added option to use seed coordinates that are not normalized to a unit cube
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@ -37,12 +37,9 @@ def findClosestSeed(fargs):
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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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def laguerreTessellation(undeformed, coords, weights, grains, periodic = True, 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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@ -71,7 +68,10 @@ def laguerreTessellation(undeformed, coords, weights, grains, nonperiodic = Fals
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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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]).astype(float)*info['size'] if periodic else \
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np.array([
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[ 0, 0, 0 ],
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]).astype(float)
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repeatweights = np.tile(weights,len(copies)).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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@ -121,8 +121,8 @@ group.add_option('--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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dest = 'periodic',
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action = 'store_false',
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help = 'nonperiodic tessellation')
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parser.add_option_group(group)
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@ -144,6 +144,10 @@ group.add_option('-o',
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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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group.add_option('--nonnormalized',
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dest = 'normalized',
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action = 'store_false',
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help = 'seed coordinates are not normalized to a unit cube')
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parser.add_option_group(group)
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@ -206,7 +210,8 @@ parser.set_defaults(pos = 'pos',
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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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periodic = True,
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normalized = True,
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config = True,
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)
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(options,filenames) = parser.parse_args()
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@ -248,7 +253,7 @@ for name in filenames:
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for i in range(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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remarks.append('rescaling size {} to {}...'.format(['x','y','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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@ -256,6 +261,7 @@ for name in filenames:
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else:
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labels += [options.pos]
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if not options.normalized: remarks.append('using real-space seed coordinates...')
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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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@ -272,7 +278,8 @@ for name in filenames:
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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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coords = table.data[:,table.label_indexrange(options.pos)] * info['size'] if options.normalized \
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else table.data[:,table.label_indexrange(options.pos)] - info['origin']
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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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@ -291,7 +298,7 @@ for name in filenames:
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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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indices = laguerreTessellation(grid, coords, weights, grains, options.periodic, options.cpus)
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# --- write header ------------------------------------------------------------------------
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