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DAMASK_EICMD
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combined assignement of curvature exponent to deal with negative dimensions

This commit is contained in:
Philip Eisenlohr 2017-08-03 12:12:47 -04:00
parent a28b4b3d27
commit 1a423617c2
1 changed files with 3 additions and 4 deletions
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7
processing/pre/geom_addPrimitive.py
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@ -54,7 +54,7 @@ parser.add_option( '--realspace', dest='realspace', action='store_true',
parser.set_defaults(center = (.0,.0,.0), parser.set_defaults(center = (.0,.0,.0),
fill = 0, fill = 0,
degrees = False, degrees = False,
exponent = (1e10,1e10,1e10), # box shape by default exponent = (20,20,20), # box shape by default
periodic = True, periodic = True,
realspace = False, realspace = False,
) )
@ -74,7 +74,8 @@ else:
options.center = np.array(options.center) options.center = np.array(options.center)
options.dimension = np.array(options.dimension) options.dimension = np.array(options.dimension)
options.exponent = np.power(2,options.exponent) # undo logarithmic sense of exponent # undo logarithmic sense of exponent and generate ellipsoids for negative dimensions (backward compatibility)
options.exponent = np.where(np.array(options.dimension) > 0, np.power(2,options.exponent), 2)
# --- loop over input files ------------------------------------------------------------------------- # --- loop over input files -------------------------------------------------------------------------
if filenames == []: filenames = [None] if filenames == []: filenames = [None]
@ -118,8 +119,6 @@ for name in filenames:
options.fill = microstructure.max()+1 if options.fill == 0 else options.fill options.fill = microstructure.max()+1 if options.fill == 0 else options.fill
# If we have a negative dimension, make it an ellipsoid for backwards compatibility
options.exponent = np.where(np.array(options.dimension) > 0, options.exponent, 2)
microstructure = microstructure.reshape(info['grid'],order='F') microstructure = microstructure.reshape(info['grid'],order='F')
# coordinates given in real space (default) vs voxel space # coordinates given in real space (default) vs voxel space