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Style and changed sampling to produce ResonanceRange objects
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Isaac Meyer
parent
1beab30db6
commit
c22b36e0c8
4 changed files with 113 additions and 111 deletions
File diff suppressed because one or more lines are too long
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@ -233,7 +233,7 @@ class IncidentNeutron(EqualityMixin):
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@property
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def resonance_covariance(self):
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return self._resoncance_covariance
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return self._resonance_covariance
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@property
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def summed_reactions(self):
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@ -298,8 +298,9 @@ class IncidentNeutron(EqualityMixin):
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@resonance_covariance.setter
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def resonance_covariance(self, resonance_covariance):
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cv.check_type('resonances', resonances, res_cov.ResonanceCovariance)
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self._resonacne_covariance = resonance_covariance
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cv.check_type('resonance covariance', resonance_covariance,
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res_cov.ResonanceCovariances)
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self._resonance_covariance = resonance_covariance
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@summed_reactions.setter
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def summed_reactions(self, summed_reactions):
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@ -1,6 +1,7 @@
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from collections import defaultdict, MutableSequence, Iterable
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import warnings
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import io
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import copy
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import numpy as np
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import pandas as pd
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@ -55,13 +56,6 @@ class ResonanceCovariances(Resonances):
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Distinct energy ranges for resonance data
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"""
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def __init__(self, ranges):
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self.ranges = ranges
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def __iter__(self):
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for r in self.ranges:
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yield r
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@property
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def ranges(self):
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return self._ranges
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@ -204,13 +198,16 @@ class ResonanceCovarianceRange:
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self.parameters_subset = parameters_subset
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self.cov_subset = cov_subset
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def sample_resonance_parameters(self, n_samples, use_subset=False):
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"""Return a IncidentNeutron object with n_samples of xs
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def sample_resonance_parameters(self, n_samples, resonances, use_subset=False):
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"""Return a list size 'n_samples' of openmc.data.ResonanceRange objects.
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Each with an indepentenly sampled set of parameters
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Parameters
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----------
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n_samples : int
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The number of samples to produce
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resonances : openmc.data.ResonanceRange object
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Corresponding resonance range with File 2 data.
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use_subset : bool, optional
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Flag on whether to sample from an already produced subset
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@ -236,7 +233,6 @@ class ResonanceCovarianceRange:
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mpar = self.mpar
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samples = []
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# Handling MLBW sampling
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if formalism == 'mlbw' or formalism == 'slbw':
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if mpar == 3:
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@ -258,9 +254,11 @@ class ResonanceCovarianceRange:
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records.append([energy[j], l_value[j], spin[j], gt[j], gn[j],
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gg[j], gf[j], gx[j]])
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columns = ['energy', 'L', 'J', 'totalWidth', 'neutronWidth',
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'captureWidth', 'fissionWidth', 'competitiveWidth']
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'captureWidth', 'fissionWidth', 'competitiveWidth']
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sample_params = pd.DataFrame.from_records(records, columns=columns)
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samples.append(sample_params)
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res_range = copy.copy(resonances)
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res_range.parameters = sample_params
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samples.append(res_range)
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elif mpar == 4:
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param_list = ['energy', 'neutronWidth', 'captureWidth', 'fissionWidth']
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@ -281,9 +279,11 @@ class ResonanceCovarianceRange:
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records.append([energy[j], l_value[j], spin[j], gt[j], gn[j],
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gg[j], gf[j], gx[j]])
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columns = ['energy', 'L', 'J', 'totalWidth', 'neutronWidth',
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'captureWidth', 'fissionWidth', 'competitiveWidth']
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'captureWidth', 'fissionWidth', 'competitiveWidth']
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sample_params = pd.DataFrame.from_records(records, columns=columns)
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samples.append(sample_params)
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res_range = copy.copy(resonances)
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res_range.parameters = sample_params
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samples.append(res_range)
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elif mpar == 5:
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param_list = ['energy', 'neutronWidth', 'captureWidth',
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@ -305,9 +305,11 @@ class ResonanceCovarianceRange:
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records.append([energy[j], l_value[j], spin[j], gt[j], gn[j],
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gg[j], gf[j], gx[j]])
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columns = ['energy', 'L', 'J', 'totalWidth', 'neutronWidth',
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'captureWidth', 'fissionWidth', 'competitveWidth']
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'captureWidth', 'fissionWidth', 'competitveWidth']
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sample_params = pd.DataFrame.from_records(records, columns=columns)
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samples.append(sample_params)
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res_range = copy.copy(resonances)
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res_range.parameters = sample_params
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samples.append(res_range)
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# Handling RM Sampling
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if formalism == 'rm':
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@ -331,7 +333,9 @@ class ResonanceCovarianceRange:
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columns = ['energy', 'L', 'J', 'neutronWidth',
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'captureWidth', 'fissionWidthA', 'fissionWidthB']
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sample_params = pd.DataFrame.from_records(records, columns=columns)
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samples.append(sample_params)
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res_range = copy.copy(resonances)
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res_range.parameters = sample_params
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samples.append(res_range)
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elif mpar == 5:
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param_list = ['energy', 'neutronWidth', 'captureWidth',
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@ -354,38 +358,12 @@ class ResonanceCovarianceRange:
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columns = ['energy', 'L', 'J', 'neutronWidth',
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'captureWidth', 'fissionWidthA', 'fissionWidthB']
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sample_params = pd.DataFrame.from_records(records, columns=columns)
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samples.append(sample_params)
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res_range = copy.copy(resonances)
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res_range.parameters = sample_params
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samples.append(res_range)
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self.samples = samples
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def reconstruct(self, energies, resonances, sampleN):
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"""Evaluate the cross section at specified energies for an already
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sampled set of resonance parameters.
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Parameters
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----------
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energies : float or Iterable of float
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Energies at which the cross section should be evaluated
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resonances : openmc.data.Resonance object
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Corresponding resonance range with File 2 data. Used for
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reconstruction method
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sampleN : int
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Index of sample of resonance parameters to be used
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Returns
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-------
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3-tuple of float or numpy.ndarray
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Elastic, capture, and fission cross sections at the specified
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energies
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"""
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if self.samples[sampleN] is None:
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raise ValueError("Sample of resonance parameters has not been set.")
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sample_parameters = self.samples[sampleN]
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xs_array = resonances.reconstruct(energies, use_sample = True,
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sample_parameters = sample_parameters)
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return xs_array
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class MultiLevelBreitWignerCovariance(ResonanceCovarianceRange):
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"""Multi-level Breit-Wigner resolved resonance formalism covariance data.
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@ -436,7 +414,9 @@ class MultiLevelBreitWignerCovariance(ResonanceCovarianceRange):
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items : list
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Items from the CONT record at the start of the resonance range
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subsection
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resonances : openmc.data.IncidentNeutron.Resonance object
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file2params : openmc.data.ResonanceRange object
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Corresponding resonance range with File 2 data. Used for
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reconstruction method
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Returns
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-------
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@ -39,7 +39,7 @@ def sm150():
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def gd154():
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"""Gd154 ENDF data (contains Reich Moore resonance range)"""
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filename = os.path.join(_ENDF_DATA, 'neutrons', 'n-064_Gd_154.endf')
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return openmc.data.IncidentNeutron.from_endf(filename, get_covariance = True)
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return openmc.data.IncidentNeutron.from_endf(filename, covariance = True)
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@pytest.fixture(scope='module')
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@ -96,11 +96,12 @@ def am244():
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endf_file = os.path.join(_ENDF_DATA, 'neutrons', 'n-095_Am_244.endf')
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return openmc.data.IncidentNeutron.from_njoy(endf_file)
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@pytest.fixture(scope='module')
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def ti50():
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"""Ti50 ENDF data (contains Multi-level Breit-Wigner resonance range)"""
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filename = os.path.join(_ENDF_DATA, 'neutrons', 'n-022_Ti_050.endf')
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return openmc.data.IncidentNeutron.from_endf(filename, get_covariance=True)
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return openmc.data.IncidentNeutron.from_endf(filename, covariance=True)
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def test_attributes(pu239):
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