numpy.dstack¶
-
numpy.
dstack
(tup)[source]¶ 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
ornp.stack
. Thenp.stack
function was added in NumPy 1.10.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
stack
- Join a sequence of arrays along a new axis.
vstack
- Stack along first axis.
hstack
- Stack along second axis.
concatenate
- Join a sequence of arrays along an existing axis.
dsplit
- Split array along third axis.
Notes
Equivalent to
np.concatenate(tup, axis=2)
if tup contains arrays that are at least 3-dimensional.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]]])