def test_multi_dimensional_value(self):
kwargs = dict(
value=np.arange(3 * 4, dtype=int).reshape(3, 4), size=3, dtype=float
)
expected_exception = ValueError
match = "value must not have more than 1 dimension."
with pytest.raises(expected_exception, match=match):
_validate_scalar_to_multi(**kwargs)
def test_list_value_uncastable_to_dtype(self):
kwargs = dict(value=[1, 2, "c"], size=3, dtype=int)
expected_exception = ValueError
match = "value and dtype are incompatible with one another."
with pytest.raises(expected_exception, match=match):
_validate_scalar_to_multi(**kwargs)
def test_value_incompatible_with_size(self):
kwargs = dict(value=[1, 2, 3, 4], size=3, dtype=int)
expected_exception = ValueError
match = "The length of value must either be 1 or it must match size if size is provided."
with pytest.raises(expected_exception, match=match):
_validate_scalar_to_multi(**kwargs)
def test_non_int_size(self):
kwargs = dict(value=[1, 2, 3, 4], size="size: not an int", dtype=float)
expected_exception = TypeError
match = "size must be either None or interpretable as an integer."
with pytest.raises(expected_exception, match=match):
_validate_scalar_to_multi(**kwargs)
def test_negative_size(self):
kwargs = dict(value=[], size=-1, dtype=float)
expected_exception = ValueError
match = "size must be non-negative."
with pytest.raises(expected_exception, match=match):
_validate_scalar_to_multi(**kwargs)
def test_scalar_value_with_size_None(self):
kwargs = dict(value=1, size=None, dtype=float)
correct_output = np.array([1], float)
assert np.array_equal(_validate_scalar_to_multi(**kwargs), correct_output)
def test_array_value(self):
kwargs = dict(value=np.array([1, 2, 3], float), size=3, dtype=int)
correct_output = np.array([1, 2, 3], int)
assert np.array_equal(_validate_scalar_to_multi(**kwargs), correct_output)
def test_list_value_dtype_casting_to_int(self):
kwargs = dict(value=[1, 2, 3.5], size=3, dtype=int)
correct_output = np.array([1, 2, 3], int)
assert np.array_equal(_validate_scalar_to_multi(**kwargs), correct_output)
def test_scalar_dtype_casting(self):
kwargs = dict(value=9.5, size=4, dtype=int)
correct_output = np.full(4, 9, int)
assert np.array_equal(_validate_scalar_to_multi(**kwargs), correct_output)
def test_empty(self):
kwargs = dict(value=1, size=0, dtype=int)
correct_output = np.array([], int)
assert np.array_equal(_validate_scalar_to_multi(**kwargs), correct_output)
