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https://github.com/openmc-dev/openmc.git
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ee7b95245a
Co-authored-by: Christina Cai <chrsitinacai48933@gmail.com> Co-authored-by: christinacai123 <63215816+christinacai123@users.noreply.github.com>
142 lines
4.3 KiB
Python
142 lines
4.3 KiB
Python
from collections.abc import Iterable
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from numbers import Real, Integral
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import numpy as np
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import openmc.checkvalue as cv
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from openmc.stats import Tabular, Univariate
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from .angle_energy import AngleEnergy
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from .endf import get_tab2_record, get_tab1_record
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class LaboratoryAngleEnergy(AngleEnergy):
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"""Laboratory angle-energy distribution
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Parameters
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----------
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breakpoints : Iterable of int
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Breakpoints defining interpolation regions
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interpolation : Iterable of int
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Interpolation codes
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energy : Iterable of float
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Incoming energies at which distributions exist
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mu : Iterable of openmc.stats.Univariate
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Distribution of scattering cosines for each incoming energy
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energy_out : Iterable of Iterable of openmc.stats.Univariate
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Distribution of outgoing energies for each incoming energy/scattering
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cosine
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Attributes
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----------
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breakpoints : Iterable of int
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Breakpoints defining interpolation regions
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interpolation : Iterable of int
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Interpolation codes
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energy : Iterable of float
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Incoming energies at which distributions exist
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mu : Iterable of openmc.stats.Univariate
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Distribution of scattering cosines for each incoming energy
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energy_out : Iterable of Iterable of openmc.stats.Univariate
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Distribution of outgoing energies for each incoming energy/scattering
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cosine
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"""
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def __init__(self, breakpoints, interpolation, energy, mu, energy_out):
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super().__init__()
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self.breakpoints = breakpoints
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self.interpolation = interpolation
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self.energy = energy
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self.mu = mu
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self.energy_out = energy_out
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@property
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def breakpoints(self):
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return self._breakpoints
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@breakpoints.setter
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def breakpoints(self, breakpoints):
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cv.check_type('laboratory angle-energy breakpoints', breakpoints,
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Iterable, Integral)
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self._breakpoints = breakpoints
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@property
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def interpolation(self):
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return self._interpolation
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@interpolation.setter
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def interpolation(self, interpolation):
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cv.check_type('laboratory angle-energy interpolation', interpolation,
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Iterable, Integral)
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self._interpolation = interpolation
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@property
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def energy(self):
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return self._energy
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@energy.setter
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def energy(self, energy):
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cv.check_type('laboratory angle-energy incoming energy', energy,
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Iterable, Real)
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self._energy = energy
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@property
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def mu(self):
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return self._mu
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@mu.setter
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def mu(self, mu):
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cv.check_type('laboratory angle-energy outgoing cosine', mu,
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Iterable, Univariate)
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self._mu = mu
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@property
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def energy_out(self):
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return self._energy_out
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@energy_out.setter
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def energy_out(self, energy_out):
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cv.check_iterable_type('laboratory angle-energy outgoing energy',
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energy_out, Univariate, 2, 2)
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self._energy_out = energy_out
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@classmethod
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def from_endf(cls, file_obj):
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"""Generate laboratory angle-energy distribution from an ENDF evaluation
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Parameters
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----------
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file_obj : file-like object
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ENDF file positioned at the start of a section for a correlated
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angle-energy distribution
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Returns
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-------
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openmc.data.LaboratoryAngleEnergy
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Laboratory angle-energy distribution
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"""
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params, tab2 = get_tab2_record(file_obj)
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ne = params[5]
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energy = np.zeros(ne)
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mu = []
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energy_out = []
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for i in range(ne):
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params, _ = get_tab2_record(file_obj)
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energy[i] = params[1]
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n_mu = params[5]
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mu_i = np.zeros(n_mu)
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p_mu_i = np.zeros(n_mu)
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energy_out_i = []
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for j in range(n_mu):
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params, f = get_tab1_record(file_obj)
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mu_i[j] = params[1]
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p_mu_i[j] = sum(f.y)
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energy_out_i.append(Tabular(f.x, f.y))
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mu.append(Tabular(mu_i, p_mu_i))
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energy_out.append(energy_out_i)
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return cls(tab2.breakpoints, tab2.interpolation, energy, mu, energy_out)
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def to_hdf5(self, group):
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raise NotImplementedError
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