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Merging with angles branch and renaming the MGXSLibrary.__getitem__ to get_by_name
This commit is contained in:
Adam Nelson
commit
2e0e37c305
8 changed files with 66 additions and 39 deletions
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@ -1,3 +1,5 @@
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import numpy as np
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import openmc
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import openmc.mgxs
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@ -26,7 +28,7 @@ uo2_xsdata.set_total(
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0.5644058])
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uo2_xsdata.set_absorption([8.0248E-03, 3.7174E-03, 2.6769E-02, 9.6236E-02,
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3.0020E-02, 1.1126E-01, 2.8278E-01])
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uo2_xsdata.set_scatter_matrix(
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scatter_matrix = np.array(
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[[[0.1275370, 0.0423780, 0.0000094, 0.0000000, 0.0000000, 0.0000000, 0.0000000],
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[0.0000000, 0.3244560, 0.0016314, 0.0000000, 0.0000000, 0.0000000, 0.0000000],
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[0.0000000, 0.0000000, 0.4509400, 0.0026792, 0.0000000, 0.0000000, 0.0000000],
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@ -34,6 +36,8 @@ uo2_xsdata.set_scatter_matrix(
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[0.0000000, 0.0000000, 0.0000000, 0.0001253, 0.2714010, 0.0102550, 0.0000000],
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[0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0012968, 0.2658020, 0.0168090],
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[0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0085458, 0.2730800]]])
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scatter_matrix = np.rollaxis(scatter_matrix, 0, 3)
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uo2_xsdata.set_scatter_matrix(scatter_matrix)
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uo2_xsdata.set_fission([7.21206E-03, 8.19301E-04, 6.45320E-03,
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1.85648E-02, 1.78084E-02, 8.30348E-02,
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2.16004E-01])
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@ -50,7 +54,7 @@ h2o_xsdata.set_total([0.15920605, 0.412969593, 0.59030986, 0.58435,
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h2o_xsdata.set_absorption([6.0105E-04, 1.5793E-05, 3.3716E-04,
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1.9406E-03, 5.7416E-03, 1.5001E-02,
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3.7239E-02])
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h2o_xsdata.set_scatter_matrix(
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scatter_matrix = np.array(
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[[[0.0444777, 0.1134000, 0.0007235, 0.0000037, 0.0000001, 0.0000000, 0.0000000],
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[0.0000000, 0.2823340, 0.1299400, 0.0006234, 0.0000480, 0.0000074, 0.0000010],
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[0.0000000, 0.0000000, 0.3452560, 0.2245700, 0.0169990, 0.0026443, 0.0005034],
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@ -58,6 +62,8 @@ h2o_xsdata.set_scatter_matrix(
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[0.0000000, 0.0000000, 0.0000000, 0.0000714, 0.1391380, 0.5118200, 0.0612290],
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[0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0022157, 0.6999130, 0.5373200],
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[0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.1324400, 2.4807000]]])
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scatter_matrix = np.rollaxis(scatter_matrix, 0, 3)
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h2o_xsdata.set_scatter_matrix(scatter_matrix)
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mg_cross_sections_file = openmc.MGXSLibrary(groups)
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mg_cross_sections_file.add_xsdatas([uo2_xsdata, h2o_xsdata])
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Binary file not shown.
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@ -100,10 +100,13 @@ class Filter(object):
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@classmethod
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def _recursive_subclasses(cls):
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"""Return all subclasses and their subclasses, etc."""
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subs = cls.__subclasses__()
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subsubs = [grand for s in subs for grand in s.__subclasses__()]
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subsubsubs = [grand for s in subsubs for grand in s.__subclasses__()]
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return subs + subsubs + subsubsubs
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all_subclasses = []
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for subclass in cls.__subclasses__():
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all_subclasses.append(subclass)
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all_subclasses.extend(subclass._recursive_subclasses())
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return all_subclasses
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@classmethod
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def from_hdf5(cls, group, **kwargs):
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@ -59,7 +59,7 @@ class Library(object):
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The spatial domain(s) for which MGXS in the Library are computed
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correction : {'P0', None}
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Apply the P0 correction to scattering matrices if set to 'P0'
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scatter_format : {'legendre', or 'histogram'}
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scatter_format : {'legendre', 'histogram'}
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Representation of the angular scattering distribution (default is
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'legendre')
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legendre_order : int
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@ -1532,9 +1532,19 @@ class MGXS(object):
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else:
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df = df.drop('score', axis=1)
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# Determine if change-in-angle bins are included in the MGXS to
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# properly tile the group boundaries
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if 'mu low' in df:
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# Find the length of the mu filters indirectly from the number
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# of times the mu bins repeats.
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num_mu = int(df.shape[0] /
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df[df['mu low'] == df['mu low'][0]].shape[0])
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else:
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num_mu = 1
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# Override energy groups bounds with indices
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all_groups = np.arange(self.num_groups, 0, -1, dtype=np.int)
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all_groups = np.repeat(all_groups, len(query_nuclides))
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all_groups = np.repeat(all_groups, len(query_nuclides) * num_mu)
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if 'energy low [eV]' in df and 'energyout low [eV]' in df:
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df.rename(columns={'energy low [eV]': 'group in'},
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inplace=True)
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@ -3795,10 +3805,8 @@ class ScatterMatrixXS(MatrixMGXS):
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# than 1, so try each axis in axes one at a time, catching the
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# ValueError as needed.
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for axis in axes:
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try:
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if xs.shape[axis] == 1:
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xs = np.squeeze(xs, axis=axis)
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except ValueError:
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pass
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return xs
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@ -3878,9 +3886,12 @@ class ScatterMatrixXS(MatrixMGXS):
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df = df[df['moment'] == 'P{}'.format(moment)]
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elif self.scatter_format == 'histogram':
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# Add a change-in-angle (mu) column to dataframe
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###TODO NOT SURE I NEED TO DO THIS
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pass
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# Replace the mu low and mu high columns with a single mu bin
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del df['mu high']
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df.rename(columns={'mu low': 'mu bins'}, inplace=True)
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bins = [i + 1 for i in range(self.histogram_bins)]
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bins = np.tile(bins, int(df.shape[0] / len(bins)))
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df['mu bins'] = bins
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return df
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@ -1784,8 +1784,14 @@ class XSdata(object):
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np.sum(self._scatter_matrix[i][p, a, g_in, :, :],
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axis=1)
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nz = np.nonzero(matrix)
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g_out_bounds[p, a, g_in, 0] = nz[0][0]
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g_out_bounds[p, a, g_in, 1] = nz[0][-1]
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# It is possible that there only zeros in matrix
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# and therefore nz will be empty, in that case set
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# g_out_bounds to 0s
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if len(nz[0]) == 0:
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g_out_bounds[p, a, g_in, :] = 0
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else:
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g_out_bounds[p, a, g_in, 0] = nz[0][0]
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g_out_bounds[p, a, g_in, 1] = nz[0][-1]
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# Now create the flattened scatter matrix array
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flat_scatt = []
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@ -2006,27 +2012,6 @@ 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 __getitem__(self, name):
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"""Access the XSdata objects by name
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Parameters
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----------
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name : str
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Name of openmc.XSdata object to obtain
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Returns
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-------
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result : openmc.XSdata or None
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Provides the matching XSdata object or None, if not found
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"""
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check_type("name", name, str)
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result = None
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for xsdata in self.xsdatas:
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if name == xsdata.name:
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result = xsdata
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return result
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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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@ -2110,6 +2095,27 @@ class MGXSLibrary(object):
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self._xsdatas.remove(xsdata)
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def get_by_name(self, name):
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"""Access the XSdata objects by name
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Parameters
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----------
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name : str
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Name of openmc.XSdata object to obtain
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Returns
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-------
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result : openmc.XSdata or None
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Provides the matching XSdata object or None, if not found
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"""
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check_type("name", name, str)
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result = None
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for xsdata in self.xsdatas:
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if name == xsdata.name:
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result = xsdata
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return result
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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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@ -722,7 +722,7 @@ def _calculate_mgxs_nuc_macro(this, types, library, orders=None,
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if orders[i]:
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cv.check_greater_than("order value", orders[i], 0, equality=True)
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xsdata = library[this.name]
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xsdata = library.get_by_name(this.name)
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if xsdata is not None:
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# Obtain the nearest temperature
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@ -3,13 +3,14 @@
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import os
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import sys
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sys.path.insert(0, os.pardir)
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import numpy as np
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from testing_harness import PyAPITestHarness
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from openmc.filter import *
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from openmc import Mesh, Tally, Tallies
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from openmc.source import Source
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from openmc.stats import Box
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class TalliesTestHarness(PyAPITestHarness):
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def _build_inputs(self):
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# Build default materials/geometry
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