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fixed issue in Python API tally arithmetic with tally multiplication

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Sam Shaner 2015-11-17 22:33:00 -05:00
parent d159b4758c
commit 17d50332b2
1 changed files with 54 additions and 20 deletions
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74
openmc/tallies.py
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@ -1487,10 +1487,16 @@ class Tally(object):
other_filters = set(other.filters)
filter_intersect = self_filters.intersection(other_filters)
# Align the shared filters to follow in each tally operand
# Align the shared filters in successive order
for i, filter in enumerate(filter_intersect):
self_index = self.filters.index(filter)
other_filter = other.filters[self_index]
self_filter = self.filters[i]
other_filter = other.filters[i]
# If necessary, swap self filter
if self_filter != filter:
self = self.swap_filters(filter, self_filter)
# If necessary, swap other filter
if other_filter != filter:
other = other.swap_filters(filter, other_filter)
@ -1559,7 +1565,7 @@ class Tally(object):
if len(self.filters) != match and len(other.filters) == match:
for filter in cross_filters[0]:
new_tally.add_filter(filter)
elif len(other.filters) == match and len(other.filters) != match:
elif len(self.filters) == match and len(other.filters) != match:
for filter in cross_filters[1]:
new_tally.add_filter(filter)
else:
@ -1644,8 +1650,8 @@ class Tally(object):
self_repeat_factor *= filter.num_bins
# Tile / repeat the tally data for the tally outer product
self_shape = list(self.mean.shape)
other_shape = list(other.mean.shape)
self_shape = list(self_mean.shape)
other_shape = list(other_mean.shape)
self_shape[0] *= self_repeat_factor
self_mean = np.repeat(self_mean, self_repeat_factor)
self_std_dev = np.repeat(self_std_dev, self_repeat_factor)
@ -1653,7 +1659,8 @@ class Tally(object):
if self_repeat_factor == 1:
other_shape[0] *= other_tile_factor
other_mean = np.repeat(other_mean, other_tile_factor, axis=0)
other_std_dev = np.repeat(other_std_dev, other_tile_factor, axis=0)
other_std_dev = np.repeat(other_std_dev, other_tile_factor,
axis=0)
else:
other_mean = np.tile(other_mean, (other_tile_factor, 1, 1))
other_std_dev = np.tile(other_std_dev, (other_tile_factor, 1, 1))
@ -1672,7 +1679,11 @@ class Tally(object):
self_repeat_factor = other.num_nuclides
other_tile_factor = self.num_nuclides
# Replicate the data
# Tile / repeat the tally data for the tally outer product
self_shape = list(self_mean.shape)
other_shape = list(other_mean.shape)
self_shape[1] *= self_repeat_factor
other_shape[1] *= other_tile_factor
self_mean = np.repeat(self_mean, self_repeat_factor, axis=1)
other_mean = np.tile(other_mean, (1, other_tile_factor, 1))
self_std_dev = np.repeat(self_std_dev, self_repeat_factor, axis=1)
@ -1680,10 +1691,10 @@ class Tally(object):
# NumPy repeat and tile routines return 1D flattened arrays
# Reshape arrays as 3D with filters, nuclides and scores axes
self_shape = list(self.mean.shape)
self_shape[1] *= self_repeat_factor
self_mean.shape = tuple(self_shape)
self_std_dev.shape = tuple(self_shape)
other_mean.shape = tuple(other_shape)
other_std_dev.shape = tuple(other_shape)
if self.scores != other.scores:
@ -1692,7 +1703,11 @@ class Tally(object):
self_repeat_factor = other.num_score_bins
other_tile_factor = self.num_score_bins
# Replicate the data
# Tile / repeat the tally data for the tally outer product
self_shape = list(self_mean.shape)
other_shape = list(other_mean.shape)
self_shape[2] *= self_repeat_factor
other_shape[2] *= other_tile_factor
self_mean = np.repeat(self_mean, self_repeat_factor, axis=2)
other_mean = np.tile(other_mean, (1, 1, other_tile_factor))
self_std_dev = np.repeat(self_std_dev, self_repeat_factor, axis=2)
@ -1700,10 +1715,10 @@ class Tally(object):
# NumPy repeat and tile routines return 1D flattened arrays
# Reshape arrays as 3D with filters, nuclides and scores axes
self_shape = list(self.mean.shape)
self_shape[2] *= self_repeat_factor
self_mean.shape = tuple(self_shape)
self_std_dev.shape = tuple(self_shape)
other_mean.shape = tuple(other_shape)
other_std_dev.shape = tuple(other_shape)
data = {}
data['self'] = {}
@ -2451,6 +2466,13 @@ class Tally(object):
A new tally which encapsulates the sum of data requested.
"""
# If user input filter type but no bins, sum across all bins and
# remove the filter
if filter_type in _FILTER_TYPES and len(filter_bins) == 0:
remove_filter = True
else:
remove_filter = False
# If user did not specify any scores, do not sum across scores
if len(scores) == 0:
scores = [[]]
@ -2467,7 +2489,14 @@ class Tally(object):
# Sum across any filter bins specified by the user
if filter_type in _FILTER_TYPES:
filter_bins = [[(filter_bin,)] for filter_bin in filter_bins]
# If user did not specify filter bins, sum across all bins
if len(filter_bins) == 0:
filter = self.find_filter(filter_type)
filter_bins = [[(filter.get_bin(i),)] for i in range(filter.num_bins)]
else:
filter_bins = [[(filter_bin,)] for filter_bin in filter_bins]
filters = [[filter_type]]
# If user did not specify a filter type, do not sum across filter bins
else:
@ -2492,12 +2521,17 @@ class Tally(object):
# Accumulate this Tally slice into the Tally sum
tally_sum += tally_slice
# Add back the filter(s) which were summed across to derived tally
for filter_type in summed_filters:
filters = summed_filters[filter_type]
for i in range(1, len(filters)):
filters[i] = CrossFilter(filters[i-1], filters[i], '+')
tally_sum.add_filter(filters[-1])
# Add back the filter(s) which were summed across to derived tally,
# if filter bins were input; otherwise, leave out summed filter(s)
if remove_filter:
# Rename tally sum indicating a summation over a particular filter
tally_sum.name = 'sum({0}, {1})'.format(self.name, filter_type)
else:
for summed_filter_type in summed_filters:
filters = summed_filters[summed_filter_type]
for i in range(1, len(filters)):
filters[i] = CrossFilter(filters[i-1], filters[i], '+')
tally_sum.add_filter(filters[-1])
return tally_sum