def test_array_of_different_depths(self):
# When multiple arrays (or array-likes) are included in a
# sequences and have different depth, we currently discover
# as many dimensions as they share. (see also gh-17224)
arr = np.zeros((3, 2))
mismatch_first_dim = np.zeros((1, 2))
mismatch_second_dim = np.zeros((3, 3))
dtype, shape = _discover_array_parameters([arr, mismatch_second_dim],
dtype=np.dtype("O"))
assert shape == (2, 3)
dtype, shape = _discover_array_parameters([arr, mismatch_first_dim],
dtype=np.dtype("O"))
assert shape == (2, )
# The second case is currently supported because the arrays
# can be stored as objects:
res = np.asarray([arr, mismatch_first_dim], dtype=np.dtype("O"))
assert res[0] is arr
assert res[1] is mismatch_first_dim
def test_default_dtype_instance(self, dtype_char):
if dtype_char in "SU":
dtype = np.dtype(dtype_char + "1")
elif dtype_char == "V":
# Legacy behaviour was to use V8. The reason was float64 being the
# default dtype and that having 8 bytes.
dtype = np.dtype("V8")
else:
dtype = np.dtype(dtype_char)
discovered_dtype, _ = _discover_array_parameters([], type(dtype))
assert discovered_dtype == dtype
assert discovered_dtype.itemsize == dtype.itemsize
