__all__ = ["Roll"]
import numpy as np
from pylops import LinearOperator
from pylops.utils._internal import _value_or_sized_to_tuple
from pylops.utils.backend import get_array_module
from pylops.utils.decorators import reshaped
from pylops.utils.typing import DTypeLike, InputDimsLike, NDArray
[docs]
class Roll(LinearOperator):
r"""Roll along an axis.
Roll a multi-dimensional array along ``axis`` for
a chosen number of samples (``shift``).
Parameters
----------
dims : :obj:`list` or :obj:`int`
Number of samples for each dimension
axis : :obj:`int`, optional
.. versionadded:: 2.0.0
Axis along which model is rolled.
shift : :obj:`int`, optional
Number of samples by which elements are shifted
dtype : :obj:`str`, optional
Type of elements in input array.
name : :obj:`str`, optional
.. versionadded:: 2.0.0
Name of operator (to be used by :func:`pylops.utils.describe.describe`)
Attributes
----------
dims : :obj:`tuple`
Shape of the array after the adjoint, but before flattening.
For example, ``x_reshaped = (Op.H * y.ravel()).reshape(Op.dims)``.
dimsd : :obj:`tuple`
Shape of the array after the forward, but before flattening. In
this case, same as ``dims``.
shape : :obj:`tuple`
Operator shape.
Notes
-----
The Roll operator is a thin wrapper around :func:`numpy.roll` and shifts
elements in a multi-dimensional array along a specified direction for a
chosen number of samples.
"""
def __init__(
self,
dims: int | InputDimsLike,
axis: int = -1,
shift: int = 1,
dtype: DTypeLike = "float64",
name: str = "R",
) -> None:
dims = _value_or_sized_to_tuple(dims)
super().__init__(dtype=np.dtype(dtype), dims=dims, dimsd=dims, name=name)
self.axis = axis
self.shift = shift
@reshaped(swapaxis=True)
def _matvec(self, x: NDArray) -> NDArray:
ncp = get_array_module(x)
return ncp.roll(x, shift=self.shift, axis=-1)
@reshaped(swapaxis=True)
def _rmatvec(self, x: NDArray) -> NDArray:
ncp = get_array_module(x)
return ncp.roll(x, shift=-self.shift, axis=-1)
PyLops