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Add from_hdf5 for atomic relaxation data
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liangjg
parent
bb30f78b0d
commit
69e1a9d30d
1 changed files with 200 additions and 159 deletions
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@ -325,8 +325,69 @@ class AtomicRelaxation(EqualityMixin):
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# Return instance of class
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return cls(binding_energy, num_electrons, transitions)
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@classmethod
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def from_hdf5(cls, group):
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"""Generate atomic relaxation data from an HDF5 group
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Parameters
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----------
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group : h5py.Group
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HDF5 group to read from
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Returns
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-------
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openmc.data.AtomicRelaxation
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Atomic relaxation data
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"""
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# Create data dictionaries
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binding_energy = {}
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num_electrons = {}
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transitions = {}
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designators = [s.decode() for s in group.attrs['designators']]
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shell_values = [None] + _SUBSHELLS
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columns = ['secondary', 'tertiary', 'energy (eV)', 'probability']
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for shell in designators:
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# Shell group
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sub_group = group[shell]
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# Read subshell binding energy and number of electrons
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if 'binding_energy' in sub_group.attrs:
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binding_energy[shell] = sub_group.attrs['binding_energy']
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if 'num_electrons' in sub_group.attrs:
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num_electrons[shell] = sub_group.attrs['num_electrons']
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# Read transition data
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if 'transitions' in sub_group:
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df = pd.DataFrame(sub_group['transitions'].value,
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columns=columns)
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# Replace float indexes back to subshell strings
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df[columns[:2]] = df[columns[:2]].replace(
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np.arange(float(len(shell_values))), shell_values)
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transitions[shell] = df
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return cls(binding_energy, num_electrons, transitions)
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def to_hdf5(self, group):
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raise NotImplementedError
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"""Write atomic relaxation data to an HDF5 group
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Parameters
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----------
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group : h5py.Group
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HDF5 group to write to
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"""
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group.attrs['mt'] = self.mt
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if self.mt in REACTION_NAME:
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group.attrs['label'] = np.string_(REACTION_NAME[self.mt])
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else:
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group.attrs['label'] = np.string_(self.mt)
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group.attrs['Q_value'] = self.q_value
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group.attrs['center_of_mass'] = 1 if self.center_of_mass else 0
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group.attrs['redundant'] = 1 if self.redundant else 0
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class IncidentPhoton(EqualityMixin):
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r"""Photon interaction data.
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@ -585,141 +646,6 @@ class IncidentPhoton(EqualityMixin):
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return data
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def export_to_hdf5(self, path, mode='a', libver='earliest'):
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"""Export incident photon data to an HDF5 file.
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Parameters
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----------
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path : str
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Path to write HDF5 file to
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mode : {'r', r+', 'w', 'x', 'a'}
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Mode that is used to open the HDF5 file. This is the second argument
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to the :class:`h5py.File` constructor.
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libver : {'earliest', 'latest'}
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Compatibility mode for the HDF5 file. 'latest' will produce files
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that are less backwards compatible but have performance benefits.
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"""
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# Open file and write version
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f = h5py.File(str(path), mode, libver=libver)
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f.attrs['filetype'] = np.string_('data_photon')
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if 'version' not in f.attrs:
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f.attrs['version'] = np.array(HDF5_VERSION)
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group = f.create_group(self.name)
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group.attrs['Z'] = Z = self.atomic_number
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# Determine union energy grid
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union_grid = np.array([])
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for rx in self:
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union_grid = np.union1d(union_grid, rx.xs.x)
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group.create_dataset('energy', data=union_grid)
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# Write coherent scattering cross section
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rx = self.reactions[502]
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coh_group = group.create_group('coherent')
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coh_group.create_dataset('xs', data=rx.xs(union_grid))
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if rx.scattering_factor is not None:
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# Create integrated form factor
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ff = deepcopy(rx.scattering_factor)
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ff.x *= ff.x
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ff.y *= ff.y/Z**2
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int_ff = Tabulated1D(ff.x, ff.integral())
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int_ff.to_hdf5(coh_group, 'integrated_scattering_factor')
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if rx.anomalous_real is not None:
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rx.anomalous_real.to_hdf5(coh_group, 'anomalous_real')
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if rx.anomalous_imag is not None:
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rx.anomalous_imag.to_hdf5(coh_group, 'anomalous_imag')
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# Write incoherent scattering cross section
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rx = self[504]
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incoh_group = group.create_group('incoherent')
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incoh_group.create_dataset('xs', data=rx.xs(union_grid))
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if rx.scattering_factor is not None:
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rx.scattering_factor.to_hdf5(incoh_group, 'scattering_factor')
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# Write electron-field pair production cross section
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if 515 in self:
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pair_group = group.create_group('pair_production_electron')
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pair_group.create_dataset('xs', data=self[515].xs(union_grid))
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# Write nuclear-field pair production cross section
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if 517 in self:
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pair_group = group.create_group('pair_production_nuclear')
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pair_group.create_dataset('xs', data=self[517].xs(union_grid))
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# Write photoelectric cross section
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photoelec_group = group.create_group('photoelectric')
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photoelec_group.create_dataset('xs', data=self[522].xs(union_grid))
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# Write heating cross section
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if 525 in self:
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heat_group = group.create_group('heating')
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heat_group.create_dataset('xs', data=self[525].xs(union_grid))
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# Write photoionization cross sections
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shell_group = group.create_group('subshells')
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designators = []
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for mt, rx in self.reactions.items():
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if mt >= 534 and mt <= 572:
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# Get name of subshell
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shell = _SUBSHELLS[mt - 534]
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designators.append(shell)
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sub_group = shell_group.create_group(shell)
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if self.atomic_relaxation is not None:
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relax = self.atomic_relaxation
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# Write subshell binding energy and number of electrons
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sub_group.attrs['binding_energy'] = relax.binding_energy[shell]
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sub_group.attrs['num_electrons'] = relax.num_electrons[shell]
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# Write transition data with replacements
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if shell in relax.transitions:
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shell_values = _SUBSHELLS.copy()
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shell_values.insert(0, None)
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df = relax.transitions[shell].replace(
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shell_values, range(len(shell_values)))
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sub_group.create_dataset(
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'transitions', data=df.values.astype(float))
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# Determine threshold
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threshold = rx.xs.x[0]
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idx = np.searchsorted(union_grid, threshold, side='right') - 1
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# Interpolate cross section onto union grid and write
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photoionization = rx.xs(union_grid[idx:])
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sub_group.create_dataset('xs', data=photoionization)
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assert len(union_grid) == len(photoionization) + idx
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sub_group['xs'].attrs['threshold_idx'] = idx
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shell_group.attrs['designators'] = np.array(designators, dtype='S')
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# Write Compton profiles
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if self.compton_profiles:
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compton_group = group.create_group('compton_profiles')
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profile = self.compton_profiles
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compton_group.create_dataset('num_electrons',
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data=profile['num_electrons'])
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compton_group.create_dataset('binding_energy',
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data=profile['binding_energy'])
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# Get electron momentum values
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compton_group.create_dataset('pz', data=profile['J'][0].x)
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# Create/write 2D array of profiles
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J = np.array([Jk.y for Jk in profile['J']])
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compton_group.create_dataset('J', data=J)
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# Write bremsstrahlung
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if self.bremsstrahlung:
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brem_group = group.create_group('bremsstrahlung')
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for key, value in self.bremsstrahlung.items():
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if key == 'I':
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brem_group.attrs[key] = value
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else:
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brem_group.create_dataset(key, data=value)
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@classmethod
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def from_hdf5(cls, group_or_filename):
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"""Generate photon reaction from an HDF5 group
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@ -808,15 +734,9 @@ class IncidentPhoton(EqualityMixin):
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rx.xs = Tabulated1D(energy, rgroup['xs'].value, [n], [5])
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data.reactions[525] = rx
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# Read photoionization cross sections and atomic relaxation
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rgroup = group['subshells']
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# Read photoionization cross sections
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designators = [i.decode() for i in rgroup.attrs['designators']]
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binding_energy = {}
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num_electrons = {}
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transitions = {}
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shell_values = _SUBSHELLS.copy()
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shell_values.insert(0, None)
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columns = ['secondary', 'tertiary', 'energy (eV)', 'probability']
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for shell in designators:
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mt = _SUBSHELL_MT[shell]
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sub_group = rgroup[shell]
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@ -826,22 +746,8 @@ class IncidentPhoton(EqualityMixin):
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rx.xs = Tabulated1D(energy[threshold_idx:], xs, [len(xs)], [5])
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data.reactions[mt] = rx
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# Read subshell binding energy and number of electrons
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binding_energy[shell] = sub_group.attrs['binding_energy']
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num_electrons[shell] = sub_group.attrs['num_electrons']
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# Read transition data
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if 'transitions' in sub_group:
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df = pd.DataFrame(sub_group['transitions'].value,
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columns=columns)
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# Replace float indexes back to subshell strings
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df[columns[:2]] = df[columns[:2]].replace(
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np.arange(float(len(shell_values))), shell_values)
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transitions[shell] = df
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if binding_energy:
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data.atomic_relaxation = AtomicRelaxation(binding_energy,
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num_electrons, transitions)
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# Read atomic relaxation
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data.atomic_relaxation = AtomicRelaxation.from_hdf5(rgroup)
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# Read Compton profiles
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if 'compton_profiles' in group:
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@ -868,6 +774,141 @@ class IncidentPhoton(EqualityMixin):
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return data
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def export_to_hdf5(self, path, mode='a', libver='earliest'):
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"""Export incident photon data to an HDF5 file.
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Parameters
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----------
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path : str
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Path to write HDF5 file to
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mode : {'r', r+', 'w', 'x', 'a'}
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Mode that is used to open the HDF5 file. This is the second argument
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to the :class:`h5py.File` constructor.
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libver : {'earliest', 'latest'}
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Compatibility mode for the HDF5 file. 'latest' will produce files
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that are less backwards compatible but have performance benefits.
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"""
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# Open file and write version
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f = h5py.File(str(path), mode, libver=libver)
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f.attrs['filetype'] = np.string_('data_photon')
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if 'version' not in f.attrs:
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f.attrs['version'] = np.array(HDF5_VERSION)
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group = f.create_group(self.name)
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group.attrs['Z'] = Z = self.atomic_number
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# Determine union energy grid
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union_grid = np.array([])
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for rx in self:
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union_grid = np.union1d(union_grid, rx.xs.x)
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group.create_dataset('energy', data=union_grid)
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# Write coherent scattering cross section
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rx = self.reactions[502]
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coh_group = group.create_group('coherent')
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coh_group.create_dataset('xs', data=rx.xs(union_grid))
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if rx.scattering_factor is not None:
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# Create integrated form factor
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ff = deepcopy(rx.scattering_factor)
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ff.x *= ff.x
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ff.y *= ff.y/Z**2
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int_ff = Tabulated1D(ff.x, ff.integral())
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int_ff.to_hdf5(coh_group, 'integrated_scattering_factor')
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if rx.anomalous_real is not None:
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rx.anomalous_real.to_hdf5(coh_group, 'anomalous_real')
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if rx.anomalous_imag is not None:
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rx.anomalous_imag.to_hdf5(coh_group, 'anomalous_imag')
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# Write incoherent scattering cross section
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rx = self[504]
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incoh_group = group.create_group('incoherent')
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incoh_group.create_dataset('xs', data=rx.xs(union_grid))
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if rx.scattering_factor is not None:
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rx.scattering_factor.to_hdf5(incoh_group, 'scattering_factor')
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# Write electron-field pair production cross section
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if 515 in self:
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pair_group = group.create_group('pair_production_electron')
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pair_group.create_dataset('xs', data=self[515].xs(union_grid))
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# Write nuclear-field pair production cross section
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if 517 in self:
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pair_group = group.create_group('pair_production_nuclear')
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pair_group.create_dataset('xs', data=self[517].xs(union_grid))
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# Write photoelectric cross section
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photoelec_group = group.create_group('photoelectric')
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photoelec_group.create_dataset('xs', data=self[522].xs(union_grid))
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# Write heating cross section
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if 525 in self:
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heat_group = group.create_group('heating')
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heat_group.create_dataset('xs', data=self[525].xs(union_grid))
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# Write photoionization cross sections
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shell_group = group.create_group('subshells')
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designators = []
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shell_values = [None] + _SUBSHELLS
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for mt, rx in self.reactions.items():
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if mt >= 534 and mt <= 572:
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# Get name of subshell
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shell = _SUBSHELLS[mt - 534]
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designators.append(shell)
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sub_group = shell_group.create_group(shell)
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if self.atomic_relaxation is not None:
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relax = self.atomic_relaxation
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# Write subshell binding energy and number of electrons
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sub_group.attrs['binding_energy'] = relax.binding_energy[shell]
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sub_group.attrs['num_electrons'] = relax.num_electrons[shell]
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# Write transition data with replacements
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if shell in relax.transitions:
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df = relax.transitions[shell].replace(
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shell_values, range(len(shell_values)))
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sub_group.create_dataset(
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'transitions', data=df.values.astype(float))
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# Determine threshold
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threshold = rx.xs.x[0]
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idx = np.searchsorted(union_grid, threshold, side='right') - 1
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# Interpolate cross section onto union grid and write
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photoionization = rx.xs(union_grid[idx:])
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sub_group.create_dataset('xs', data=photoionization)
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assert len(union_grid) == len(photoionization) + idx
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sub_group['xs'].attrs['threshold_idx'] = idx
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shell_group.attrs['designators'] = np.array(designators, dtype='S')
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# Write Compton profiles
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if self.compton_profiles:
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compton_group = group.create_group('compton_profiles')
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profile = self.compton_profiles
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compton_group.create_dataset('num_electrons',
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data=profile['num_electrons'])
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compton_group.create_dataset('binding_energy',
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data=profile['binding_energy'])
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# Get electron momentum values
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compton_group.create_dataset('pz', data=profile['J'][0].x)
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# Create/write 2D array of profiles
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J = np.array([Jk.y for Jk in profile['J']])
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compton_group.create_dataset('J', data=J)
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# Write bremsstrahlung
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if self.bremsstrahlung:
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brem_group = group.create_group('bremsstrahlung')
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for key, value in self.bremsstrahlung.items():
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if key == 'I':
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brem_group.attrs[key] = value
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else:
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brem_group.create_dataset(key, data=value)
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def _add_bremsstrahlung(self):
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"""Add the data used in the thick-target bremsstrahlung approximation
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