def test_legendre():
n = 5
f = openmc.LegendreFilter(n)
assert f.order == n
assert f.bins[0] == 'P0'
assert f.bins[-1] == 'P5'
assert len(f.bins) == n + 1
# Make sure __repr__ works
repr(f)
# to_xml_element()
elem = f.to_xml_element()
assert elem.tag == 'filter'
assert elem.attrib['type'] == 'legendre'
assert elem.find('order').text == str(n)
def test_first_moment(run_in_tmpdir, box_model):
plain_tally = openmc.Tally()
plain_tally.scores = ['flux', 'scatter']
# Create tallies with expansion filters
leg_tally = openmc.Tally()
leg_tally.filters = [openmc.LegendreFilter(3)]
leg_tally.scores = ['scatter']
leg_sptl_tally = openmc.Tally()
leg_sptl_tally.filters = [openmc.SpatialLegendreFilter(3, 'x', -5., 5.)]
leg_sptl_tally.scores = ['scatter']
sph_scat_filter = openmc.SphericalHarmonicsFilter(5)
sph_scat_filter.cosine = 'scatter'
sph_scat_tally = openmc.Tally()
sph_scat_tally.filters = [sph_scat_filter]
sph_scat_tally.scores = ['scatter']
sph_flux_filter = openmc.SphericalHarmonicsFilter(5)
sph_flux_filter.cosine = 'particle'
sph_flux_tally = openmc.Tally()
sph_flux_tally.filters = [sph_flux_filter]
sph_flux_tally.scores = ['flux']
zernike_tally = openmc.Tally()
zernike_tally.filters = [openmc.ZernikeFilter(3, r=10.)]
zernike_tally.scores = ['scatter']
# Add tallies to model and ensure they all use the same estimator
box_model.tallies = [
plain_tally, leg_tally, leg_sptl_tally, sph_scat_tally, sph_flux_tally,
zernike_tally
]
for t in box_model.tallies:
t.estimator = 'analog'
sp_name = box_model.run()
# Check that first moment matches the score from the plain tally
with openmc.StatePoint(sp_name) as sp:
# Get scores from tally without expansion filters
flux, scatter = sp.tallies[plain_tally.id].mean.ravel()
# Check that first moment matches
first_score = lambda t: sp.tallies[t.id].mean.ravel()[0]
assert first_score(leg_tally) == scatter
assert first_score(leg_sptl_tally) == scatter
assert first_score(sph_scat_tally) == scatter
assert first_score(sph_flux_tally) == approx(flux)
assert first_score(zernike_tally) == approx(scatter)