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Removed manual tuple construction for tally shape in place of new shape property
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2 changed files with 4 additions and 14 deletions
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@ -789,10 +789,8 @@ class MGXS(object):
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std_dev = np.sqrt(std_dev)
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# Reshape condensed data arrays with one dimension for all filters
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new_shape = \
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(tally.num_filter_bins, tally.num_nuclides, tally.num_scores,)
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mean = np.reshape(mean, new_shape)
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std_dev = np.reshape(std_dev, new_shape)
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mean = np.reshape(mean, tally.shape)
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std_dev = np.reshape(std_dev, tally.shape)
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# Override tally's data with the new condensed data
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tally._mean = mean
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@ -873,10 +871,8 @@ class MGXS(object):
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domain_filter.num_bins = 1
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# Reshape averaged data arrays with one dimension for all filters
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new_shape = \
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(tally.num_filter_bins, tally.num_nuclides, tally.num_scores,)
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mean = np.reshape(mean, new_shape)
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std_dev = np.reshape(std_dev, new_shape)
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mean = np.reshape(mean, tally.shape)
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std_dev = np.reshape(std_dev, tally.shape)
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# Override tally's data with the new condensed data
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tally._mean = mean
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@ -2841,12 +2841,6 @@ class Tally(object):
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new_tally = copy.deepcopy(self)
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new_tally.add_filter(new_filter)
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# Determine the shape of data in the new diagonalized Tally
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num_filter_bins = new_tally.num_filter_bins
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num_nuclides = new_tally.num_nuclides
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num_scores = new_tally.num_scores
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new_shape = (num_filter_bins, num_nuclides, num_scores)
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# Determine "base" indices along the new "diagonal", and the factor
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# by which the "base" indices should be repeated to account for all
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# other filter bins in the diagonalized tally
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