e V is a dense matrix with dimensions (N, K).
dtype : dtype
    Data type of the matrix.
rmatmat : callable f(V)
    Returns A^H @ V, where V is a dense matrix with dimensions (M, K).

Attributes
----------
args : tuple
    For linear operators describing products etc. of other linear
    operators, the operands of the binary operation.
ndim : int
    Number of dimensions (this is always 2)

See Also
--------
aslinearoperator : Construct LinearOperators

Notes
-----
The user-defined matvec() function must properly handle the case
where v has shape (N,) as well as the (N,1) case.  The shape of
the return type is handled internally by LinearOperator.

It is highly recommended to explicitly specify the `dtype`, otherwise
it is determined automatically at the cost of a single matvec application
on `int8` zero vector using the promoted `dtype` of the output.
Python `int` could be difficult to automatically cast to numpy integers
in the definition of the `matvec` so the determination may be inaccurate.
It is assumed that `matmat`, `rmatvec`, and `rmatmat` would result in
the same dtype of the output given an `int8` input as `matvec`.

LinearOperator instances can also be multiplied, added with each
other and exponentiated, all lazily: the result of these operations
is always a new, composite LinearOperator, that defers linear
operations to the original operators and combines the results.

More details regarding how to subclass a LinearOperator and several
examples of concrete LinearOperator instances can be found in the
external project `PyLops <https://pylops.readthedocs.io>`_.


Examples
--------
>>> import numpy as np
>>> from scipy.sparse.linalg import LinearOperator
>>> def mv(v):
...     return np.array([2*v[0], 3*v[1]])
...
>>> A = LinearOperator((2,2), matvec=mv)
>>> A
<2x2 _CustomLinearOperator with dtype=int8>
>>> A.matvec(np.ones(2))
array([ 2.,  3.])
>>> A @ np.ones(2)
array([ 2.,  3.])

