mxnet.np.roll

roll(a, shift, axis=None)

Roll array elements along a given axis.

Elements that roll beyond the last position are re-introduced at the first.

Parameters

  • a (ndarray) – Input array.

  • shift (int or tuple of ints) – The number of places by which elements are shifted. If a tuple, then axis must be a tuple of the same size, and each of the given axes is shifted by the corresponding number. If an int while axis is a tuple of ints, then the same value is used for all given axes.

  • axis (int or tuple of ints, optional) – Axis or axes along which elements are shifted. By default, the array is flattened before shifting, after which the original shape is restored.

Returns

res – Output array, with the same shape as a.

Return type

ndarray

Notes

Supports rolling over multiple dimensions simultaneously.

Examples

>>> x = np.arange(10)
>>> np.roll(x, 2)
array([8., 9., 0., 1., 2., 3., 4., 5., 6., 7.])
>>> np.roll(x, -2)
array([2., 3., 4., 5., 6., 7., 8., 9., 0., 1.])

>>> x2 = np.reshape(x, (2,5))
>>> x2
array([[0., 1., 2., 3., 4.],
       [5., 6., 7., 8., 9.]])
>>> np.roll(x2, 1)
array([[9., 0., 1., 2., 3.],
       [4., 5., 6., 7., 8.]])
>>> np.roll(x2, -1)
array([[1., 2., 3., 4., 5.],
       [6., 7., 8., 9., 0.]])
>>> np.roll(x2, 1, axis=0)
array([[5., 6., 7., 8., 9.],
       [0., 1., 2., 3., 4.]])
>>> np.roll(x2, -1, axis=0)
array([[5., 6., 7., 8., 9.],
       [0., 1., 2., 3., 4.]])
>>> np.roll(x2, 1, axis=1)
array([[4., 0., 1., 2., 3.],
       [9., 5., 6., 7., 8.]])
>>> np.roll(x2, -1, axis=1)
array([[1., 2., 3., 4., 0.],
       [6., 7., 8., 9., 5.]])