4.]]),
 array([[ 3.],
       [ 7.],
       [11.],
       [15.]]),
 array([], shape=(4, 0), dtype=float64)]

With a higher dimensional array the split is still along the second axis.

>>> x = np.arange(8.0).reshape(2, 2, 2)
>>> x
array([[[0.,  1.],
        [2.,  3.]],
       [[4.,  5.],
        [6.,  7.]]])
>>> np.hsplit(x, 2)
[array([[[0.,  1.]],
       [[4.,  5.]]]),
 array([[[2.,  3.]],
       [[6.,  7.]]])]

With a 1-D array, the split is along axis 0.

>>> x = np.array([0, 1, 2, 3, 4, 5])
>>> np.hsplit(x, 2)
[array([0, 1, 2]), array([3, 4, 5])]

r