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| author | Sebastian Berg <sebastian@sipsolutions.net> | 2021-04-19 21:51:47 -0500 |
|---|---|---|
| committer | Sebastian Berg <sebastian@sipsolutions.net> | 2021-05-12 15:33:34 -0700 |
| commit | 6fd0f97b436c162ba4b613c7dff665d56d351f84 (patch) | |
| tree | 1c5960816f601770757d0c05822c8ef601088e69 /numpy | |
| parent | 834b1184c1f609a4e9ba06c55ea64ba882e4cdc1 (diff) | |
| download | numpy-6fd0f97b436c162ba4b613c7dff665d56d351f84.tar.gz | |
TST: Fixup tests and make sure complex is also the value
Diffstat (limited to 'numpy')
| -rw-r--r-- | numpy/core/tests/test_dtype.py | 24 |
1 files changed, 21 insertions, 3 deletions
diff --git a/numpy/core/tests/test_dtype.py b/numpy/core/tests/test_dtype.py index 2246a4802..34d418926 100644 --- a/numpy/core/tests/test_dtype.py +++ b/numpy/core/tests/test_dtype.py @@ -1097,12 +1097,12 @@ class TestPromotion: (2**32-1, np.complex128), (np.float16(2), np.complex64), (np.float32(2), np.complex64), - (np.float128(2), np.complex64), + (np.longdouble(2), np.complex64), (np.nextafter(np.longdouble(1.7e308), 0.), np.complex128), (np.longdouble(1.7e308), np.clongdouble), ]) - def test_complex_value_based(self, other, expected): - # This would change if we modfiy the value based promotion + def test_complex_other_value_based(self, other, expected): + # This would change if we modify the value based promotion min_complex = np.dtype(np.complex64) res = np.result_type(other, min_complex) @@ -1111,6 +1111,24 @@ class TestPromotion: res = np.minimum(other, np.ones(3, dtype=min_complex)).dtype assert res == expected + @pytest.mark.parametrize(["other", "expected"], + [(np.bool_, np.complex128), + (np.int64, np.complex128), + (np.float16, np.complex64), + (np.float32, np.complex64), + (np.float64, np.complex128), + (np.longdouble, np.clongdouble), + ]) + def test_complex_scalar_value_based(self, other, expected): + # This would change if we modify the value based promotion + complex_scalar = 1j + + res = np.result_type(other, complex_scalar) + assert res == expected + # Check the same for a simple ufunc call that uses the same logic: + res = np.minimum(np.ones(3, dtype=other), complex_scalar).dtype + assert res == expected + @pytest.mark.parametrize(["dtypes", "expected"], [([np.uint16, np.int16, np.float16], np.float32), ([np.uint16, np.int8, np.float16], np.float32), |