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Removed comments from consistent scattering matrix implementation
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Will Boyd
parent
b1574c359d
commit
b2ad5087ca
1 changed files with 10 additions and 100 deletions
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@ -4903,8 +4903,6 @@ class MultiplicityMatrixXS(MatrixMGXS):
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return self._xs_tally
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# FIXME: Kord's scattering matrix idea
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class ScatterProbabilityMatrix(MatrixMGXS):
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r"""The group-to-group scattering matrix.
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@ -5053,7 +5051,6 @@ class ScatterProbabilityMatrix(MatrixMGXS):
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energy = openmc.EnergyFilter(group_edges)
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energyout = openmc.EnergyoutFilter(group_edges)
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filters = [[energy, energyout]]
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return self._add_angle_filters(filters)
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@property
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@ -5067,11 +5064,11 @@ class ScatterProbabilityMatrix(MatrixMGXS):
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def xs_tally(self):
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if self._xs_tally is None:
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# energyout = self.filters[0][1]
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energyout_bins = \
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[self.energy_groups.get_group_bounds(i) for i in range(self.num_groups, 0, -1)]
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norm = self.rxn_rate_tally.summation(
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filter_type=openmc.EnergyoutFilter, filter_bins=energyout_bins)
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# Remove the AggregateFilter summed across energyout bins
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norm._filters = norm._filters[:2]
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@ -5082,8 +5079,6 @@ class ScatterProbabilityMatrix(MatrixMGXS):
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return self._xs_tally
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# FIXME: Kord's scattering matrix idea
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class NuScatterProbabilityMatrix(ScatterProbabilityMatrix):
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r"""The group-to-group nu-scattering matrix.
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@ -5221,9 +5216,6 @@ class NuScatterProbabilityMatrix(ScatterProbabilityMatrix):
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self._hdf5_key = 'nu-scatter probability matrix'
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# FIXME: Kord's scattering matrix idea
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@add_metaclass(ABCMeta)
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class ConvolvedMGXS(MGXS):
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@ -5478,28 +5470,12 @@ class ConvolvedMGXS(MGXS):
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sp_tally.sparse = self.sparse
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self._tallies[tally_type] = sp_tally
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# Load data for the tallies in each MGXS in the convolution
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for mgxs in self.mgxs:
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mgxs.load_from_statepoint(statepoint)
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self._loaded_sp = True
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'''
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# Clear any tallies previously loaded from a statepoint
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if self.loaded_sp:
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self._tallies = None
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self._xs_tally = None
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self._rxn_rate_tally = None
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self._loaded_sp = False
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for mgxs in self.mgxs:
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mgxs.load_from_statepoint(statepoint)
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self._loaded_sp = True
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'''
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# FIXME: Kord's scattering matrix idea
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# FIXME: Note that this does not yet support transport correction
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class ConsistentScatterMatrixXS(ConvolvedMGXS, ScatterMatrixXS):
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@ -5534,7 +5510,7 @@ class ConsistentScatterMatrixXS(ConvolvedMGXS, ScatterMatrixXS):
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def scores(self):
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scores = super(ConsistentScatterMatrixXS, self).scores
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# FIXME: Add scores for transport correction
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# Add scores for transport correction
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if self.correction == 'P0' and self.legendre_order == 0:
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scores += ['{}-1'.format(self.rxn_type)]
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@ -5544,7 +5520,7 @@ class ConsistentScatterMatrixXS(ConvolvedMGXS, ScatterMatrixXS):
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def filters(self):
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filters = super(ConsistentScatterMatrixXS, self).filters
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# FIXME: Add filters for transport correction
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# Add filters for transport correction
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if self.correction == 'P0' and self.legendre_order == 0:
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group_edges = self.energy_groups.group_edges
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energyout = openmc.EnergyoutFilter(group_edges)
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@ -5556,23 +5532,20 @@ class ConsistentScatterMatrixXS(ConvolvedMGXS, ScatterMatrixXS):
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def tally_keys(self):
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tally_keys = super(ConsistentScatterMatrixXS, self).tally_keys
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# FIXME: Add key for transport correction tally
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# Add key for transport correction tally
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if self.correction == 'P0' and self.legendre_order == 0:
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tally_keys += ['scatter-1']
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return tally_keys
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# FIXME: Make this work for transport correction
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@property
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def tallies(self):
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if self._tallies is None:
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self._tallies = super(ConsistentScatterMatrixXS, self).tallies
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# FIXME: Add in the transport correction tally
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# Add in the transport correction tally
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if self.correction == 'P0' and self.legendre_order == 0:
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tally_key = 'scatter-1'
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# Create a domain Filter object
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@ -5613,22 +5586,6 @@ class ConsistentScatterMatrixXS(ConvolvedMGXS, ScatterMatrixXS):
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@property
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def rxn_rate_tally(self):
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raise NotImplementedError('The rxn rate tally is not well defined ')
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'''
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if self._rxn_rate_tally is None:
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# FIXME: Add transport correction option
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# If using P0 correction subtract scatter-1 from the diagonal
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if self.correction == 'P0' and self.legendre_order == 0:
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scatter_p0 = self.tallies['{}-0'.format(self.rxn_type)]
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scatter_p1 = self.tallies['{}-1'.format(self.rxn_type)]
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self._rxn_rate_tally = self.mgxs[0].rxn_rate_tally
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self._rxn_rate_tally.sparse = self.sparse
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return self._rxn_rate_tally
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'''
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# FIXME: Apply transport correction
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@property
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def xs_tally(self):
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@ -5638,10 +5595,8 @@ class ConsistentScatterMatrixXS(ConvolvedMGXS, ScatterMatrixXS):
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'not been loaded from a statepoint'
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raise ValueError(msg)
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# FIXME: If using P0 correction subtract scatter-1 from the diagonal
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# If using P0 correction subtract scatter-1 from the diagonal
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if self.correction == 'P0' and self.legendre_order == 0:
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# FIXME: The flux tally must also use an analog estimator
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flux = self.tallies['{} : flux'.format(self.rxn_type)]
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scatter_p0 = self.tallies['{0} : {0}'.format(self.rxn_type)]
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scatter_p1 = self.tallies['scatter-1']
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@ -5660,62 +5615,17 @@ class ConsistentScatterMatrixXS(ConvolvedMGXS, ScatterMatrixXS):
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return self._xs_tally
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# FIXME: Add not implemented yet errors to these property getters/setters
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'''
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@ScatterMatrixXS.correction.setter
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def correction(self, correction):
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cv.check_value('correction', correction, ('P0', None))
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if self.scatter_format == 'legendre':
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if correction == 'P0' and self.legendre_order > 0:
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msg = 'The P0 correction will be ignored since the ' \
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'scattering order {} is greater than '\
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'zero'.format(self.legendre_order)
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warnings.warn(msg)
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elif self.scatter_format == 'histogram':
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msg = 'The P0 correction will be ignored since the ' \
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'scatter format is set to histogram'
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warnings.warn(msg)
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self._correction = correction
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@ScatterMatrixXS.scatter_format.setter
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def scatter_format(self, scatter_format):
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cv.check_value('scatter_format', scatter_format, MU_TREATMENTS)
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self._scatter_format = scatter_format
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raise NotImplementedError('Not yet supported')
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@ScatterMatrixXS.legendre_order.setter
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def legendre_order(self, legendre_order):
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cv.check_type('legendre_order', legendre_order, Integral)
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cv.check_greater_than('legendre_order', legendre_order, 0,
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equality=True)
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cv.check_less_than('legendre_order', legendre_order, _MAX_LEGENDRE,
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equality=True)
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if self.scatter_format == 'legendre':
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if self.correction == 'P0' and legendre_order > 0:
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msg = 'The P0 correction will be ignored since the ' \
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'scattering order {} is greater than ' \
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'zero'.format(self.legendre_order)
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warnings.warn(msg, RuntimeWarning)
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self.correction = None
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elif self.scatter_format == 'histogram':
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msg = 'The legendre order will be ignored since the ' \
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'scatter format is set to histogram'
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warnings.warn(msg)
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self._legendre_order = legendre_order
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raise NotImplementedError('Not yet supported')
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@ScatterMatrixXS.histogram_bins.setter
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def histogram_bins(self, histogram_bins):
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cv.check_type('histogram_bins', histogram_bins, Integral)
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cv.check_greater_than('histogram_bins', histogram_bins, 0)
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self._histogram_bins = histogram_bins
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'''
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# def load_from_statepoint(self, statepoint):
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# super(ConsistentScatterMatrixXS, self).load_from_statepoint(statepoint)
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raise NotImplementedError('Not yet supported')
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def get_condensed_xs(self, coarse_groups):
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condense_xs = \
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