def test_result_type_dask_array():
# verify it works without evaluating dask arrays
da = pytest.importorskip('dask.array')
dask = pytest.importorskip('dask')
def error():
raise RuntimeError
array = da.from_delayed(dask.delayed(error)(), (), np.float64)
with pytest.raises(RuntimeError):
array.compute()
actual = dtypes.result_type(array)
assert actual == np.float64
# note that this differs from the behavior for scalar numpy arrays, which
# would get promoted to float32
actual = dtypes.result_type(array, np.array([0.5, 1.0], dtype=np.float32))
assert actual == np.float64
def test_result_type_dask_array():
# verify it works without evaluating dask arrays
da = pytest.importorskip('dask.array')
dask = pytest.importorskip('dask')
def error():
raise RuntimeError
array = da.from_delayed(dask.delayed(error)(), (), np.float64)
with pytest.raises(RuntimeError):
array.compute()
actual = dtypes.result_type(array)
assert actual == np.float64
# note that this differs from the behavior for scalar numpy arrays, which
# would get promoted to float32
actual = dtypes.result_type(array, np.array([0.5, 1.0], dtype=np.float32))
assert actual == np.float64
def test_result_type_scalar():
actual = dtypes.result_type(np.arange(3, dtype=np.float32), np.nan)
assert actual == np.float32
def test_result_type(args, expected):
actual = dtypes.result_type(*args)
assert actual == expected
def test_result_type_scalar():
actual = dtypes.result_type(np.arange(3, dtype=np.float32), np.nan)
assert actual == np.float32
def test_result_type(args, expected):
actual = dtypes.result_type(*args)
assert actual == expected