/*
SNESSetFromOptions_VINEWTONSSLS - Sets various parameters for the SNESVI method.
Input Parameter:
. snes - the SNES context
Application Interface Routine: SNESSetFromOptions()
*/
static PetscErrorCode SNESSetFromOptions_VINEWTONSSLS(PetscOptionItems *PetscOptionsObject,SNES snes)
{
PetscErrorCode ierr;
PetscFunctionBegin;
ierr = SNESSetFromOptions_VI(PetscOptionsObject,snes);CHKERRQ(ierr);
ierr = PetscOptionsHead(PetscOptionsObject,"SNES semismooth method options");CHKERRQ(ierr);
ierr = PetscOptionsTail();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
static PetscErrorCode TaoSetFromOptions_BLMVM(PetscOptionItems* PetscOptionsObject,Tao tao)
{
PetscErrorCode ierr;
PetscFunctionBegin;
ierr = PetscOptionsHead(PetscOptionsObject,"Limited-memory variable-metric method for bound constrained optimization");CHKERRQ(ierr);
ierr = TaoLineSearchSetFromOptions(tao->linesearch);CHKERRQ(ierr);
ierr = PetscOptionsTail();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
PetscErrorCode KSPSetFromOptions_PGMRES(KSP ksp)
{
PetscErrorCode ierr;
PetscFunctionBegin;
ierr = KSPSetFromOptions_GMRES(ksp);CHKERRQ(ierr);
ierr = PetscOptionsHead("KSP pipelined GMRES Options");CHKERRQ(ierr);
ierr = PetscOptionsTail();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
static PetscErrorCode TaoSetFromOptions_BMRM(PetscOptionItems *PetscOptionsObject,Tao tao)
{
PetscErrorCode ierr;
TAO_BMRM* bmrm = (TAO_BMRM*)tao->data;
PetscFunctionBegin;
ierr = PetscOptionsHead(PetscOptionsObject,"BMRM for regularized risk minimization");CHKERRQ(ierr);
ierr = PetscOptionsReal("-tao_bmrm_lambda", "regulariser weight","", 100,&bmrm->lambda,NULL);CHKERRQ(ierr);
ierr = PetscOptionsTail();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
static PetscErrorCode KSPSetFromOptions_Chebyshev(PetscOptions *PetscOptionsObject,KSP ksp)
{
KSP_Chebyshev *cheb = (KSP_Chebyshev*)ksp->data;
PetscErrorCode ierr;
PetscInt neigarg = 2, nestarg = 4;
PetscReal eminmax[2] = {0., 0.};
PetscReal tform[4] = {PETSC_DECIDE,PETSC_DECIDE,PETSC_DECIDE,PETSC_DECIDE};
PetscBool flgeig, flgest;
PetscFunctionBegin;
ierr = PetscOptionsHead(PetscOptionsObject,"KSP Chebyshev Options");CHKERRQ(ierr);
ierr = PetscOptionsInt("-ksp_chebyshev_esteig_steps","Number of est steps in Chebyshev","",cheb->eststeps,&cheb->eststeps,NULL);CHKERRQ(ierr);
ierr = PetscOptionsRealArray("-ksp_chebyshev_eigenvalues","extreme eigenvalues","KSPChebyshevSetEigenvalues",eminmax,&neigarg,&flgeig);CHKERRQ(ierr);
if (flgeig) {
if (neigarg != 2) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_INCOMP,"-ksp_chebyshev_eigenvalues: must specify 2 parameters, min and max eigenvalues");
ierr = KSPChebyshevSetEigenvalues(ksp, eminmax[1], eminmax[0]);CHKERRQ(ierr);
}
ierr = PetscOptionsRealArray("-ksp_chebyshev_esteig","estimate eigenvalues using a Krylov method, then use this transform for Chebyshev eigenvalue bounds","KSPChebyshevEstEigSet",tform,&nestarg,&flgest);CHKERRQ(ierr);
if (flgest) {
switch (nestarg) {
case 0:
ierr = KSPChebyshevEstEigSet(ksp,PETSC_DECIDE,PETSC_DECIDE,PETSC_DECIDE,PETSC_DECIDE);CHKERRQ(ierr);
break;
case 2: /* Base everything on the max eigenvalues */
ierr = KSPChebyshevEstEigSet(ksp,PETSC_DECIDE,tform[0],PETSC_DECIDE,tform[1]);CHKERRQ(ierr);
break;
case 4: /* Use the full 2x2 linear transformation */
ierr = KSPChebyshevEstEigSet(ksp,tform[0],tform[1],tform[2],tform[3]);CHKERRQ(ierr);
break;
default: SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_INCOMP,"Must specify either 0, 2, or 4 parameters for eigenvalue estimation");
}
}
/* We need to estimate eigenvalues; need to set this here so that KSPSetFromOptions() is called on the estimator */
if ((cheb->emin == 0. || cheb->emax == 0.) && !cheb->kspest) {
ierr = KSPChebyshevEstEigSet(ksp,PETSC_DECIDE,PETSC_DECIDE,PETSC_DECIDE,PETSC_DECIDE);CHKERRQ(ierr);
}
if (cheb->kspest) {
ierr = PetscOptionsBool("-ksp_chebyshev_esteig_random","Use random right hand side for estimate","KSPChebyshevEstEigSetUseRandom",cheb->userandom,&cheb->userandom,NULL);CHKERRQ(ierr);
if (cheb->userandom) {
const char *ksppre;
if (!cheb->random) {
ierr = PetscRandomCreate(PetscObjectComm((PetscObject)ksp),&cheb->random);CHKERRQ(ierr);
}
ierr = KSPGetOptionsPrefix(cheb->kspest, &ksppre);CHKERRQ(ierr);
ierr = PetscObjectSetOptionsPrefix((PetscObject)cheb->random,ksppre);CHKERRQ(ierr);
ierr = PetscRandomSetFromOptions(cheb->random);CHKERRQ(ierr);
}
ierr = KSPSetFromOptions(cheb->kspest);CHKERRQ(ierr);
}
ierr = PetscOptionsTail();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
PetscErrorCode KSPSetFromOptions_LSQR(KSP ksp)
{
PetscErrorCode ierr;
KSP_LSQR *lsqr = (KSP_LSQR*)ksp->data;
PetscFunctionBegin;
ierr = PetscOptionsHead("KSP LSQR Options");CHKERRQ(ierr);
ierr = PetscOptionsName("-ksp_LSQR_set_standard_error","Set Standard Error Estimates of Solution","KSPLSQRSetStandardErrorVec",&lsqr->se_flg);CHKERRQ(ierr);
ierr = PetscOptionsTail();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
static PetscErrorCode TSSetFromOptions_RK(TS ts)
{
TS_RK *rk = (TS_RK*)ts->data;
PetscErrorCode ierr;
PetscFunctionBegin;
ierr = PetscOptionsHead("RK ODE solver options");CHKERRQ(ierr);
ierr = PetscOptionsReal("-ts_rk_tol","Tolerance for convergence","TSRKSetTolerance",rk->tolerance,&rk->tolerance,PETSC_NULL);CHKERRQ(ierr);
ierr = PetscOptionsTail();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
/*
MatMFFDSetFromOptions_WP - Looks in the options database for
any options appropriate for this method
Input Parameter:
. ctx - the matrix free context
*/
static PetscErrorCode MatMFFDSetFromOptions_WP(MatMFFD ctx)
{
PetscErrorCode ierr;
MatMFFD_WP *hctx = (MatMFFD_WP*)ctx->hctx;
PetscFunctionBegin;
ierr = PetscOptionsHead("Walker-Pernice options");CHKERRQ(ierr);
ierr = PetscOptionsBool("-mat_mffd_compute_normu","Compute the norm of u","MatMFFDWPSetComputeNormU", hctx->computenormU,&hctx->computenormU,0);CHKERRQ(ierr);
ierr = PetscOptionsTail();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
static PetscErrorCode SNESSetFromOptions_Test(SNES snes)
{
SNES_Test *ls = (SNES_Test*)snes->data;
PetscErrorCode ierr;
PetscFunctionBegin;
ierr = PetscOptionsHead("Hand-coded Jacobian tester options");CHKERRQ(ierr);
ierr = PetscOptionsBool("-snes_test_display","Display difference between hand-coded and finite difference Jacobians","None",ls->complete_print,&ls->complete_print,NULL);CHKERRQ(ierr);
ierr = PetscOptionsTail();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
static PetscErrorCode PCSetFromOptions_Redundant(PetscOptionItems *PetscOptionsObject,PC pc)
{
PetscErrorCode ierr;
PC_Redundant *red = (PC_Redundant*)pc->data;
PetscFunctionBegin;
ierr = PetscOptionsHead(PetscOptionsObject,"Redundant options");CHKERRQ(ierr);
ierr = PetscOptionsInt("-pc_redundant_number","Number of redundant pc","PCRedundantSetNumber",red->nsubcomm,&red->nsubcomm,0);CHKERRQ(ierr);
ierr = PetscOptionsTail();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
PetscErrorCode PFSetFromOptions_Constant(PF pf)
{
PetscErrorCode ierr;
PetscScalar *value = (PetscScalar*)pf->data;
PetscFunctionBegin;
ierr = PetscOptionsHead("Constant function options");CHKERRQ(ierr);
ierr = PetscOptionsScalar("-pf_constant","The constant value","None",*value,value,0);CHKERRQ(ierr);
ierr = PetscOptionsTail();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
/*
MatMFFDSetFromOptions_DS - Looks in the options database for
any options appropriate for this method.
Input Parameter:
. ctx - the matrix free context
*/
static PetscErrorCode MatMFFDSetFromOptions_DS(PetscOptionItems *PetscOptionsObject,MatMFFD ctx)
{
PetscErrorCode ierr;
MatMFFD_DS *hctx = (MatMFFD_DS*)ctx->hctx;
PetscFunctionBegin;
ierr = PetscOptionsHead(PetscOptionsObject,"Finite difference matrix free parameters");CHKERRQ(ierr);
ierr = PetscOptionsReal("-mat_mffd_umin","umin","MatMFFDDSSetUmin",hctx->umin,&hctx->umin,0);CHKERRQ(ierr);
ierr = PetscOptionsTail();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
static PetscErrorCode PetscSFSetFromOptions_Window(PetscOptionItems *PetscOptionsObject,PetscSF sf)
{
PetscSF_Window *w = (PetscSF_Window*)sf->data;
PetscErrorCode ierr;
PetscFunctionBegin;
ierr = PetscOptionsHead(PetscOptionsObject,"PetscSF Window options");CHKERRQ(ierr);
ierr = PetscOptionsEnum("-sf_window_sync","synchronization type to use for PetscSF Window communication","PetscSFWindowSetSyncType",PetscSFWindowSyncTypes,(PetscEnum)w->sync,(PetscEnum*)&w->sync,NULL);CHKERRQ(ierr);
ierr = PetscOptionsTail();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
PetscErrorCode MatColoringSetFromOptions_JP(PetscOptionItems *PetscOptionsObject,MatColoring mc)
{
PetscErrorCode ierr;
MC_JP *jp = (MC_JP*)mc->data;
PetscFunctionBegin;
ierr = PetscOptionsHead(PetscOptionsObject,"JP options");CHKERRQ(ierr);
ierr = PetscOptionsBool("-mat_coloring_jp_local","Do an initial coloring of local columns","",jp->local,&jp->local,NULL);CHKERRQ(ierr);
ierr = PetscOptionsTail();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
static PetscErrorCode MatColoringSetFromOptions_Greedy(PetscOptionItems *PetscOptionsObject, MatColoring mc)
{
MC_Greedy *gr = (MC_Greedy *) mc->data;
PetscErrorCode ierr;
PetscFunctionBegin;
ierr = PetscOptionsHead(PetscOptionsObject, "Greedy options");CHKERRQ(ierr);
ierr = PetscOptionsBool("-mat_coloring_greedy_symmetric", "Flag for assuming a symmetric matrix", "", gr->symmetric, &gr->symmetric, NULL);CHKERRQ(ierr);
ierr = PetscOptionsTail();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
PetscErrorCode PCSetFromOptions_Kaczmarz(PetscOptionItems *PetscOptionsObject,PC pc)
{
PC_Kaczmarz *jac = (PC_Kaczmarz*)pc->data;
PetscErrorCode ierr;
PetscFunctionBegin;
ierr = PetscOptionsHead(PetscOptionsObject,"Kaczmarz options");CHKERRQ(ierr);
ierr = PetscOptionsReal("-pc_kaczmarz_lambda","relaxation factor (0 < lambda)","",jac->lambda,&jac->lambda,NULL);CHKERRQ(ierr);
ierr = PetscOptionsBool("-pc_kaczmarz_symmetric","apply row projections symmetrically","",jac->symmetric,&jac->symmetric,NULL);CHKERRQ(ierr);
ierr = PetscOptionsTail();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
static PetscErrorCode TaoSetFromOptions_BQPIP(Tao tao)
{
TAO_BQPIP *qp = (TAO_BQPIP*)tao->data;
PetscErrorCode ierr;
PetscFunctionBegin;
ierr = PetscOptionsHead("Interior point method for bound constrained quadratic optimization");CHKERRQ(ierr);
ierr = PetscOptionsInt("-tao_bqpip_predcorr","Use a predictor-corrector method","",qp->predcorr,&qp->predcorr,0);CHKERRQ(ierr);
ierr = PetscOptionsTail();CHKERRQ(ierr);
ierr = KSPSetFromOptions(tao->ksp);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
PetscErrorCode KSPSetFromOptions_Chebychev(KSP ksp)
{
KSP_Chebychev *cheb = (KSP_Chebychev*)ksp->data;
PetscErrorCode ierr;
PetscInt two = 2;
PetscFunctionBegin;
ierr = PetscOptionsHead("KSP Chebychev Options");CHKERRQ(ierr);
ierr = PetscOptionsRealArray("-ksp_chebychev_eigenvalues","extreme eigenvalues","KSPChebychevSetEigenvalues",&cheb->emin,&two,0);CHKERRQ(ierr);
ierr = PetscOptionsTail();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
PetscErrorCode KSPSetFromOptions_STCG(KSP ksp)
{
PetscErrorCode ierr;
KSP_STCG *cg = (KSP_STCG*)ksp->data;
PetscFunctionBegin;
ierr = PetscOptionsHead("KSP STCG options");CHKERRQ(ierr);
ierr = PetscOptionsReal("-ksp_stcg_radius", "Trust Region Radius", "KSPSTCGSetRadius", cg->radius, &cg->radius, NULL);CHKERRQ(ierr);
ierr = PetscOptionsEList("-ksp_stcg_dtype", "Norm used for direction", "", DType_Table, STCG_DIRECTION_TYPES, DType_Table[cg->dtype], &cg->dtype, NULL);CHKERRQ(ierr);
ierr = PetscOptionsTail();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
/*
TSAdaptSetFromOptions - Sets various TSAdapt parameters from user options.
Collective on TSAdapt
Input Parameter:
. adapt - the TSAdapt context
Options Database Keys:
+ -ts_adapt_type <type> - algorithm to use for adaptivity
. -ts_adapt_always_accept - always accept steps regardless of error/stability goals
. -ts_adapt_safety <safety> - safety factor relative to target error/stability goal
. -ts_adapt_reject_safety <safety> - extra safety factor to apply if the last step was rejected
. -ts_adapt_clip <low,high> - admissible time step decrease and increase factors
. -ts_adapt_dt_min <min> - minimum timestep to use
. -ts_adapt_dt_max <max> - maximum timestep to use
. -ts_adapt_scale_solve_failed <scale> - scale timestep by this factor if a solve fails
. -ts_adapt_wnormtype <2 or infinity> - type of norm for computing error estimates
- -ts_adapt_time_step_increase_delay - number of timesteps to delay increasing the time step after it has been decreased due to failed solver
Level: advanced
Notes:
This function is automatically called by TSSetFromOptions()
.keywords: TS, TSGetAdapt(), TSAdaptSetType(), TSAdaptSetStepLimits()
.seealso: TSGetAdapt(), TSAdaptSetType(), TSAdaptSetAlwaysAccept(), TSAdaptSetSafety(),
TSAdaptSetClip(), TSAdaptSetStepLimits(), TSAdaptSetMonitor()
*/
PetscErrorCode TSAdaptSetFromOptions(PetscOptionItems *PetscOptionsObject,TSAdapt adapt)
{
PetscErrorCode ierr;
char type[256] = TSADAPTBASIC;
PetscReal safety,reject_safety,clip[2],hmin,hmax;
PetscBool set,flg;
PetscInt two;
PetscFunctionBegin;
PetscValidHeaderSpecific(adapt,TSADAPT_CLASSID,1);
/* This should use PetscOptionsBegin() if/when this becomes an object used outside of TS, but currently this
* function can only be called from inside TSSetFromOptions() */
ierr = PetscOptionsHead(PetscOptionsObject,"TS Adaptivity options");CHKERRQ(ierr);
ierr = PetscOptionsFList("-ts_adapt_type","Algorithm to use for adaptivity","TSAdaptSetType",TSAdaptList,((PetscObject)adapt)->type_name ? ((PetscObject)adapt)->type_name : type,type,sizeof(type),&flg);CHKERRQ(ierr);
if (flg || !((PetscObject)adapt)->type_name) {
ierr = TSAdaptSetType(adapt,type);CHKERRQ(ierr);
}
ierr = PetscOptionsBool("-ts_adapt_always_accept","Always accept the step","TSAdaptSetAlwaysAccept",adapt->always_accept,&flg,&set);CHKERRQ(ierr);
if (set) {ierr = TSAdaptSetAlwaysAccept(adapt,flg);CHKERRQ(ierr);}
safety = adapt->safety; reject_safety = adapt->reject_safety;
ierr = PetscOptionsReal("-ts_adapt_safety","Safety factor relative to target error/stability goal","TSAdaptSetSafety",safety,&safety,&set);CHKERRQ(ierr);
ierr = PetscOptionsReal("-ts_adapt_reject_safety","Extra safety factor to apply if the last step was rejected","TSAdaptSetSafety",reject_safety,&reject_safety,&flg);CHKERRQ(ierr);
if (set || flg) {ierr = TSAdaptSetSafety(adapt,safety,reject_safety);CHKERRQ(ierr);}
two = 2; clip[0] = adapt->clip[0]; clip[1] = adapt->clip[1];
ierr = PetscOptionsRealArray("-ts_adapt_clip","Admissible decrease/increase factor in step size","TSAdaptSetClip",clip,&two,&set);CHKERRQ(ierr);
if (set && (two != 2)) SETERRQ(PetscObjectComm((PetscObject)adapt),PETSC_ERR_ARG_OUTOFRANGE,"Must give exactly two values to -ts_adapt_clip");
if (set) {ierr = TSAdaptSetClip(adapt,clip[0],clip[1]);CHKERRQ(ierr);}
hmin = adapt->dt_min; hmax = adapt->dt_max;
ierr = PetscOptionsReal("-ts_adapt_dt_min","Minimum time step considered","TSAdaptSetStepLimits",hmin,&hmin,&set);CHKERRQ(ierr);
ierr = PetscOptionsReal("-ts_adapt_dt_max","Maximum time step considered","TSAdaptSetStepLimits",hmax,&hmax,&flg);CHKERRQ(ierr);
if (set || flg) {ierr = TSAdaptSetStepLimits(adapt,hmin,hmax);CHKERRQ(ierr);}
ierr = PetscOptionsReal("-ts_adapt_max_ignore","Adaptor ignores (absolute) solution values smaller than this value","",adapt->ignore_max,&adapt->ignore_max,&set);CHKERRQ(ierr);
ierr = PetscOptionsBool("-ts_adapt_glee_use_local","GLEE adaptor uses local error estimation for step control","",adapt->glee_use_local,&adapt->glee_use_local,&set);CHKERRQ(ierr);
ierr = PetscOptionsReal("-ts_adapt_scale_solve_failed","Scale step by this factor if solve fails","",adapt->scale_solve_failed,&adapt->scale_solve_failed,NULL);CHKERRQ(ierr);
ierr = PetscOptionsEnum("-ts_adapt_wnormtype","Type of norm computed for error estimation","",NormTypes,(PetscEnum)adapt->wnormtype,(PetscEnum*)&adapt->wnormtype,NULL);CHKERRQ(ierr);
if (adapt->wnormtype != NORM_2 && adapt->wnormtype != NORM_INFINITY) SETERRQ(PetscObjectComm((PetscObject)adapt),PETSC_ERR_SUP,"Only 2-norm and infinite norm supported");
ierr = PetscOptionsInt("-ts_adapt_time_step_increase_delay","Number of timesteps to delay increasing the time step after it has been decreased due to failed solver","TSAdaptSetTimeStepIncreaseDelay",adapt->timestepjustdecreased_delay,&adapt->timestepjustdecreased_delay,NULL);CHKERRQ(ierr);
ierr = PetscOptionsBool("-ts_adapt_monitor","Print choices made by adaptive controller","TSAdaptSetMonitor",adapt->monitor ? PETSC_TRUE : PETSC_FALSE,&flg,&set);CHKERRQ(ierr);
if (set) {ierr = TSAdaptSetMonitor(adapt,flg);CHKERRQ(ierr);}
if (adapt->ops->setfromoptions) {ierr = (*adapt->ops->setfromoptions)(PetscOptionsObject,adapt);CHKERRQ(ierr);}
ierr = PetscOptionsTail();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
PetscErrorCode DMSetFromOptions_Patch(PetscOptionItems *PetscOptionsObject,DM dm)
{
/* DM_Patch *mesh = (DM_Patch*) dm->data; */
PetscErrorCode ierr;
PetscFunctionBegin;
PetscValidHeaderSpecific(dm, DM_CLASSID, 1);
ierr = PetscOptionsHead(PetscOptionsObject,"DMPatch Options");CHKERRQ(ierr);
/* Handle associated vectors */
/* Handle viewing */
ierr = PetscOptionsTail();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
PetscErrorCode MatSetFromOptions_SchurComplement(PetscOptions *PetscOptionsObject,Mat N)
{
Mat_SchurComplement *Na = (Mat_SchurComplement*)N->data;
PetscErrorCode ierr;
PetscFunctionBegin;
ierr = PetscOptionsHead(PetscOptionsObject,"MatSchurComplementOptions");CHKERRQ(ierr);
Na->ainvtype = MAT_SCHUR_COMPLEMENT_AINV_DIAG;
ierr = PetscOptionsEnum("-mat_schur_complement_ainv_type","Type of approximation for inv(A00) used when assembling Sp = A11 - A10 inv(A00) A01","MatSchurComplementSetAinvType",MatSchurComplementAinvTypes,(PetscEnum)Na->ainvtype,(PetscEnum*)&Na->ainvtype,NULL);CHKERRQ(ierr);
ierr = PetscOptionsTail();CHKERRQ(ierr);
ierr = KSPSetFromOptions(Na->ksp);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
static PetscErrorCode PCSetFromOptions_KSP(PetscOptionItems *PetscOptionsObject,PC pc)
{
PC_KSP *jac = (PC_KSP*)pc->data;
PetscErrorCode ierr;
PetscFunctionBegin;
ierr = PetscOptionsHead(PetscOptionsObject,"PC KSP options");CHKERRQ(ierr);
if (jac->ksp) {
ierr = KSPSetFromOptions(jac->ksp);CHKERRQ(ierr);
}
ierr = PetscOptionsTail();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
static PetscErrorCode TaoSetFromOptions_OWLQN(Tao tao)
{
TAO_OWLQN *lmP = (TAO_OWLQN *)tao->data;
PetscBool flg;
PetscErrorCode ierr;
PetscFunctionBegin;
ierr = PetscOptionsHead("Orthant-Wise Limited-memory method for Quasi-Newton unconstrained optimization");CHKERRQ(ierr);
ierr = PetscOptionsReal("-tao_owlqn_lambda", "regulariser weight","", 100,&lmP->lambda,&flg); CHKERRQ(ierr);
ierr = PetscOptionsTail();CHKERRQ(ierr);
ierr = TaoLineSearchSetFromOptions(tao->linesearch);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
static PetscErrorCode PCSetFromOptions_LSC(PetscOptions *PetscOptionsObject,PC pc)
{
PC_LSC *lsc = (PC_LSC*)pc->data;
PetscErrorCode ierr;
PetscFunctionBegin;
ierr = PetscOptionsHead(PetscOptionsObject,"LSC options");CHKERRQ(ierr);
{
ierr = PetscOptionsBool("-pc_lsc_scale_diag","Use diagonal of velocity block (A) for scaling","None",lsc->scalediag,&lsc->scalediag,NULL);CHKERRQ(ierr);
}
ierr = PetscOptionsTail();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
static PetscErrorCode PCSetFromOptions_SupportGraph(PC pc)
{
PC_SupportGraph *sg = (PC_SupportGraph*)pc->data;
PetscErrorCode ierr;
PetscFunctionBegin;
ierr = PetscOptionsHead("SupportGraph options");CHKERRQ(ierr);
ierr = PetscOptionsBool("-pc_sg_augment","Max congestion","",sg->augment,&sg->augment,0);CHKERRQ(ierr);
ierr = PetscOptionsReal("-pc_sg_cong","Max congestion","",sg->maxCong,&sg->maxCong,0);CHKERRQ(ierr);
ierr = PetscOptionsReal("-pc_sg_tol","Smallest usable value","",sg->tol,&sg->tol,0);CHKERRQ(ierr);
ierr = PetscOptionsTail();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
static PetscErrorCode TSAdaptSetFromOptions_CFL(PetscOptionItems *PetscOptionsObject,TSAdapt adapt)
{
TSAdapt_CFL *cfl = (TSAdapt_CFL*)adapt->data;
PetscErrorCode ierr;
PetscFunctionBegin;
ierr = PetscOptionsHead(PetscOptionsObject,"CFL adaptive controller options");CHKERRQ(ierr);
ierr = PetscOptionsReal("-ts_adapt_cfl_safety","Safety factor relative to target error","",cfl->safety,&cfl->safety,NULL);CHKERRQ(ierr);
ierr = PetscOptionsBool("-ts_adapt_cfl_always_accept","Always accept the step regardless of whether local truncation error meets goal","",cfl->always_accept,&cfl->always_accept,NULL);CHKERRQ(ierr);
if (!cfl->always_accept) SETERRQ(PetscObjectComm((PetscObject)adapt),PETSC_ERR_SUP,"step rejection not implemented yet");
ierr = PetscOptionsTail();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
static PetscErrorCode PCSetFromOptions_Cholesky(PetscOptionItems *PetscOptionsObject,PC pc)
{
PetscErrorCode ierr;
PetscFunctionBegin;
ierr = PetscOptionsHead(PetscOptionsObject,"Cholesky options");
CHKERRQ(ierr);
ierr = PCSetFromOptions_Factor(PetscOptionsObject,pc);
CHKERRQ(ierr);
ierr = PetscOptionsTail();
CHKERRQ(ierr);
PetscFunctionReturn(0);
}
static PetscErrorCode TaoSetFromOptions_GPCG(Tao tao)
{
TAO_GPCG *gpcg = (TAO_GPCG *)tao->data;
PetscErrorCode ierr;
PetscBool flg;
PetscFunctionBegin;
ierr = PetscOptionsHead("Gradient Projection, Conjugate Gradient method for bound constrained optimization");CHKERRQ(ierr);
ierr=PetscOptionsInt("-gpcg_maxpgits","maximum number of gradient projections per GPCG iterate",0,gpcg->maxgpits,&gpcg->maxgpits,&flg);CHKERRQ(ierr);
ierr = PetscOptionsTail();CHKERRQ(ierr);
ierr = TaoLineSearchSetFromOptions(tao->linesearch);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
PetscErrorCode KSPSetFromOptions_GCR(KSP ksp)
{
PetscErrorCode ierr;
KSP_GCR *ctx = (KSP_GCR *)ksp->data;
PetscInt restart;
PetscBool flg;
PetscFunctionBegin;
ierr = PetscOptionsHead("KSP GCR options");CHKERRQ(ierr);
ierr = PetscOptionsInt("-ksp_gcr_restart","Number of Krylov search directions","KSPGCRSetRestart",ctx->restart,&restart,&flg);CHKERRQ(ierr);
if (flg) { ierr = KSPGCRSetRestart(ksp,restart);CHKERRQ(ierr); }
ierr = PetscOptionsTail();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
