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Improvements to docstrings for openmc.mgxs.MultiGroupXS
This commit is contained in:
Will Boyd
parent
a886a16b04
commit
665b8226e8
1 changed files with 203 additions and 196 deletions
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@ -17,31 +17,18 @@ if sys.version_info[0] >= 3:
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basestring = str
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# Supported cross-section types
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XS_TYPES = ('total',
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'transport',
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'absorption',
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'capture',
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'scatter',
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'nu-scatter',
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'scatter matrix',
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'nu-scatter matrix',
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'fission',
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'nu-fission',
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'chi')
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# Supported domain types
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DOMAIN_TYPES = ('cell',
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DOMAIN_TYPES = ['cell',
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'distribcell',
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'universe',
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'material',
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'mesh')
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'mesh']
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# Supported domain objects
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DOMAINS = (openmc.Cell,
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DOMAINS = [openmc.Cell,
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openmc.Universe,
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openmc.Material,
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openmc.Mesh)
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openmc.Mesh]
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# LaTeX Greek symbols for each cross-section type
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GREEK = dict()
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@ -59,7 +46,7 @@ GREEK['chi'] = '$\\chi$'
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class MultiGroupXS(object):
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"""A multi-group cross-section for some energy groups structure within
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"""A multi-group cross-section for some energy group structure within
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some spatial domain.
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This class can be used for both OpenMC input generation and tally data
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@ -68,15 +55,15 @@ class MultiGroupXS(object):
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Parameters
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----------
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name : str, optional
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Name of the multi-group cross-section. If not specified, the name is
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the empty string.
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domain : Material or Cell or Universe or Mesh
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The domain for spatial homogenization
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domain_type : {'material', 'cell', 'distribcell', 'universe' or 'mesh'}
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The domain type for spatial homogenization
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energy_groups : EnergyGroups
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The energy group structure for energy condensation
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name : str, optional
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Name of the multi-group cross-section. Used as a label to identify
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tallies in OpenMC tallies.xml file.
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Attributes
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----------
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@ -93,16 +80,16 @@ class MultiGroupXS(object):
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num_groups : Integral
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Number of energy groups
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tallies : dict
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Tallies needed to compute the multi-group cross-section
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xs : Tally
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OpenMC tallies needed to compute the multi-group cross-section
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xs_tally : Tally
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Derived tally for the multi-group cross-section. This attribute
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is None unless the multi-group cross-section has been computed.
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subdomain_offsets : dict
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Integral subdomain IDs (keys) mapped to integral tally data array
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offsets (values). When the domain_type is 'distribcell', each subdomain
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ID corresponds to an instance of the cell domain. For all other domain
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types, there is only one subdomain for the domain and this dictionary
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will trivially map zero to zero.
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subdomain_indices : dict
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Integer subdomain IDs (keys) mapped to integer tally data array
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indices (values) for 'distribcell' domain types. Each subdomain ID
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corresponds to an instance of the cell domain. For all other domain
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types, the domain has only one subdomain and this dictionary will
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trivially map zero to zero.
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offset : Integral
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The filter offset for the domain filter
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@ -124,7 +111,7 @@ class MultiGroupXS(object):
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self._xs_tally = None
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# A dictionary used to compute indices into the xs array
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# Keys - Domain ID (ie, Material ID, Region ID for districell, etc)
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# Keys - Domain ID (ie, maaterial ID, distribcell instance ID, etc)
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# Values - Offset/stride into xs array
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# NOTE: This is primarily used for distribcell domain types
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self._subdomain_indices = dict()
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@ -150,7 +137,7 @@ class MultiGroupXS(object):
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clone._domain_type = self.domain_type
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clone._energy_groups = copy.deepcopy(self.energy_groups, memo)
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clone._num_groups = self.num_groups
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clone._xs_tally = copy.deepcopy(self._xs_tally, memo)
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clone._xs_tally = copy.deepcopy(self.xs_tally, memo)
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clone._subdomain_indices = \
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copy.deepcopy(self.subdomain_indices, memo)
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clone._offset = copy.deepcopy(self.offset, memo)
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@ -210,14 +197,14 @@ class MultiGroupXS(object):
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@domain.setter
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def domain(self, domain):
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cv.check_type('domain', domain, DOMAINS)
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cv.check_type('domain', domain, tuple(DOMAINS))
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self._domain = domain
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if self._domain_type in ['material', 'cell', 'universe', 'mesh']:
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self._subdomain_indices[domain.id] = 0
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@domain_type.setter
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def domain_type(self, domain_type):
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cv.check_value('domain type', domain_type, DOMAIN_TYPES)
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cv.check_value('domain type', domain_type, tuple(DOMAIN_TYPES))
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self._domain_type = domain_type
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@energy_groups.setter
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@ -228,16 +215,17 @@ class MultiGroupXS(object):
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def _find_domain_offset(self):
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"""Finds and stores the offset of the domain tally filter"""
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tally = self.tallies.values()[0]
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filter = tally.find_filter(self.domain_type, [self.domain.id])
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self._offset = filter.offset
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domain_filter = tally.find_filter(self.domain_type, [self.domain.id])
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self._offset = domain_filter.offset
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def set_subdomain_index(self, subdomain_id, index):
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"""Set the filter bin index for a subdomain of the domain.
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This is primarily useful when the domain type is 'distribcell', in
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which case one may wish to map each subdomain (a cell instance) to its
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filter bin in the derived multi-group cross-section tally data array.
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This is useful when the domain type is 'distribcell', in which case one
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may wish to map each subdomain (a cell instance) to its filter bin in
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the derived multi-group cross-section tally data array.
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Parameters
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----------
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@ -246,17 +234,120 @@ class MultiGroupXS(object):
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index : Integral
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The filter bin index for the subdomain
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See also
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--------
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MultiGroupXS.get_subdomains(), MultiGroupXS.get_subdomain_indices()
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"""
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cv.check_type('subdomain id', subdomain_id, Integral)
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cv.check_type('subdomain offset', index, Integral)
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cv.check_greater_than('subdomain id', subdomain_id, 0, True)
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cv.check_greater_than('subdomain offset', subdomain_id, 0, True)
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cv.check_type('subdomain index', index, Integral)
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cv.check_greater_than('subdomain id', subdomain_id, 0, equality=True)
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cv.check_greater_than('subdomain index', index, 0, equality=True)
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self._subdomain_indices[subdomain_id] = index
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def get_subdomain_indices(self, subdomains='all'):
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"""Get the indices for one or more subdomains.
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This method can be used to extract the indices into the multi-group
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cross-section tally data array for a subdomain. This is useful when the
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domain type is 'distribcell', in which case one may wish to map each
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subdomain (a cell instance) to its filter bin index in the derived
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multi-group cross-section tally data array.
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Parameters
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----------
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subdomains : Iterable of Integral or 'all'
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Subdomain IDs (distribcell instance IDs) of interest
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Returns
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----------
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indices : ndarray
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The subdomain indices indexed in the order of the subdomains
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Raises
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------
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ValueError
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When one of the subdomains is not a valid subdomain ID.
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See also
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--------
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MultiGroupXS.get_subdomains(), MultiGroupXS.set_subdomain_index()
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"""
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if subdomains != 'all':
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cv.check_type('subdomains', subdomains, Iterable, Integral)
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if subdomains == 'all':
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num_subdomains = len(self.subdomain_indices)
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indices = np.arange(num_subdomains)
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else:
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indices = np.zeros(len(subdomains), dtype=np.int64)
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for i, subdomain in enumerate(subdomains):
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if subdomain in self.subdomain_indices:
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indices[i] = self.subdomain_indices[subdomain]
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else:
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msg = 'Unable to get index for subdomain "{0}" since it ' \
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'is not a valid subdomain'.format(subdomain)
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raise ValueError(msg)
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return indices
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def get_subdomains(self, indices='all'):
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"""Get the subdomain IDs for one or more indices.
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This method can be used to extract the subdomains for the multi-group
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cross-section from their indices in the tally data array. This is useful
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when the domain type is 'distribcell', in which case one may wish to map
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each subdomain (a cell instance) to its filter bin index in the derived
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multi-group cross-section tally data array.
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Parameters
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----------
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indices : Iterable of Integral or 'all'
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Subdomain indices of interest
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Returns
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----------
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subdomains : ndarray
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Array of subdomain IDs indexed in the order of the indices
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Raises
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------
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ValueError
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When one of the indices is not a valid subdomain index.
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See also
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--------
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MultiGroupXS.get_subdomain_indices(), MultiGroupXS.set_subdomain_index()
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"""
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if indices != 'all':
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cv.check_type('offsets', indices, Iterable, Integral)
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if indices == 'all':
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indices = self.get_subdomain_indices()
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subdomains = np.zeros(len(indices), dtype=np.int64)
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keys = self.subdomain_indices.keys()
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values = self.subdomain_indices.values()
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for i, index in enumerate(indices):
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if index in values:
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subdomains[i] = keys[values.index(index)]
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else:
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msg = 'Unable to get subdomain for index "{0}" since it ' \
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'is not a valid index'.format(index)
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raise ValueError(msg)
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return subdomains
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@abc.abstractmethod
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def create_tallies(self, scores, all_filters, keys, estimator):
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"""Instantiates tallies needed to compute the multi-group cross-section
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"""Instantiates tallies needed to compute the multi-group cross-section.
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This is a helper method for MultiGroupXS subclasses to create tallies
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for input file generation. The tallies are stored in the tallies dict.
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@ -293,94 +384,37 @@ class MultiGroupXS(object):
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for filter in filters:
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self.tallies[key].add_filter(filter)
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def get_subdomain_indices(self, subdomains='all'):
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"""Get the indices for one or more subdomains.
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def load_from_statepoint(self, statepoint):
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"""Extracts tallies in an OpenMC StatePoint with the data needed to
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compute multi-group cross-sections.
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This method can be used to extract the indices into the multi-group
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cross-section tally data array for a subdomain (i.e., cell instance).
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See also : get_subdomains
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This method is needed to compute cross-section data from tallies
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in an OpenMC StatePoint object.
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Parameters
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----------
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subdomains : Iterable of Integral or 'all'
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Subdomain IDs of interest
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Returns
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----------
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indices : ndarray
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The subdomain indices indexed in the order of the subdomains
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Raises
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------
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ValueError
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When one of the subdomains is not a valid subdomain ID.
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statepoint : openmc.StatePoint
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An OpenMC StatePoint object with tally data
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"""
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if subdomains != 'all':
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cv.check_type('subdomains', subdomains, Iterable, Integral)
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cv.check_type('statepoint', statepoint, openmc.statepoint.StatePoint)
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if subdomains == 'all':
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num_subdomains = len(self.subdomain_indices)
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indices = np.arange(num_subdomains)
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else:
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indices = np.zeros(len(subdomains), dtype=np.int64)
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# Ensure that tally metadata has been loaded from the statepoint file
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statepoint.read_results()
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for i, subdomain in enumerate(subdomains):
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if subdomain in self.subdomain_indices:
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indices[i] = self.subdomain_indices[subdomain]
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else:
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msg = 'Unable to get index for subdomain "{0}" since it ' \
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'is not a valid subdomain'.format(subdomain)
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raise ValueError(msg)
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# Create Tallies to search for in StatePoint
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if self.tallies is None:
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self.create_tallies()
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return indices
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def get_subdomains(self, indices='all'):
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"""Get the subdomain IDs for one or more indices.
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This method can be used to extract the subdomains for the multi-group
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cross-section from their indices in the tally data array.
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See also : get_subdomain_indices
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Parameters
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----------
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indices : Iterable of Integral or 'all'
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Subdomain indices of interest
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Returns
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----------
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subdomains : ndarray
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Array of subdomain IDs indexed in the order of the indices
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Raises
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------
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ValueError
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When one of the indices is not a valid subdomain index.
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"""
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if indices != 'all':
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cv.check_type('offsets', indices, Iterable, Integral)
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if indices == 'all':
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indices = self.get_subdomain_indices()
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subdomains = np.zeros(len(indices), dtype=np.int64)
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keys = self.subdomain_indices.keys()
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values = self.subdomain_indices.values()
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for i, index in enumerate(indices):
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if index in values:
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subdomains[i] = keys[values.index(index)]
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else:
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msg = 'Unable to get subdomain for index "{0}" since it ' \
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'is not a valid index'.format(index)
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raise ValueError(msg)
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return subdomains
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# Find, slice and store Tallies from StatePoint
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# The tally slicing is needed if tally merging was used
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for tally_type, tally in self.tallies.items():
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sp_tally = statepoint.get_tally(tally.scores, tally.filters,
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tally.nuclides,
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estimator=tally.estimator)
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sp_tally = sp_tally.get_slice(scores=tally.scores, nuclides=tally.nuclides)
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self.tallies[tally_type] = sp_tally
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def get_xs(self, groups='all', subdomains='all', value='mean'):
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"""Returns an array of multi-group cross-sections.
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@ -412,7 +446,7 @@ class MultiGroupXS(object):
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"""
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if self._xs_tally is None:
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if self.xs_tally is None:
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msg = 'Unable to get cross-section since it has not been computed'
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raise ValueError(msg)
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@ -433,15 +467,23 @@ class MultiGroupXS(object):
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filter_bins.append(self.energy_groups.get_group_bounds(group))
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# Query the multi-group cross-section tally for the data
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xs = self._xs_tally.get_values(filters=filters,
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xs = self.xs_tally.get_values(filters=filters,
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filter_bins=filter_bins, value=value)
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return xs
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def get_condensed_xs(self, coarse_groups):
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"""
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"""Construct an energy-condensed version of this cross-section.
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Parameters
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----------
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coarse_groups : openmc.mgxs.EnergyGroups
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The coarse energy group structure of interest
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Returns
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-------
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MultiGroupXS
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A new MultiGroupXS condensed to the group structure of interest
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:param coarse_groups:
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:return:
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"""
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raise NotImplementedError('Energy condensation is not yet implemented')
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@ -449,6 +491,8 @@ class MultiGroupXS(object):
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def get_subdomain_avg_xs(self, subdomains='all'):
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"""Construct a subdomain-averaged version of this cross-section.
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This is primarily useful for averaging across distribcell instances.
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Parameters
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----------
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subdomains : Iterable of Integral or 'all'
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@ -467,7 +511,7 @@ class MultiGroupXS(object):
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"""
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if self._xs_tally is None:
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if self.xs_tally is None:
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msg = 'Unable to get cross-section since it has not been computed'
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raise ValueError(msg)
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@ -497,6 +541,7 @@ class MultiGroupXS(object):
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# Compute the condensed single group cross-section
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avg_xs.compute_xs()
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return avg_xs
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def print_xs(self, subdomains='all'):
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@ -515,7 +560,7 @@ class MultiGroupXS(object):
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"""
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if self._xs_tally is None:
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if self.xs_tally is None:
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msg = 'Unable to print cross-section since it has not been computed'
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raise ValueError(msg)
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@ -527,7 +572,7 @@ class MultiGroupXS(object):
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string += '{0: <16}=\t{1}\n'.format('\tDomain Type', self.domain_type)
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string += '{0: <16}=\t{1}\n'.format('\tDomain ID', self.domain.id)
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if self._xs_tally is not None:
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if self.xs_tally is not None:
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if subdomains == 'all':
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subdomains = self.get_subdomain_indices()
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@ -581,7 +626,7 @@ class MultiGroupXS(object):
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xs_results['domain'] = self.domain
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xs_results['energy_groups'] = self.energy_groups
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xs_results['tallies'] = self.tallies
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xs_results['xs_tally'] = self._xs_tally
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xs_results['xs_tally'] = self.xs_tally
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xs_results['offset'] = self.offset
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xs_results['subdomain_indices'] = self.subdomain_indices
|
||||
|
||||
|
|
@ -632,36 +677,6 @@ class MultiGroupXS(object):
|
|||
self._offset = xs_results['offset']
|
||||
self._subdomain_indices = xs_results['subdomain_indices']
|
||||
|
||||
def load_from_statepoint(self, statepoint):
|
||||
"""Find tallies in an OpenMC StatePoint with the data needed to compute
|
||||
multi-group cross-sections.
|
||||
|
||||
This method is needed to compute cross-section data from tallies
|
||||
in an OpenMC StatePoint object.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
statepoint : openmc.StatePoint
|
||||
An OpenMC StatePoint object with tally data
|
||||
|
||||
"""
|
||||
|
||||
cv.check_type('statepoint', statepoint, openmc.statepoint.StatePoint)
|
||||
|
||||
statepoint.read_results()
|
||||
|
||||
# Create Tallies to search for in StatePoint
|
||||
if self.tallies is None:
|
||||
self.create_tallies()
|
||||
|
||||
# Find and store Tallies in StatePoint
|
||||
for tally_type, tally in self.tallies.items():
|
||||
sp_tally = statepoint.get_tally(tally.scores, tally.filters,
|
||||
tally.nuclides,
|
||||
estimator=tally.estimator)
|
||||
sp_tally = sp_tally.get_slice(scores=tally.scores, nuclides=tally.nuclides)
|
||||
self.tallies[tally_type] = sp_tally
|
||||
|
||||
def build_hdf5_store(self, filename='mgxs', directory='mgxs',
|
||||
append=True, key=None):
|
||||
"""
|
||||
|
|
@ -701,7 +716,7 @@ class MultiGroupXS(object):
|
|||
|
||||
"""
|
||||
|
||||
if self._xs_tally is None:
|
||||
if self.xs_tally is None:
|
||||
msg = 'Unable to export cross-section since it has not been computed'
|
||||
raise ValueError(msg)
|
||||
|
||||
|
|
@ -749,23 +764,15 @@ class MultiGroupXS(object):
|
|||
|
||||
"""
|
||||
|
||||
if self._xs_tally is None:
|
||||
if self.xs_tally is None:
|
||||
msg = 'Unable to get Pandas DataFrame since the ' \
|
||||
'cross-section has not been computed'
|
||||
raise ValueError(msg)
|
||||
|
||||
# TODO: Reset column labels as cross-sections if needed
|
||||
df = self._xs_tally.get_pandas_dataframe()
|
||||
df = self.xs_tally.get_pandas_dataframe()
|
||||
return df
|
||||
|
||||
def from_statepoint(self, sp):
|
||||
"""
|
||||
|
||||
:return:
|
||||
"""
|
||||
|
||||
# Get the tallies from a statepoint file
|
||||
|
||||
|
||||
class TotalXS(MultiGroupXS):
|
||||
|
||||
|
|
@ -794,8 +801,8 @@ class TotalXS(MultiGroupXS):
|
|||
tally arithmetic"""
|
||||
|
||||
self._xs_tally = self.tallies['total'] / self.tallies['flux']
|
||||
self._xs_tally._mean = np.nan_to_num(self._xs_tally.mean)
|
||||
self._xs_tally._std_dev = np.nan_to_num(self._xs_tally.std_dev)
|
||||
self._xs_tally._mean = np.nan_to_num(self.xs_tally.mean)
|
||||
self._xs_tally._std_dev = np.nan_to_num(self.xs_tally.std_dev)
|
||||
|
||||
|
||||
class TransportXS(MultiGroupXS):
|
||||
|
|
@ -832,8 +839,8 @@ class TransportXS(MultiGroupXS):
|
|||
|
||||
self._xs_tally = self.tallies['total'] - self.tallies['scatter-P1']
|
||||
self._xs_tally /= self.tallies['flux']
|
||||
self._xs_tally._mean = np.nan_to_num(self._xs_tally.mean)
|
||||
self._xs_tally._std_dev = np.nan_to_num(self._xs_tally.std_dev)
|
||||
self._xs_tally._mean = np.nan_to_num(self.xs_tally.mean)
|
||||
self._xs_tally._std_dev = np.nan_to_num(self.xs_tally.std_dev)
|
||||
|
||||
|
||||
class AbsorptionXS(MultiGroupXS):
|
||||
|
|
@ -863,8 +870,8 @@ class AbsorptionXS(MultiGroupXS):
|
|||
tally arithmetic"""
|
||||
|
||||
self._xs_tally = self.tallies['absorption'] / self.tallies['flux']
|
||||
self._xs_tally._mean = np.nan_to_num(self._xs_tally.mean)
|
||||
self._xs_tally._std_dev = np.nan_to_num(self._xs_tally.std_dev)
|
||||
self._xs_tally._mean = np.nan_to_num(self.xs_tally.mean)
|
||||
self._xs_tally._std_dev = np.nan_to_num(self.xs_tally.std_dev)
|
||||
|
||||
|
||||
class CaptureXS(MultiGroupXS):
|
||||
|
|
@ -895,8 +902,8 @@ class CaptureXS(MultiGroupXS):
|
|||
|
||||
self._xs_tally = self.tallies['absorption'] - self.tallies['fission']
|
||||
self._xs_tally /= self.tallies['flux']
|
||||
self._xs_tally._mean = np.nan_to_num(self._xs_tally.mean)
|
||||
self._xs_tally._std_dev = np.nan_to_num(self._xs_tally.std_dev)
|
||||
self._xs_tally._mean = np.nan_to_num(self.xs_tally.mean)
|
||||
self._xs_tally._std_dev = np.nan_to_num(self.xs_tally.std_dev)
|
||||
|
||||
|
||||
class FissionXS(MultiGroupXS):
|
||||
|
|
@ -926,8 +933,8 @@ class FissionXS(MultiGroupXS):
|
|||
tally arithmetic"""
|
||||
|
||||
self._xs_tally = self.tallies['fission'] / self.tallies['flux']
|
||||
self._xs_tally._mean = np.nan_to_num(self._xs_tally.mean)
|
||||
self._xs_tally._std_dev = np.nan_to_num(self._xs_tally.std_dev)
|
||||
self._xs_tally._mean = np.nan_to_num(self.xs_tally.mean)
|
||||
self._xs_tally._std_dev = np.nan_to_num(self.xs_tally.std_dev)
|
||||
|
||||
|
||||
class NuFissionXS(MultiGroupXS):
|
||||
|
|
@ -957,8 +964,8 @@ class NuFissionXS(MultiGroupXS):
|
|||
tally arithmetic"""
|
||||
|
||||
self._xs_tally = self.tallies['nu-fission'] / self.tallies['flux']
|
||||
self._xs_tally._mean = np.nan_to_num(self._xs_tally.mean)
|
||||
self._xs_tally._std_dev = np.nan_to_num(self._xs_tally.std_dev)
|
||||
self._xs_tally._mean = np.nan_to_num(self.xs_tally.mean)
|
||||
self._xs_tally._std_dev = np.nan_to_num(self.xs_tally.std_dev)
|
||||
|
||||
|
||||
class ScatterXS(MultiGroupXS):
|
||||
|
|
@ -988,8 +995,8 @@ class ScatterXS(MultiGroupXS):
|
|||
OpenMC tally arithmetic"""
|
||||
|
||||
self._xs_tally = self.tallies['scatter'] / self.tallies['flux']
|
||||
self._xs_tally._mean = np.nan_to_num(self._xs_tally.mean)
|
||||
self._xs_tally._std_dev = np.nan_to_num(self._xs_tally.std_dev)
|
||||
self._xs_tally._mean = np.nan_to_num(self.xs_tally.mean)
|
||||
self._xs_tally._std_dev = np.nan_to_num(self.xs_tally.std_dev)
|
||||
|
||||
|
||||
class NuScatterXS(MultiGroupXS):
|
||||
|
|
@ -1019,8 +1026,8 @@ class NuScatterXS(MultiGroupXS):
|
|||
tally arithmetic"""
|
||||
|
||||
self._xs_tally = self.tallies['nu-scatter'] / self.tallies['flux']
|
||||
self._xs_tally._mean = np.nan_to_num(self._xs_tally.mean)
|
||||
self._xs_tally._std_dev = np.nan_to_num(self._xs_tally.std_dev)
|
||||
self._xs_tally._mean = np.nan_to_num(self.xs_tally.mean)
|
||||
self._xs_tally._std_dev = np.nan_to_num(self.xs_tally.std_dev)
|
||||
|
||||
|
||||
class ScatterMatrixXS(MultiGroupXS):
|
||||
|
|
@ -1067,8 +1074,8 @@ class ScatterMatrixXS(MultiGroupXS):
|
|||
rxn_tally = self.tallies['scatter']
|
||||
|
||||
self._xs_tally = rxn_tally / self.tallies['flux']
|
||||
self._xs_tally._mean = np.nan_to_num(self._xs_tally.mean)
|
||||
self._xs_tally._std_dev = np.nan_to_num(self._xs_tally.std_dev)
|
||||
self._xs_tally._mean = np.nan_to_num(self.xs_tally.mean)
|
||||
self._xs_tally._std_dev = np.nan_to_num(self.xs_tally.std_dev)
|
||||
|
||||
def get_xs(self, in_groups='all', out_groups='all',
|
||||
subdomains='all', value='mean'):
|
||||
|
|
@ -1103,7 +1110,7 @@ class ScatterMatrixXS(MultiGroupXS):
|
|||
|
||||
"""
|
||||
|
||||
if self._xs_tally is None:
|
||||
if self.xs_tally is None:
|
||||
msg = 'Unable to get cross-section since it has not been computed'
|
||||
raise ValueError(msg)
|
||||
|
||||
|
|
@ -1131,7 +1138,7 @@ class ScatterMatrixXS(MultiGroupXS):
|
|||
filter_bins.append(self.energy_groups.get_group_bounds(out_group))
|
||||
|
||||
# Query the multi-group cross-section tally for the data
|
||||
xs = self._xs_tally.get_values(filters=filters,
|
||||
xs = self.xs_tally.get_values(filters=filters,
|
||||
filter_bins=filter_bins, value=value)
|
||||
return xs
|
||||
|
||||
|
|
@ -1151,7 +1158,7 @@ class ScatterMatrixXS(MultiGroupXS):
|
|||
|
||||
"""
|
||||
|
||||
if self._xs_tally is None:
|
||||
if self.xs_tally is None:
|
||||
msg = 'Unable to print cross-section since it has not been computed'
|
||||
raise ValueError(msg)
|
||||
|
||||
|
|
@ -1239,8 +1246,8 @@ class NuScatterMatrixXS(ScatterMatrixXS):
|
|||
rxn_tally = self.tallies['nu-scatter']
|
||||
|
||||
self._xs_tally = rxn_tally / self.tallies['flux']
|
||||
self._xs_tally._mean = np.nan_to_num(self._xs_tally.mean)
|
||||
self._xs_tally._std_dev = np.nan_to_num(self._xs_tally.std_dev)
|
||||
self._xs_tally._mean = np.nan_to_num(self.xs_tally.mean)
|
||||
self._xs_tally._std_dev = np.nan_to_num(self.xs_tally.std_dev)
|
||||
|
||||
class Chi(MultiGroupXS):
|
||||
|
||||
|
|
@ -1292,7 +1299,7 @@ class Chi(MultiGroupXS):
|
|||
self._xs_tally = nu_fission_out / sum_nu_fission_in
|
||||
|
||||
# Normalize chi to 1.0
|
||||
norm = self._xs_tally.summation(filters=['energyout'],
|
||||
norm = self.xs_tally.summation(filters=['energyout'],
|
||||
filter_bins=energy_bins)
|
||||
|
||||
# FIXME: CrossFilter for energy + energy messes up tally arithmetic
|
||||
|
|
@ -1304,7 +1311,7 @@ class Chi(MultiGroupXS):
|
|||
norm = norm.tile_filter(energy_filter)
|
||||
|
||||
self._xs_tally /= norm
|
||||
self._xs_tally._mean = np.nan_to_num(self._xs_tally.mean)
|
||||
self._xs_tally._std_dev = np.nan_to_num(self._xs_tally.std_dev)
|
||||
self._xs_tally._mean = np.nan_to_num(self.xs_tally.mean)
|
||||
self._xs_tally._std_dev = np.nan_to_num(self.xs_tally.std_dev)
|
||||
|
||||
# FIXME: Does this need to reset NaNs to zero?
|
||||
Loading…
Add table
Add a link
Reference in a new issue