__all__ = ["Real"]
import numpy as np
from pylops import LinearOperator
from pylops.utils._internal import _value_or_sized_to_tuple
from pylops.utils.typing import DTypeLike, InputDimsLike, NDArray
[docs]
class Real(LinearOperator):
r"""Real operator.
Return the real component of the input. The adjoint returns a complex
number with the same real component as the input and zero imaginary
component.
Parameters
----------
dims : :obj:`int` or :obj:`tuple`
Number of samples for each dimension
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``.
rdtype : :obj:`numpy.dtype`
Real dtype corresponding to ``dtype``.
shape : :obj:`tuple`
Operator shape.
Notes
-----
In forward mode:
.. math::
y_{i} = \Re\{x_{i}\} \quad \forall i=0,\ldots,N-1
In adjoint mode:
.. math::
x_{i} = \Re\{y_{i}\} + 0i \quad \forall i=0,\ldots,N-1
"""
def __init__(
self,
dims: int | InputDimsLike,
dtype: DTypeLike = "complex128",
name: str = "R",
) -> None:
dims = _value_or_sized_to_tuple(dims)
super().__init__(
dtype=np.dtype(dtype), dims=dims, dimsd=dims, clinear=False, name=name
)
self.rdtype = np.real(np.ones(1, self.dtype)).dtype
def _matvec(self, x: NDArray) -> NDArray:
return x.real.astype(self.rdtype)
def _rmatvec(self, x: NDArray) -> NDArray:
return (x.real + 0j).astype(self.dtype)
PyLops