Stack arrays in sequence horizontally (column wise).
This is equivalent to concatenation along the second axis, except for 1-D arrays where it concatenates along the first axis. Rebuilds arrays divided by
This function makes most sense for arrays with up to 3 dimensions. For instance, for pixel-data with a height (first axis), width (second axis), and r/g/b channels (third axis). The functions
blockprovide more general stacking and concatenation operations.
- tupsequence of ndarrays
The arrays must have the same shape along all but the second axis, except 1-D arrays which can be any length.
The array formed by stacking the given arrays.
>>> a = np.array((1,2,3)) >>> b = np.array((2,3,4)) >>> np.hstack((a,b)) array([1, 2, 3, 2, 3, 4]) >>> a = np.array([,,]) >>> b = np.array([,,]) >>> np.hstack((a,b)) array([[1, 2], [2, 3], [3, 4]])