static PetscErrorCode PCPreSolve_Eisenstat(PC pc,KSP ksp,Vec b,Vec x)
{
PC_Eisenstat *eis = (PC_Eisenstat*)pc->data;
PetscBool nonzero;
PetscErrorCode ierr;
PetscFunctionBegin;
if (pc->presolvedone < 2) {
if (pc->mat != pc->pmat) SETERRQ(((PetscObject)pc)->comm,PETSC_ERR_SUP,"Cannot have different mat and pmat");
/* swap shell matrix and true matrix */
eis->A = pc->mat;
pc->mat = eis->shell;
}
if (!eis->b[pc->presolvedone-1]) {
ierr = VecDuplicate(b,&eis->b[pc->presolvedone-1]);CHKERRQ(ierr);
ierr = PetscLogObjectParent(pc,eis->b[pc->presolvedone-1]);CHKERRQ(ierr);
}
/* if nonzero initial guess, modify x */
ierr = KSPGetInitialGuessNonzero(ksp,&nonzero);CHKERRQ(ierr);
if (nonzero) {
ierr = VecCopy(x,eis->b[pc->presolvedone-1]);CHKERRQ(ierr);
ierr = MatSOR(eis->A,eis->b[pc->presolvedone-1],eis->omega,SOR_APPLY_UPPER,0.0,1,1,x);CHKERRQ(ierr);
}
/* save true b, other option is to swap pointers */
ierr = VecCopy(b,eis->b[pc->presolvedone-1]);CHKERRQ(ierr);
/* modify b by (L + D/omega)^{-1} */
ierr = MatSOR(eis->A,eis->b[pc->presolvedone-1],eis->omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),0.0,1,1,b);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
static PetscErrorCode KSPSetUp_SpecEst(KSP ksp)
{
KSP_SpecEst *spec = (KSP_SpecEst*)ksp->data;
PetscErrorCode ierr;
PetscBool nonzero;
PetscFunctionBegin;
ierr = KSPSetPC(spec->kspest,ksp->pc);CHKERRQ(ierr);
ierr = KSPSetPC(spec->kspcheap,ksp->pc);CHKERRQ(ierr);
ierr = KSPGetInitialGuessNonzero(ksp,&nonzero);CHKERRQ(ierr);
ierr = KSPSetInitialGuessNonzero(spec->kspest,nonzero);CHKERRQ(ierr);
ierr = KSPSetInitialGuessNonzero(spec->kspcheap,nonzero);CHKERRQ(ierr);
ierr = KSPSetComputeSingularValues(spec->kspest,PETSC_TRUE);CHKERRQ(ierr);
ierr = KSPSetUp(spec->kspest);CHKERRQ(ierr);
spec->current = PETSC_FALSE;
PetscFunctionReturn(0);
}
static PetscErrorCode KSPChebyshevSetEstimateEigenvalues_Chebyshev(KSP ksp,PetscReal a,PetscReal b,PetscReal c,PetscReal d)
{
KSP_Chebyshev *cheb = (KSP_Chebyshev*)ksp->data;
PetscErrorCode ierr;
PetscFunctionBegin;
if (a != 0.0 || b != 0.0 || c != 0.0 || d != 0.0) {
if (!cheb->kspest) { /* should this block of code be moved to KSPSetUp_Chebyshev()? */
PetscBool nonzero;
ierr = KSPCreate(PetscObjectComm((PetscObject)ksp),&cheb->kspest);CHKERRQ(ierr);
ierr = PetscObjectIncrementTabLevel((PetscObject)cheb->kspest,(PetscObject)ksp,1);CHKERRQ(ierr);
ierr = KSPSetOptionsPrefix(cheb->kspest,((PetscObject)ksp)->prefix);CHKERRQ(ierr);
ierr = KSPAppendOptionsPrefix(cheb->kspest,"est_");CHKERRQ(ierr);
ierr = KSPGetPC(cheb->kspest,&cheb->pcnone);CHKERRQ(ierr);
ierr = PetscObjectReference((PetscObject)cheb->pcnone);CHKERRQ(ierr);
ierr = PCSetType(cheb->pcnone,PCNONE);CHKERRQ(ierr);
ierr = KSPSetPC(cheb->kspest,ksp->pc);CHKERRQ(ierr);
ierr = KSPGetInitialGuessNonzero(ksp,&nonzero);CHKERRQ(ierr);
ierr = KSPSetInitialGuessNonzero(cheb->kspest,nonzero);CHKERRQ(ierr);
ierr = KSPSetComputeEigenvalues(cheb->kspest,PETSC_TRUE);CHKERRQ(ierr);
/* Estimate with a fixed number of iterations */
ierr = KSPSetConvergenceTest(cheb->kspest,KSPConvergedSkip,0,0);CHKERRQ(ierr);
ierr = KSPSetNormType(cheb->kspest,KSP_NORM_NONE);CHKERRQ(ierr);
ierr = KSPSetTolerances(cheb->kspest,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,cheb->eststeps);CHKERRQ(ierr);
}
if (a >= 0) cheb->tform[0] = a;
if (b >= 0) cheb->tform[1] = b;
if (c >= 0) cheb->tform[2] = c;
if (d >= 0) cheb->tform[3] = d;
cheb->estimate_current = PETSC_FALSE;
} else {
ierr = KSPDestroy(&cheb->kspest);CHKERRQ(ierr);
ierr = PCDestroy(&cheb->pcnone);CHKERRQ(ierr);
}
PetscFunctionReturn(0);
}
void PETScKrylovLinearSolver::initializeSolverState(const SAMRAIVectorReal<NDIM, double>& x,
const SAMRAIVectorReal<NDIM, double>& b)
{
IBTK_TIMER_START(t_initialize_solver_state);
int ierr;
// Rudimentary error checking.
#if !defined(NDEBUG)
if (x.getNumberOfComponents() != b.getNumberOfComponents())
{
TBOX_ERROR(d_object_name << "::initializeSolverState()\n"
<< " vectors must have the same number of components"
<< std::endl);
}
const Pointer<PatchHierarchy<NDIM> >& patch_hierarchy = x.getPatchHierarchy();
if (patch_hierarchy != b.getPatchHierarchy())
{
TBOX_ERROR(d_object_name << "::initializeSolverState()\n"
<< " vectors must have the same hierarchy" << std::endl);
}
const int coarsest_ln = x.getCoarsestLevelNumber();
if (coarsest_ln < 0)
{
TBOX_ERROR(d_object_name << "::initializeSolverState()\n"
<< " coarsest level number must not be negative"
<< std::endl);
}
if (coarsest_ln != b.getCoarsestLevelNumber())
{
TBOX_ERROR(d_object_name << "::initializeSolverState()\n"
<< " vectors must have same coarsest level number"
<< std::endl);
}
const int finest_ln = x.getFinestLevelNumber();
if (finest_ln < coarsest_ln)
{
TBOX_ERROR(d_object_name << "::initializeSolverState()\n"
<< " finest level number must be >= coarsest level number"
<< std::endl);
}
if (finest_ln != b.getFinestLevelNumber())
{
TBOX_ERROR(d_object_name << "::initializeSolverState()\n"
<< " vectors must have same finest level number"
<< std::endl);
}
for (int ln = coarsest_ln; ln <= finest_ln; ++ln)
{
if (!patch_hierarchy->getPatchLevel(ln))
{
TBOX_ERROR(d_object_name << "::initializeSolverState()\n"
<< " hierarchy level " << ln << " does not exist"
<< std::endl);
}
}
#endif
// Deallocate the solver state if the solver is already initialized.
if (d_is_initialized)
{
d_reinitializing_solver = true;
deallocateSolverState();
}
// Create the KSP solver.
if (d_managing_petsc_ksp)
{
ierr = KSPCreate(d_petsc_comm, &d_petsc_ksp);
IBTK_CHKERRQ(ierr);
resetKSPOptions();
}
else if (!d_petsc_ksp)
{
TBOX_ERROR(d_object_name
<< "::initializeSolverState()\n"
<< " cannot initialize solver state for wrapped PETSc KSP object "
"if the wrapped object is NULL" << std::endl);
}
// Setup solution and rhs vectors.
d_x = x.cloneVector(x.getName());
d_petsc_x = PETScSAMRAIVectorReal::createPETScVector(d_x, d_petsc_comm);
d_b = b.cloneVector(b.getName());
d_petsc_b = PETScSAMRAIVectorReal::createPETScVector(d_b, d_petsc_comm);
// Initialize the linear operator and preconditioner objects.
if (d_A) d_A->initializeOperatorState(*d_x, *d_b);
if (d_managing_petsc_ksp || d_user_provided_mat) resetKSPOperators();
if (d_pc_solver) d_pc_solver->initializeSolverState(*d_x, *d_b);
if (d_managing_petsc_ksp || d_user_provided_pc) resetKSPPC();
// Set the KSP options from the PETSc options database.
if (d_options_prefix != "")
{
ierr = KSPSetOptionsPrefix(d_petsc_ksp, d_options_prefix.c_str());
IBTK_CHKERRQ(ierr);
}
ierr = KSPSetFromOptions(d_petsc_ksp);
IBTK_CHKERRQ(ierr);
// Reset the member state variables to correspond to the values used by the
// KSP object. (Command-line options always take precedence.)
const char* ksp_type;
ierr = KSPGetType(d_petsc_ksp, &ksp_type);
IBTK_CHKERRQ(ierr);
d_ksp_type = ksp_type;
PetscBool initial_guess_nonzero;
ierr = KSPGetInitialGuessNonzero(d_petsc_ksp, &initial_guess_nonzero);
IBTK_CHKERRQ(ierr);
d_initial_guess_nonzero = (initial_guess_nonzero == PETSC_TRUE);
ierr = KSPGetTolerances(
d_petsc_ksp, &d_rel_residual_tol, &d_abs_residual_tol, NULL, &d_max_iterations);
IBTK_CHKERRQ(ierr);
// Configure the nullspace object.
resetKSPNullspace();
// Indicate that the solver is initialized.
d_reinitializing_solver = false;
d_is_initialized = true;
IBTK_TIMER_STOP(t_initialize_solver_state);
return;
} // initializeSolverState
/*@
KSPSetFromOptions - Sets KSP options from the options database.
This routine must be called before KSPSetUp() if the user is to be
allowed to set the Krylov type.
Collective on KSP
Input Parameters:
. ksp - the Krylov space context
Options Database Keys:
+ -ksp_max_it - maximum number of linear iterations
. -ksp_rtol rtol - relative tolerance used in default determination of convergence, i.e.
if residual norm decreases by this factor than convergence is declared
. -ksp_atol abstol - absolute tolerance used in default convergence test, i.e. if residual
norm is less than this then convergence is declared
. -ksp_divtol tol - if residual norm increases by this factor than divergence is declared
. -ksp_converged_use_initial_residual_norm - see KSPConvergedDefaultSetUIRNorm()
. -ksp_converged_use_min_initial_residual_norm - see KSPConvergedDefaultSetUMIRNorm()
. -ksp_norm_type - none - skip norms used in convergence tests (useful only when not using
convergence test (say you always want to run with 5 iterations) to
save on communication overhead
preconditioned - default for left preconditioning
unpreconditioned - see KSPSetNormType()
natural - see KSPSetNormType()
. -ksp_check_norm_iteration it - do not compute residual norm until iteration number it (does compute at 0th iteration)
works only for PCBCGS, PCIBCGS and and PCCG
. -ksp_lag_norm - compute the norm of the residual for the ith iteration on the i+1 iteration; this means that one can use
the norm of the residual for convergence test WITHOUT an extra MPI_Allreduce() limiting global synchronizations.
This will require 1 more iteration of the solver than usual.
. -ksp_fischer_guess <model,size> - uses the Fischer initial guess generator for repeated linear solves
. -ksp_constant_null_space - assume the operator (matrix) has the constant vector in its null space
. -ksp_test_null_space - tests the null space set with KSPSetNullSpace() to see if it truly is a null space
. -ksp_knoll - compute initial guess by applying the preconditioner to the right hand side
. -ksp_monitor_cancel - cancel all previous convergene monitor routines set
. -ksp_monitor <optional filename> - print residual norm at each iteration
. -ksp_monitor_lg_residualnorm - plot residual norm at each iteration
. -ksp_monitor_solution - plot solution at each iteration
- -ksp_monitor_singular_value - monitor extremem singular values at each iteration
Notes:
To see all options, run your program with the -help option
or consult Users-Manual: ch_ksp
Level: beginner
.keywords: KSP, set, from, options, database
.seealso: KSPSetUseFischerGuess()
@*/
PetscErrorCode KSPSetFromOptions(KSP ksp)
{
PetscErrorCode ierr;
PetscInt indx;
const char *convtests[] = {"default","skip"};
char type[256], monfilename[PETSC_MAX_PATH_LEN];
PetscViewer monviewer;
PetscBool flg,flag,reuse;
PetscInt model[2]={0,0},nmax;
KSPNormType normtype;
PCSide pcside;
void *ctx;
PetscFunctionBegin;
PetscValidHeaderSpecific(ksp,KSP_CLASSID,1);
if (!ksp->pc) {ierr = KSPGetPC(ksp,&ksp->pc);CHKERRQ(ierr);}
ierr = PCSetFromOptions(ksp->pc);CHKERRQ(ierr);
if (!KSPRegisterAllCalled) {ierr = KSPRegisterAll();CHKERRQ(ierr);}
ierr = PetscObjectOptionsBegin((PetscObject)ksp);CHKERRQ(ierr);
ierr = PetscOptionsFList("-ksp_type","Krylov method","KSPSetType",KSPList,(char*)(((PetscObject)ksp)->type_name ? ((PetscObject)ksp)->type_name : KSPGMRES),type,256,&flg);CHKERRQ(ierr);
if (flg) {
ierr = KSPSetType(ksp,type);CHKERRQ(ierr);
}
/*
Set the type if it was never set.
*/
if (!((PetscObject)ksp)->type_name) {
ierr = KSPSetType(ksp,KSPGMRES);CHKERRQ(ierr);
}
ierr = PetscOptionsInt("-ksp_max_it","Maximum number of iterations","KSPSetTolerances",ksp->max_it,&ksp->max_it,NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-ksp_rtol","Relative decrease in residual norm","KSPSetTolerances",ksp->rtol,&ksp->rtol,NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-ksp_atol","Absolute value of residual norm","KSPSetTolerances",ksp->abstol,&ksp->abstol,NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-ksp_divtol","Residual norm increase cause divergence","KSPSetTolerances",ksp->divtol,&ksp->divtol,NULL);CHKERRQ(ierr);
flag = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_converged_use_initial_residual_norm","Use initial residual residual norm for computing relative convergence","KSPConvergedDefaultSetUIRNorm",flag,&flag,NULL);CHKERRQ(ierr);
if (flag) {ierr = KSPConvergedDefaultSetUIRNorm(ksp);CHKERRQ(ierr);}
flag = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_converged_use_min_initial_residual_norm","Use minimum of initial residual norm and b for computing relative convergence","KSPConvergedDefaultSetUMIRNorm",flag,&flag,NULL);CHKERRQ(ierr);
if (flag) {ierr = KSPConvergedDefaultSetUMIRNorm(ksp);CHKERRQ(ierr);}
ierr = KSPGetInitialGuessNonzero(ksp,&flag);CHKERRQ(ierr);
ierr = PetscOptionsBool("-ksp_initial_guess_nonzero","Use the contents of the solution vector for initial guess","KSPSetInitialNonzero",flag,&flag,&flg);CHKERRQ(ierr);
if (flg) {
ierr = KSPSetInitialGuessNonzero(ksp,flag);CHKERRQ(ierr);
}
ierr = PCGetReusePreconditioner(ksp->pc,&reuse);CHKERRQ(ierr);
ierr = PetscOptionsBool("-ksp_reuse_preconditioner","Use initial preconditioner and don't ever compute a new one ","KSPReusePreconditioner",reuse,&reuse,NULL);CHKERRQ(ierr);
ierr = KSPSetReusePreconditioner(ksp,reuse);CHKERRQ(ierr);
ierr = PetscOptionsBool("-ksp_knoll","Use preconditioner applied to b for initial guess","KSPSetInitialGuessKnoll",ksp->guess_knoll,&ksp->guess_knoll,NULL);CHKERRQ(ierr);
ierr = PetscOptionsBool("-ksp_error_if_not_converged","Generate error if solver does not converge","KSPSetErrorIfNotConverged",ksp->errorifnotconverged,&ksp->errorifnotconverged,NULL);CHKERRQ(ierr);
nmax = 2;
ierr = PetscOptionsIntArray("-ksp_fischer_guess","Use Paul Fischer's algorithm for initial guess","KSPSetUseFischerGuess",model,&nmax,&flag);CHKERRQ(ierr);
if (flag) {
if (nmax != 2) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Must pass in model,size as arguments");
ierr = KSPSetUseFischerGuess(ksp,model[0],model[1]);CHKERRQ(ierr);
}
ierr = PetscOptionsEList("-ksp_convergence_test","Convergence test","KSPSetConvergenceTest",convtests,2,"default",&indx,&flg);CHKERRQ(ierr);
if (flg) {
switch (indx) {
case 0:
ierr = KSPConvergedDefaultCreate(&ctx);CHKERRQ(ierr);
ierr = KSPSetConvergenceTest(ksp,KSPConvergedDefault,ctx,KSPConvergedDefaultDestroy);CHKERRQ(ierr);
break;
case 1: ierr = KSPSetConvergenceTest(ksp,KSPConvergedSkip,NULL,NULL);CHKERRQ(ierr); break;
}
}
ierr = KSPSetUpNorms_Private(ksp,&normtype,&pcside);CHKERRQ(ierr);
ierr = PetscOptionsEnum("-ksp_norm_type","KSP Norm type","KSPSetNormType",KSPNormTypes,(PetscEnum)normtype,(PetscEnum*)&normtype,&flg);CHKERRQ(ierr);
if (flg) { ierr = KSPSetNormType(ksp,normtype);CHKERRQ(ierr); }
ierr = PetscOptionsInt("-ksp_check_norm_iteration","First iteration to compute residual norm","KSPSetCheckNormIteration",ksp->chknorm,&ksp->chknorm,NULL);CHKERRQ(ierr);
flag = ksp->lagnorm;
ierr = PetscOptionsBool("-ksp_lag_norm","Lag the calculation of the residual norm","KSPSetLagNorm",flag,&flag,&flg);CHKERRQ(ierr);
if (flg) {
ierr = KSPSetLagNorm(ksp,flag);CHKERRQ(ierr);
}
ierr = KSPGetDiagonalScale(ksp,&flag);CHKERRQ(ierr);
ierr = PetscOptionsBool("-ksp_diagonal_scale","Diagonal scale matrix before building preconditioner","KSPSetDiagonalScale",flag,&flag,&flg);CHKERRQ(ierr);
if (flg) {
ierr = KSPSetDiagonalScale(ksp,flag);CHKERRQ(ierr);
}
ierr = KSPGetDiagonalScaleFix(ksp,&flag);CHKERRQ(ierr);
ierr = PetscOptionsBool("-ksp_diagonal_scale_fix","Fix diagonally scaled matrix after solve","KSPSetDiagonalScaleFix",flag,&flag,&flg);CHKERRQ(ierr);
if (flg) {
ierr = KSPSetDiagonalScaleFix(ksp,flag);CHKERRQ(ierr);
}
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_constant_null_space","Add constant null space to Krylov solver","KSPSetNullSpace",flg,&flg,NULL);CHKERRQ(ierr);
if (flg) {
MatNullSpace nsp;
ierr = MatNullSpaceCreate(PetscObjectComm((PetscObject)ksp),PETSC_TRUE,0,0,&nsp);CHKERRQ(ierr);
ierr = KSPSetNullSpace(ksp,nsp);CHKERRQ(ierr);
ierr = MatNullSpaceDestroy(&nsp);CHKERRQ(ierr);
}
/* option is actually checked in KSPSetUp(), just here so goes into help message */
if (ksp->nullsp) {
ierr = PetscOptionsName("-ksp_test_null_space","Is provided null space correct","None",&flg);CHKERRQ(ierr);
}
/*
Prints reason for convergence or divergence of each linear solve
*/
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_converged_reason","Print reason for converged or diverged","KSPSolve",flg,&flg,NULL);CHKERRQ(ierr);
if (flg) ksp->printreason = PETSC_TRUE;
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_monitor_cancel","Remove any hardwired monitor routines","KSPMonitorCancel",flg,&flg,NULL);CHKERRQ(ierr);
/* -----------------------------------------------------------------------*/
/*
Cancels all monitors hardwired into code before call to KSPSetFromOptions()
*/
if (flg) {
ierr = KSPMonitorCancel(ksp);CHKERRQ(ierr);
}
/*
Prints preconditioned residual norm at each iteration
*/
ierr = PetscOptionsString("-ksp_monitor","Monitor preconditioned residual norm","KSPMonitorSet","stdout",monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr);
if (flg) {
ierr = PetscViewerASCIIOpen(PetscObjectComm((PetscObject)ksp),monfilename,&monviewer);CHKERRQ(ierr);
ierr = KSPMonitorSet(ksp,KSPMonitorDefault,monviewer,(PetscErrorCode (*)(void**))PetscViewerDestroy);CHKERRQ(ierr);
}
/*
Prints preconditioned residual norm at each iteration
*/
ierr = PetscOptionsString("-ksp_monitor_range","Monitor percent of residual entries more than 10 percent of max","KSPMonitorRange","stdout",monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr);
if (flg) {
ierr = PetscViewerASCIIOpen(PetscObjectComm((PetscObject)ksp),monfilename,&monviewer);CHKERRQ(ierr);
ierr = KSPMonitorSet(ksp,KSPMonitorRange,monviewer,(PetscErrorCode (*)(void**))PetscViewerDestroy);CHKERRQ(ierr);
}
ierr = PetscObjectTypeCompare((PetscObject)ksp->pc,PCKSP,&flg);CHKERRQ(ierr);
ierr = PetscObjectTypeCompare((PetscObject)ksp->pc,PCBJACOBI,&flag);CHKERRQ(ierr);
if (flg || flag) {
/* A hack for using dynamic tolerance in preconditioner */
ierr = PetscOptionsString("-sub_ksp_dynamic_tolerance","Use dynamic tolerance for PC if PC is a KSP","KSPMonitorDynamicTolerance","stdout",monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr);
if (flg) {
KSPDynTolCtx *scale = NULL;
PetscReal defaultv = 1.0;
ierr = PetscMalloc1(1,&scale);CHKERRQ(ierr);
scale->bnrm = -1.0;
scale->coef = defaultv;
ierr = PetscOptionsReal("-sub_ksp_dynamic_tolerance_param","Parameter of dynamic tolerance for inner PCKSP","KSPMonitorDynamicToleranceParam",defaultv,&(scale->coef),&flg);CHKERRQ(ierr);
ierr = KSPMonitorSet(ksp,KSPMonitorDynamicTolerance,scale,KSPMonitorDynamicToleranceDestroy);CHKERRQ(ierr);
}
}
/*
Plots the vector solution
*/
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_monitor_solution","Monitor solution graphically","KSPMonitorSet",flg,&flg,NULL);CHKERRQ(ierr);
if (flg) {
ierr = KSPMonitorSet(ksp,KSPMonitorSolution,NULL,NULL);CHKERRQ(ierr);
}
/*
Prints preconditioned and true residual norm at each iteration
*/
ierr = PetscOptionsString("-ksp_monitor_true_residual","Monitor true residual norm","KSPMonitorSet","stdout",monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr);
if (flg) {
ierr = PetscViewerASCIIOpen(PetscObjectComm((PetscObject)ksp),monfilename,&monviewer);CHKERRQ(ierr);
ierr = KSPMonitorSet(ksp,KSPMonitorTrueResidualNorm,monviewer,(PetscErrorCode (*)(void**))PetscViewerDestroy);CHKERRQ(ierr);
}
/*
Prints with max norm at each iteration
*/
ierr = PetscOptionsString("-ksp_monitor_max","Monitor true residual max norm","KSPMonitorSet","stdout",monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr);
if (flg) {
ierr = PetscViewerASCIIOpen(PetscObjectComm((PetscObject)ksp),monfilename,&monviewer);CHKERRQ(ierr);
ierr = KSPMonitorSet(ksp,KSPMonitorTrueResidualMaxNorm,monviewer,(PetscErrorCode (*)(void**))PetscViewerDestroy);CHKERRQ(ierr);
}
/*
Prints extreme eigenvalue estimates at each iteration
*/
ierr = PetscOptionsString("-ksp_monitor_singular_value","Monitor singular values","KSPMonitorSet","stdout",monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr);
if (flg) {
ierr = KSPSetComputeSingularValues(ksp,PETSC_TRUE);CHKERRQ(ierr);
ierr = PetscViewerASCIIOpen(PetscObjectComm((PetscObject)ksp),monfilename,&monviewer);CHKERRQ(ierr);
ierr = KSPMonitorSet(ksp,KSPMonitorSingularValue,monviewer,(PetscErrorCode (*)(void**))PetscViewerDestroy);CHKERRQ(ierr);
}
/*
Prints preconditioned residual norm with fewer digits
*/
ierr = PetscOptionsString("-ksp_monitor_short","Monitor preconditioned residual norm with fewer digits","KSPMonitorSet","stdout",monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr);
if (flg) {
ierr = PetscViewerASCIIOpen(PetscObjectComm((PetscObject)ksp),monfilename,&monviewer);CHKERRQ(ierr);
ierr = KSPMonitorSet(ksp,KSPMonitorDefaultShort,monviewer,(PetscErrorCode (*)(void**))PetscViewerDestroy);CHKERRQ(ierr);
}
/*
Calls Python function
*/
ierr = PetscOptionsString("-ksp_monitor_python","Use Python function","KSPMonitorSet",0,monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr);
if (flg) {ierr = PetscPythonMonitorSet((PetscObject)ksp,monfilename);CHKERRQ(ierr);}
/*
Graphically plots preconditioned residual norm
*/
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_monitor_lg_residualnorm","Monitor graphically preconditioned residual norm","KSPMonitorSet",flg,&flg,NULL);CHKERRQ(ierr);
if (flg) {
PetscDrawLG ctx;
ierr = KSPMonitorLGResidualNormCreate(0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,&ctx);CHKERRQ(ierr);
ierr = KSPMonitorSet(ksp,KSPMonitorLGResidualNorm,ctx,(PetscErrorCode (*)(void**))KSPMonitorLGResidualNormDestroy);CHKERRQ(ierr);
}
/*
Graphically plots preconditioned and true residual norm
*/
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_monitor_lg_true_residualnorm","Monitor graphically true residual norm","KSPMonitorSet",flg,&flg,NULL);CHKERRQ(ierr);
if (flg) {
PetscDrawLG ctx;
ierr = KSPMonitorLGTrueResidualNormCreate(PetscObjectComm((PetscObject)ksp),0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,&ctx);CHKERRQ(ierr);
ierr = KSPMonitorSet(ksp,KSPMonitorLGTrueResidualNorm,ctx,(PetscErrorCode (*)(void**))KSPMonitorLGTrueResidualNormDestroy);CHKERRQ(ierr);
}
/*
Graphically plots preconditioned residual norm and range of residual element values
*/
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_monitor_lg_range","Monitor graphically range of preconditioned residual norm","KSPMonitorSet",flg,&flg,NULL);CHKERRQ(ierr);
if (flg) {
PetscViewer ctx;
ierr = PetscViewerDrawOpen(PetscObjectComm((PetscObject)ksp),0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,&ctx);CHKERRQ(ierr);
ierr = KSPMonitorSet(ksp,KSPMonitorLGRange,ctx,(PetscErrorCode (*)(void**))PetscViewerDestroy);CHKERRQ(ierr);
}
#if defined(PETSC_HAVE_SAWS)
/*
Publish convergence information using AMS
*/
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_monitor_saws","Publish KSP progress using SAWs","KSPMonitorSet",flg,&flg,NULL);CHKERRQ(ierr);
if (flg) {
void *ctx;
ierr = KSPMonitorSAWsCreate(ksp,&ctx);CHKERRQ(ierr);
ierr = KSPMonitorSet(ksp,KSPMonitorSAWs,ctx,KSPMonitorSAWsDestroy);CHKERRQ(ierr);
ierr = KSPSetComputeSingularValues(ksp,PETSC_TRUE);CHKERRQ(ierr);
}
#endif
/* -----------------------------------------------------------------------*/
ierr = KSPSetUpNorms_Private(ksp,&normtype,&pcside);CHKERRQ(ierr);
ierr = PetscOptionsEnum("-ksp_pc_side","KSP preconditioner side","KSPSetPCSide",PCSides,(PetscEnum)pcside,(PetscEnum*)&pcside,&flg);CHKERRQ(ierr);
if (flg) {ierr = KSPSetPCSide(ksp,pcside);CHKERRQ(ierr);}
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_compute_singularvalues","Compute singular values of preconditioned operator","KSPSetComputeSingularValues",flg,&flg,NULL);CHKERRQ(ierr);
if (flg) { ierr = KSPSetComputeSingularValues(ksp,PETSC_TRUE);CHKERRQ(ierr); }
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_compute_eigenvalues","Compute eigenvalues of preconditioned operator","KSPSetComputeSingularValues",flg,&flg,NULL);CHKERRQ(ierr);
if (flg) { ierr = KSPSetComputeSingularValues(ksp,PETSC_TRUE);CHKERRQ(ierr); }
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_plot_eigenvalues","Scatter plot extreme eigenvalues","KSPSetComputeSingularValues",flg,&flg,NULL);CHKERRQ(ierr);
if (flg) { ierr = KSPSetComputeSingularValues(ksp,PETSC_TRUE);CHKERRQ(ierr); }
#if defined(PETSC_HAVE_SAWS)
{
PetscBool set;
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_saws_block","Block for SAWs at end of KSPSolve","PetscObjectSAWsBlock",((PetscObject)ksp)->amspublishblock,&flg,&set);CHKERRQ(ierr);
if (set) {
ierr = PetscObjectSAWsSetBlock((PetscObject)ksp,flg);CHKERRQ(ierr);
}
}
#endif
if (ksp->ops->setfromoptions) {
ierr = (*ksp->ops->setfromoptions)(ksp);CHKERRQ(ierr);
}
/* process any options handlers added with PetscObjectAddOptionsHandler() */
ierr = PetscObjectProcessOptionsHandlers((PetscObject)ksp);CHKERRQ(ierr);
ierr = PetscOptionsEnd();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
