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Changes in mgxs_library.py from PullRequest Inc. review
This commit is contained in:
Paul Romano
parent
34e57d4ba3
commit
97a0260784
1 changed files with 193 additions and 205 deletions
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@ -13,12 +13,25 @@ import openmc.mgxs
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from openmc.checkvalue import check_type, check_value, check_greater_than, \
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check_iterable_type, check_less_than, check_filetype_version
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ROOM_TEMPERATURE_KELVIN = 294.0
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# Supported incoming particle MGXS angular treatment representations
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_REPRESENTATIONS = ['isotropic', 'angle']
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REPRESENTATION_ISOTROPIC = 'isotropic'
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REPRESENTATION_ANGLE = 'angle'
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_REPRESENTATIONS = [
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REPRESENTATION_ISOTROPIC,
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REPRESENTATION_ANGLE
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]
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# Supported scattering angular distribution representations
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_SCATTER_TYPES = ['tabular', 'legendre', 'histogram']
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SCATTER_TABULAR = 'tabular'
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SCATTER_LEGENDRE = 'legendre'
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SCATTER_HISTOGRAM = 'histogram'
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_SCATTER_TYPES = [
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SCATTER_TABULAR,
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SCATTER_LEGENDRE,
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SCATTER_HISTOGRAM
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]
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# List of MGXS indexing schemes
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_XS_SHAPES = ["[G][G'][Order]", "[G]", "[G']", "[G][G']", "[DG]", "[DG][G]",
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@ -44,7 +57,7 @@ class XSdata:
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Name of the mgxs data set.
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energy_groups : openmc.mgxs.EnergyGroups
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Energy group structure
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representation : {'isotropic', 'angle'}, optional
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representation : {'isotropic', REPRESENTATION_ANGLE}, optional
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Method used in generating the MGXS (isotropic or angle-dependent flux
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weighting). Defaults to 'isotropic'
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temperatures : Iterable of float
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@ -75,7 +88,7 @@ class XSdata:
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Either the Legendre order, number of bins, or number of points used to
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describe the angular distribution associated with each group-to-group
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transfer probability.
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representation : {'isotropic', 'angle'}
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representation : {'isotropic', REPRESENTATION_ANGLE}
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Method used in generating the MGXS (isotropic or angle-dependent flux
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weighting).
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num_azimuthal : int
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@ -168,8 +181,8 @@ class XSdata:
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"""
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def __init__(self, name, energy_groups, temperatures=[294.],
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representation='isotropic', num_delayed_groups=0):
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def __init__(self, name, energy_groups, temperatures=[ROOM_TEMPERATURE_KELVIN],
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representation=REPRESENTATION_ISOTROPIC, num_delayed_groups=0):
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# Initialize class attributes
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self.name = name
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@ -179,7 +192,7 @@ class XSdata:
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self.representation = representation
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self._atomic_weight_ratio = None
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self._fissionable = False
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self._scatter_format = 'legendre'
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self._scatter_format = SCATTER_LEGENDRE
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self._order = None
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self._num_polar = None
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self._num_azimuthal = None
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@ -340,11 +353,13 @@ class XSdata:
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@property
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def num_orders(self):
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if self._order is not None:
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if self._scatter_format in (None, 'legendre'):
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return self._order + 1
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else:
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return self._order
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if self._order is None:
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raise ValueError('Order has not been set.')
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if self._scatter_format in (None, SCATTER_LEGENDRE):
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return self._order + 1
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else:
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return self._order
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@property
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def xs_shapes(self):
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@ -370,7 +385,7 @@ class XSdata:
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self.energy_groups.num_groups, self.num_orders)
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# If representation is by angle prepend num polar and num azim
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if self.representation == 'angle':
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if self.representation == REPRESENTATION_ANGLE:
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for key, shapes in self._xs_shapes.items():
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self._xs_shapes[key] \
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= (self.num_polar, self.num_azimuthal) + shapes
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@ -483,7 +498,18 @@ class XSdata:
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self._decay_rate.append(None)
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self._inverse_velocity.append(None)
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def set_total(self, total, temperature=294.):
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def _check_temperature(self, temperature):
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check_type('temperature', temperature, Real)
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check_value('temperature', temperature, self.temperatures)
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def _temperature_index(self, temperature):
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return np.where(self.temperatures == temperature)[0][0]
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def _set_fissionable(self, array):
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if np.sum(array) > 0:
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self._fissionable = True
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def set_total(self, total, temperature=ROOM_TEMPERATURE_KELVIN):
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"""This method sets the cross section for this XSdata object at the
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provided temperature.
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@ -507,13 +533,12 @@ class XSdata:
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# Convert to a numpy array so we can easily get the shape for checking
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total = np.asarray(total)
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check_value('total shape', total.shape, shapes)
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check_type('temperature', temperature, Real)
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check_value('temperature', temperature, self.temperatures)
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self._check_temperature(temperature)
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i = np.where(self.temperatures == temperature)[0][0]
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i = self._temperature_index(temperature)
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self._total[i] = total
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def set_absorption(self, absorption, temperature=294.):
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def set_absorption(self, absorption, temperature=ROOM_TEMPERATURE_KELVIN):
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"""This method sets the cross section for this XSdata object at the
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provided temperature.
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@ -537,13 +562,12 @@ class XSdata:
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# Convert to a numpy array so we can easily get the shape for checking
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absorption = np.asarray(absorption)
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check_value('absorption shape', absorption.shape, shapes)
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check_type('temperature', temperature, Real)
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check_value('temperature', temperature, self.temperatures)
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self._check_temperature(temperature)
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i = np.where(self.temperatures == temperature)[0][0]
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i = self._temperature_index(temperature)
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self._absorption[i] = absorption
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def set_fission(self, fission, temperature=294.):
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def set_fission(self, fission, temperature=ROOM_TEMPERATURE_KELVIN):
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"""This method sets the cross section for this XSdata object at the
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provided temperature.
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@ -567,16 +591,14 @@ class XSdata:
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# Convert to a numpy array so we can easily get the shape for checking
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fission = np.asarray(fission)
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check_value('fission shape', fission.shape, shapes)
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check_type('temperature', temperature, Real)
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check_value('temperature', temperature, self.temperatures)
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self._check_temperature(temperature)
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i = np.where(self.temperatures == temperature)[0][0]
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i = self._temperature_index(temperature)
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self._fission[i] = fission
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if np.sum(fission) > 0.0:
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self._fissionable = True
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self._set_fissionable(fission)
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def set_kappa_fission(self, kappa_fission, temperature=294.):
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def set_kappa_fission(self, kappa_fission, temperature=ROOM_TEMPERATURE_KELVIN):
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"""This method sets the cross section for this XSdata object at the
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provided temperature.
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@ -600,16 +622,14 @@ class XSdata:
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# Convert to a numpy array so we can easily get the shape for checking
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kappa_fission = np.asarray(kappa_fission)
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check_value('kappa fission shape', kappa_fission.shape, shapes)
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check_type('temperature', temperature, Real)
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check_value('temperature', temperature, self.temperatures)
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self._check_temperature(temperature)
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i = np.where(self.temperatures == temperature)[0][0]
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i = self._temperature_index(temperature)
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self._kappa_fission[i] = kappa_fission
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if np.sum(kappa_fission) > 0.0:
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self._fissionable = True
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self._set_fissionable(kappa_fission)
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def set_chi(self, chi, temperature=294.):
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def set_chi(self, chi, temperature=ROOM_TEMPERATURE_KELVIN):
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"""This method sets the cross section for this XSdata object at the
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provided temperature.
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@ -633,13 +653,12 @@ class XSdata:
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# Convert to a numpy array so we can easily get the shape for checking
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chi = np.asarray(chi)
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check_value('chi shape', chi.shape, shapes)
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check_type('temperature', temperature, Real)
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check_value('temperature', temperature, self.temperatures)
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self._check_temperature(temperature)
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i = np.where(self.temperatures == temperature)[0][0]
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i = self._temperature_index(temperature)
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self._chi[i] = chi
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def set_chi_prompt(self, chi_prompt, temperature=294.):
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def set_chi_prompt(self, chi_prompt, temperature=ROOM_TEMPERATURE_KELVIN):
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"""This method sets the cross section for this XSdata object at the
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provided temperature.
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@ -663,13 +682,12 @@ class XSdata:
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# Convert to a numpy array so we can easily get the shape for checking
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chi_prompt = np.asarray(chi_prompt)
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check_value('chi prompt shape', chi_prompt.shape, shapes)
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check_type('temperature', temperature, Real)
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check_value('temperature', temperature, self.temperatures)
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self._check_temperature(temperature)
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i = np.where(self.temperatures == temperature)[0][0]
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i = self._temperature_index(temperature)
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self._chi_prompt[i] = chi_prompt
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def set_chi_delayed(self, chi_delayed, temperature=294.):
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def set_chi_delayed(self, chi_delayed, temperature=ROOM_TEMPERATURE_KELVIN):
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"""This method sets the cross section for this XSdata object at the
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provided temperature.
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@ -693,13 +711,14 @@ class XSdata:
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# Convert to a numpy array so we can easily get the shape for checking
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chi_delayed = np.asarray(chi_delayed)
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check_value('chi delayed shape', chi_delayed.shape, shapes)
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self._check_temperature(temperature)
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check_type('temperature', temperature, Real)
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check_value('temperature', temperature, self.temperatures)
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i = np.where(self.temperatures == temperature)[0][0]
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i = self._temperature_index(temperature)
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self._chi_delayed[i] = chi_delayed
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def set_beta(self, beta, temperature=294.):
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def set_beta(self, beta, temperature=ROOM_TEMPERATURE_KELVIN):
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"""This method sets the cross section for this XSdata object at the
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provided temperature.
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@ -723,13 +742,12 @@ class XSdata:
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# Convert to a numpy array so we can easily get the shape for checking
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beta = np.asarray(beta)
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check_value('beta shape', beta.shape, shapes)
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check_type('temperature', temperature, Real)
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check_value('temperature', temperature, self.temperatures)
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self._check_temperature(temperature)
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i = np.where(self.temperatures == temperature)[0][0]
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i = self._temperature_index(temperature)
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self._beta[i] = beta
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def set_decay_rate(self, decay_rate, temperature=294.):
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def set_decay_rate(self, decay_rate, temperature=ROOM_TEMPERATURE_KELVIN):
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"""This method sets the cross section for this XSdata object at the
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provided temperature.
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@ -753,13 +771,12 @@ class XSdata:
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# Convert to a numpy array so we can easily get the shape for checking
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decay_rate = np.asarray(decay_rate)
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check_value('decay rate shape', decay_rate.shape, shapes)
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check_type('temperature', temperature, Real)
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check_value('temperature', temperature, self.temperatures)
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self._check_temperature(temperature)
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i = np.where(self.temperatures == temperature)[0][0]
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i = self._temperature_index(temperature)
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self._decay_rate[i] = decay_rate
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def set_scatter_matrix(self, scatter, temperature=294.):
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def set_scatter_matrix(self, scatter, temperature=ROOM_TEMPERATURE_KELVIN):
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"""This method sets the cross section for this XSdata object at the
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provided temperature.
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@ -785,13 +802,12 @@ class XSdata:
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check_iterable_type('scatter', scatter, Real,
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max_depth=len(scatter.shape))
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check_value('scatter shape', scatter.shape, shapes)
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check_type('temperature', temperature, Real)
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check_value('temperature', temperature, self.temperatures)
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self._check_temperature(temperature)
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i = np.where(self.temperatures == temperature)[0][0]
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i = self._temperature_index(temperature)
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self._scatter_matrix[i] = scatter
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def set_multiplicity_matrix(self, multiplicity, temperature=294.):
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def set_multiplicity_matrix(self, multiplicity, temperature=ROOM_TEMPERATURE_KELVIN):
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"""This method sets the cross section for this XSdata object at the
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provided temperature.
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@ -817,13 +833,12 @@ class XSdata:
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check_iterable_type('multiplicity', multiplicity, Real,
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max_depth=len(multiplicity.shape))
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check_value('multiplicity shape', multiplicity.shape, shapes)
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check_type('temperature', temperature, Real)
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check_value('temperature', temperature, self.temperatures)
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self._check_temperature(temperature)
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i = np.where(self.temperatures == temperature)[0][0]
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i = self._temperature_index(temperature)
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self._multiplicity_matrix[i] = multiplicity
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def set_nu_fission(self, nu_fission, temperature=294.):
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def set_nu_fission(self, nu_fission, temperature=ROOM_TEMPERATURE_KELVIN):
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"""This method sets the cross section for this XSdata object at the
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provided temperature.
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@ -849,15 +864,13 @@ class XSdata:
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check_value('nu_fission shape', nu_fission.shape, shapes)
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check_iterable_type('nu_fission', nu_fission, Real,
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max_depth=len(nu_fission.shape))
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check_type('temperature', temperature, Real)
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check_value('temperature', temperature, self.temperatures)
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self._check_temperature(temperature)
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i = np.where(self.temperatures == temperature)[0][0]
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i = self._temperature_index(temperature)
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self._nu_fission[i] = nu_fission
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if np.sum(nu_fission) > 0.0:
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self._fissionable = True
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self._set_fissionable(nu_fission)
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def set_prompt_nu_fission(self, prompt_nu_fission, temperature=294.):
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def set_prompt_nu_fission(self, prompt_nu_fission, temperature=ROOM_TEMPERATURE_KELVIN):
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"""This method sets the cross section for this XSdata object at the
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provided temperature.
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@ -883,15 +896,13 @@ class XSdata:
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check_value('prompt_nu_fission shape', prompt_nu_fission.shape, shapes)
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check_iterable_type('prompt_nu_fission', prompt_nu_fission, Real,
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max_depth=len(prompt_nu_fission.shape))
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check_type('temperature', temperature, Real)
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check_value('temperature', temperature, self.temperatures)
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self._check_temperature(temperature)
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i = np.where(self.temperatures == temperature)[0][0]
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i = self._temperature_index(temperature)
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self._prompt_nu_fission[i] = prompt_nu_fission
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if np.sum(prompt_nu_fission) > 0.0:
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self._fissionable = True
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self._set_fissionable(prompt_nu_fission)
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def set_delayed_nu_fission(self, delayed_nu_fission, temperature=294.):
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def set_delayed_nu_fission(self, delayed_nu_fission, temperature=ROOM_TEMPERATURE_KELVIN):
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"""This method sets the cross section for this XSdata object at the
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provided temperature.
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@ -918,15 +929,13 @@ class XSdata:
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shapes)
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check_iterable_type('delayed_nu_fission', delayed_nu_fission, Real,
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max_depth=len(delayed_nu_fission.shape))
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check_type('temperature', temperature, Real)
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check_value('temperature', temperature, self.temperatures)
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self._check_temperature(temperature)
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i = np.where(self.temperatures == temperature)[0][0]
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i = self._temperature_index(temperature)
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self._delayed_nu_fission[i] = delayed_nu_fission
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if np.sum(delayed_nu_fission) > 0.0:
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self._fissionable = True
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self._set_fissionable(delayed_nu_fission)
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def set_inverse_velocity(self, inv_vel, temperature=294.):
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def set_inverse_velocity(self, inv_vel, temperature=ROOM_TEMPERATURE_KELVIN):
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"""This method sets the inverse velocity for this XSdata object at the
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provided temperature.
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@ -946,13 +955,12 @@ class XSdata:
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# Convert to a numpy array so we can easily get the shape for checking
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inv_vel = np.asarray(inv_vel)
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check_value('inverse_velocity shape', inv_vel.shape, shapes)
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check_type('temperature', temperature, Real)
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check_value('temperature', temperature, self.temperatures)
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self._check_temperature(temperature)
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i = np.where(self.temperatures == temperature)[0][0]
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i = self._temperature_index(temperature)
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self._inverse_velocity[i] = inv_vel
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def set_total_mgxs(self, total, temperature=294., nuclide='total',
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def set_total_mgxs(self, total, temperature=ROOM_TEMPERATURE_KELVIN, nuclide='total',
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xs_type='macro', subdomain=None):
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"""This method allows for an openmc.mgxs.TotalXS or
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openmc.mgxs.TransportXS to be used to set the total cross section for
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@ -987,14 +995,13 @@ class XSdata:
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openmc.mgxs.TransportXS))
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check_value('energy_groups', total.energy_groups, [self.energy_groups])
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check_value('domain_type', total.domain_type, openmc.mgxs.DOMAIN_TYPES)
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check_type('temperature', temperature, Real)
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check_value('temperature', temperature, self.temperatures)
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self._check_temperature(temperature)
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i = np.where(self.temperatures == temperature)[0][0]
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i = self._temperature_index(temperature)
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self._total[i] = total.get_xs(nuclides=nuclide, xs_type=xs_type,
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subdomains=subdomain)
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def set_absorption_mgxs(self, absorption, temperature=294.,
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def set_absorption_mgxs(self, absorption, temperature=ROOM_TEMPERATURE_KELVIN,
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nuclide='total', xs_type='macro', subdomain=None):
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||||
"""This method allows for an openmc.mgxs.AbsorptionXS
|
||||
to be used to set the absorption cross section for this XSdata object.
|
||||
|
|
@ -1029,15 +1036,14 @@ class XSdata:
|
|||
[self.energy_groups])
|
||||
check_value('domain_type', absorption.domain_type,
|
||||
openmc.mgxs.DOMAIN_TYPES)
|
||||
check_type('temperature', temperature, Real)
|
||||
check_value('temperature', temperature, self.temperatures)
|
||||
self._check_temperature(temperature)
|
||||
|
||||
i = np.where(self.temperatures == temperature)[0][0]
|
||||
i = self._temperature_index(temperature)
|
||||
self._absorption[i] = absorption.get_xs(nuclides=nuclide,
|
||||
xs_type=xs_type,
|
||||
subdomains=subdomain)
|
||||
|
||||
def set_fission_mgxs(self, fission, temperature=294., nuclide='total',
|
||||
def set_fission_mgxs(self, fission, temperature=ROOM_TEMPERATURE_KELVIN, nuclide='total',
|
||||
xs_type='macro', subdomain=None):
|
||||
"""This method allows for an openmc.mgxs.FissionXS
|
||||
to be used to set the fission cross section for this XSdata object.
|
||||
|
|
@ -1072,15 +1078,14 @@ class XSdata:
|
|||
[self.energy_groups])
|
||||
check_value('domain_type', fission.domain_type,
|
||||
openmc.mgxs.DOMAIN_TYPES)
|
||||
check_type('temperature', temperature, Real)
|
||||
check_value('temperature', temperature, self.temperatures)
|
||||
self._check_temperature(temperature)
|
||||
|
||||
i = np.where(self.temperatures == temperature)[0][0]
|
||||
i = self._temperature_index(temperature)
|
||||
self._fission[i] = fission.get_xs(nuclides=nuclide,
|
||||
xs_type=xs_type,
|
||||
subdomains=subdomain)
|
||||
|
||||
def set_nu_fission_mgxs(self, nu_fission, temperature=294.,
|
||||
def set_nu_fission_mgxs(self, nu_fission, temperature=ROOM_TEMPERATURE_KELVIN,
|
||||
nuclide='total', xs_type='macro', subdomain=None):
|
||||
"""This method allows for an openmc.mgxs.FissionXS
|
||||
to be used to set the nu-fission cross section for this XSdata object.
|
||||
|
|
@ -1118,18 +1123,16 @@ class XSdata:
|
|||
[self.energy_groups])
|
||||
check_value('domain_type', nu_fission.domain_type,
|
||||
openmc.mgxs.DOMAIN_TYPES)
|
||||
check_type('temperature', temperature, Real)
|
||||
check_value('temperature', temperature, self.temperatures)
|
||||
self._check_temperature(temperature)
|
||||
|
||||
i = np.where(self.temperatures == temperature)[0][0]
|
||||
i = self._temperature_index(temperature)
|
||||
self._nu_fission[i] = nu_fission.get_xs(nuclides=nuclide,
|
||||
xs_type=xs_type,
|
||||
subdomains=subdomain)
|
||||
|
||||
if np.sum(self._nu_fission) > 0.0:
|
||||
self._fissionable = True
|
||||
self._set_fissionable(self._nu_fission)
|
||||
|
||||
def set_prompt_nu_fission_mgxs(self, prompt_nu_fission, temperature=294.,
|
||||
def set_prompt_nu_fission_mgxs(self, prompt_nu_fission, temperature=ROOM_TEMPERATURE_KELVIN,
|
||||
nuclide='total', xs_type='macro',
|
||||
subdomain=None):
|
||||
"""Sets the prompt-nu-fission cross section.
|
||||
|
|
@ -1170,17 +1173,15 @@ class XSdata:
|
|||
[self.energy_groups])
|
||||
check_value('domain_type', prompt_nu_fission.domain_type,
|
||||
openmc.mgxs.DOMAIN_TYPES)
|
||||
check_type('temperature', temperature, Real)
|
||||
check_value('temperature', temperature, self.temperatures)
|
||||
self._check_temperature(temperature)
|
||||
|
||||
i = np.where(self.temperatures == temperature)[0][0]
|
||||
i = self._temperature_index(temperature)
|
||||
self._prompt_nu_fission[i] = prompt_nu_fission.get_xs(
|
||||
nuclides=nuclide, xs_type=xs_type, subdomains=subdomain)
|
||||
|
||||
if np.sum(self._prompt_nu_fission) > 0.0:
|
||||
self._fissionable = True
|
||||
self._set_fissionable(self._prompt_nu_fission)
|
||||
|
||||
def set_delayed_nu_fission_mgxs(self, delayed_nu_fission, temperature=294.,
|
||||
def set_delayed_nu_fission_mgxs(self, delayed_nu_fission, temperature=ROOM_TEMPERATURE_KELVIN,
|
||||
nuclide='total', xs_type='macro',
|
||||
subdomain=None):
|
||||
"""This method allows for an openmc.mgxs.DelayedNuFissionXS or
|
||||
|
|
@ -1221,17 +1222,15 @@ class XSdata:
|
|||
[self.num_delayed_groups])
|
||||
check_value('domain_type', delayed_nu_fission.domain_type,
|
||||
openmc.mgxs.DOMAIN_TYPES)
|
||||
check_type('temperature', temperature, Real)
|
||||
check_value('temperature', temperature, self.temperatures)
|
||||
self._check_temperature(temperature)
|
||||
|
||||
i = np.where(self.temperatures == temperature)[0][0]
|
||||
i = self._temperature_index(temperature)
|
||||
self._delayed_nu_fission[i] = delayed_nu_fission.get_xs(
|
||||
nuclides=nuclide, xs_type=xs_type, subdomains=subdomain)
|
||||
|
||||
if np.sum(self._delayed_nu_fission) > 0.0:
|
||||
self._fissionable = True
|
||||
self._set_fissionable(self._delayed_nu_fission)
|
||||
|
||||
def set_kappa_fission_mgxs(self, k_fission, temperature=294.,
|
||||
def set_kappa_fission_mgxs(self, k_fission, temperature=ROOM_TEMPERATURE_KELVIN,
|
||||
nuclide='total', xs_type='macro',
|
||||
subdomain=None):
|
||||
"""This method allows for an openmc.mgxs.KappaFissionXS
|
||||
|
|
@ -1268,15 +1267,14 @@ class XSdata:
|
|||
[self.energy_groups])
|
||||
check_value('domain_type', k_fission.domain_type,
|
||||
openmc.mgxs.DOMAIN_TYPES)
|
||||
check_type('temperature', temperature, Real)
|
||||
check_value('temperature', temperature, self.temperatures)
|
||||
self._check_temperature(temperature)
|
||||
|
||||
i = np.where(self.temperatures == temperature)[0][0]
|
||||
i = self._temperature_index(temperature)
|
||||
self._kappa_fission[i] = k_fission.get_xs(nuclides=nuclide,
|
||||
xs_type=xs_type,
|
||||
subdomains=subdomain)
|
||||
|
||||
def set_chi_mgxs(self, chi, temperature=294., nuclide='total',
|
||||
def set_chi_mgxs(self, chi, temperature=ROOM_TEMPERATURE_KELVIN, nuclide='total',
|
||||
xs_type='macro', subdomain=None):
|
||||
"""This method allows for an openmc.mgxs.Chi
|
||||
to be used to set chi for this XSdata object.
|
||||
|
|
@ -1308,14 +1306,13 @@ class XSdata:
|
|||
check_type('chi', chi, openmc.mgxs.Chi)
|
||||
check_value('energy_groups', chi.energy_groups, [self.energy_groups])
|
||||
check_value('domain_type', chi.domain_type, openmc.mgxs.DOMAIN_TYPES)
|
||||
check_type('temperature', temperature, Real)
|
||||
check_value('temperature', temperature, self.temperatures)
|
||||
self._check_temperature(temperature)
|
||||
|
||||
i = np.where(self.temperatures == temperature)[0][0]
|
||||
i = self._temperature_index(temperature)
|
||||
self._chi[i] = chi.get_xs(nuclides=nuclide, xs_type=xs_type,
|
||||
subdomains=subdomain)
|
||||
|
||||
def set_chi_prompt_mgxs(self, chi_prompt, temperature=294.,
|
||||
def set_chi_prompt_mgxs(self, chi_prompt, temperature=ROOM_TEMPERATURE_KELVIN,
|
||||
nuclide='total', xs_type='macro', subdomain=None):
|
||||
"""This method allows for an openmc.mgxs.Chi to be used to set
|
||||
chi-prompt for this XSdata object.
|
||||
|
|
@ -1350,15 +1347,14 @@ class XSdata:
|
|||
[self.energy_groups])
|
||||
check_value('domain_type', chi_prompt.domain_type,
|
||||
openmc.mgxs.DOMAIN_TYPES)
|
||||
check_type('temperature', temperature, Real)
|
||||
check_value('temperature', temperature, self.temperatures)
|
||||
self._check_temperature(temperature)
|
||||
|
||||
i = np.where(self.temperatures == temperature)[0][0]
|
||||
i = self._temperature_index(temperature)
|
||||
self._chi_prompt[i] = chi_prompt.get_xs(nuclides=nuclide,
|
||||
xs_type=xs_type,
|
||||
subdomains=subdomain)
|
||||
|
||||
def set_chi_delayed_mgxs(self, chi_delayed, temperature=294.,
|
||||
def set_chi_delayed_mgxs(self, chi_delayed, temperature=ROOM_TEMPERATURE_KELVIN,
|
||||
nuclide='total', xs_type='macro', subdomain=None):
|
||||
"""This method allows for an openmc.mgxs.ChiDelayed
|
||||
to be used to set chi-delayed for this XSdata object.
|
||||
|
|
@ -1394,15 +1390,14 @@ class XSdata:
|
|||
[self.num_delayed_groups])
|
||||
check_value('domain_type', chi_delayed.domain_type,
|
||||
openmc.mgxs.DOMAIN_TYPES)
|
||||
check_type('temperature', temperature, Real)
|
||||
check_value('temperature', temperature, self.temperatures)
|
||||
self._check_temperature(temperature)
|
||||
|
||||
i = np.where(self.temperatures == temperature)[0][0]
|
||||
i = self._temperature_index(temperature)
|
||||
self._chi_delayed[i] = chi_delayed.get_xs(nuclides=nuclide,
|
||||
xs_type=xs_type,
|
||||
subdomains=subdomain)
|
||||
|
||||
def set_beta_mgxs(self, beta, temperature=294.,
|
||||
def set_beta_mgxs(self, beta, temperature=ROOM_TEMPERATURE_KELVIN,
|
||||
nuclide='total', xs_type='macro', subdomain=None):
|
||||
"""This method allows for an openmc.mgxs.Beta
|
||||
to be used to set beta for this XSdata object.
|
||||
|
|
@ -1435,15 +1430,14 @@ class XSdata:
|
|||
check_value('num_delayed_groups', beta.num_delayed_groups,
|
||||
[self.num_delayed_groups])
|
||||
check_value('domain_type', beta.domain_type, openmc.mgxs.DOMAIN_TYPES)
|
||||
check_type('temperature', temperature, Real)
|
||||
check_value('temperature', temperature, self.temperatures)
|
||||
self._check_temperature(temperature)
|
||||
|
||||
i = np.where(self.temperatures == temperature)[0][0]
|
||||
i = self._temperature_index(temperature)
|
||||
self._beta[i] = beta.get_xs(nuclides=nuclide,
|
||||
xs_type=xs_type,
|
||||
subdomains=subdomain)
|
||||
|
||||
def set_decay_rate_mgxs(self, decay_rate, temperature=294.,
|
||||
def set_decay_rate_mgxs(self, decay_rate, temperature=ROOM_TEMPERATURE_KELVIN,
|
||||
nuclide='total', xs_type='macro', subdomain=None):
|
||||
"""This method allows for an openmc.mgxs.DecayRate
|
||||
to be used to set decay rate for this XSdata object.
|
||||
|
|
@ -1477,15 +1471,14 @@ class XSdata:
|
|||
[self.num_delayed_groups])
|
||||
check_value('domain_type', decay_rate.domain_type,
|
||||
openmc.mgxs.DOMAIN_TYPES)
|
||||
check_type('temperature', temperature, Real)
|
||||
check_value('temperature', temperature, self.temperatures)
|
||||
self._check_temperature(temperature)
|
||||
|
||||
i = np.where(self.temperatures == temperature)[0][0]
|
||||
i = self._temperature_index(temperature)
|
||||
self._decay_rate[i] = decay_rate.get_xs(nuclides=nuclide,
|
||||
xs_type=xs_type,
|
||||
subdomains=subdomain)
|
||||
|
||||
def set_scatter_matrix_mgxs(self, scatter, temperature=294.,
|
||||
def set_scatter_matrix_mgxs(self, scatter, temperature=ROOM_TEMPERATURE_KELVIN,
|
||||
nuclide='total', xs_type='macro',
|
||||
subdomain=None):
|
||||
"""This method allows for an openmc.mgxs.ScatterMatrixXS
|
||||
|
|
@ -1523,8 +1516,7 @@ class XSdata:
|
|||
[self.energy_groups])
|
||||
check_value('domain_type', scatter.domain_type,
|
||||
openmc.mgxs.DOMAIN_TYPES)
|
||||
check_type('temperature', temperature, Real)
|
||||
check_value('temperature', temperature, self.temperatures)
|
||||
self._check_temperature(temperature)
|
||||
|
||||
# Set the value of scatter_format based on the same value within
|
||||
# scatter
|
||||
|
|
@ -1534,30 +1526,30 @@ class XSdata:
|
|||
# the order based on the data within scatter.
|
||||
# Otherwise, we will check to see that XSdata.order matches
|
||||
# the order of scatter
|
||||
if self.scatter_format == 'legendre':
|
||||
if self.scatter_format == SCATTER_LEGENDRE:
|
||||
if self.order is None:
|
||||
self.order = scatter.legendre_order
|
||||
else:
|
||||
check_value('legendre_order', scatter.legendre_order,
|
||||
[self.order])
|
||||
elif self.scatter_format == 'histogram':
|
||||
elif self.scatter_format == SCATTER_HISTOGRAM:
|
||||
if self.order is None:
|
||||
self.order = scatter.histogram_bins
|
||||
else:
|
||||
check_value('histogram_bins', scatter.histogram_bins,
|
||||
[self.order])
|
||||
|
||||
i = np.where(self.temperatures == temperature)[0][0]
|
||||
if self.scatter_format == 'legendre':
|
||||
i = self._temperature_index(temperature)
|
||||
if self.scatter_format == SCATTER_LEGENDRE:
|
||||
self._scatter_matrix[i] = \
|
||||
np.zeros(self.xs_shapes["[G][G'][Order]"])
|
||||
# Get the scattering orders in the outermost dimension
|
||||
if self.representation == 'isotropic':
|
||||
if self.representation == REPRESENTATION_ISOTROPIC:
|
||||
for moment in range(self.num_orders):
|
||||
self._scatter_matrix[i][:, :, moment] = \
|
||||
scatter.get_xs(nuclides=nuclide, xs_type=xs_type,
|
||||
moment=moment, subdomains=subdomain)
|
||||
elif self.representation == 'angle':
|
||||
elif self.representation == REPRESENTATION_ANGLE:
|
||||
for moment in range(self.num_orders):
|
||||
self._scatter_matrix[i][:, :, :, :, moment] = \
|
||||
scatter.get_xs(nuclides=nuclide, xs_type=xs_type,
|
||||
|
|
@ -1568,7 +1560,7 @@ class XSdata:
|
|||
subdomains=subdomain)
|
||||
|
||||
def set_multiplicity_matrix_mgxs(self, nuscatter, scatter=None,
|
||||
temperature=294., nuclide='total',
|
||||
temperature=ROOM_TEMPERATURE_KELVIN, nuclide='total',
|
||||
xs_type='macro', subdomain=None):
|
||||
"""This method allows for either the direct use of only an
|
||||
openmc.mgxs.MultiplicityMatrixXS or an openmc.mgxs.ScatterMatrixXS and
|
||||
|
|
@ -1613,8 +1605,7 @@ class XSdata:
|
|||
[self.energy_groups])
|
||||
check_value('domain_type', nuscatter.domain_type,
|
||||
openmc.mgxs.DOMAIN_TYPES)
|
||||
check_type('temperature', temperature, Real)
|
||||
check_value('temperature', temperature, self.temperatures)
|
||||
self._check_temperature(temperature)
|
||||
|
||||
if scatter is not None:
|
||||
check_type('scatter', scatter, openmc.mgxs.ScatterMatrixXS)
|
||||
|
|
@ -1627,7 +1618,7 @@ class XSdata:
|
|||
[self.energy_groups])
|
||||
check_value('domain_type', scatter.domain_type,
|
||||
openmc.mgxs.DOMAIN_TYPES)
|
||||
i = np.where(self.temperatures == temperature)[0][0]
|
||||
i = self._temperature_index(temperature)
|
||||
nuscatt = nuscatter.get_xs(nuclides=nuclide,
|
||||
xs_type=xs_type, moment=0,
|
||||
subdomains=subdomain)
|
||||
|
|
@ -1637,16 +1628,16 @@ class XSdata:
|
|||
scatt = scatter.get_xs(nuclides=nuclide,
|
||||
xs_type=xs_type, moment=0,
|
||||
subdomains=subdomain)
|
||||
if scatter.scatter_format == 'histogram':
|
||||
if scatter.scatter_format == SCATTER_HISTOGRAM:
|
||||
scatt = np.sum(scatt, axis=2)
|
||||
if nuscatter.scatter_format == 'histogram':
|
||||
if nuscatter.scatter_format == SCATTER_HISTOGRAM:
|
||||
nuscatt = np.sum(nuscatt, axis=2)
|
||||
self._multiplicity_matrix[i] = np.divide(nuscatt, scatt)
|
||||
|
||||
self._multiplicity_matrix[i] = \
|
||||
np.nan_to_num(self._multiplicity_matrix[i])
|
||||
|
||||
def set_inverse_velocity_mgxs(self, inverse_velocity, temperature=294.,
|
||||
def set_inverse_velocity_mgxs(self, inverse_velocity, temperature=ROOM_TEMPERATURE_KELVIN,
|
||||
nuclide='total', xs_type='macro',
|
||||
subdomain=None):
|
||||
"""This method allows for an openmc.mgxs.InverseVelocity
|
||||
|
|
@ -1683,10 +1674,9 @@ class XSdata:
|
|||
[self.energy_groups])
|
||||
check_value('domain_type', inverse_velocity.domain_type,
|
||||
openmc.mgxs.DOMAIN_TYPES)
|
||||
check_type('temperature', temperature, Real)
|
||||
check_value('temperature', temperature, self.temperatures)
|
||||
self._check_temperature(temperature)
|
||||
|
||||
i = np.where(self.temperatures == temperature)[0][0]
|
||||
i = self._temperature_index(temperature)
|
||||
self._inverse_velocity[i] = inverse_velocity.get_xs(
|
||||
nuclides=nuclide, xs_type=xs_type, subdomains=subdomain)
|
||||
|
||||
|
|
@ -1727,7 +1717,7 @@ class XSdata:
|
|||
|
||||
check_value('target_representation', target_representation,
|
||||
_REPRESENTATIONS)
|
||||
if target_representation == 'angle':
|
||||
if target_representation == REPRESENTATION_ANGLE:
|
||||
check_type('num_polar', num_polar, Integral)
|
||||
check_type('num_azimuthal', num_azimuthal, Integral)
|
||||
check_greater_than('num_polar', num_polar, 0)
|
||||
|
|
@ -1739,7 +1729,7 @@ class XSdata:
|
|||
# representations are the same
|
||||
if target_representation == self.representation:
|
||||
# Check to make sure the num_polar and num_azimuthal values match
|
||||
if target_representation == 'angle':
|
||||
if target_representation == REPRESENTATION_ANGLE:
|
||||
if num_polar != self.num_polar or num_azimuthal != self.num_azimuthal:
|
||||
raise ValueError("Cannot translate between `angle`"
|
||||
" representations with different angle"
|
||||
|
|
@ -1749,13 +1739,13 @@ class XSdata:
|
|||
|
||||
xsdata.representation = target_representation
|
||||
# We have different actions depending on the representation conversion
|
||||
if target_representation == 'isotropic':
|
||||
if target_representation == REPRESENTATION_ISOTROPIC:
|
||||
# This is not needed for the correct functionality, but these
|
||||
# values are changed back to None for clarity
|
||||
xsdata._num_polar = None
|
||||
xsdata._num_azimuthal = None
|
||||
|
||||
elif target_representation == 'angle':
|
||||
elif target_representation == REPRESENTATION_ANGLE:
|
||||
xsdata.num_polar = num_polar
|
||||
xsdata.num_azimuthal = num_azimuthal
|
||||
|
||||
|
|
@ -1777,7 +1767,7 @@ class XSdata:
|
|||
# current data is just the average over the angle bins
|
||||
new_data = orig_data.mean(axis=(0, 1))
|
||||
|
||||
elif target_representation == 'angle':
|
||||
elif target_representation == REPRESENTATION_ANGLE:
|
||||
# Since we are going from isotropic to angle, the
|
||||
# current data is just copied for every angle bin
|
||||
new_shape = (num_polar, num_azimuthal) + \
|
||||
|
|
@ -1812,7 +1802,7 @@ class XSdata:
|
|||
|
||||
check_value('target_format', target_format, _SCATTER_TYPES)
|
||||
check_type('target_order', target_order, Integral)
|
||||
if target_format == 'legendre':
|
||||
if target_format == SCATTER_LEGENDRE:
|
||||
check_greater_than('target_order', target_order, 0, equality=True)
|
||||
else:
|
||||
check_greater_than('target_order', target_order, 0)
|
||||
|
|
@ -1829,14 +1819,14 @@ class XSdata:
|
|||
new_shape = orig_data.shape[:-1] + (xsdata.num_orders,)
|
||||
new_data = np.zeros(new_shape)
|
||||
|
||||
if self.scatter_format == 'legendre':
|
||||
if target_format == 'legendre':
|
||||
if self.scatter_format == SCATTER_LEGENDRE:
|
||||
if target_format == SCATTER_LEGENDRE:
|
||||
# Then we are changing orders and only need to change
|
||||
# dimensionality of the mu data and pad/truncate as needed
|
||||
order = min(xsdata.num_orders, self.num_orders)
|
||||
new_data[..., :order] = orig_data[..., :order]
|
||||
|
||||
elif target_format == 'tabular':
|
||||
elif target_format == SCATTER_TABULAR:
|
||||
mu = np.linspace(-1, 1, xsdata.num_orders)
|
||||
# Evaluate the legendre on the mu grid
|
||||
for imu in range(len(mu)):
|
||||
|
|
@ -1845,7 +1835,7 @@ class XSdata:
|
|||
(l + 0.5) * eval_legendre(l, mu[imu]) *
|
||||
orig_data[..., l])
|
||||
|
||||
elif target_format == 'histogram':
|
||||
elif target_format == SCATTER_HISTOGRAM:
|
||||
# This code uses the vectorized integration capabilities
|
||||
# instead of having an isotropic and angle representation
|
||||
# path.
|
||||
|
|
@ -1863,27 +1853,26 @@ class XSdata:
|
|||
orig_data[..., l])
|
||||
new_data[..., h_bin] = simps(table_fine, mu_fine)
|
||||
|
||||
elif self.scatter_format == 'tabular':
|
||||
elif self.scatter_format == SCATTER_TABULAR:
|
||||
# Calculate the mu points of the current data
|
||||
mu_self = np.linspace(-1, 1, self.num_orders)
|
||||
|
||||
if target_format == 'legendre':
|
||||
if target_format == SCATTER_LEGENDRE:
|
||||
# Find the Legendre coefficients via integration. To best
|
||||
# use the vectorized integration capabilities of scipy,
|
||||
# this is done with fixed sample integration routines.
|
||||
mu_fine = np.linspace(-1, 1, _NMU)
|
||||
y = [interp1d(mu_self, orig_data)(mu_fine) *
|
||||
eval_legendre(l, mu_fine)
|
||||
for l in range(xsdata.num_orders)]
|
||||
for l in range(xsdata.num_orders):
|
||||
new_data[..., l] = simps(y[l], mu_fine)
|
||||
y = (interp1d(mu_self, orig_data)(mu_fine) *
|
||||
eval_legendre(l, mu_fine))
|
||||
new_data[..., l] = simps(y, mu_fine)
|
||||
|
||||
elif target_format == 'tabular':
|
||||
elif target_format == SCATTER_TABULAR:
|
||||
# Simply use an interpolating function to get the new data
|
||||
mu = np.linspace(-1, 1, xsdata.num_orders)
|
||||
new_data[..., :] = interp1d(mu_self, orig_data)(mu)
|
||||
|
||||
elif target_format == 'histogram':
|
||||
elif target_format == SCATTER_HISTOGRAM:
|
||||
# Use an interpolating function to do the bin-wise
|
||||
# integrals
|
||||
mu = np.linspace(-1, 1, xsdata.num_orders + 1)
|
||||
|
|
@ -1897,7 +1886,7 @@ class XSdata:
|
|||
mu_fine = np.linspace(mu[h_bin], mu[h_bin + 1], _NMU)
|
||||
new_data[..., h_bin] = simps(interp(mu_fine), mu_fine)
|
||||
|
||||
elif self.scatter_format == 'histogram':
|
||||
elif self.scatter_format == SCATTER_HISTOGRAM:
|
||||
# The histogram format does not have enough information to
|
||||
# convert to the other forms without inducing some amount of
|
||||
# error. We will make the assumption that the center of the bin
|
||||
|
|
@ -1914,22 +1903,21 @@ class XSdata:
|
|||
|
||||
# We now have a tabular distribution in tab_data on mu_self.
|
||||
# We now proceed just like the tabular branch above.
|
||||
if target_format == 'legendre':
|
||||
if target_format == SCATTER_LEGENDRE:
|
||||
# find the legendre coefficients via integration. To best
|
||||
# use the vectorized integration capabilities of scipy,
|
||||
# this will be done with fixed sample integration routines.
|
||||
mu_fine = np.linspace(-1, 1, _NMU)
|
||||
y = [interp(mu_fine) * norm * eval_legendre(l, mu_fine)
|
||||
for l in range(xsdata.num_orders)]
|
||||
for l in range(xsdata.num_orders):
|
||||
new_data[..., l] = simps(y[l], mu_fine)
|
||||
y = interp(mu_fine) * norm * eval_legendre(l, mu_fine)
|
||||
new_data[..., l] = simps(y, mu_fine)
|
||||
|
||||
elif target_format == 'tabular':
|
||||
elif target_format == SCATTER_TABULAR:
|
||||
# Simply use an interpolating function to get the new data
|
||||
mu = np.linspace(-1, 1, xsdata.num_orders)
|
||||
new_data[..., :] = interp(mu) * norm
|
||||
|
||||
elif target_format == 'histogram':
|
||||
elif target_format == SCATTER_HISTOGRAM:
|
||||
# Use an interpolating function to do the bin-wise
|
||||
# integrals
|
||||
mu = np.linspace(-1, 1, xsdata.num_orders + 1)
|
||||
|
|
@ -1968,7 +1956,7 @@ class XSdata:
|
|||
|
||||
if self.representation is not None:
|
||||
grp.attrs['representation'] = np.string_(self.representation)
|
||||
if self.representation == 'angle':
|
||||
if self.representation == REPRESENTATION_ANGLE:
|
||||
if self.num_azimuthal is not None:
|
||||
grp.attrs['num_azimuthal'] = self.num_azimuthal
|
||||
|
||||
|
|
@ -2055,10 +2043,10 @@ class XSdata:
|
|||
|
||||
# Get the sparse scattering data to print to the library
|
||||
G = self.energy_groups.num_groups
|
||||
if self.representation == 'isotropic':
|
||||
if self.representation == REPRESENTATION_ISOTROPIC:
|
||||
Np = 1
|
||||
Na = 1
|
||||
elif self.representation == 'angle':
|
||||
elif self.representation == REPRESENTATION_ANGLE:
|
||||
Np = self.num_polar
|
||||
Na = self.num_azimuthal
|
||||
|
||||
|
|
@ -2066,19 +2054,19 @@ class XSdata:
|
|||
for p in range(Np):
|
||||
for a in range(Na):
|
||||
for g_in in range(G):
|
||||
if self.scatter_format == 'legendre':
|
||||
if self.representation == 'isotropic':
|
||||
if self.scatter_format == SCATTER_LEGENDRE:
|
||||
if self.representation == REPRESENTATION_ISOTROPIC:
|
||||
matrix = \
|
||||
self._scatter_matrix[i][g_in, :, 0]
|
||||
elif self.representation == 'angle':
|
||||
elif self.representation == REPRESENTATION_ANGLE:
|
||||
matrix = \
|
||||
self._scatter_matrix[i][p, a, g_in, :, 0]
|
||||
else:
|
||||
if self.representation == 'isotropic':
|
||||
if self.representation == REPRESENTATION_ISOTROPIC:
|
||||
matrix = \
|
||||
np.sum(self._scatter_matrix[i][g_in, :, :],
|
||||
axis=1)
|
||||
elif self.representation == 'angle':
|
||||
elif self.representation == REPRESENTATION_ANGLE:
|
||||
matrix = \
|
||||
np.sum(self._scatter_matrix[i][p, a, g_in, :, :],
|
||||
axis=1)
|
||||
|
|
@ -2096,9 +2084,9 @@ class XSdata:
|
|||
flat_scatt = []
|
||||
for p in range(Np):
|
||||
for a in range(Na):
|
||||
if self.representation == 'isotropic':
|
||||
if self.representation == REPRESENTATION_ISOTROPIC:
|
||||
matrix = self._scatter_matrix[i][:, :, :]
|
||||
elif self.representation == 'angle':
|
||||
elif self.representation == REPRESENTATION_ANGLE:
|
||||
matrix = self._scatter_matrix[i][p, a, :, :, :]
|
||||
for g_in in range(G):
|
||||
for g_out in range(g_out_bounds[p, a, g_in, 0],
|
||||
|
|
@ -2118,9 +2106,9 @@ class XSdata:
|
|||
flat_mult = []
|
||||
for p in range(Np):
|
||||
for a in range(Na):
|
||||
if self.representation == 'isotropic':
|
||||
if self.representation == REPRESENTATION_ISOTROPIC:
|
||||
matrix = self._multiplicity_matrix[i][:, :]
|
||||
elif self.representation == 'angle':
|
||||
elif self.representation == REPRESENTATION_ANGLE:
|
||||
matrix = self._multiplicity_matrix[i][p, a, :, :]
|
||||
for g_in in range(G):
|
||||
for g_out in range(g_out_bounds[p, a, g_in, 0],
|
||||
|
|
@ -2134,10 +2122,10 @@ class XSdata:
|
|||
# And finally, adjust g_out_bounds for 1-based group counting
|
||||
# and write it.
|
||||
g_out_bounds[:, :, :, :] += 1
|
||||
if self.representation == 'isotropic':
|
||||
if self.representation == REPRESENTATION_ISOTROPIC:
|
||||
scatt_grp.create_dataset("g_min", data=g_out_bounds[0, 0, :, 0])
|
||||
scatt_grp.create_dataset("g_max", data=g_out_bounds[0, 0, :, 1])
|
||||
elif self.representation == 'angle':
|
||||
elif self.representation == REPRESENTATION_ANGLE:
|
||||
scatt_grp.create_dataset("g_min", data=g_out_bounds[:, :, :, 0])
|
||||
scatt_grp.create_dataset("g_max", data=g_out_bounds[:, :, :, 1])
|
||||
|
||||
|
|
@ -2190,7 +2178,7 @@ class XSdata:
|
|||
if 'representation' in attrs:
|
||||
representation = group.attrs['representation'].decode()
|
||||
else:
|
||||
representation = 'isotropic'
|
||||
representation = REPRESENTATION_ISOTROPIC
|
||||
|
||||
data = cls(name, energy_groups, float_temperatures, representation,
|
||||
num_delayed_groups)
|
||||
|
|
@ -2203,7 +2191,7 @@ class XSdata:
|
|||
data.atomic_weight_ratio = group.attrs['atomic_weight_ratio']
|
||||
if 'order' in attrs:
|
||||
data.order = group.attrs['order']
|
||||
if data.representation == 'angle':
|
||||
if data.representation == REPRESENTATION_ANGLE:
|
||||
data.num_azimuthal = group.attrs['num_azimuthal']
|
||||
data.num_polar = group.attrs['num_polar']
|
||||
|
||||
|
|
@ -2230,28 +2218,28 @@ class XSdata:
|
|||
flat_scatter = scatt_group['scatter_matrix'][()]
|
||||
scatter_matrix = np.zeros(data.xs_shapes["[G][G'][Order]"])
|
||||
G = data.energy_groups.num_groups
|
||||
if data.representation == 'isotropic':
|
||||
if data.representation == REPRESENTATION_ISOTROPIC:
|
||||
Np = 1
|
||||
Na = 1
|
||||
elif data.representation == 'angle':
|
||||
elif data.representation == REPRESENTATION_ANGLE:
|
||||
Np = data.num_polar
|
||||
Na = data.num_azimuthal
|
||||
flat_index = 0
|
||||
for p in range(Np):
|
||||
for a in range(Na):
|
||||
for g_in in range(G):
|
||||
if data.representation == 'isotropic':
|
||||
if data.representation == REPRESENTATION_ISOTROPIC:
|
||||
g_mins = g_min[g_in]
|
||||
g_maxs = g_max[g_in]
|
||||
elif data.representation == 'angle':
|
||||
elif data.representation == REPRESENTATION_ANGLE:
|
||||
g_mins = g_min[p, a, g_in]
|
||||
g_maxs = g_max[p, a, g_in]
|
||||
for g_out in range(g_mins - 1, g_maxs):
|
||||
for ang in range(data.num_orders):
|
||||
if data.representation == 'isotropic':
|
||||
if data.representation == REPRESENTATION_ISOTROPIC:
|
||||
scatter_matrix[g_in, g_out, ang] = \
|
||||
flat_scatter[flat_index]
|
||||
elif data.representation == 'angle':
|
||||
elif data.representation == REPRESENTATION_ANGLE:
|
||||
scatter_matrix[p, a, g_in, g_out, ang] = \
|
||||
flat_scatter[flat_index]
|
||||
flat_index += 1
|
||||
|
|
@ -2265,17 +2253,17 @@ class XSdata:
|
|||
for p in range(Np):
|
||||
for a in range(Na):
|
||||
for g_in in range(G):
|
||||
if data.representation == 'isotropic':
|
||||
if data.representation == REPRESENTATION_ISOTROPIC:
|
||||
g_mins = g_min[g_in]
|
||||
g_maxs = g_max[g_in]
|
||||
elif data.representation == 'angle':
|
||||
elif data.representation == REPRESENTATION_ANGLE:
|
||||
g_mins = g_min[p, a, g_in]
|
||||
g_maxs = g_max[p, a, g_in]
|
||||
for g_out in range(g_mins - 1, g_maxs):
|
||||
if data.representation == 'isotropic':
|
||||
if data.representation == REPRESENTATION_ISOTROPIC:
|
||||
mult_matrix[g_in, g_out] = \
|
||||
flat_mult[flat_index]
|
||||
elif data.representation == 'angle':
|
||||
elif data.representation == REPRESENTATION_ANGLE:
|
||||
mult_matrix[p, a, g_in, g_out] = \
|
||||
flat_mult[flat_index]
|
||||
flat_index += 1
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue