def test_allnans(self):
mat = np.array([np.nan]*9).reshape(3, 3)
for axis in [None, 0, 1]:
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
assert_(np.isnan(np.nanpercentile(mat, 60, axis=axis)).all())
if axis is None:
assert_(len(w) == 1)
else:
assert_(len(w) == 3)
assert_(issubclass(w[0].category, RuntimeWarning))
# Check scalar
assert_(np.isnan(np.nanpercentile(np.nan, 60)))
if axis is None:
assert_(len(w) == 2)
else:
assert_(len(w) == 4)
assert_(issubclass(w[0].category, RuntimeWarning))
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