import numpy as np
from pylops import LinearOperator
[docs]class Roll(LinearOperator):
r"""Roll along an axis.
Roll a multi-dimensional array along a specified direction ``dir`` for
a chosen number of samples (``shift``).
Parameters
----------
N : :obj:`int`
Number of samples in model.
dims : :obj:`list`, optional
Number of samples for each dimension
(``None`` if only one dimension is available)
dir : :obj:`int`, optional
Direction along which rolling is applied.
shift : :obj:`int`, optional
Number of samples by which elements are shifted
dtype : :obj:`str`, optional
Type of elements in input array.
Attributes
----------
shape : :obj:`tuple`
Operator shape
explicit : :obj:`bool`
Operator contains a matrix that can be solved explicitly
(``True``) or not (``False``)
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, N, dims=None, dir=0, shift=1, dtype="float64"):
self.N = N
self.dir = dir
if dims is None:
self.dims = (self.N,)
self.reshape = False
else:
if np.prod(dims) != self.N:
raise ValueError("product of dims must equal N")
else:
self.dims = dims
self.reshape = True
self.shift = shift
self.shape = (self.N, self.N)
self.dtype = np.dtype(dtype)
self.explicit = False
def _matvec(self, x):
if self.reshape:
x = np.reshape(x, self.dims)
y = np.roll(x, shift=self.shift, axis=self.dir)
return y.ravel()
def _rmatvec(self, x):
if self.reshape:
x = np.reshape(x, self.dims)
y = np.roll(x, shift=-self.shift, axis=self.dir)
return y.ravel()