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Added Tally average aggregation operation to Python API
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wbinventor@gmail.com
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commit
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2 changed files with 160 additions and 9 deletions
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@ -13,7 +13,7 @@ if sys.version_info[0] >= 3:
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basestring = str
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# Acceptable tally aggregation operations
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_TALLY_AGGREGATE_OPS = ['sum', 'mean']
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_TALLY_AGGREGATE_OPS = ['sum', 'avg']
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class AggregateScore(object):
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@ -25,7 +25,7 @@ class AggregateScore(object):
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scores : Iterable of str or CrossScore
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The scores included in the aggregation
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aggregate_op : str
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The tally aggregation operator (e.g., 'sum', 'mean', etc.) used
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The tally aggregation operator (e.g., 'sum', 'avg', etc.) used
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to aggregate across a tally's scores with this AggregateScore
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Attributes
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@ -33,7 +33,7 @@ class AggregateScore(object):
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scores : Iterable of str or CrossScore
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The scores included in the aggregation
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aggregate_op : str
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The tally aggregation operator (e.g., 'sum', 'mean', etc.) used
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The tally aggregation operator (e.g., 'sum', 'avg', etc.) used
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to aggregate across a tally's scores with this AggregateScore
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"""
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@ -108,7 +108,7 @@ class AggregateNuclide(object):
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nuclides : Iterable of str or Nuclide or CrossNuclide
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The nuclides included in the aggregation
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aggregate_op : str
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The tally aggregation operator (e.g., 'sum', 'mean', etc.) used
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The tally aggregation operator (e.g., 'sum', 'avg', etc.) used
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to aggregate across a tally's nuclides with this AggregateNuclide
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Attributes
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@ -116,7 +116,7 @@ class AggregateNuclide(object):
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nuclides : Iterable of str or Nuclide or CrossNuclide
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The nuclides included in the aggregation
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aggregate_op : str
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The tally aggregation operator (e.g., 'sum', 'mean', etc.) used
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The tally aggregation operator (e.g., 'sum', 'avg', etc.) used
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to aggregate across a tally's nuclides with this AggregateNuclide
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"""
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@ -198,7 +198,7 @@ class AggregateFilter(object):
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bins : Iterable of tuple
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The filter bins included in the aggregation
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aggregate_op : str
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The tally aggregation operator (e.g., 'sum', 'mean', etc.) used
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The tally aggregation operator (e.g., 'sum', 'avg', etc.) used
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to aggregate across a tally filter's bins with this AggregateFilter
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Attributes
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@ -208,7 +208,7 @@ class AggregateFilter(object):
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aggregate_filter : filter
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The filter included in the aggregation
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aggregate_op : str
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The tally aggregation operator (e.g., 'sum', 'mean', etc.) used
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The tally aggregation operator (e.g., 'sum', 'avg', etc.) used
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to aggregate across a tally filter's bins with this AggregateFilter
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bins : Iterable of tuple
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The filter bins included in the aggregation
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@ -2758,7 +2758,7 @@ class Tally(object):
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def summation(self, scores=[], filter_type=None,
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filter_bins=[], nuclides=[], remove_filter=False):
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"""Vectorized sum of tally data across scores, filter bins and/or
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nuclides using tally addition.
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nuclides using tally aggregation.
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This method constructs a new tally to encapsulate the sum of the data
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represented by the summation of the data in this tally. The tally data
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@ -2800,7 +2800,7 @@ class Tally(object):
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tally_sum._derived = True
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tally_sum._estimator = self.estimator
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tally_sum._num_realizations = self.num_realizations
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tally_sum.with_batch_statistics = self.with_batch_statistics
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tally_sum._with_batch_statistics = self.with_batch_statistics
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tally_sum._with_summary = self.with_summary
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tally_sum._sp_filename = self._sp_filename
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tally_sum._results_read = self._results_read
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@ -2903,6 +2903,157 @@ class Tally(object):
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tally_sum.sparse = self.sparse
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return tally_sum
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def average(self, scores=[], filter_type=None,
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filter_bins=[], nuclides=[], remove_filter=False):
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"""Vectorized average of tally data across scores, filter bins and/or
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nuclides using tally aggregation.
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This method constructs a new tally to encapsulate the average of the
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data represented by the average of the data in this tally. The tally
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data average is determined by the scores, filter bins and nuclides
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specified in the input parameters.
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Parameters
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----------
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scores : list of str
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A list of one or more score strings to average across
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(e.g., ['absorption', 'nu-fission']; default is [])
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filter_type : str
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A filter type string (e.g., 'cell', 'energy') corresponding to the
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filter bins to average across
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filter_bins : Iterable of Integral or tuple
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A list of the filter bins corresponding to the filter_type parameter
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Each bin in the list is the integer ID for 'material', 'surface',
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'cell', 'cellborn', and 'universe' Filters. Each bin is an integer
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for the cell instance ID for 'distribcell' Filters. Each bin is a
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2-tuple of floats for 'energy' and 'energyout' filters corresponding
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to the energy boundaries of the bin of interest. Each bin is an
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(x,y,z) 3-tuple for 'mesh' filters corresponding to the mesh cell of
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interest.
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nuclides : list of str
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A list of nuclide name strings to average across
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(e.g., ['U-235', 'U-238']; default is [])
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remove_filter : bool
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If a filter is being averaged over, this bool indicates whether to
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remove that filter in the returned tally. Default is False.
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Returns
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-------
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Tally
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A new tally which encapsulates the average of data requested.
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"""
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# Create new derived Tally for average
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tally_avg = Tally()
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tally_avg._derived = True
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tally_avg._estimator = self.estimator
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tally_avg._num_realizations = self.num_realizations
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tally_avg._with_batch_statistics = self.with_batch_statistics
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tally_avg._with_summary = self.with_summary
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tally_avg._sp_filename = self._sp_filename
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tally_avg._results_read = self._results_read
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# Get tally data arrays reshaped with one dimension per filter
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mean = self.get_reshaped_data(value='mean')
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std_dev = self.get_reshaped_data(value='std_dev')
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# Average across any filter bins specified by the user
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if filter_type in _FILTER_TYPES:
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find_filter = self.find_filter(filter_type)
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# If user did not specify filter bins, average across all bins
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if len(filter_bins) == 0:
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bin_indices = np.arange(find_filter.num_bins)
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if filter_type == 'distribcell':
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filter_bins = np.arange(find_filter.num_bins)
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else:
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num_bins = find_filter.num_bins
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filter_bins = \
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[(find_filter.get_bin(i)) for i in range(num_bins)]
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# Only average across bins specified by the user
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else:
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bin_indices = \
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[find_filter.get_bin_index(bin) for bin in filter_bins]
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# Average across the bins in the user-specified filter
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for i, self_filter in enumerate(self.filters):
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if self_filter.type == filter_type:
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mean = np.take(mean, indices=bin_indices, axis=i)
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std_dev = np.take(std_dev, indices=bin_indices, axis=i)
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mean = np.mean(mean, axis=i, keepdims=True)
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std_dev = np.mean(std_dev**2, axis=i, keepdims=True)
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std_dev /= len(bin_indices)
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std_dev = np.sqrt(std_dev)
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# Add AggregateFilter to the tally avg
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if not remove_filter:
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filter_sum = \
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AggregateFilter(self_filter, filter_bins, 'avg')
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tally_avg.add_filter(filter_sum)
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# Add a copy of each filter not averaged across to the tally avg
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else:
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tally_avg.add_filter(copy.deepcopy(self_filter))
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# Add a copy of this tally's filters to the tally avg
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else:
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tally_avg._filters = copy.deepcopy(self.filters)
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# Sum across any nuclides specified by the user
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if len(nuclides) != 0:
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nuclide_bins = [self.get_nuclide_index(nuclide) for nuclide in nuclides]
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axis_index = self.num_filters
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mean = np.take(mean, indices=nuclide_bins, axis=axis_index)
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std_dev = np.take(std_dev, indices=nuclide_bins, axis=axis_index)
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mean = np.mean(mean, axis=axis_index, keepdims=True)
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std_dev = np.mean(std_dev**2, axis=axis_index, keepdims=True)
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std_dev /= len(nuclide_bins)
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std_dev = np.sqrt(std_dev)
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# Add AggregateNuclide to the tally avg
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nuclide_avg = AggregateNuclide(nuclides, 'avg')
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tally_avg.add_nuclide(nuclide_avg)
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# Add a copy of this tally's nuclides to the tally avg
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else:
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tally_avg._nuclides = copy.deepcopy(self.nuclides)
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# Sum across any scores specified by the user
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if len(scores) != 0:
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score_bins = [self.get_score_index(score) for score in scores]
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axis_index = self.num_filters + 1
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mean = np.take(mean, indices=score_bins, axis=axis_index)
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std_dev = np.take(std_dev, indices=score_bins, axis=axis_index)
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mean = np.sum(mean, axis=axis_index, keepdims=True)
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std_dev = np.sum(std_dev**2, axis=axis_index, keepdims=True)
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std_dev /= len(score_bins)
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std_dev = np.sqrt(std_dev)
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# Add AggregateScore to the tally avg
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score_sum = AggregateScore(scores, 'avg')
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tally_avg.add_score(score_sum)
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# Add a copy of this tally's scores to the tally avg
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else:
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tally_avg._scores = copy.deepcopy(self.scores)
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# Update the tally avg's filter strides
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tally_avg._update_filter_strides()
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# Reshape condensed data arrays with one dimension for all filters
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mean = np.reshape(mean, tally_avg.shape)
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std_dev = np.reshape(std_dev, tally_avg.shape)
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# Assign tally avg's data with the new arrays
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tally_avg._mean = mean
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tally_avg._std_dev = std_dev
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# If original tally was sparse, sparsify the tally average
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tally_avg.sparse = self.sparse
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return tally_avg
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def diagonalize_filter(self, new_filter):
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"""Diagonalize the tally data array along a new axis of filter bins.
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