Source code for pylops.basicoperators.flip

__all__ = ["Flip"]

from typing import Union

import numpy as np

from pylops import LinearOperator
from pylops.utils._internal import _value_or_sized_to_tuple
from pylops.utils.decorators import reshaped
from pylops.utils.typing import DTypeLike, InputDimsLike, NDArray

[docs]class Flip(LinearOperator): r"""Flip along an axis. Flip a multi-dimensional array along ``axis``. 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 flipped. 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 ---------- shape : :obj:`tuple` Operator shape explicit : :obj:`bool` Operator contains a matrix that can be solved explicitly (``True``) or not (``False``) Notes ----- The Flip operator flips the input model (and data) along any chosen direction. For simplicity, given a one dimensional array, in forward mode this is equivalent to: .. math:: y[i] = x[N-1-i] \quad \forall i=0,1,2,\ldots,N-1 where :math:`N` is the dimension of the input model along ``axis``. As this operator is self-adjoint, :math:`x` and :math:`y` in the equation above are simply swapped in adjoint mode. """ def __init__( self, dims: Union[int, InputDimsLike], axis: int = -1, dtype: DTypeLike = "float64", name: str = "F", ) -> None: dims = _value_or_sized_to_tuple(dims) super().__init__(dtype=np.dtype(dtype), dims=dims, dimsd=dims, name=name) self.axis = axis @reshaped(swapaxis=True) def _matvec(self, x: NDArray) -> NDArray: y = np.flip(x, axis=-1) return y def _rmatvec(self, x: NDArray) -> NDArray: return self._matvec(x)