PETSc version 3.16.6
KSPLSQRConvergedDefault
Determines convergence of the LSQR Krylov method.
Synopsis
#include "petscksp.h"
PetscErrorCode KSPLSQRConvergedDefault(KSP ksp,PetscInt n,PetscReal rnorm,KSPConvergedReason *reason,void *ctx)
Collective on ksp
Input Parameters
| ksp | - iterative context
|
| n | - iteration number
|
| rnorm | - 2-norm residual value (may be estimated)
|
| ctx | - convergence context which must be created by KSPConvergedDefaultCreate()
|
reason is set to
| positive | - if the iteration has converged;
|
| negative | - if residual norm exceeds divergence threshold;
|
| 0 | - otherwise.
|
Notes
KSPConvergedDefault() is called first to check for convergence in A*x=b.
If that does not determine convergence then checks convergence for the least squares problem, i.e. in min{|b-A*x|}.
Possible convergence for the least squares problem (which is based on the residual of the normal equations) are KSP_CONVERGED_RTOL_NORMAL norm and KSP_CONVERGED_ATOL_NORMAL.
KSP_CONVERGED_RTOL_NORMAL is returned if ||A'*r|| < rtol * ||A|| * ||r||.
Matrix norm ||A|| is iteratively refined estimate, see KSPLSQRGetNorms().
This criterion is now largely compatible with that in MATLAB lsqr().
See Also
KSPLSQR, KSPSetConvergenceTest(), KSPSetTolerances(), KSPConvergedSkip(), KSPConvergedReason, KSPGetConvergedReason(),
KSPConvergedDefaultSetUIRNorm(), KSPConvergedDefaultSetUMIRNorm(), KSPConvergedDefaultCreate(), KSPConvergedDefaultDestroy(), KSPConvergedDefault(), KSPLSQRGetNorms(), KSPLSQRSetExactMatNorm()
Level
intermediate
Location
src/ksp/ksp/impls/lsqr/lsqr.c
Index of all KSP routines
Table of Contents for all manual pages
Index of all manual pages