numpy.unstack — NumPy v2.3.dev0 Manual (original) (raw)

numpy.unstack(x, /, *, axis=0)[source]#

Split an array into a sequence of arrays along the given axis.

The axis parameter specifies the dimension along which the array will be split. For example, if axis=0 (the default) it will be the first dimension and if axis=-1 it will be the last dimension.

The result is a tuple of arrays split along axis.

New in version 2.1.0.

Parameters:

xndarray

The array to be unstacked.

axisint, optional

Axis along which the array will be split. Default: 0.

Returns:

unstackedtuple of ndarrays

The unstacked arrays.

See also

stack

Join a sequence of arrays along a new axis.

concatenate

Join a sequence of arrays along an existing axis.

block

Assemble an nd-array from nested lists of blocks.

split

Split array into a list of multiple sub-arrays of equal size.

Notes

unstack serves as the reverse operation of stack, i.e.,stack(unstack(x, axis=axis), axis=axis) == x.

This function is equivalent to tuple(np.moveaxis(x, axis, 0)), since iterating on an array iterates along the first axis.

Examples

arr = np.arange(24).reshape((2, 3, 4)) np.unstack(arr) (array([[ 0, 1, 2, 3], [ 4, 5, 6, 7], [ 8, 9, 10, 11]]), array([[12, 13, 14, 15], [16, 17, 18, 19], [20, 21, 22, 23]])) np.unstack(arr, axis=1) (array([[ 0, 1, 2, 3], [12, 13, 14, 15]]), array([[ 4, 5, 6, 7], [16, 17, 18, 19]]), array([[ 8, 9, 10, 11], [20, 21, 22, 23]])) arr2 = np.stack(np.unstack(arr, axis=1), axis=1) arr2.shape (2, 3, 4) np.all(arr == arr2) np.True_