mxnet.np.stack¶
-
stack
(arrays, axis=0, out=None)¶ - 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 if axis=-1 it will be the last dimension.
- 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 – The stacked array has one more dimension than the input arrays.
- Return type
ndarray
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.
Examples
>>> arrays = [np.random.rand(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.]])
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