SciPy = < instance at 0x52b9502c>

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.

This function continues to be supported for backward compatibility, but you should prefer np.concatenate or np.stack. The np.stack function was added in NumPy 1.10.


tup : sequence of arrays

Arrays to stack. All of them must have the same shape along all but the third axis.


stacked : ndarray

The array formed by stacking the given arrays.

See also

Join a sequence of arrays along a new axis.
Stack along first axis.
Stack along second axis.
Join a sequence of arrays along an existing axis.
Split array along third axis.


The function is applied to both the _data and the _mask, if any.


>>> 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]]])

Previous topic

Next topic