deepmr.optim.power_method#
- deepmr.optim.power_method = <function power_method>#
Use power iteration to calculate the spectral norm of a Linop.
From MIRTorch (guanhuaw/MIRTorch)
- Parameters:
A (Callable | torch.Tensor | np.ndarray) – Linear opeartor
x (torch.Tensor | np.ndarray) – Initial guess of singular vector corresponding to max singular value
AH (Callable | torch.Tensor | np.ndarray, optional) – Adjoint operator AH = A.H. If not provided, attempt to estimate from A. The default is
None
.AHA (Callable | torch.Tensor | np.ndarray, optional) – Normal operator AHA = AH * A. If not provided, estimate from A and AH. The default is
None
.device (str, optional) – Computational device. The default is
None
(infer from input).niter (int, optional) – Maximum number of iterations. The default is
10
.tol (float, optional) – Stopping criterion. The default is
None
(run untilniter
).
- Returns:
The spectral norm of the operator
A
.- Return type: