KSPComputeEigenvaluesExplicitly#
Computes all of the eigenvalues of the preconditioned operator using LAPACK.
Synopsis#
#include "petscksp.h"
PetscErrorCode KSPComputeEigenvaluesExplicitly(KSP ksp, PetscInt nmax, PetscReal r[], PetscReal c[])
Collective
Input Parameters#
ksp - iterative context obtained from
KSPCreate()nmax - size of arrays
randc
Output Parameters#
r - real part of computed eigenvalues, provided by user with a dimension at least of
nc - complex part of computed eigenvalues, provided by user with a dimension at least of
n
Notes#
This approach is very slow but will generally provide accurate eigenvalue
estimates. This routine explicitly forms a dense matrix representing
the preconditioned operator, and thus will run only for relatively small
problems, say n < 500.
Many users may just want to use the monitoring routine
KSPMonitorSingularValue() (which can be set with option -ksp_monitor_singular_value)
to print the singular values at each iteration of the linear solve.
The preconditioner operator, rhs vector, and solution vectors should be
set before this routine is called. i.e use KSPSetOperators(), KSPSolve()
See Also#
KSP: Linear System Solvers, KSP, KSPComputeEigenvalues(), KSPMonitorSingularValue(), KSPComputeExtremeSingularValues(), KSPSetOperators(), KSPSolve()
Level#
advanced
Location#
Index of all KSP routines
Table of Contents for all manual pages
Index of all manual pages