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Added ability to convert the isotropic or angle representation from one to the other for XSdata objects and MGXSLibrary objects
This commit is contained in:
Adam Nelson
parent
6e3f6bf8b1
commit
756a43f1c5
2 changed files with 194 additions and 4 deletions
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@ -205,7 +205,7 @@ class MGXS(object):
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clone._name = self.name
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clone._rxn_type = self.rxn_type
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clone._by_nuclide = self.by_nuclide
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clone._nuclides = copy.deepcopy(self._nuclides)
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clone._nuclides = copy.deepcopy(self._nuclides, memo)
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clone._domain = self.domain
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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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@ -1,4 +1,4 @@
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from collections import Iterable
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import copy
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from numbers import Real, Integral
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import os
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@ -185,6 +185,52 @@ class XSdata(object):
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self._inverse_velocity = len(temperatures) * [None]
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self._xs_shapes = None
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def __deepcopy__(self, memo):
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existing = memo.get(id(self))
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# If this is the first time we have tried to copy this object, copy it
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if existing is None:
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clone = type(self).__new__(type(self))
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clone._name = self.name
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clone._energy_groups = copy.deepcopy(self.energy_groups, memo)
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clone._num_delayed_groups = self.num_delayed_groups
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clone._temperatures = copy.deepcopy(self.temperatures, memo)
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clone._drepresentation = self.representation
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clone._atomic_weight_ratio = self._atomic_weight_ratio
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clone._fissionable = self._fissionable
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clone._scatter_format = self._scatter_format
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clone._order = self._order
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clone._num_polar = self._num_polar
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clone._num_azimuthal = self._num_azimuthal
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clone._total = copy.deepcopy(self._total, memo)
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clone._absorption = copy.deepcopy(self._absorption, memo)
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clone._scatter_matrix = copy.deepcopy(self._scatter_matrix, memo)
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clone._multiplicity_matrix = \
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copy.deepcopy(self._multiplicity_matrix, memo)
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clone._fission = copy.deepcopy(self._fission, memo)
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clone._nu_fission = copy.deepcopy(self._nu_fission, memo)
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clone._prompt_nu_fission = \
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copy.deepcopy(self._prompt_nu_fission, memo)
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clone._delayed_nu_fission = \
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copy.deepcopy(self._delayed_nu_fission, memo)
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clone._kappa_fission = copy.deepcopy(self._kappa_fission, memo)
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clone._chi = copy.deepcopy(self._chi, memo)
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clone._chi_prompt = copy.deepcopy(self._chi_prompt, memo)
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clone._chi_delayed = copy.deepcopy(self._chi_delayed, memo)
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clone._beta = copy.deepcopy(self._beta, memo)
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clone._decay_rate = copy.deepcopy(self._decay_rate, memo)
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clone._inverse_velocity = \
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copy.deepcopy(self._inverse_velocity, memo)
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clone._xs_shapes = copy.deepcopy(self._xs_shapes, memo)
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memo[id(self)] = clone
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return clone
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# If this object has been copied before, return the first copy made
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else:
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return existing
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@property
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def name(self):
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return self._name
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@ -348,7 +394,7 @@ class XSdata(object):
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@representation.setter
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def representation(self, representation):
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# Check it is of valid type.
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# Check it is of valid value.
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check_value('representation', representation, _REPRESENTATIONS)
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self._representation = representation
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@ -1622,7 +1668,8 @@ class XSdata(object):
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"""
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check_type('inverse_velocity', inverse_velocity, openmc.mgxs.InverseVelocity)
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check_type('inverse_velocity', inverse_velocity,
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openmc.mgxs.InverseVelocity)
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check_value('energy_groups', inverse_velocity.energy_groups,
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[self.energy_groups])
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check_value('domain_type', inverse_velocity.domain_type,
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@ -1634,6 +1681,89 @@ class XSdata(object):
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self._inverse_velocity[i] = inverse_velocity.get_xs(
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nuclides=nuclide, xs_type=xs_type, subdomains=subdomain)
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def convert_representation(self, target_representation, num_polar=None,
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num_azimuthal=None):
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"""Produce a new XSdata object with the same data, but converted to the
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new representation
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Parameters
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----------
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target_representation : {'isotropic', 'angle'}
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Representation of the MGXS (isotropic or angle-dependent flux
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weighting).
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num_polar : int, optional
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Number of equal width angular bins that the polar angular
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domain is subdivided into. This is required when
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:param:`target_representation` is "angle".
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num_azimuthal : int, optional
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Number of equal width angular bins that the azimuthal angular
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domain is subdivided into. This is required when
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:param:`target_representation` is "angle".
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Returns
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-------
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openmc.XSdata
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Multi-group cross section data with the same data as self, but
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represented as specified in :param:`target_representation`.
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"""
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check_value('target_representation', target_representation,
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_REPRESENTATIONS)
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if target_representation == 'angle':
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check_type('num_polar', num_polar, Integral)
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check_type('num_azimuthal', num_azimuthal, Integral)
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check_greater_than('num_polar', num_polar, 0)
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check_greater_than('num_azimuthal', num_azimuthal, 0)
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xsdata = copy.deepcopy(self)
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if target_representation == self.representation:
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# Check to make sure the num_polar and num_azimuthal values match
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if target_representation == 'angle':
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if num_polar != self.num_polar or num_azimuthal != self.num_azimuthal:
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raise NotImplementedError("XSdata.convert_representation "
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"cannot translate between "
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"`angle` representations with "
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"different angle bin structures")
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# Nothing to do
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return xsdata
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types = ['total', 'absorption', 'fission', 'nu_fission',
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'scatter_matrix', 'multiplicity_matrix', 'prompt_nu_fission',
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'delayed_nu_fission', 'kappa_fission', 'chi', 'chi_prompt',
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'chi_delayed', 'beta', 'decay_rate', 'inverse_velocity']
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xsdata.representation = target_representation
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# We have different actions depending on the representation conversion
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if target_representation == 'isotropic':
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xsdata.num_polar = None
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xsdata.num_azimuthal = None
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for i, temp in enumerate(xsdata.temperatures):
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for xs in types:
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# Get the original data
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orig_data = getattr(self, '_' + xs)[i]
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# Since we are going from angle to isotropic, the current
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# data should be just averaged over the angle bins
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new_data = orig_data.mean(axis=(0, 1))
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setter = getattr(xsdata, 'set_' + xs)
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setter(new_data, temp)
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elif target_representation == 'angle':
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xsdata.num_polar = num_polar
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xsdata.num_azimuthal = num_azimuthal
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for i, temp in enumerate(xsdata.temperatures):
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for xs in types:
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# Get the original data
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orig_data = getattr(self, '_' + xs)[i]
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# Since we are going from isotropic to angle, the current
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# data should be just copied for every polar/azimuthal bin
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new_shape = (num_polar, num_azimuthal) + orig_data.shape
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new_data = np.resize(orig_data, new_shape)
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setter = getattr(xsdata, 'set_' + xs)
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setter(new_data, temp)
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return xsdata
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def to_hdf5(self, file):
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"""Write XSdata to an HDF5 file
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@ -1995,6 +2125,24 @@ class MGXSLibrary(object):
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self.num_delayed_groups = num_delayed_groups
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self._xsdatas = []
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def __deepcopy__(self, memo):
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existing = memo.get(id(self))
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# If this is the first time we have tried to copy this object, copy it
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if existing is None:
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clone = type(self).__new__(type(self))
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clone._energy_groups = copy.deepcopy(self.energy_groups, memo)
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clone._num_delayed_groups = self.num_delayed_groups
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clone._xsdatas = copy.deepcopy(self.xsdatas, memo)
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memo[id(self)] = clone
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return clone
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# If this object has been copied before, return the first copy made
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else:
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return existing
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@property
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def energy_groups(self):
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return self._energy_groups
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@ -2099,6 +2247,48 @@ class MGXSLibrary(object):
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result = xsdata
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return result
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def convert_representation(self, target_representation, num_polar=None,
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num_azimuthal=None):
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"""Produce a new MGXSLibrary object with the same data, but converted
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to the new representation
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Parameters
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----------
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target_representation : {'isotropic', 'angle'}
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Representation of the MGXS (isotropic or angle-dependent flux
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weighting).
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num_polar : int, optional
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Number of equal width angular bins that the polar angular
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domain is subdivided into. This is required when
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:param:`target_representation` is "angle".
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num_azimuthal : int, optional
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Number of equal width angular bins that the azimuthal angular
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domain is subdivided into. This is required when
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:param:`target_representation` is "angle".
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Returns
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-------
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openmc.MGXSLibrary
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Multi-group Library with the same data as self, but represented as
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specified in :param:`target_representation`.
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"""
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check_value('target_representation', target_representation,
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_REPRESENTATIONS)
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if target_representation == 'angle':
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check_type('num_polar', num_polar, Integral)
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check_type('num_azimuthal', num_azimuthal, Integral)
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check_greater_than('num_polar', num_polar, 0)
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check_greater_than('num_azimuthal', num_azimuthal, 0)
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library = copy.deepcopy(self)
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for i, xsdata in enumerate(self.xsdatas):
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library.xsdatas[i] = \
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xsdata.convert_representation(target_representation,
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num_polar, num_azimuthal)
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return library
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def export_to_hdf5(self, filename='mgxs.h5'):
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"""Create an hdf5 file that can be used for a simulation.
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