def test_remove_nans():
tests = [
((1, 1, 2), (1, 1, 2)),
((None, 1, 2), (1, 1, 2)),
((1, None, 2), (1, 2, 2)),
((1, 2, None), (1, 2, 2)),
((1, 2, None, None), (1, 2, 2, 2)),
((None, None, 1, 2), (1, 1, 1, 2)),
((1, None, None, 2), (1, 2, 2, 2)),
((None, 1, None, 2, None, 3, None), (1, 1, 2, 2, 3, 3, 3)),
]
converters = [
(int, np.nan),
(float, np.nan),
(str, np.nan),
(lambda x: pd.to_datetime(x, unit='ns'), np.datetime64('NaT')),
]
for conv, none_val in converters:
for inputs, expected in tests:
params = [none_val if x is None else conv(x) for x in inputs]
expected = [conv(x) for x in expected]
assert remove_nans(params) == expected
def test_remove_nans():
tests = [
((1, 1, 2), (1, 1, 2)),
((None, 1, 2), (1, 1, 2)),
((1, None, 2), (1, 2, 2)),
((1, 2, None), (1, 2, 2)),
((1, 2, None, None), (1, 2, 2, 2)),
((None, None, 1, 2), (1, 1, 1, 2)),
((1, None, None, 2), (1, 2, 2, 2)),
((None, 1, None, 2, None, 3, None), (1, 1, 2, 2, 3, 3, 3)),
]
converters = [
(int, np.nan),
(float, np.nan),
(str, np.nan),
(lambda x: pd.to_datetime(x, unit='ns'), np.datetime64('NaT')),
]
for conv, none_val in converters:
for inputs, expected in tests:
params = [none_val if x is None else conv(x) for x in inputs]
expected = [conv(x) for x in expected]
assert remove_nans(params) == expected
