def estimate_spectral_norm_diff(A, B, its=20):
"""
Estimate spectral norm of the difference of two matrices by the randomized
power method.
.. This function automatically detects the matrix data type and calls the
appropriate backend. For details, see :func:`backend.idd_diffsnorm` and
:func:`backend.idz_diffsnorm`.
Parameters
----------
A : :class:`scipy.sparse.linalg.LinearOperator`
First matrix given as a :class:`scipy.sparse.linalg.LinearOperator` with the
`matvec` and `rmatvec` methods (to apply the matrix and its adjoint).
B : :class:`scipy.sparse.linalg.LinearOperator`
Second matrix given as a :class:`scipy.sparse.linalg.LinearOperator` with
the `matvec` and `rmatvec` methods (to apply the matrix and its adjoint).
its : int, optional
Number of power method iterations.
Returns
-------
float
Spectral norm estimate of matrix difference.
"""
from scipy.sparse.linalg import aslinearoperator
A = aslinearoperator(A)
B = aslinearoperator(B)
m, n = A.shape
matvec1 = lambda x: A.matvec(x)
matveca1 = lambda x: A.rmatvec(x)
matvec2 = lambda x: B.matvec(x)
matveca2 = lambda x: B.rmatvec(x)
if _is_real(A):
return backend.idd_diffsnorm(m,
n,
matveca1,
matveca2,
matvec1,
matvec2,
its=its)
else:
return backend.idz_diffsnorm(m,
n,
matveca1,
matveca2,
matvec1,
matvec2,
its=its)
def estimate_spectral_norm_diff(A, B, its=20):
"""
Estimate spectral norm of the difference of two matrices by the randomized
power method.
.. This function automatically detects the matrix data type and calls the
appropriate backend. For details, see :func:`backend.idd_diffsnorm` and
:func:`backend.idz_diffsnorm`.
Parameters
----------
A : :class:`scipy.sparse.linalg.LinearOperator`
First matrix given as a :class:`scipy.sparse.linalg.LinearOperator` with the
`matvec` and `rmatvec` methods (to apply the matrix and its adjoint).
B : :class:`scipy.sparse.linalg.LinearOperator`
Second matrix given as a :class:`scipy.sparse.linalg.LinearOperator` with
the `matvec` and `rmatvec` methods (to apply the matrix and its adjoint).
its : int
Number of power method iterations.
Returns
-------
float
Spectral norm estimate of matrix difference.
"""
from scipy.sparse.linalg import aslinearoperator
A = aslinearoperator(A)
B = aslinearoperator(B)
m, n = A.shape
matvec1 = lambda x: A. matvec(x)
matveca1 = lambda x: A.rmatvec(x)
matvec2 = lambda x: B. matvec(x)
matveca2 = lambda x: B.rmatvec(x)
if _is_real(A):
return backend.idd_diffsnorm(
m, n, matveca1, matveca2, matvec1, matvec2, its=its)
else:
return backend.idz_diffsnorm(
m, n, matveca1, matveca2, matvec1, matvec2, its=its)
