Source code for pylops.basicoperators.Flip

import numpy as np

from pylops import LinearOperator

[docs]class Flip(LinearOperator): r"""Flip along an axis. Flip a multi-dimensional array along a specified direction ``dir``. 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 flipping is applied. 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 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 lenght of the input model. As this operator is self-adjoint, :math:`x` and :math:`y` in the equation above are simply swapped in adjoint mode. """ def __init__(self, N, dims=None, dir=0, dtype="float64"): self.N = N self.dir = dir if dims is None: self.dims = (self.N,) self.reshape = False else: if != self.N: raise ValueError("product of dims must equal N") else: self.dims = dims self.reshape = True 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.flip(x, axis=self.dir) if self.reshape: y = y.ravel() return y def _rmatvec(self, x): return self._matvec(x)