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make search=True the defaut and vectfit_nuclide public

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This commit is contained in:
Jingang Liang 2020-10-13 16:40:37 +08:00
parent 4024f07fe2
commit 5249fe661d
1 changed files with 9 additions and 5 deletions
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14
openmc/data/multipole.py
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@ -207,7 +207,8 @@ def _vectfit_xs(energy, ce_xs, mts, rtol=1e-3, atol=1e-5, orders=None,
# inverse weighting is used for minimizing the relative deviation instead of
# absolute deviation in vector fitting
weight = 1.0/f
with np.errstate(divide='ignore'):
weight = 1.0/f
# avoid too large weights which will harm the fitting accuracy
min_cross_section = 1e-7
@ -387,7 +388,7 @@ def _vectfit_xs(energy, ce_xs, mts, rtol=1e-3, atol=1e-5, orders=None,
return (mp_poles, mp_residues)
def _vectfit_nuclide(endf_file, njoy_error=5e-4, vf_pieces=None,
def vectfit_nuclide(endf_file, njoy_error=5e-4, vf_pieces=None,
log=False, path_out=None, mp_filename=None, **kwargs):
r"""Generate multipole data for a nuclide from ENDF.
@ -1023,7 +1024,7 @@ class WindowedMultipole(EqualityMixin):
Whether to print running logs (use int for verbosity control)
vf_options : dict, optional
Dictionary of keyword arguments, e.g. {'njoy_error': 0.001},
passed to :func:`openmc.data.multipole._vectfit_nuclide`
passed to :func:`openmc.data.multipole.vectfit_nuclide`
wmp_options : dict, optional
Dictionary of keyword arguments, e.g. {'search': True, 'rtol': 0.01},
passed to :func:`openmc.data.WindowedMultipole.from_multipole`
@ -1047,13 +1048,13 @@ class WindowedMultipole(EqualityMixin):
wmp_options.update(log=log)
# generate multipole data from EDNF
mp_data = _vectfit_nuclide(endf_file, **vf_options)
mp_data = vectfit_nuclide(endf_file, **vf_options)
# windowing
return cls.from_multipole(mp_data, **wmp_options)
@classmethod
def from_multipole(cls, mp_data, search=False, log=False, **kwargs):
def from_multipole(cls, mp_data, search=True, log=False, **kwargs):
"""Generate windowed multipole neutron data from multipole data.
Parameters
@ -1082,6 +1083,9 @@ class WindowedMultipole(EqualityMixin):
# windowing with specific options
if not search:
# set default value for curvefit order if not specified
if 'n_cf' not in kwargs:
kwargs.update(n_cf=5)
return _windowing(mp_data, log=log, **kwargs)
# search optimal WMP from a range of window sizes and CF orders