dpnp.dstack

dpnp.dstack(tup)[source]

Stack arrays in sequence depth wise (along third axis).

This is equivalent to concatenation along the third axis after 2-D arrays of shape (M, N) have been reshaped to (M, N, 1) and 1-D arrays of shape (N,) have been reshaped to (1, N, 1). Rebuilds arrays divided by dpnp.dsplit.

For full documentation refer to numpy.dstack.

Parameters:: tup ({dpnp.ndarray, usm_ndarray}) -- One or more array-like sequences. The arrays must have the same shape along all but the third axis. 1-D or 2-D arrays must have the same shape.
Returns:: out -- The array formed by stacking the given arrays, will be at least 3-D.
Return type:: dpnp.ndarray

See also

dpnp.concatenate: Join a sequence of arrays along an existing axis.
dpnp.vstack: Stack arrays in sequence vertically (row wise).
dpnp.hstack: Stack arrays in sequence horizontally (column wise).
dpnp.column_stack: Stack 1-D arrays as columns into a 2-D array.
dpnp.stack: Join a sequence of arrays along a new axis.
dpnp.block: Assemble an ndarray from nested lists of blocks.
dpnp.dsplit: Split array along third axis.

Examples

>>> import dpnp as np
>>> a = np.array((1, 2, 3))
>>> b = np.array((2, 3, 4))
>>> np.dstack((a, b))
array([[[1, 2],
        [2, 3],
        [3, 4]]])

>>> a = np.array([[1], [2], [3]])
>>> b = np.array([[2], [3], [4]])
>>> np.dstack((a, b))
array([[[1, 2]],
       [[2, 3]],
       [[3, 4]]])