numpy.stack¶
-
numpy.
stack
(arrays, axis=0, out=None)[source]¶ Join a sequence of arrays along a new axis.
The axis parameter specifies the index of the new axis in the dimensions of the result. For example, if
axis=0
it will be the first dimension and ifaxis=-1
it will be the last dimension.New in version 1.10.0.
Parameters: arrays : sequence of array_like
Each array must have the same shape.
axis : int, optional
The axis in the result array along which the input arrays are stacked.
out : ndarray, optional
If provided, the destination to place the result. The shape must be correct, matching that of what stack would have returned if no out argument were specified.
Returns: stacked : ndarray
The stacked array has one more dimension than the input arrays.
See also
concatenate
- Join a sequence of arrays along an existing axis.
split
- Split array into a list of multiple sub-arrays of equal size.
block
- Assemble arrays from blocks.
Examples
>>> arrays = [np.random.randn(3, 4) for _ in range(10)] >>> np.stack(arrays, axis=0).shape (10, 3, 4)
>>> np.stack(arrays, axis=1).shape (3, 10, 4)
>>> np.stack(arrays, axis=2).shape (3, 4, 10)
>>> a = np.array([1, 2, 3]) >>> b = np.array([2, 3, 4]) >>> np.stack((a, b)) array([[1, 2, 3], [2, 3, 4]])
>>> np.stack((a, b), axis=-1) array([[1, 2], [2, 3], [3, 4]])