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Removed unused Tally.tile_filter(...) routine

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This commit is contained in:
Will Boyd 2015-10-03 01:08:37 -04:00
parent 5ee352bc95
commit dd50063e87
3 changed files with 93 additions and 1774 deletions
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1424
docs/source/pythonapi/examples/pandas-dataframes.ipynb
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docs/source/pythonapi/examples/post-processing.ipynb
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75
openmc/tallies.py
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@ -2379,15 +2379,13 @@ class Tally(object):
for filter_bin in filter_bins[i]:
bin_index = filter.get_bin_index(filter_bin)
if filter_type in ['energy', 'energyout']:
bin_indices.append(bin_index)
bin_indices.append(bin_index+1)
bin_indices.extend([bin_index, bin_index+1])
elif filter_type == 'distribcell':
bin_indices.append(0)
else:
bin_indices.append(bin_index)
new_bins = filter.bins[bin_indices]
filter.bins = new_bins
filter.bins = filter.bins[bin_indices]
filter.num_bins = len(filter_bins[i])
# Correct each Filter's stride
@ -2478,7 +2476,6 @@ class Tally(object):
# Accumulate this Tally slice into the Tally sum
tally_sum += tally_slice
# FIXME: test if this works for filter
for filter_type in summed_filters:
filters = summed_filters[filter_type]
for i in range(1, len(filters)):
@ -2487,74 +2484,6 @@ class Tally(object):
return tally_sum
def tile_filter(self, new_filter):
"""Combines filters, scores and nuclides with another tally.
This is a helper method for the tally arithmetic methods. The filters,
scores and nuclides from both tallies are enumerated into all possible
combinations and expressed as CrossFilter, CrossScore and
CrossNuclide objects in the new derived tally.
Parameters
----------
other : Tally
The tally on the right hand side of the outer product
binary_op : {'+', '-', '*', '/', '^'}
The binary operation in the outer product
Returns
-------
Tally
A new Tally that is the outer product with this one.
"""
cv.check_type('new_filter', new_filter, Filter)
if new_filter in self.filters:
msg = 'Unable to tile Tally ID="{0}" which already ' \
'contains a "{1}" filter'.format(self.id, new_filter.type)
raise ValueError(msg)
new_tally = copy.deepcopy(self)
new_tally.add_filter(new_filter)
num_filter_bins = new_tally.num_filter_bins
num_nuclides = new_tally.num_nuclides
num_score_bins = new_tally.num_score_bins
new_shape = (num_filter_bins, num_nuclides, num_score_bins)
repeat_indices = np.arange(0, new_tally.num_bins, new_filter.num_bins)
repeat_factor = new_filter.num_bins
if self.sum is not None:
new_tally._sum = np.zeros(new_shape, dtype=np.float64)
if self.sum_sq is not None:
new_tally._sum_sq = np.zeros(new_shape, dtype=np.float64)
if self.mean is not None:
new_tally._mean = np.zeros(new_shape, dtype=np.float64)
if self.std_dev is not None:
new_tally._std_dev = np.zeros(new_shape, dtype=np.float64)
for i in range(repeat_factor):
if self.sum is not None:
new_tally._sum[repeat_indices+i, :, :] = self.sum
if self.sum_sq is not None:
new_tally._sum_sq[repeat_indices+i, :, :] = self.sum_sq
if self.mean is not None:
new_tally._mean[repeat_indices+i, :, :] = self.mean
if self.std_dev is not None:
new_tally._std_dev[repeat_indices+i, :, :] = self.std_dev
# Correct each Filter's stride
stride = new_tally.num_nuclides * new_tally.num_score_bins
for filter in reversed(new_tally.filters):
filter.stride = stride
stride *= filter.num_bins
return new_tally
def diagonalize_filter(self, new_filter):
"""Combines filters, scores and nuclides with another tally.