def dstack(tup):
return _nx.concatenate([atleast_3d(_m) for _m in tup], <NUM_LIT:2>)<EOL>
Stack arrays in sequence depth wise (along third axis).

Takes a sequence of arrays and stack them along the third axis
to make a single array. Rebuilds arrays divided by `dsplit`.
This is a simple way to stack 2D arrays (images) into a single
3D array for processing.

Parameters
----------
tup : sequence of arrays
    Arrays to stack. All of them must have the same shape along all
    but the third axis.

Returns
-------
stacked : ndarray
    The array formed by stacking the given arrays.

See Also
--------
vstack : Stack along first axis.
hstack : Stack along second axis.
concatenate : Join arrays.
dsplit : Split array along third axis.

Notes
-----
Equivalent to ``np.concatenate(tup, axis=2)``.

Examples
--------
>>> 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]]])