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Resolve warnings related to numpy 2.0 (#3044)

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Paul Romano 2024-06-19 15:47:08 -05:00 • committed by GitHub
parent 3bedd043d0
commit 3dff03f824
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4 changed files with 9 additions and 17 deletions
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10
openmc/mgxs_library.py
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@ -1862,7 +1862,7 @@ class XSdata:
table_fine[..., imu] += ((l + 0.5)
* eval_legendre(l, mu_fine[imu]) *
orig_data[..., l])
new_data[..., h_bin] = integrate(table_fine, mu_fine)
new_data[..., h_bin] = integrate(table_fine, x=mu_fine)
elif self.scatter_format == SCATTER_TABULAR:
# Calculate the mu points of the current data
@ -1876,7 +1876,7 @@ class XSdata:
for l in range(xsdata.num_orders):
y = (interp1d(mu_self, orig_data)(mu_fine) *
eval_legendre(l, mu_fine))
new_data[..., l] = integrate(y, mu_fine)
new_data[..., l] = integrate(y, x=mu_fine)
elif target_format == SCATTER_TABULAR:
# Simply use an interpolating function to get the new data
@ -1895,7 +1895,7 @@ class XSdata:
interp = interp1d(mu_self, orig_data)
for h_bin in range(xsdata.num_orders):
mu_fine = np.linspace(mu[h_bin], mu[h_bin + 1], _NMU)
new_data[..., h_bin] = integrate(interp(mu_fine), mu_fine)
new_data[..., h_bin] = integrate(interp(mu_fine), x=mu_fine)
elif self.scatter_format == SCATTER_HISTOGRAM:
# The histogram format does not have enough information to
@ -1921,7 +1921,7 @@ class XSdata:
mu_fine = np.linspace(-1, 1, _NMU)
for l in range(xsdata.num_orders):
y = interp(mu_fine) * norm * eval_legendre(l, mu_fine)
new_data[..., l] = integrate(y, mu_fine)
new_data[..., l] = integrate(y, x=mu_fine)
elif target_format == SCATTER_TABULAR:
# Simply use an interpolating function to get the new data
@ -1940,7 +1940,7 @@ class XSdata:
for h_bin in range(xsdata.num_orders):
mu_fine = np.linspace(mu[h_bin], mu[h_bin + 1], _NMU)
new_data[..., h_bin] = \
norm * integrate(interp(mu_fine), mu_fine)
norm * integrate(interp(mu_fine), x=mu_fine)
# Remove small values resulting from numerical precision issues
new_data[..., np.abs(new_data) < 1.E-10] = 0.

2
openmc/statepoint.py
View file

@ -235,7 +235,7 @@ class StatePoint:
if self._global_tallies is None:
data = self._f['global_tallies'][()]
gt = np.zeros(data.shape[0], dtype=[
('name', 'a14'), ('sum', 'f8'), ('sum_sq', 'f8'),
('name', 'S14'), ('sum', 'f8'), ('sum_sq', 'f8'),
('mean', 'f8'), ('std_dev', 'f8')])
gt['name'] = ['k-collision', 'k-absorption', 'k-tracklength',
'leakage']

5
tests/regression_tests/mg_temperature/build_2g.py
View file

@ -289,8 +289,9 @@ def build_inf_model(xsnames, xslibname, temperature, tempmethod='nearest'):
settings_file.output = {'summary': False}
# Create an initial uniform spatial source distribution over fissionable zones
bounds = [-INF, -INF, -INF, INF, INF, INF]
uniform_dist = openmc.stats.Box(bounds[:3], bounds[3:], only_fissionable=True)
uniform_dist = openmc.stats.Box(bounds[:3], bounds[3:])
settings_file.temperature = {'method': tempmethod}
settings_file.source = openmc.IndependentSource(space=uniform_dist)
settings_file.source = openmc.IndependentSource(
space=uniform_dist, constraints={'fissionable': True})
model.settings = settings_file
model.export_to_model_xml()

9
tests/unit_tests/test_stats.py
View file

@ -376,15 +376,6 @@ def test_box():
d = openmc.stats.Box.from_xml_element(elem)
assert d.lower_left == pytest.approx(lower_left)
assert d.upper_right == pytest.approx(upper_right)
assert not d.only_fissionable
# only fissionable parameter
d2 = openmc.stats.Box(lower_left, upper_right, True)
assert d2.only_fissionable
elem = d2.to_xml_element()
assert elem.attrib['type'] == 'fission'
d = openmc.stats.Spatial.from_xml_element(elem)
assert isinstance(d, openmc.stats.Box)
def test_point():