void
petscSetDefaults(FEProblem & problem)
{
// dig out Petsc solver
NonlinearSystem & nl = problem.getNonlinearSystem();
PetscNonlinearSolver<Number> * petsc_solver = dynamic_cast<PetscNonlinearSolver<Number> *>(nl.sys().nonlinear_solver.get());
SNES snes = petsc_solver->snes();
KSP ksp;
SNESGetKSP(snes, &ksp);
PCSide pcside = getPetscPCSide(nl.getPCSide());
#if PETSC_VERSION_LESS_THAN(3,2,0)
// PETSc 3.1.x-
KSPSetPreconditionerSide(ksp, pcside);
#else
// PETSc 3.2.x+
KSPSetPCSide(ksp, pcside);
#endif
SNESSetMaxLinearSolveFailures(snes, 1000000);
#if PETSC_VERSION_LESS_THAN(3,0,0)
// PETSc 2.3.3-
KSPSetConvergenceTest(ksp, petscConverged, &problem);
SNESSetConvergenceTest(snes, petscNonlinearConverged, &problem);
#else
// PETSc 3.0.0+
// In 3.0.0, the context pointer must actually be used, and the
// final argument to KSPSetConvergenceTest() is a pointer to a
// routine for destroying said private data context. In this case,
// we use the default context provided by PETSc in addition to
// a few other tests.
{
PetscErrorCode ierr = KSPSetConvergenceTest(ksp,
petscConverged,
&problem,
PETSC_NULL);
CHKERRABORT(nl.comm().get(),ierr);
ierr = SNESSetConvergenceTest(snes,
petscNonlinearConverged,
&problem,
PETSC_NULL);
CHKERRABORT(nl.comm().get(),ierr);
}
#endif
}
/*@
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);
}
/*@
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_guess_type - Type of initial guess generator for repeated linear solves
. -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 MatSetNullSpace() 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 [ascii binary or draw][:filename][:format option] - plot solution at each iteration
- -ksp_monitor_singular_value - monitor extreme 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: KSPSetOptionsPrefix(), KSPResetFromOptions(), KSPSetUseFischerGuess()
@*/
PetscErrorCode KSPSetFromOptions(KSP ksp)
{
PetscInt indx;
const char *convtests[] = {"default","skip","lsqr"};
char type[256], guesstype[256], monfilename[PETSC_MAX_PATH_LEN];
PetscBool flg,flag,reuse,set;
PetscInt model[2]={0,0},nmax;
KSPNormType normtype;
PCSide pcside;
void *ctx;
MPI_Comm comm;
const char *prefix;
PetscErrorCode ierr;
PetscFunctionBegin;
PetscValidHeaderSpecific(ksp,KSP_CLASSID,1);
ierr = PetscObjectGetComm((PetscObject) ksp, &comm);CHKERRQ(ierr);
ierr = PetscObjectGetOptionsPrefix((PetscObject) ksp, &prefix);CHKERRQ(ierr);
if (!ksp->skippcsetfromoptions) {
if (!ksp->pc) {ierr = KSPGetPC(ksp,&ksp->pc);CHKERRQ(ierr);}
ierr = PCSetFromOptions(ksp->pc);CHKERRQ(ierr);
}
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 = KSPResetViewers(ksp);CHKERRQ(ierr);
ierr = PetscObjectTypeCompare((PetscObject)ksp,KSPPREONLY,&flg);CHKERRQ(ierr);
if (flg) {
ierr = PCGetReusePreconditioner(ksp->pc,&reuse);CHKERRQ(ierr);
ierr = PetscOptionsBool("-ksp_error_if_not_converged","Generate error if solver does not converge","KSPSetErrorIfNotConverged",ksp->errorifnotconverged,&ksp->errorifnotconverged,NULL);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 = PetscOptionsGetViewer(comm,((PetscObject) ksp)->options,prefix,"-ksp_view", &ksp->viewer, &ksp->format, &ksp->view);CHKERRQ(ierr);
ierr = PetscOptionsGetViewer(comm,((PetscObject) ksp)->options,prefix,"-ksp_converged_reason", &ksp->viewerReason, &ksp->formatReason, &ksp->viewReason);CHKERRQ(ierr);
ierr = PetscOptionsGetViewer(comm,((PetscObject) ksp)->options,prefix,"-ksp_view_mat", &ksp->viewerMat, &ksp->formatMat, &ksp->viewMat);CHKERRQ(ierr);
ierr = PetscOptionsGetViewer(comm,((PetscObject) ksp)->options,prefix,"-ksp_view_pmat", &ksp->viewerPMat, &ksp->formatPMat, &ksp->viewPMat);CHKERRQ(ierr);
ierr = PetscOptionsGetViewer(comm,((PetscObject) ksp)->options,prefix,"-ksp_view_rhs", &ksp->viewerRhs, &ksp->formatRhs, &ksp->viewRhs);CHKERRQ(ierr);
ierr = PetscOptionsGetViewer(comm,((PetscObject) ksp)->options,prefix,"-ksp_view_solution", &ksp->viewerSol, &ksp->formatSol, &ksp->viewSol);CHKERRQ(ierr);
ierr = PetscOptionsGetViewer(comm,((PetscObject) ksp)->options,prefix,"-ksp_view_mat_explicit", &ksp->viewerMatExp, &ksp->formatMatExp, &ksp->viewMatExp);CHKERRQ(ierr);
ierr = PetscOptionsGetViewer(comm,((PetscObject) ksp)->options,prefix,"-ksp_view_final_residual", &ksp->viewerFinalRes,&ksp->formatFinalRes,&ksp->viewFinalRes);CHKERRQ(ierr);
ierr = PetscOptionsGetViewer(comm,((PetscObject) ksp)->options,prefix,"-ksp_view_preconditioned_operator_explicit",&ksp->viewerPOpExp, &ksp->formatPOpExp, &ksp->viewPOpExp);CHKERRQ(ierr);
ierr = PetscOptionsGetViewer(comm,((PetscObject) ksp)->options,prefix,"-ksp_view_diagonal_scale", &ksp->viewerDScale, &ksp->formatDScale, &ksp->viewDScale);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);
}
goto skipoptions;
}
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);
ierr = PetscOptionsBool("-ksp_converged_use_initial_residual_norm","Use initial residual norm for computing relative convergence","KSPConvergedDefaultSetUIRNorm",PETSC_FALSE,&flag,&set);CHKERRQ(ierr);
if (set && flag) {ierr = KSPConvergedDefaultSetUIRNorm(ksp);CHKERRQ(ierr);}
ierr = PetscOptionsBool("-ksp_converged_use_min_initial_residual_norm","Use minimum of initial residual norm and b for computing relative convergence","KSPConvergedDefaultSetUMIRNorm",PETSC_FALSE,&flag,&set);CHKERRQ(ierr);
if (set && flag) {ierr = KSPConvergedDefaultSetUMIRNorm(ksp);CHKERRQ(ierr);}
ierr = PetscOptionsBool("-ksp_initial_guess_nonzero","Use the contents of the solution vector for initial guess","KSPSetInitialNonzero",ksp->guess_zero ? PETSC_FALSE : PETSC_TRUE,&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);
ierr = PetscOptionsFList("-ksp_guess_type","Initial guess in Krylov method",NULL,KSPGuessList,NULL,guesstype,256,&flg);CHKERRQ(ierr);
if (flg) {
ierr = KSPGetGuess(ksp,&ksp->guess);CHKERRQ(ierr);
ierr = KSPGuessSetType(ksp->guess,guesstype);CHKERRQ(ierr);
ierr = KSPGuessSetFromOptions(ksp->guess);CHKERRQ(ierr);
} else { /* old option for KSP */
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(comm,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,3,"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;
case 2:
ierr = KSPConvergedDefaultCreate(&ctx);CHKERRQ(ierr);
ierr = KSPSetConvergenceTest(ksp,KSPLSQRConvergedDefault,ctx,KSPConvergedDefaultDestroy);CHKERRQ(ierr);
break;
}
}
ierr = KSPSetUpNorms_Private(ksp,PETSC_FALSE,&normtype,NULL);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);
ierr = PetscOptionsBool("-ksp_lag_norm","Lag the calculation of the residual norm","KSPSetLagNorm",ksp->lagnorm,&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);
}
ierr = PetscOptionsBool("-ksp_constant_null_space","Add constant null space to Krylov solver matrix","MatSetNullSpace",PETSC_FALSE,&flg,&set);CHKERRQ(ierr);
if (set && flg) {
MatNullSpace nsp;
Mat Amat;
ierr = MatNullSpaceCreate(comm,PETSC_TRUE,0,NULL,&nsp);CHKERRQ(ierr);
ierr = PCGetOperators(ksp->pc,&Amat,NULL);CHKERRQ(ierr);
if (Amat) {
ierr = MatSetNullSpace(Amat,nsp);CHKERRQ(ierr);
ierr = MatNullSpaceDestroy(&nsp);CHKERRQ(ierr);
} else SETERRQ(comm,PETSC_ERR_ARG_WRONGSTATE,"Cannot set nullspace, matrix has not yet been provided");
}
ierr = PetscOptionsBool("-ksp_monitor_cancel","Remove any hardwired monitor routines","KSPMonitorCancel",PETSC_FALSE,&flg,&set);CHKERRQ(ierr);
/* -----------------------------------------------------------------------*/
/*
Cancels all monitors hardwired into code before call to KSPSetFromOptions()
*/
if (set && flg) {
ierr = KSPMonitorCancel(ksp);CHKERRQ(ierr);
}
ierr = KSPMonitorSetFromOptions(ksp,"-ksp_monitor","Monitor the (preconditioned) residual norm","KSPMonitorDefault",KSPMonitorDefault);CHKERRQ(ierr);
ierr = KSPMonitorSetFromOptions(ksp,"-ksp_monitor_range","Monitor the percentage of large entries in the residual","KSPMonitorRange",KSPMonitorRange);CHKERRQ(ierr);
ierr = KSPMonitorSetFromOptions(ksp,"-ksp_monitor_true_residual","Monitor the unprecondiitoned residual norm","KSPMOnitorTrueResidual",KSPMonitorTrueResidualNorm);CHKERRQ(ierr);
ierr = KSPMonitorSetFromOptions(ksp,"-ksp_monitor_max","Monitor the maximum norm of the residual","KSPMonitorTrueResidualMaxNorm",KSPMonitorTrueResidualMaxNorm);CHKERRQ(ierr);
ierr = KSPMonitorSetFromOptions(ksp,"-ksp_monitor_short","Monitor preconditioned residual norm with fewer digits","KSPMonitorDefaultShort",KSPMonitorDefaultShort);CHKERRQ(ierr);
ierr = KSPMonitorSetFromOptions(ksp,"-ksp_monitor_solution","Monitor the solution","KSPMonitorSolution",KSPMonitorSolution);CHKERRQ(ierr);
ierr = KSPMonitorSetFromOptions(ksp,"-ksp_monitor_singular_value","Monitor singular values","KSPMonitorSingularValue",KSPMonitorSingularValue);CHKERRQ(ierr);
ierr = PetscOptionsHasName(NULL,((PetscObject)ksp)->prefix,"-ksp_monitor_singular_value",&flg);CHKERRQ(ierr);
if (flg) {
ierr = KSPSetComputeSingularValues(ksp,PETSC_TRUE);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;
ierr = PetscMalloc1(1,&scale);CHKERRQ(ierr);
scale->bnrm = -1.0;
scale->coef = 1.0;
ierr = PetscOptionsReal("-sub_ksp_dynamic_tolerance_param","Parameter of dynamic tolerance for inner PCKSP","KSPMonitorDynamicToleranceParam",scale->coef,&scale->coef,&flg);CHKERRQ(ierr);
ierr = KSPMonitorSet(ksp,KSPMonitorDynamicTolerance,scale,KSPMonitorDynamicToleranceDestroy);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
*/
ierr = PetscOptionsBool("-ksp_monitor_lg_residualnorm","Monitor graphically preconditioned residual norm","KSPMonitorSet",PETSC_FALSE,&flg,&set);CHKERRQ(ierr);
if (set && flg) {
PetscDrawLG ctx;
ierr = KSPMonitorLGResidualNormCreate(comm,NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,&ctx);CHKERRQ(ierr);
ierr = KSPMonitorSet(ksp,KSPMonitorLGResidualNorm,ctx,(PetscErrorCode (*)(void**))PetscDrawLGDestroy);CHKERRQ(ierr);
}
/*
Graphically plots preconditioned and true residual norm
*/
ierr = PetscOptionsBool("-ksp_monitor_lg_true_residualnorm","Monitor graphically true residual norm","KSPMonitorSet",PETSC_FALSE,&flg,&set);CHKERRQ(ierr);
if (set && flg) {
PetscDrawLG ctx;
ierr = KSPMonitorLGTrueResidualNormCreate(comm,NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,&ctx);CHKERRQ(ierr);
ierr = KSPMonitorSet(ksp,KSPMonitorLGTrueResidualNorm,ctx,(PetscErrorCode (*)(void**))PetscDrawLGDestroy);CHKERRQ(ierr);
}
/*
Graphically plots preconditioned residual norm and range of residual element values
*/
ierr = PetscOptionsBool("-ksp_monitor_lg_range","Monitor graphically range of preconditioned residual norm","KSPMonitorSet",PETSC_FALSE,&flg,&set);CHKERRQ(ierr);
if (set && flg) {
PetscViewer ctx;
ierr = PetscViewerDrawOpen(comm,NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,&ctx);CHKERRQ(ierr);
ierr = KSPMonitorSet(ksp,KSPMonitorLGRange,ctx,(PetscErrorCode (*)(void**))PetscViewerDestroy);CHKERRQ(ierr);
}
/* TODO Do these show up in help? */
ierr = PetscOptionsGetViewer(comm,((PetscObject) ksp)->options,prefix,"-ksp_view", &ksp->viewer, &ksp->format, &ksp->view);CHKERRQ(ierr);
ierr = PetscOptionsGetViewer(comm,((PetscObject) ksp)->options,prefix,"-ksp_view_pre", &ksp->viewerPre, &ksp->formatPre, &ksp->viewPre);CHKERRQ(ierr);
ierr = PetscOptionsGetViewer(comm,((PetscObject) ksp)->options,prefix,"-ksp_converged_reason", &ksp->viewerReason, &ksp->formatReason, &ksp->viewReason);CHKERRQ(ierr);
ierr = PetscOptionsGetViewer(comm,((PetscObject) ksp)->options,prefix,"-ksp_view_mat", &ksp->viewerMat, &ksp->formatMat, &ksp->viewMat);CHKERRQ(ierr);
ierr = PetscOptionsGetViewer(comm,((PetscObject) ksp)->options,prefix,"-ksp_view_pmat", &ksp->viewerPMat, &ksp->formatPMat, &ksp->viewPMat);CHKERRQ(ierr);
ierr = PetscOptionsGetViewer(comm,((PetscObject) ksp)->options,prefix,"-ksp_view_rhs", &ksp->viewerRhs, &ksp->formatRhs, &ksp->viewRhs);CHKERRQ(ierr);
ierr = PetscOptionsGetViewer(comm,((PetscObject) ksp)->options,prefix,"-ksp_view_solution", &ksp->viewerSol, &ksp->formatSol, &ksp->viewSol);CHKERRQ(ierr);
ierr = PetscOptionsGetViewer(comm,((PetscObject) ksp)->options,prefix,"-ksp_view_mat_explicit", &ksp->viewerMatExp, &ksp->formatMatExp, &ksp->viewMatExp);CHKERRQ(ierr);
ierr = PetscOptionsGetViewer(comm,((PetscObject) ksp)->options,prefix,"-ksp_view_eigenvalues", &ksp->viewerEV, &ksp->formatEV, &ksp->viewEV);CHKERRQ(ierr);
ierr = PetscOptionsGetViewer(comm,((PetscObject) ksp)->options,prefix,"-ksp_view_singularvalues", &ksp->viewerSV, &ksp->formatSV, &ksp->viewSV);CHKERRQ(ierr);
ierr = PetscOptionsGetViewer(comm,((PetscObject) ksp)->options,prefix,"-ksp_view_eigenvalues_explicit", &ksp->viewerEVExp, &ksp->formatEVExp, &ksp->viewEVExp);CHKERRQ(ierr);
ierr = PetscOptionsGetViewer(comm,((PetscObject) ksp)->options,prefix,"-ksp_view_final_residual", &ksp->viewerFinalRes,&ksp->formatFinalRes,&ksp->viewFinalRes);CHKERRQ(ierr);
ierr = PetscOptionsGetViewer(comm,((PetscObject) ksp)->options,prefix,"-ksp_view_preconditioned_operator_explicit",&ksp->viewerPOpExp, &ksp->formatPOpExp, &ksp->viewPOpExp);CHKERRQ(ierr);
ierr = PetscOptionsGetViewer(comm,((PetscObject) ksp)->options,prefix,"-ksp_view_diagonal_scale", &ksp->viewerDScale, &ksp->formatDScale, &ksp->viewDScale);CHKERRQ(ierr);
/* Deprecated options */
if (!ksp->viewEV) {ierr = PetscOptionsGetViewer(comm, ((PetscObject) ksp)->options,prefix, "-ksp_compute_eigenvalues", &ksp->viewerEV, &ksp->formatEV, &ksp->viewEV);CHKERRQ(ierr);}
if (!ksp->viewEV) {
ierr = PetscOptionsName("-ksp_plot_eigenvalues", "[deprecated since PETSc 3.9; use -ksp_view_eigenvalues draw]", "KSPView", &ksp->viewEV);CHKERRQ(ierr);
if (ksp->viewEV) {
ksp->formatEV = PETSC_VIEWER_DEFAULT;
ksp->viewerEV = PETSC_VIEWER_DRAW_(comm);
ierr = PetscObjectReference((PetscObject) ksp->viewerEV);CHKERRQ(ierr);
}
}
if (!ksp->viewEV) {
ierr = PetscOptionsName("-ksp_plot_eigencontours", "[deprecated since PETSc 3.9; use -ksp_view_eigenvalues draw::draw_contour]", "KSPView", &ksp->viewEV);CHKERRQ(ierr);
if (ksp->viewEV) {
ksp->formatEV = PETSC_VIEWER_DRAW_CONTOUR;
ksp->viewerEV = PETSC_VIEWER_DRAW_(comm);
ierr = PetscObjectReference((PetscObject) ksp->viewerEV);CHKERRQ(ierr);
}
}
if (!ksp->viewEVExp) {ierr = PetscOptionsGetViewer(comm, ((PetscObject) ksp)->options,prefix, "-ksp_compute_eigenvalues_explicitly", &ksp->viewerEVExp, &ksp->formatEVExp, &ksp->viewEVExp);CHKERRQ(ierr);}
if (!ksp->viewEVExp) {
ierr = PetscOptionsName("-ksp_plot_eigenvalues_explicitly", "[deprecated since PETSc 3.9; use -ksp_view_eigenvalues_explicit draw]", "KSPView", &ksp->viewEVExp);CHKERRQ(ierr);
if (ksp->viewEVExp) {
ksp->formatEVExp = PETSC_VIEWER_DEFAULT;
ksp->viewerEVExp = PETSC_VIEWER_DRAW_(comm);
ierr = PetscObjectReference((PetscObject) ksp->viewerEVExp);CHKERRQ(ierr);
}
}
if (!ksp->viewSV) {ierr = PetscOptionsGetViewer(comm, ((PetscObject) ksp)->options,prefix, "-ksp_compute_singularvalues", &ksp->viewerSV, &ksp->formatSV, &ksp->viewSV);CHKERRQ(ierr);}
if (!ksp->viewFinalRes) {ierr = PetscOptionsGetViewer(comm, ((PetscObject) ksp)->options,prefix, "-ksp_final_residual", &ksp->viewerFinalRes, &ksp->formatFinalRes, &ksp->viewFinalRes);CHKERRQ(ierr);}
#if defined(PETSC_HAVE_SAWS)
/*
Publish convergence information using AMS
*/
ierr = PetscOptionsBool("-ksp_monitor_saws","Publish KSP progress using SAWs","KSPMonitorSet",PETSC_FALSE,&flg,&set);CHKERRQ(ierr);
if (set && 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,PETSC_FALSE,NULL,&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);}
ierr = PetscOptionsBool("-ksp_compute_singularvalues","Compute singular values of preconditioned operator","KSPSetComputeSingularValues",ksp->calc_sings,&flg,&set);CHKERRQ(ierr);
if (set) { ierr = KSPSetComputeSingularValues(ksp,flg);CHKERRQ(ierr); }
ierr = PetscOptionsBool("-ksp_compute_eigenvalues","Compute eigenvalues of preconditioned operator","KSPSetComputeSingularValues",ksp->calc_sings,&flg,&set);CHKERRQ(ierr);
if (set) { ierr = KSPSetComputeSingularValues(ksp,flg);CHKERRQ(ierr); }
ierr = PetscOptionsBool("-ksp_plot_eigenvalues","Scatter plot extreme eigenvalues","KSPSetComputeSingularValues",PETSC_FALSE,&flg,&set);CHKERRQ(ierr);
if (set) { ierr = KSPSetComputeSingularValues(ksp,flg);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)(PetscOptionsObject,ksp);CHKERRQ(ierr);
}
skipoptions:
/* process any options handlers added with PetscObjectAddOptionsHandler() */
ierr = PetscObjectProcessOptionsHandlers(PetscOptionsObject,(PetscObject)ksp);CHKERRQ(ierr);
ierr = PetscOptionsEnd();CHKERRQ(ierr);
ksp->setfromoptionscalled++;
PetscFunctionReturn(0);
}