shortened code with utility function coordGridAndSize
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@ -139,12 +139,7 @@ for name in filenames:
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table.data_readArray()
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table.data_readArray()
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coords = [np.unique(table.data[:,coordCol+i]) for i in range(3)]
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grid,size = damask.util.gridAndSize(table.data[:,table.label_indexrange(options.pos)])
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mincorner = np.array(map(min,coords))
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maxcorner = np.array(map(max,coords))
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grid = np.array(map(len,coords),'i')
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size = grid/np.maximum(np.ones(3,'d'), grid-1.0) * (maxcorner-mincorner) # size from edge to edge = dim * n/(n-1)
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size = np.where(grid > 1, size, min(size[grid > 1]/grid[grid > 1])) # spacing for grid==1 equal to smallest among other ones
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# ------------------------------------------ process value field -----------------------------------
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# ------------------------------------------ process value field -----------------------------------
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@ -136,12 +136,7 @@ for name in filenames:
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table.data_readArray()
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table.data_readArray()
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coords = [np.unique(table.data[:,coordCol+i]) for i in range(3)]
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grid,size = damask.util.coordGridAndSize(table.data[:,table.label_indexrange(options.pos)])
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mincorner = np.array(map(min,coords))
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maxcorner = np.array(map(max,coords))
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grid = np.array(map(len,coords),'i')
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size = grid/np.maximum(np.ones(3,'d'), grid-1.0) * (maxcorner-mincorner) # size from edge to edge = dim * n/(n-1)
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size = np.where(grid > 1, size, min(size[grid > 1]/grid[grid > 1])) # spacing for grid==1 equal to smallest among other ones
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# ------------------------------------------ process value field -----------------------------------
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# ------------------------------------------ process value field -----------------------------------
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@ -18,7 +18,7 @@ scriptID = ' '.join([scriptName,damask.version])
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parser = OptionParser(option_class=damask.extendableOption, usage='%prog option(s) [ASCIItable(s)]', description = """
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parser = OptionParser(option_class=damask.extendableOption, usage='%prog option(s) [ASCIItable(s)]', description = """
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Add column(s) containing Gaussian filtered values of requested column(s).
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Add column(s) containing Gaussian filtered values of requested column(s).
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Operates on periodic and non-periodic ordered three-dimensional data sets.
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Operates on periodic and non-periodic ordered three-dimensional data sets.
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For Details see scipy.ndimage documentation.
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For details see scipy.ndimage documentation.
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""", version = scriptID)
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""", version = scriptID)
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@ -43,15 +43,14 @@ parser.add_option('--sigma',
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parser.add_option('--periodic',
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parser.add_option('--periodic',
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dest = 'periodic',
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dest = 'periodic',
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action = 'store_true',
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action = 'store_true',
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help = 'assume periodic grain structure'
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help = 'assume periodic grain structure')
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)
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parser.set_defaults(pos = 'pos',
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parser.set_defaults(pos = 'pos',
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order = 0,
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order = 0,
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sigma = 1,
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sigma = 1,
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periodic = False
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periodic = False,
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)
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)
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(options,filenames) = parser.parse_args()
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(options,filenames) = parser.parse_args()
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@ -110,12 +109,7 @@ for name in filenames:
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table.data_readArray()
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table.data_readArray()
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coords = [np.unique(table.data[:,colCoord+i]) for i in range(3)]
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grid,size = damask.util.coordGridAndSize(table.data[:,table.label_indexrange(options.pos)])
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mincorner = np.array(map(min,coords))
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maxcorner = np.array(map(max,coords))
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grid = np.array(map(len,coords),'i')
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size = grid/np.maximum(np.ones(3,'d'), grid-1.0) * (maxcorner-mincorner) # size from edge to edge = dim * n/(n-1)
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size = np.where(grid > 1, size, min(size[grid > 1]/grid[grid > 1])) # spacing for grid==1 equal to smallest among other ones
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# ------------------------------------------ process value field -----------------------------------
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# ------------------------------------------ process value field -----------------------------------
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@ -135,12 +135,7 @@ for name in filenames:
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table.data_readArray()
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table.data_readArray()
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coords = [np.unique(table.data[:,coordCol+i]) for i in range(3)]
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grid,size = damask.util.coordGridAndSize(table.data[:,table.label_indexrange(options.pos)])
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mincorner = np.array(map(min,coords))
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maxcorner = np.array(map(max,coords))
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grid = np.array(map(len,coords),'i')
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size = grid/np.maximum(np.ones(3,'d'), grid-1.0) * (maxcorner-mincorner) # size from edge to edge = dim * n/(n-1)
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size = np.where(grid > 1, size, min(size[grid > 1]/grid[grid > 1])) # spacing for grid==1 equal to smallest among other ones
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# ------------------------------------------ process value field -----------------------------------
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# ------------------------------------------ process value field -----------------------------------
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