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