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Updated python api to support new MGXS Library format
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Adam Nelson
parent
0c92b18a1e
commit
35c8caaae8
2 changed files with 471 additions and 425 deletions
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@ -822,11 +822,12 @@ class Library(object):
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return pickle.load(open(full_filename, 'rb'))
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def get_xsdata(self, domain, xsdata_name, nuclide='total', xs_type='macro',
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order=None, tabular_legendre=None, tabular_points=33,
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subdomain=None):
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order=None, subdomain=None):
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"""Generates an openmc.XSdata object describing a multi-group cross section
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data set for eventual combination in to an openmc.MGXSLibrary object
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(i.e., the library).
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(i.e., the library). Note that this method does not build an XSdata
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object with nested temperature tables. The temperature of each
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XsData object will be left at the default value of 300K.
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Parameters
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----------
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@ -845,18 +846,6 @@ class Library(object):
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Scattering order for this data entry. Default is None,
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which will set the XSdata object to use the order of the
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Library.
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tabular_legendre : None or bool
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Flag to denote whether or not the Legendre expansion of the
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scattering angular distribution is to be converted to a tabular
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representation by OpenMC. A value of `True` means that it is to be
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converted while a value of `False` means that it will not be.
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Defaults to `None` which leaves the default behavior of OpenMC in
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place (the distribution is converted to a tabular representation).
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tabular_points : int
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This parameter is not used unless the ``tabular_legendre``
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parameter is set to `True`. In this case, this parameter sets the
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number of equally-spaced points in the domain of [-1,1] to be used
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in building the tabular distribution. Default is `33`.
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subdomain : iterable of int
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This parameter is not used unless using a mesh domain. In that
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case, the subdomain is an [i,j,k] index (1-based indexing) of the
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@ -890,10 +879,6 @@ class Library(object):
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if order is not None:
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cv.check_greater_than('order', order, 0, equality=True)
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cv.check_less_than('order', order, 10, equality=True)
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cv.check_type('tabular_legendre', tabular_legendre,
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(type(None), bool))
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if tabular_points is not None:
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cv.check_greater_than('tabular_points', tabular_points, 1)
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if subdomain is not None:
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cv.check_iterable_type('subdomain', subdomain, Integral,
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max_depth=3)
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@ -922,11 +907,6 @@ class Library(object):
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# the provided order or the Library's order.
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xsdata.order = min(order, self.legendre_order)
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# Set the tabular_legendre option if needed
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if tabular_legendre is not None:
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xsdata.tabular_legendre = {'enable': tabular_legendre,
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'num_points': tabular_points}
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if nuclide is not 'total':
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xsdata.zaid = self._nuclides[nuclide][0]
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xsdata.awr = self._nuclides[nuclide][1]
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@ -979,48 +959,52 @@ class Library(object):
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# If multiplicity matrix is available, prefer that
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if 'multiplicity matrix' in self.mgxs_types:
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mymgxs = self.get_mgxs(domain, 'multiplicity matrix')
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xsdata.set_multiplicity_mgxs(mymgxs, xs_type=xs_type,
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nuclide=[nuclide],
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subdomain=subdomain)
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xsdata.set_multiplicity_matrix_mgxs(mymgxs, xs_type=xs_type,
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nuclide=[nuclide],
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subdomain=subdomain)
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using_multiplicity = True
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# multiplicity will fall back to using scatter and nu-scatter
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elif ((('scatter matrix' in self.mgxs_types) and
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('nu-scatter matrix' in self.mgxs_types))):
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scatt_mgxs = self.get_mgxs(domain, 'scatter matrix')
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nuscatt_mgxs = self.get_mgxs(domain, 'nu-scatter matrix')
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xsdata.set_multiplicity_mgxs(nuscatt_mgxs, scatt_mgxs,
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xs_type=xs_type, nuclide=[nuclide],
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subdomain=subdomain)
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xsdata.set_multiplicity_matrix_mgxs(nuscatt_mgxs, scatt_mgxs,
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xs_type=xs_type,
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nuclide=[nuclide],
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subdomain=subdomain)
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using_multiplicity = True
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else:
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using_multiplicity = False
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if using_multiplicity:
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nuscatt_mgxs = self.get_mgxs(domain, 'nu-scatter matrix')
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xsdata.set_scatter_mgxs(nuscatt_mgxs, xs_type=xs_type,
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nuclide=[nuclide], subdomain=subdomain)
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xsdata.set_scatter_matrix_mgxs(nuscatt_mgxs, xs_type=xs_type,
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nuclide=[nuclide],
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subdomain=subdomain)
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else:
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if 'nu-scatter matrix' in self.mgxs_types:
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nuscatt_mgxs = self.get_mgxs(domain, 'nu-scatter matrix')
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xsdata.set_scatter_mgxs(nuscatt_mgxs, xs_type=xs_type,
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nuclide=[nuclide],
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subdomain=subdomain)
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xsdata.set_scatter_matrix_mgxs(nuscatt_mgxs, xs_type=xs_type,
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nuclide=[nuclide],
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subdomain=subdomain)
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# Since we are not using multiplicity, then
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# scattering multiplication (nu-scatter) must be
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# accounted for approximately by using an adjusted
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# absorption cross section.
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if 'total' in self.mgxs_types:
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xsdata.absorption = \
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np.subtract(xsdata.total,
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np.sum(xsdata.scatter[0, :, :], axis=1))
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for i in range(len(xsdata.temperatures)):
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xsdata._absorption[i] = \
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np.subtract(xsdata._total[i], np.sum(
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xsdata._scatter_matrix[i][0, :, :], axis=1))
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return xsdata
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def create_mg_library(self, xs_type='macro', xsdata_names=None,
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tabular_legendre=None, tabular_points=33):
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def create_mg_library(self, xs_type='macro', xsdata_names=None):
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"""Creates an openmc.MGXSLibrary object to contain the MGXS data for the
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Multi-Group mode of OpenMC.
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Multi-Group mode of OpenMC. Note that this library will not make use
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of nested temperature tables. Every dataset in te library will be
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treated as if it was at the same default temperature.
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Parameters
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----------
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@ -1031,18 +1015,6 @@ class Library(object):
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xsdata_names : Iterable of str
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List of names to apply to the "xsdata" entries in the
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resultant mgxs data file. Defaults to 'set1', 'set2', ...
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tabular_legendre : None or bool
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Flag to denote whether or not the Legendre expansion of the
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scattering angular distribution is to be converted to a tabular
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representation by OpenMC. A value of `True` means that it is to be
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converted while a value of `False` means that it will not be.
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Defaults to `None` which leaves the default behavior of OpenMC in
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place (the distribution is converted to a tabular representation).
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tabular_points : int
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This parameter is not used unless the ``tabular_legendre``
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parameter is set to `True`. In this case, this parameter sets the
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number of equally-spaced points in the domain of [-1,1] to be used
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in building the tabular distribution. Default is `33`.
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Returns
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-------
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@ -1094,8 +1066,6 @@ class Library(object):
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# Create XSdata and Macroscopic for this domain
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xsdata = self.get_xsdata(domain, xsdata_name,
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tabular_legendre=tabular_legendre,
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tabular_points=tabular_points,
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subdomain=subdomain)
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mgxs_file.add_xsdata(xsdata)
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i += 1
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@ -1117,16 +1087,13 @@ class Library(object):
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xsdata_name += '_' + nuclide
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xsdata = self.get_xsdata(domain, xsdata_name,
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nuclide=nuclide, xs_type=xs_type,
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tabular_legendre=tabular_legendre,
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tabular_points=tabular_points)
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nuclide=nuclide, xs_type=xs_type)
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mgxs_file.add_xsdata(xsdata)
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return mgxs_file
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def create_mg_mode(self, xsdata_names=None, tabular_legendre=None,
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tabular_points=33, bc=['reflective'] * 6):
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def create_mg_mode(self, xsdata_names=None, bc=['reflective'] * 6):
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"""Creates an openmc.MGXSLibrary object to contain the MGXS data for the
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Multi-Group mode of OpenMC as well as the associated openmc.Materials
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and openmc.Geometry objects. The created Geometry is the same as that
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@ -1134,24 +1101,15 @@ class Library(object):
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modifications to point to newly-created Materials which point to the
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multi-group data. This method only creates a macroscopic
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MGXS Library even if nuclidic tallies are specified in the Library.
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Note that this library will not make use of nested temperature tables.
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Every dataset in te library will be treated as if it was at the same
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default temperature.
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Parameters
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----------
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xsdata_names : Iterable of str
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List of names to apply to the "xsdata" entries in the
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resultant mgxs data file. Defaults to 'set1', 'set2', ...
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tabular_legendre : None or bool
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Flag to denote whether or not the Legendre expansion of the
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scattering angular distribution is to be converted to a tabular
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representation by OpenMC. A value of `True` means that it is to be
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converted while a value of `False` means that it will not be.
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Defaults to `None` which leaves the default behavior of OpenMC in
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place (the distribution is converted to a tabular representation).
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tabular_points : int
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This parameter is not used unless the ``tabular_legendre``
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parameter is set to `True`. In this case, this parameter sets the
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number of equally-spaced points in the domain of [-1,1] to be used
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in building the tabular distribution. Default is `33`.
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bc : iterable of {'reflective', 'periodic', 'transmission', or 'vacuum'}
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Boundary conditions for each of the four faces of a rectangle
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(if applying to a 2D mesh) or six faces of a parallelepiped
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@ -1198,8 +1156,7 @@ class Library(object):
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cv.check_length("domains", self.domains, 1, 1)
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# Get the MGXS File Data
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mgxs_file = self.create_mg_library('macro', xsdata_names,
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tabular_legendre, tabular_points)
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mgxs_file = self.create_mg_library('macro', xsdata_names)
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# Now move on the creating the geometry and assigning materials
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if self.domain_type == 'mesh':
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