axis=1) - weights[i]
bestseed = np.where(dist < bestdist, np.ones(len(undeformed))*(i+1),bestseed)
bestdist = np.where(dist < bestdist, dist,bestdist)
return bestseed
diff = undeformed - np.repeat((seed+info['size']*copy).reshape(3,1),len(undeformed),axis=1).T
dist = np.sum(diff*diff,axis=1) - weights[i]
bestseed = np.where(dist < bestdist, np.ones(len(undeformed))*(i+1),bestseed)
bestdist = np.where(dist < bestdist, dist,bestdist)
return bestseed
# --------------------------------------------------------------------
@ -109,8 +109,6 @@ parser.add_option('--secondphase', type='float', dest='secondphase', metavar= 'f
help='volume fraction of randomly distribute second phase [%default]')
parser.add_option('--laguerre', dest='laguerre', action='store_true',
help='for weighted voronoi (Laguerre) tessellation [%default]')
parser.set_defaults(grid = (0,0,0))
parser.set_defaults(size = (0.0,0.0,0.0))
parser.set_defaults(origin = (0.0,0.0,0.0))
@ -159,7 +157,7 @@ for file in files:
file['croak'].write('no coordinate data (1_coords/x) found ...')
continue
hasEulers = np.any(np.asarray(table.labels_index(['phi1','Phi','phi2'])) == -1)
hasEulers = np.all(np.asarray(table.labels_index(['phi1','Phi','phi2'])) != -1)
if hasEulers:
labels += ['phi1','Phi','phi2']
@ -174,8 +172,8 @@ for file in files:
table.data_readArray(labels)
coords = table.data[:,table.labels_index(coords)]
eulers = table.data[:,table.labels_index(['phi1','Phi','phi2'])] if hasEulers else np.zeros(3*len(coords))
grain = table.data[:,table.labels_index('microstructure')] if hasGrains else 1+np.arange(len(coords))
weights = table.data[:,table.labels_index('weight')] if hasWeight else np.zeros(len(coords))
grain = table.data[:,table.labels.index('microstructure')] if hasGrains else 1+np.arange(len(coords))
weights = table.data[:,table.labels.index('weight')] if hasWeight else np.zeros(len(coords))
grainIDs = np.unique(grain).astype('i')
@ -308,6 +306,4 @@ for file in files:
if file['name'] != 'STDIN':
table.input_close()
table.output_close()
os.rename(file['name']+'_tmp',os.path.splitext(file['name'])[0] + \
{True: '_material.config',
False:'.geom'}[options.config])
os.rename(file['name']+'_tmp',os.path.splitext(file['name'])[0] + '_material.config' if options.config else '.geom')

32
processing/pre/seeds_fromTable.py
View File

@ -36,22 +36,18 @@ Examples:
""", version = scriptID)
parser.add_option('-p', '--positions', dest = 'pos', type = 'string',
help = 'coordinate label')
parser.add_option('-p', '--positions', dest = 'pos', metavar='string',
help = 'coordinate label')
parser.add_option('--boundingbox', dest = 'box', type = 'float', nargs = 6,
help = 'min (x,y,z) and max (x,y,z) to specify bounding box [auto]')
help = 'min (x,y,z) and max (x,y,z) to specify bounding box [auto]')
parser.add_option('-i', '--index', dest = 'index', type = 'string',
help = 'microstructure index label')
parser.add_option('-w','--white', dest = 'whitelist', action = 'extend', type = 'string', \
help = 'white list of microstructure indices', metavar = '<LIST>')
parser.add_option('-b','--black', dest = 'blacklist', action = 'extend', type = 'string', \
help = 'black list of microstructure indices', metavar = '<LIST>')
help = 'microstructure index label')
parser.add_option('-w','--white', dest = 'whitelist', action = 'extend',\
help = 'white list of microstructure indices', metavar = '<LIST>')
parser.add_option('-b','--black', dest = 'blacklist', action = 'extend',\
help = 'black list of microstructure indices', metavar = '<LIST>')
parser.set_defaults(pos = 'pos')
parser.set_defaults(index = 'microstructure')
parser.set_defaults(box = ())
parser.set_defaults(whitelist = [])
parser.set_defaults(blacklist = [])
(options,filenames) = parser.parse_args()
@ -62,10 +58,10 @@ datainfo = { # lis
'label':[]},
}
if options.pos != None: datainfo['vector']['label'] += [options.pos]
if options.index != None: datainfo['scalar']['label'] += [options.index]
options.whitelist = map(int,options.whitelist)
options.blacklist = map(int,options.blacklist)
datainfo['vector']['label'] += [options.pos]
datainfo['scalar']['label'] += [options.index]
if options.whitelist != None: options.whitelist = map(int,options.whitelist)
if options.blacklist != None: options.blacklist = map(int,options.blacklist)
#--- setup file handles --------------------------------------------------------------------------
files = []
@ -126,10 +122,10 @@ for file in files:
#--- filtering of grain voxels ------------------------------------------------------------------------------------
mask = np.logical_and(\
np.ones_like(table.data[:,3],bool) \
if options.whitelist == [] \
if options.whitelist == None \
else np.in1d(table.data[:,3].ravel(), options.whitelist).reshape(table.data[:,3].shape),
np.ones_like(table.data[:,3],bool) \
if options.blacklist == [] \
if options.blacklist == None \
else np.invert(np.in1d(table.data[:,3].ravel(), options.blacklist).reshape(table.data[:,3].shape))
)
table.data = table.data[mask]