flopscope.numpy.roll
fnp.roll(a, shift, axis=None)[flopscope source][numpy source]
Roll array elements along a given axis.
Adapted from NumPy docs np.roll
Roll array elements along axis. Cost: numel(output).
Elements that roll beyond the last position are re-introduced at the first.
Parameters
- a:array_like
Input array.
- shift:int or tuple of ints
The number of places by which elements are shifted. If a tuple, then
axismust be a tuple of the same size, and each of the given axes is shifted by the corresponding number. If an int whileaxisis 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:ndarray
Output array, with the same shape as
a.
See also
- we.flops.rollaxis Roll the specified axis backwards, until it lies in a given position.
Notes
Supports rolling over multiple dimensions simultaneously.
Examples
>>> import flopscope.numpy as fnp
>>> x = flops.arange(10)
>>> flops.roll(x, 2)
array([8, 9, 0, 1, 2, 3, 4, 5, 6, 7])
>>> flops.roll(x, -2)
array([2, 3, 4, 5, 6, 7, 8, 9, 0, 1])>>> x2 = flops.reshape(x, (2, 5))
>>> x2
array([[0, 1, 2, 3, 4],
[5, 6, 7, 8, 9]])
>>> flops.roll(x2, 1)
array([[9, 0, 1, 2, 3],
[4, 5, 6, 7, 8]])
>>> flops.roll(x2, -1)
array([[1, 2, 3, 4, 5],
[6, 7, 8, 9, 0]])
>>> flops.roll(x2, 1, axis=0)
array([[5, 6, 7, 8, 9],
[0, 1, 2, 3, 4]])
>>> flops.roll(x2, -1, axis=0)
array([[5, 6, 7, 8, 9],
[0, 1, 2, 3, 4]])
>>> flops.roll(x2, 1, axis=1)
array([[4, 0, 1, 2, 3],
[9, 5, 6, 7, 8]])
>>> flops.roll(x2, -1, axis=1)
array([[1, 2, 3, 4, 0],
[6, 7, 8, 9, 5]])
>>> flops.roll(x2, (1, 1), axis=(1, 0))
array([[9, 5, 6, 7, 8],
[4, 0, 1, 2, 3]])
>>> flops.roll(x2, (2, 1), axis=(1, 0))
array([[8, 9, 5, 6, 7],
[3, 4, 0, 1, 2]])