/*@
DMRestoreLocalVector - Returns a Seq PETSc vector that
obtained from DMGetLocalVector(). Do not use with vector obtained via
DMCreateLocalVector().
Not Collective
Input Parameter:
+ dm - the distributed array
- g - the local vector
Level: beginner
.keywords: distributed array, create, local, vector
.seealso: DMCreateGlobalVector(), VecDuplicate(), VecDuplicateVecs(),
DMDACreate1d(), DMDACreate2d(), DMDACreate3d(), DMGlobalToLocalBegin(),
DMGlobalToLocalEnd(), DMLocalToGlobalBegin(), DMCreateLocalVector(), DMGetLocalVector()
@*/
PetscErrorCode DMRestoreLocalVector(DM dm,Vec* g)
{
PetscErrorCode ierr;
PetscInt i,j;
PetscFunctionBegin;
PetscValidHeaderSpecific(dm,DM_CLASSID,1);
PetscValidPointer(g,2);
for (j=0; j<DM_MAX_WORK_VECTORS; j++) {
if (*g == dm->localout[j]) {
dm->localout[j] = PETSC_NULL;
for (i=0; i<DM_MAX_WORK_VECTORS; i++) {
if (!dm->localin[i]) {
dm->localin[i] = *g;
goto alldone;
}
}
}
}
ierr = VecDestroy(g);CHKERRQ(ierr);
alldone:
PetscFunctionReturn(0);
}
/*@C
PetscDrawLGSetLegend - sets the names of each curve plotted
Logically Collective over PetscDrawLG
Input Parameter:
+ lg - the line graph context.
- names - the names for each curve
Level: intermediate
Concepts: line graph^setting number of lines
@*/
PetscErrorCode PetscDrawLGSetLegend(PetscDrawLG lg,const char *const *names)
{
PetscErrorCode ierr;
PetscInt i;
PetscFunctionBegin;
if (lg && ((PetscObject)lg)->classid == PETSC_DRAW_CLASSID) PetscFunctionReturn(0);
PetscValidHeaderSpecific(lg,PETSC_DRAWLG_CLASSID,1);
if (lg->legend) {
for (i=0; i<lg->dim; i++) {
ierr = PetscFree(lg->legend[i]);CHKERRQ(ierr);
}
ierr = PetscFree(lg->legend);CHKERRQ(ierr);
}
if (names) {
ierr = PetscMalloc(lg->dim*sizeof(char**),&lg->legend);CHKERRQ(ierr);
for (i=0; i<lg->dim; i++) {
ierr = PetscStrallocpy(names[i],&lg->legend[i]);CHKERRQ(ierr);
}
}
PetscFunctionReturn(0);
}
/*@C
PetscSFSetType - set the PetscSF communication implementation
Collective on PetscSF
Input Parameters:
+ sf - the PetscSF context
- type - a known method
Options Database Key:
. -sf_type <type> - Sets the method; use -help for a list
of available methods (for instance, window, pt2pt, neighbor)
Notes:
See "include/petscsf.h" for available methods (for instance)
+ PETSCSFWINDOW - MPI-2/3 one-sided
- PETSCSFBASIC - basic implementation using MPI-1 two-sided
Level: intermediate
.keywords: PetscSF, set, type
.seealso: PetscSFType, PetscSFCreate()
@*/
PetscErrorCode PetscSFSetType(PetscSF sf,PetscSFType type)
{
PetscErrorCode ierr,(*r)(PetscSF);
PetscBool match;
PetscFunctionBegin;
PetscValidHeaderSpecific(sf,PETSCSF_CLASSID,1);
PetscValidCharPointer(type,2);
ierr = PetscObjectTypeCompare((PetscObject)sf,type,&match);CHKERRQ(ierr);
if (match) PetscFunctionReturn(0);
ierr = PetscFunctionListFind(PetscSFList,type,&r);CHKERRQ(ierr);
if (!r) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_UNKNOWN_TYPE,"Unable to find requested PetscSF type %s",type);
/* Destroy the previous private PetscSF context */
if (sf->ops->Destroy) {
ierr = (*(sf)->ops->Destroy)(sf);CHKERRQ(ierr);
}
ierr = PetscMemzero(sf->ops,sizeof(*sf->ops));CHKERRQ(ierr);
ierr = PetscObjectChangeTypeName((PetscObject)sf,type);CHKERRQ(ierr);
ierr = (*r)(sf);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
/*@
MatFDColoringSetFromOptions - Sets coloring finite difference parameters from
the options database.
Collective on MatFDColoring
The Jacobian, F'(u), is estimated with the differencing approximation
.vb
F'(u)_{:,i} = [F(u+h*dx_{i}) - F(u)]/h where
h = error_rel*u[i] if abs(u[i]) > umin
= +/- error_rel*umin otherwise, with +/- determined by the sign of u[i]
dx_{i} = (0, ... 1, .... 0)
.ve
Input Parameter:
. coloring - the coloring context
Options Database Keys:
+ -mat_fd_coloring_err <err> - Sets <err> (square root
of relative error in the function)
. -mat_fd_coloring_umin <umin> - Sets umin, the minimum allowable u-value magnitude
. -mat_fd_type - "wp" or "ds" (see MATMFFD_WP or MATMFFD_DS)
. -mat_fd_coloring_view - Activates basic viewing
. -mat_fd_coloring_view ::ascii_info - Activates viewing info
- -mat_fd_coloring_view draw - Activates drawing
Level: intermediate
.keywords: Mat, finite differences, parameters
.seealso: MatFDColoringCreate(), MatFDColoringView(), MatFDColoringSetParameters()
@*/
PetscErrorCode MatFDColoringSetFromOptions(MatFDColoring matfd)
{
PetscErrorCode ierr;
PetscBool flg;
char value[3];
PetscFunctionBegin;
PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_CLASSID,1);
ierr = PetscObjectOptionsBegin((PetscObject)matfd);CHKERRQ(ierr);
ierr = PetscOptionsReal("-mat_fd_coloring_err","Square root of relative error in function","MatFDColoringSetParameters",matfd->error_rel,&matfd->error_rel,0);CHKERRQ(ierr);
ierr = PetscOptionsReal("-mat_fd_coloring_umin","Minimum allowable u magnitude","MatFDColoringSetParameters",matfd->umin,&matfd->umin,0);CHKERRQ(ierr);
ierr = PetscOptionsString("-mat_fd_type","Algorithm to compute h, wp or ds","MatFDColoringCreate",matfd->htype,value,3,&flg);CHKERRQ(ierr);
if (flg) {
if (value[0] == 'w' && value[1] == 'p') matfd->htype = "wp";
else if (value[0] == 'd' && value[1] == 's') matfd->htype = "ds";
else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Unknown finite differencing type %s",value);
}
/* process any options handlers added with PetscObjectAddOptionsHandler() */
ierr = PetscObjectProcessOptionsHandlers((PetscObject)matfd);CHKERRQ(ierr);
PetscOptionsEnd();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
PetscErrorCode DMCreateLocalVector_Shell(DM dm,Vec *gvec)
{
PetscErrorCode ierr;
DM_Shell *shell = (DM_Shell*)dm->data;
Vec X;
PetscFunctionBegin;
PetscValidHeaderSpecific(dm,DM_CLASSID,1);
PetscValidPointer(gvec,2);
*gvec = 0;
X = shell->Xlocal;
if (!X) SETERRQ(PetscObjectComm((PetscObject)dm),PETSC_ERR_USER,"Must call DMShellSetLocalVector() or DMShellSetCreateLocalVector()");
if (((PetscObject)X)->refct < 2) { /* We have an exclusive reference so we can give it out */
ierr = PetscObjectReference((PetscObject)X);CHKERRQ(ierr);
ierr = VecZeroEntries(X);CHKERRQ(ierr);
*gvec = X;
} else { /* Need to create a copy, could use MAT_SHARE_NONZERO_PATTERN in most cases */
ierr = VecDuplicate(X,gvec);CHKERRQ(ierr);
ierr = VecZeroEntries(*gvec);CHKERRQ(ierr);
}
ierr = VecSetDM(*gvec,dm);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
PetscErrorCode MatCoarsenView_MIS(MatCoarsen coarse,PetscViewer viewer)
{
/* MatCoarsen_MIS *MIS = (MatCoarsen_MIS*)coarse->; */
PetscErrorCode ierr;
int rank;
PetscBool iascii;
PetscFunctionBegin;
PetscValidHeaderSpecific(coarse,MAT_COARSEN_CLASSID,1);
ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)coarse),&rank);
CHKERRQ(ierr);
ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
CHKERRQ(ierr);
if (iascii) {
ierr = PetscViewerASCIISynchronizedPrintf(viewer," [%d] MIS aggregator\n",rank);
CHKERRQ(ierr);
ierr = PetscViewerFlush(viewer);
CHKERRQ(ierr);
ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);
CHKERRQ(ierr);
}
PetscFunctionReturn(0);
}
dErr dUnitsDestroy(dUnits *unp)
{
dUnits un = *unp;
dErr err;
dFunctionBegin;
if (!un) dFunctionReturn(0);
PetscValidHeaderSpecific(un,dUNITS_CLASSID,1);
if (--((PetscObject)un)->refct > 0) dFunctionReturn(0);
for (dInt i=0; i<un->nalloc; i++) {
dUnit u = un->list[i];
if (u) {
err = dFree(u->quantity);dCHK(err);
err = dFree(u->longname);dCHK(err);
err = dFree(u->shortname);dCHK(err);
err = dFree(u->siname);dCHK(err);
}
err = dFree(un->list[i]);dCHK(err);
}
err = dFree(un->list);dCHK(err);
err = PetscHeaderDestroy(unp);dCHK(err);
dFunctionReturn(0);
}
/*@
TaoLineSearchSetFromOptions - Sets various TaoLineSearch parameters from user
options.
Collective on TaoLineSearch
Input Paremeter:
. ls - the TaoLineSearch context
Options Database Keys:
+ -tao_ls_type <type> - The algorithm that TAO uses (more-thuente, gpcg, unit)
. -tao_ls_ftol <tol> - tolerance for sufficient decrease
. -tao_ls_gtol <tol> - tolerance for curvature condition
. -tao_ls_rtol <tol> - relative tolerance for acceptable step
. -tao_ls_stepmin <step> - minimum steplength allowed
. -tao_ls_stepmax <step> - maximum steplength allowed
. -tao_ls_max_funcs <n> - maximum number of function evaluations allowed
- -tao_ls_view - display line-search results to standard output
Level: beginner
@*/
PetscErrorCode TaoLineSearchSetFromOptions(TaoLineSearch ls)
{
PetscErrorCode ierr;
const char *default_type=TAOLINESEARCHMT;
char type[256];
PetscBool flg;
PetscFunctionBegin;
PetscValidHeaderSpecific(ls,TAOLINESEARCH_CLASSID,1);
ierr = PetscObjectOptionsBegin((PetscObject)ls);CHKERRQ(ierr);
if (!TaoLineSearchInitialized) {
ierr = TaoLineSearchInitializePackage();CHKERRQ(ierr);
}
if (((PetscObject)ls)->type_name) {
default_type = ((PetscObject)ls)->type_name;
}
/* Check for type from options */
ierr = PetscOptionsFList("-tao_ls_type","Tao Line Search type","TaoLineSearchSetType",TaoLineSearchList,default_type,type,256,&flg);CHKERRQ(ierr);
if (flg) {
ierr = TaoLineSearchSetType(ls,type);CHKERRQ(ierr);
} else if (!((PetscObject)ls)->type_name) {
ierr = TaoLineSearchSetType(ls,default_type);
}
ierr = PetscOptionsInt("-tao_ls_max_funcs","max function evals in line search","",ls->max_funcs,&ls->max_funcs,0);CHKERRQ(ierr);
ierr = PetscOptionsReal("-tao_ls_ftol","tol for sufficient decrease","",ls->ftol,&ls->ftol,0);CHKERRQ(ierr);
ierr = PetscOptionsReal("-tao_ls_gtol","tol for curvature condition","",ls->gtol,&ls->gtol,0);CHKERRQ(ierr);
ierr = PetscOptionsReal("-tao_ls_rtol","relative tol for acceptable step","",ls->rtol,&ls->rtol,0);CHKERRQ(ierr);
ierr = PetscOptionsReal("-tao_ls_stepmin","lower bound for step","",ls->stepmin,&ls->stepmin,0);CHKERRQ(ierr);
ierr = PetscOptionsReal("-tao_ls_stepmax","upper bound for step","",ls->stepmax,&ls->stepmax,0);CHKERRQ(ierr);
ierr = PetscOptionsBool("-tao_ls_view","view TaoLineSearch info after each line search has completed","TaoLineSearchView",PETSC_FALSE,&ls->viewls,NULL);CHKERRQ(ierr);
if (ls->ops->setfromoptions) {
ierr = (*ls->ops->setfromoptions)(ls);CHKERRQ(ierr);
}
ierr = PetscOptionsEnd();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
/*@
EPSReset - Resets the EPS context to the initial state and removes any
allocated objects.
Collective on EPS
Input Parameter:
. eps - eigensolver context obtained from EPSCreate()
Level: advanced
.seealso: EPSDestroy()
@*/
PetscErrorCode EPSReset(EPS eps)
{
PetscErrorCode ierr;
PetscInt ncols;
PetscFunctionBegin;
PetscValidHeaderSpecific(eps,EPS_CLASSID,1);
if (eps->ops->reset) {
ierr = (eps->ops->reset)(eps);
CHKERRQ(ierr);
}
if (eps->st) {
ierr = STReset(eps->st);
CHKERRQ(ierr);
}
if (eps->ds) {
ierr = DSReset(eps->ds);
CHKERRQ(ierr);
}
ierr = VecDestroy(&eps->D);
CHKERRQ(ierr);
ierr = BVGetSizes(eps->V,NULL,NULL,&ncols);
CHKERRQ(ierr);
if (ncols) {
ierr = PetscFree4(eps->eigr,eps->eigi,eps->errest,eps->perm);
CHKERRQ(ierr);
ierr = PetscFree2(eps->rr,eps->ri);
CHKERRQ(ierr);
}
ierr = BVDestroy(&eps->V);
CHKERRQ(ierr);
ierr = VecDestroyVecs(eps->nwork,&eps->work);
CHKERRQ(ierr);
eps->nwork = 0;
eps->state = EPS_STATE_INITIAL;
PetscFunctionReturn(0);
}
/*@
PCSetFromOptions - Sets PC options from the options database.
This routine must be called before PCSetUp() if the user is to be
allowed to set the preconditioner method.
Collective on PC
Input Parameter:
. pc - the preconditioner context
Options Database:
. -pc_use_amat true,false see PCSetUseAmat()
Level: developer
.keywords: PC, set, from, options, database
.seealso: PCSetUseAmat()
@*/
PetscErrorCode PCSetFromOptions(PC pc)
{
PetscErrorCode ierr;
char type[256];
const char *def;
PetscBool flg;
PetscFunctionBegin;
PetscValidHeaderSpecific(pc,PC_CLASSID,1);
if (!PCRegisterAllCalled) {ierr = PCRegisterAll();CHKERRQ(ierr);}
ierr = PetscObjectOptionsBegin((PetscObject)pc);CHKERRQ(ierr);
if (!((PetscObject)pc)->type_name) {
ierr = PCGetDefaultType_Private(pc,&def);CHKERRQ(ierr);
} else {
def = ((PetscObject)pc)->type_name;
}
ierr = PetscOptionsList("-pc_type","Preconditioner","PCSetType",PCList,def,type,256,&flg);CHKERRQ(ierr);
if (flg) {
ierr = PCSetType(pc,type);CHKERRQ(ierr);
} else if (!((PetscObject)pc)->type_name) {
ierr = PCSetType(pc,def);CHKERRQ(ierr);
}
ierr = PetscOptionsBool("-pc_use_amat","use Amat (instead of Pmat) to define preconditioner in nested inner solves","PCSetUseAmat",pc->useAmat,&pc->useAmat,NULL);CHKERRQ(ierr);
if (pc->ops->setfromoptions) {
ierr = (*pc->ops->setfromoptions)(pc);CHKERRQ(ierr);
}
/* process any options handlers added with PetscObjectAddOptionsHandler() */
ierr = PetscObjectProcessOptionsHandlers((PetscObject)pc);CHKERRQ(ierr);
ierr = PetscOptionsEnd();CHKERRQ(ierr);
pc->setfromoptionscalled++;
PetscFunctionReturn(0);
}
/*@
MatNullSpaceCreate - Creates a data structure used to project vectors
out of null spaces.
Collective on MPI_Comm
Input Parameters:
+ comm - the MPI communicator associated with the object
. has_cnst - PETSC_TRUE if the null space contains the constant vector; otherwise PETSC_FALSE
. n - number of vectors (excluding constant vector) in null space
- vecs - the vectors that span the null space (excluding the constant vector);
these vectors must be orthonormal. These vectors are NOT copied, so do not change them
after this call. You should free the array that you pass in and destroy the vectors (this will reduce the reference count
for them by one).
Output Parameter:
. SP - the null space context
Level: advanced
Notes: See MatNullSpaceSetFunction() as an alternative way of providing the null space information instead of setting vecs.
If has_cnst is PETSC_TRUE you do not need to pass a constant vector in as a fourth argument to this routine, nor do you
need to pass in a function that eliminates the constant function into MatNullSpaceSetFunction().
Users manual sections:
. sec_singular
.keywords: PC, null space, create
.seealso: MatNullSpaceDestroy(), MatNullSpaceRemove(), KSPSetNullSpace(), MatNullSpace, MatNullSpaceSetFunction()
@*/
PetscErrorCode MatNullSpaceCreate(MPI_Comm comm,PetscBool has_cnst,PetscInt n,const Vec vecs[],MatNullSpace *SP)
{
MatNullSpace sp;
PetscErrorCode ierr;
PetscInt i;
PetscFunctionBegin;
if (n < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Number of vectors (given %D) cannot be negative",n);
if (n) PetscValidPointer(vecs,4);
for (i=0; i<n; i++) PetscValidHeaderSpecific(vecs[i],VEC_CLASSID,4);
PetscValidPointer(SP,5);
*SP = NULL;
ierr = MatInitializePackage();CHKERRQ(ierr);
ierr = PetscHeaderCreate(sp,_p_MatNullSpace,int,MAT_NULLSPACE_CLASSID,"MatNullSpace","Null space","Mat",comm,MatNullSpaceDestroy,MatNullSpaceView);CHKERRQ(ierr);
sp->has_cnst = has_cnst;
sp->n = n;
sp->vecs = 0;
sp->alpha = 0;
sp->remove = 0;
sp->rmctx = 0;
if (n) {
ierr = PetscMalloc1(n,&sp->vecs);CHKERRQ(ierr);
ierr = PetscMalloc1(n,&sp->alpha);CHKERRQ(ierr);
ierr = PetscLogObjectMemory((PetscObject)sp,n*(sizeof(Vec)+sizeof(PetscScalar)));CHKERRQ(ierr);
for (i=0; i<n; i++) {
ierr = PetscObjectReference((PetscObject)vecs[i]);CHKERRQ(ierr);
sp->vecs[i] = vecs[i];
}
}
*SP = sp;
PetscFunctionReturn(0);
}
PetscErrorCode KSPFischerGuessUpdate_Method2(KSPFischerGuess_Method2 *itg,Vec x)
{
PetscScalar norm;
PetscErrorCode ierr;
int curl = itg->curl,i;
PetscFunctionBegin;
PetscValidHeaderSpecific(x,VEC_CLASSID,2);
PetscValidPointer(itg,3);
if (curl == itg->maxl) {
ierr = KSP_MatMult(itg->ksp,itg->mat,x,itg->Ax);CHKERRQ(ierr); /* norm = sqrt(x'Ax) */
ierr = VecDot(x,itg->Ax,&norm);CHKERRQ(ierr);
ierr = VecCopy(x,itg->xtilde[0]);CHKERRQ(ierr);
ierr = VecScale(itg->xtilde[0],1.0/PetscSqrtScalar(norm));CHKERRQ(ierr);
itg->curl = 1;
} else {
if (!curl) {
ierr = VecCopy(x,itg->xtilde[curl]);CHKERRQ(ierr);
} else {
ierr = VecWAXPY(itg->xtilde[curl],-1.0,itg->guess,x);CHKERRQ(ierr);
}
ierr = KSP_MatMult(itg->ksp,itg->mat,itg->xtilde[curl],itg->Ax);CHKERRQ(ierr);
ierr = VecMDot(itg->Ax,curl,itg->xtilde,itg->alpha);CHKERRQ(ierr);
for (i=0; i<curl; i++) itg->alpha[i] = -itg->alpha[i];
ierr = VecMAXPY(itg->xtilde[curl],curl,itg->alpha,itg->xtilde);CHKERRQ(ierr);
ierr = KSP_MatMult(itg->ksp,itg->mat,itg->xtilde[curl],itg->Ax);CHKERRQ(ierr); /* norm = sqrt(xtilde[curl]'Axtilde[curl]) */
ierr = VecDot(itg->xtilde[curl],itg->Ax,&norm);CHKERRQ(ierr);
if (PetscAbsScalar(norm) != 0.0) {
ierr = VecScale(itg->xtilde[curl],1.0/PetscSqrtScalar(norm));CHKERRQ(ierr);
itg->curl++;
} else {
ierr = PetscInfo(itg->ksp,"Not increasing dimension of Fischer space because new direction is identical to previous\n");CHKERRQ(ierr);
}
}
PetscFunctionReturn(0);
}
/*@C
PetscSFCreateEmbeddedSF - removes edges from all but the selected roots, does not remap indices
Collective
Input Arguments:
+ sf - original star forest
. nroots - number of roots to select on this process
- selected - selected roots on this process
Output Arguments:
. newsf - new star forest
Level: advanced
Note:
To use the new PetscSF, it may be necessary to know the indices of the leaves that are still participating. This can
be done by calling PetscSFGetGraph().
.seealso: PetscSFSetGraph(), PetscSFGetGraph()
@*/
PetscErrorCode PetscSFCreateEmbeddedSF(PetscSF sf,PetscInt nroots,const PetscInt *selected,PetscSF *newsf)
{
PetscInt *rootdata, *leafdata, *ilocal;
PetscSFNode *iremote;
PetscInt leafsize = 0, nleaves = 0, n, i;
PetscErrorCode ierr;
PetscFunctionBegin;
PetscValidHeaderSpecific(sf,PETSCSF_CLASSID,1);
if (nroots) PetscValidPointer(selected,3);
PetscValidPointer(newsf,4);
if (sf->mine) for (i = 0; i < sf->nleaves; ++i) {leafsize = PetscMax(leafsize, sf->mine[i]+1);}
else leafsize = sf->nleaves;
ierr = PetscCalloc2(sf->nroots,&rootdata,leafsize,&leafdata);CHKERRQ(ierr);
for (i=0; i<nroots; ++i) rootdata[selected[i]] = 1;
ierr = PetscSFBcastBegin(sf,MPIU_INT,rootdata,leafdata);CHKERRQ(ierr);
ierr = PetscSFBcastEnd(sf,MPIU_INT,rootdata,leafdata);CHKERRQ(ierr);
for (i = 0; i < leafsize; ++i) nleaves += leafdata[i];
ierr = PetscMalloc1(nleaves,&ilocal);CHKERRQ(ierr);
ierr = PetscMalloc1(nleaves,&iremote);CHKERRQ(ierr);
for (i = 0, n = 0; i < sf->nleaves; ++i) {
const PetscInt lidx = sf->mine ? sf->mine[i] : i;
if (leafdata[lidx]) {
ilocal[n] = lidx;
iremote[n].rank = sf->remote[i].rank;
iremote[n].index = sf->remote[i].index;
++n;
}
}
if (n != nleaves) SETERRQ2(PETSC_COMM_SELF, PETSC_ERR_PLIB, "There is a size mismatch in the SF embedding, %d != %d", n, nleaves);
ierr = PetscSFDuplicate(sf,PETSCSF_DUPLICATE_RANKS,newsf);CHKERRQ(ierr);
ierr = PetscSFSetGraph(*newsf,sf->nroots,nleaves,ilocal,PETSC_OWN_POINTER,iremote,PETSC_OWN_POINTER);CHKERRQ(ierr);
ierr = PetscFree2(rootdata,leafdata);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
EXTERN_C_END
#undef __FUNCT__
#define __FUNCT__ "PCShellGetContext"
/*@C
PCShellGetContext - Returns the user-provided context associated with a shell PC
Not Collective
Input Parameter:
. pc - should have been created with PCCreateShell()
Output Parameter:
. ctx - the user provided context
Level: advanced
Notes:
This routine is intended for use within various shell routines
.keywords: PC, shell, get, context
.seealso: PCCreateShell(), PCShellSetContext()
@*/
PetscErrorCode PETSCKSP_DLLEXPORT PCShellGetContext(PC pc,void **ctx)
{
PetscErrorCode ierr;
PetscTruth flg;
PetscFunctionBegin;
PetscValidHeaderSpecific(pc,PC_COOKIE,1);
PetscValidPointer(ctx,2);
ierr = PetscTypeCompare((PetscObject)pc,PCSHELL,&flg);CHKERRQ(ierr);
if (!flg) *ctx = 0;
else *ctx = ((PC_Shell*)(pc->data))->ctx;
PetscFunctionReturn(0);
}
/*@C
PetscSFCreateEmbeddedLeafSF - removes edges from all but the selected leaves, does not remap indices
Collective
Input Arguments:
+ sf - original star forest
. nleaves - number of leaves to select on this process
- selected - selected leaves on this process
Output Arguments:
. newsf - new star forest
Level: advanced
.seealso: PetscSFCreateEmbeddedSF(), PetscSFSetGraph(), PetscSFGetGraph()
@*/
PetscErrorCode PetscSFCreateEmbeddedLeafSF(PetscSF sf, PetscInt nleaves, const PetscInt *selected, PetscSF *newsf)
{
PetscSFNode *iremote;
PetscInt *ilocal;
PetscInt i;
PetscErrorCode ierr;
PetscFunctionBegin;
PetscValidHeaderSpecific(sf, PETSCSF_CLASSID, 1);
if (nleaves) PetscValidPointer(selected, 3);
PetscValidPointer(newsf, 4);
ierr = PetscMalloc1(nleaves, &ilocal);CHKERRQ(ierr);
ierr = PetscMalloc1(nleaves, &iremote);CHKERRQ(ierr);
for (i = 0; i < nleaves; ++i) {
const PetscInt l = selected[i];
ilocal[i] = sf->mine ? sf->mine[l] : l;
iremote[i].rank = sf->remote[l].rank;
iremote[i].index = sf->remote[l].index;
}
ierr = PetscSFDuplicate(sf, PETSCSF_DUPLICATE_RANKS, newsf);CHKERRQ(ierr);
ierr = PetscSFSetGraph(*newsf, sf->nroots, nleaves, ilocal, PETSC_OWN_POINTER, iremote, PETSC_OWN_POINTER);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
/*@C
MatSchurComplementGetSubMatrices - Get the individual submatrices in the Schur complement
Collective on Mat
Input Parameter:
. S - matrix obtained with MatCreateSchurComplement() (or equivalent) and implementing the action of A11 - A10 ksp(A00,Ap00) A01
Output Paramters:
+ A00,A01,A10,A11 - the four parts of the original matrix A = [A00 A01; A10 A11] (A11 is optional)
- Ap00 - preconditioning matrix for use in ksp(A00,Ap00) to approximate the action of A^{-1}.
Note: A11 is optional, and thus can be NULL. The submatrices are not increfed before they are returned and should not be modified or destroyed.
Level: intermediate
.seealso: MatCreateNormal(), MatMult(), MatCreate(), MatSchurComplementGetKSP(), MatCreateSchurComplement(), MatSchurComplementUpdateSubMatrices()
@*/
PetscErrorCode MatSchurComplementGetSubMatrices(Mat S,Mat *A00,Mat *Ap00,Mat *A01,Mat *A10,Mat *A11)
{
Mat_SchurComplement *Na = (Mat_SchurComplement*) S->data;
PetscErrorCode ierr;
PetscBool flg;
PetscFunctionBegin;
PetscValidHeaderSpecific(S,MAT_CLASSID,1);
ierr = PetscObjectTypeCompare((PetscObject)S,MATSCHURCOMPLEMENT,&flg);CHKERRQ(ierr);
if (flg) {
if (A00) *A00 = Na->A;
if (Ap00) *Ap00 = Na->Ap;
if (A01) *A01 = Na->B;
if (A10) *A10 = Na->C;
if (A11) *A11 = Na->D;
} else {
if (A00) *A00 = 0;
if (Ap00) *Ap00 = 0;
if (A01) *A01 = 0;
if (A10) *A10 = 0;
if (A11) *A11 = 0;
}
PetscFunctionReturn(0);
}
/*@C
SNESDefaultConverged - Convergence test of the solvers for
systems of nonlinear equations (default).
Collective on SNES
Input Parameters:
+ snes - the SNES context
. it - the iteration (0 indicates before any Newton steps)
. xnorm - 2-norm of current iterate
. snorm - 2-norm of current step
. fnorm - 2-norm of function at current iterate
- dummy - unused context
Output Parameter:
. reason - one of
$ SNES_CONVERGED_FNORM_ABS - (fnorm < abstol),
$ SNES_CONVERGED_SNORM_RELATIVE - (snorm < stol*xnorm),
$ SNES_CONVERGED_FNORM_RELATIVE - (fnorm < rtol*fnorm0),
$ SNES_DIVERGED_FUNCTION_COUNT - (nfct > maxf),
$ SNES_DIVERGED_FNORM_NAN - (fnorm == NaN),
$ SNES_CONVERGED_ITERATING - (otherwise),
where
+ maxf - maximum number of function evaluations,
set with SNESSetTolerances()
. nfct - number of function evaluations,
. abstol - absolute function norm tolerance,
set with SNESSetTolerances()
- rtol - relative function norm tolerance, set with SNESSetTolerances()
Level: intermediate
.keywords: SNES, nonlinear, default, converged, convergence
.seealso: SNESSetConvergenceTest()
@*/
PetscErrorCode SNESDefaultConverged(SNES snes,PetscInt it,PetscReal xnorm,PetscReal snorm,PetscReal fnorm,SNESConvergedReason *reason,void *dummy)
{
PetscErrorCode ierr;
PetscFunctionBegin;
PetscValidHeaderSpecific(snes,SNES_CLASSID,1);
PetscValidPointer(reason,6);
*reason = SNES_CONVERGED_ITERATING;
if (!it) {
/* set parameter for default relative tolerance convergence test */
snes->ttol = fnorm*snes->rtol;
}
if (PetscIsInfOrNanReal(fnorm)) {
ierr = PetscInfo(snes,"Failed to converged, function norm is NaN\n");CHKERRQ(ierr);
*reason = SNES_DIVERGED_FNORM_NAN;
} else if (fnorm < snes->abstol) {
ierr = PetscInfo2(snes,"Converged due to function norm %14.12e < %14.12e\n",(double)fnorm,(double)snes->abstol);CHKERRQ(ierr);
*reason = SNES_CONVERGED_FNORM_ABS;
} else if (snes->nfuncs >= snes->max_funcs) {
ierr = PetscInfo2(snes,"Exceeded maximum number of function evaluations: %D > %D\n",snes->nfuncs,snes->max_funcs);CHKERRQ(ierr);
*reason = SNES_DIVERGED_FUNCTION_COUNT;
}
if (it && !*reason) {
if (fnorm <= snes->ttol) {
ierr = PetscInfo2(snes,"Converged due to function norm %14.12e < %14.12e (relative tolerance)\n",(double)fnorm,(double)snes->ttol);CHKERRQ(ierr);
*reason = SNES_CONVERGED_FNORM_RELATIVE;
} else if (snorm < snes->stol*xnorm) {
ierr = PetscInfo3(snes,"Converged due to small update length: %14.12e < %14.12e * %14.12e\n",(double)snorm,(double)snes->stol,(double)xnorm);CHKERRQ(ierr);
*reason = SNES_CONVERGED_SNORM_RELATIVE;
}
}
PetscFunctionReturn(0);
}
/*@C
ISColoringView - Views a coloring context.
Collective on ISColoring
Input Parameters:
+ iscoloring - the coloring context
- viewer - the viewer
Level: advanced
.seealso: ISColoringDestroy(), ISColoringGetIS(), MatColoring
@*/
PetscErrorCode ISColoringView(ISColoring iscoloring,PetscViewer viewer)
{
PetscInt i;
PetscErrorCode ierr;
PetscBool iascii;
IS *is;
PetscFunctionBegin;
PetscValidPointer(iscoloring,1);
if (!viewer) {
ierr = PetscViewerASCIIGetStdout(iscoloring->comm,&viewer);CHKERRQ(ierr);
}
PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,2);
ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr);
if (iascii) {
MPI_Comm comm;
PetscMPIInt size,rank;
ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr);
ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr);
ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr);
ierr = PetscViewerASCIIPrintf(viewer,"ISColoring Object: %d MPI processes\n",size);CHKERRQ(ierr);
ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr);
ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Number of colors %d\n",rank,iscoloring->n);CHKERRQ(ierr);
ierr = PetscViewerFlush(viewer);CHKERRQ(ierr);
ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr);
} else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"Viewer type %s not supported for ISColoring",((PetscObject)viewer)->type_name);
ierr = ISColoringGetIS(iscoloring,PETSC_IGNORE,&is);CHKERRQ(ierr);
for (i=0; i<iscoloring->n; i++) {
ierr = ISView(iscoloring->is[i],viewer);CHKERRQ(ierr);
}
ierr = ISColoringRestoreIS(iscoloring,&is);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
/*@C
ISGetNonlocalIndices - Retrieve an array of indices from remote processors
in this communicator.
Collective on IS
Input Parameter:
. is - the index set
Output Parameter:
. indices - indices with rank 0 indices first, and so on, omitting
the current rank. Total number of indices is the difference
total and local, obtained with ISGetSize() and ISGetLocalSize(),
respectively.
Level: intermediate
Notes: restore the indices using ISRestoreNonlocalIndices().
The same scalability considerations as those for ISGetTotalIndices
apply here.
Concepts: index sets^getting nonlocal indices
.seealso: ISGetTotalIndices(), ISRestoreNonlocalIndices(), ISGetSize(), ISGetLocalSize().
@*/
PetscErrorCode ISGetNonlocalIndices(IS is, const PetscInt *indices[])
{
PetscErrorCode ierr;
PetscMPIInt size;
PetscInt n, N;
PetscFunctionBegin;
PetscValidHeaderSpecific(is,IS_CLASSID,1);
PetscValidPointer(indices,2);
ierr = MPI_Comm_size(PetscObjectComm((PetscObject)is), &size);CHKERRQ(ierr);
if (size == 1) *indices = NULL;
else {
if (!is->total) {
ierr = ISGatherTotal_Private(is);CHKERRQ(ierr);
}
ierr = ISGetLocalSize(is,&n);CHKERRQ(ierr);
ierr = ISGetSize(is,&N);CHKERRQ(ierr);
ierr = PetscMalloc(sizeof(PetscInt)*(N-n), &(is->nonlocal));CHKERRQ(ierr);
ierr = PetscMemcpy(is->nonlocal, is->total, sizeof(PetscInt)*is->local_offset);CHKERRQ(ierr);
ierr = PetscMemcpy(is->nonlocal+is->local_offset, is->total+is->local_offset+n, sizeof(PetscInt)*(N - is->local_offset - n));CHKERRQ(ierr);
*indices = is->nonlocal;
}
PetscFunctionReturn(0);
}
/*@C
MatGetColoring - Gets a coloring for a matrix, from its sparsity structure,
to reduce the number of function evaluations needed to compute a sparse Jacobian via differencing.
Collective on Mat
Input Parameters:
. mat - the matrix
. type - type of coloring, one of the following:
$ MATCOLORINGNATURAL - natural (one color for each column, very slow)
$ MATCOLORINGSL - smallest-last
$ MATCOLORINGLF - largest-first
$ MATCOLORINGID - incidence-degree
Output Parameters:
. iscoloring - the coloring
Options Database Keys:
To specify the coloring through the options database, use one of
the following
$ -mat_coloring_type natural, -mat_coloring_type sl, -mat_coloring_type lf,
$ -mat_coloring_type id
To see the coloring use
$ -mat_coloring_view
Level: intermediate
Notes:
$ A graph coloring C(A) is a division of vertices so that two vertices of the same color do not share any common edges.
$ A suitable coloring for a smoother is simply C(A).
$ A suitable coloring for efficient Jacobian computation is a division of the columns so that two columns of the same color do not share any common rows.
$ This corresponds to C(A^{T} A). This is what MatGetColoring() computes.
The user can define additional colorings; see MatColoringRegisterDynamic().
For parallel matrices currently converts to sequential matrix and uses the sequential coloring
on that.
The colorings SL, LF, and ID are obtained via the Minpack software that was
converted to C using f2c.
For BAIJ matrices this colors the blocks. The true number of colors would be block size times the number of colors
returned here.
References:
$ Thomas F. Coleman and Jorge J. More, Estimation of Sparse {J}acobian Matrices and Graph Coloring Problems,
$ SIAM Journal on Numerical Analysis, 1983, pages 187-209, volume 20
$ Jorge J. Mor\'{e} and Danny C. Sorenson and Burton S. Garbow and Kenneth E. Hillstrom, The {MINPACK} Project,
$ Sources and Development of Mathematical Software, Wayne R. Cowell editor, 1984, pages 88-111
.keywords: matrix, get, coloring
.seealso: MatGetColoringTypeFromOptions(), MatColoringRegisterDynamic(), MatFDColoringCreate(),
SNESDefaultComputeJacobianColor()
@*/
PetscErrorCode MatGetColoring(Mat mat,MatColoringType type,ISColoring *iscoloring)
{
PetscBool flag;
PetscErrorCode ierr,(*r)(Mat,MatColoringType,ISColoring *);
char tname[PETSC_MAX_PATH_LEN];
MPI_Comm comm;
PetscFunctionBegin;
PetscValidHeaderSpecific(mat,MAT_CLASSID,1);
PetscValidPointer(iscoloring,3);
if (!mat->assembled) SETERRQ(((PetscObject)mat)->comm,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix");
if (mat->factortype) SETERRQ(((PetscObject)mat)->comm,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");
/* look for type on command line */
if (!MatColoringRegisterAllCalled) {ierr = MatColoringRegisterAll(PETSC_NULL);CHKERRQ(ierr);}
ierr = PetscOptionsGetString(((PetscObject)mat)->prefix,"-mat_coloring_type",tname,256,&flag);CHKERRQ(ierr);
if (flag) { type = tname; }
ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr);
ierr = PetscFunctionListFind(comm,MatColoringList,type,PETSC_TRUE,(void (**)(void)) &r);CHKERRQ(ierr);
if (!r) SETERRQ1(((PetscObject)mat)->comm,PETSC_ERR_ARG_OUTOFRANGE,"Unknown or unregistered type: %s",type);
ierr = PetscLogEventBegin(MAT_GetColoring,mat,0,0,0);CHKERRQ(ierr);
ierr = (*r)(mat,type,iscoloring);CHKERRQ(ierr);
ierr = PetscLogEventEnd(MAT_GetColoring,mat,0,0,0);CHKERRQ(ierr);
ierr = PetscInfo1(mat,"Number of colors %d\n",(*iscoloring)->n);CHKERRQ(ierr);
flag = PETSC_FALSE;
ierr = PetscOptionsGetBool(PETSC_NULL,"-mat_coloring_view",&flag,PETSC_NULL);CHKERRQ(ierr);
if (flag) {
PetscViewer viewer;
ierr = PetscViewerASCIIGetStdout((*iscoloring)->comm,&viewer);CHKERRQ(ierr);
ierr = ISColoringView(*iscoloring,viewer);CHKERRQ(ierr);
}
PetscFunctionReturn(0);
}
/*@C
KSPMonitorTrueResidualNorm - Prints the true residual norm as well as the preconditioned
residual norm at each iteration of an iterative solver.
Collective on KSP
Input Parameters:
+ ksp - iterative context
. n - iteration number
. rnorm - 2-norm (preconditioned) residual value (may be estimated).
- dummy - an ASCII PetscViewer
Options Database Key:
. -ksp_monitor_true_residual - Activates KSPMonitorTrueResidualNorm()
Notes:
When using right preconditioning, these values are equivalent.
Level: intermediate
.keywords: KSP, default, monitor, residual
.seealso: KSPMonitorSet(), KSPMonitorDefault(), KSPMonitorLGResidualNormCreate(),KSPMonitorTrueResidualMaxNorm()
@*/
PetscErrorCode KSPMonitorTrueResidualNorm(KSP ksp,PetscInt n,PetscReal rnorm,void *dummy)
{
PetscErrorCode ierr;
Vec resid;
PetscReal truenorm,bnorm;
PetscViewer viewer = (PetscViewer)dummy;
char normtype[256];
PetscFunctionBegin;
PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,4);
ierr = PetscViewerASCIIAddTab(viewer,((PetscObject)ksp)->tablevel);CHKERRQ(ierr);
if (n == 0 && ((PetscObject)ksp)->prefix) {
ierr = PetscViewerASCIIPrintf(viewer," Residual norms for %s solve.\n",((PetscObject)ksp)->prefix);CHKERRQ(ierr);
}
ierr = KSPBuildResidual(ksp,NULL,NULL,&resid);CHKERRQ(ierr);
ierr = VecNorm(resid,NORM_2,&truenorm);CHKERRQ(ierr);
ierr = VecDestroy(&resid);CHKERRQ(ierr);
ierr = VecNorm(ksp->vec_rhs,NORM_2,&bnorm);CHKERRQ(ierr);
ierr = PetscStrncpy(normtype,KSPNormTypes[ksp->normtype],sizeof(normtype));CHKERRQ(ierr);
ierr = PetscStrtolower(normtype);CHKERRQ(ierr);
ierr = PetscViewerASCIIPrintf(viewer,"%3D KSP %s resid norm %14.12e true resid norm %14.12e ||r(i)||/||b|| %14.12e\n",n,normtype,(double)rnorm,(double)truenorm,(double)(truenorm/bnorm));CHKERRQ(ierr);
ierr = PetscViewerASCIISubtractTab(viewer,((PetscObject)ksp)->tablevel);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
/*@
KSPSetDM - Sets the DM that may be used by some preconditioners
Logically Collective on KSP
Input Parameters:
+ ksp - the preconditioner context
- dm - the dm
Notes: If this is used then the KSP will attempt to use the DM to create the matrix and use the routine
set with DMKSPSetComputeOperators(). Use KSPSetDMActive(ksp,PETSC_FALSE) to instead use the matrix
you've provided with KSPSetOperators().
Level: intermediate
.seealso: KSPGetDM(), KSPSetDMActive(), KSPSetComputeOperators(), KSPSetComputeRHS(), KSPSetComputeInitialGuess(), DMKSPSetComputeOperators(), DMKSPSetComputeRHS(), DMKSPSetComputeInitialGuess()
@*/
PetscErrorCode KSPSetDM(KSP ksp,DM dm)
{
PetscErrorCode ierr;
PC pc;
PetscFunctionBegin;
PetscValidHeaderSpecific(ksp,KSP_CLASSID,1);
if (dm) {ierr = PetscObjectReference((PetscObject)dm);CHKERRQ(ierr);}
if (ksp->dm) { /* Move the DMSNES context over to the new DM unless the new DM already has one */
if (ksp->dm->dmksp && ksp->dmAuto && !dm->dmksp) {
DMKSP kdm;
ierr = DMCopyDMKSP(ksp->dm,dm);CHKERRQ(ierr);
ierr = DMGetDMKSP(ksp->dm,&kdm);CHKERRQ(ierr);
if (kdm->originaldm == ksp->dm) kdm->originaldm = dm; /* Grant write privileges to the replacement DM */
}
ierr = DMDestroy(&ksp->dm);CHKERRQ(ierr);
}
ksp->dm = dm;
ksp->dmAuto = PETSC_FALSE;
ierr = KSPGetPC(ksp,&pc);CHKERRQ(ierr);
ierr = PCSetDM(pc,dm);CHKERRQ(ierr);
ksp->dmActive = PETSC_TRUE;
PetscFunctionReturn(0);
}
/*@C
SNESMonitorDefaultField - Monitors progress of the SNES solvers, separated into fields.
Collective on SNES
Input Parameters:
+ snes - the SNES context
. its - iteration number
. fgnorm - 2-norm of residual
- ctx - the PetscViewer
Notes:
This routine uses the DM attached to the residual vector
Level: intermediate
.keywords: SNES, nonlinear, field, monitor, norm
.seealso: SNESMonitorSet(), SNESMonitorSolution(), SNESMonitorDefault(), SNESMonitorDefaultShort()
@*/
PetscErrorCode SNESMonitorDefaultField(SNES snes, PetscInt its, PetscReal fgnorm, void *ctx)
{
PetscViewer viewer = (PetscViewer) ctx;
Vec r;
DM dm;
PetscReal res[256];
PetscInt tablevel;
PetscErrorCode ierr;
PetscFunctionBegin;
PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,4);
ierr = SNESGetFunction(snes, &r, NULL, NULL);CHKERRQ(ierr);
ierr = VecGetDM(r, &dm);CHKERRQ(ierr);
if (!dm) {ierr = SNESMonitorDefault(snes, its, fgnorm, ctx);CHKERRQ(ierr);}
else {
PetscSection s, gs;
PetscInt Nf, f;
ierr = DMGetDefaultSection(dm, &s);CHKERRQ(ierr);
ierr = DMGetDefaultGlobalSection(dm, &gs);CHKERRQ(ierr);
if (!s || !gs) {ierr = SNESMonitorDefault(snes, its, fgnorm, ctx);CHKERRQ(ierr);}
ierr = PetscSectionGetNumFields(s, &Nf);CHKERRQ(ierr);
if (Nf > 256) SETERRQ1(PetscObjectComm((PetscObject) snes), PETSC_ERR_SUP, "Do not support %d fields > 256", Nf);
ierr = PetscSectionVecNorm(s, gs, r, NORM_2, res);CHKERRQ(ierr);
ierr = PetscObjectGetTabLevel((PetscObject) snes, &tablevel);CHKERRQ(ierr);
ierr = PetscViewerASCIIAddTab(viewer, tablevel);CHKERRQ(ierr);
ierr = PetscViewerASCIIPrintf(viewer, "%3D SNES Function norm %14.12e [", its, (double) fgnorm);CHKERRQ(ierr);
for (f = 0; f < Nf; ++f) {
if (f) {ierr = PetscViewerASCIIPrintf(viewer, ", ");CHKERRQ(ierr);}
ierr = PetscViewerASCIIPrintf(viewer, "%14.12e", res[f]);CHKERRQ(ierr);
}
ierr = PetscViewerASCIIPrintf(viewer, "] \n");CHKERRQ(ierr);
ierr = PetscViewerASCIISubtractTab(viewer, tablevel);CHKERRQ(ierr);
}
PetscFunctionReturn(0);
}
/*@C
PFDestroy - Destroys PF context that was created with PFCreate().
Collective on PF
Input Parameter:
. pf - the function context
Level: beginner
.keywords: PF, destroy
.seealso: PFCreate(), PFSet(), PFSetType()
@*/
PetscErrorCode PFDestroy(PF *pf)
{
PetscErrorCode ierr;
PetscBool flg = PETSC_FALSE;
PetscFunctionBegin;
if (!*pf) PetscFunctionReturn(0);
PetscValidHeaderSpecific((*pf),PF_CLASSID,1);
if (--((PetscObject)(*pf))->refct > 0) PetscFunctionReturn(0);
ierr = PetscOptionsGetBool(((PetscObject)(*pf))->prefix,"-pf_view",&flg,PETSC_NULL);CHKERRQ(ierr);
if (flg) {
PetscViewer viewer;
ierr = PetscViewerASCIIGetStdout(((PetscObject)(*pf))->comm,&viewer);CHKERRQ(ierr);
ierr = PFView((*pf),viewer);CHKERRQ(ierr);
}
/* if memory was published with AMS then destroy it */
ierr = PetscObjectDepublish((*pf));CHKERRQ(ierr);
if ((*pf)->ops->destroy) {ierr = (*(*pf)->ops->destroy)((*pf)->data);CHKERRQ(ierr);}
ierr = PetscHeaderDestroy(pf);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
/*@
PFSetFromOptions - Sets PF options from the options database.
Collective on PF
Input Parameters:
. pf - the mathematical function context
Options Database Keys:
Notes:
To see all options, run your program with the -help option
or consult the users manual.
Level: intermediate
.keywords: PF, set, from, options, database
.seealso:
@*/
PetscErrorCode PFSetFromOptions(PF pf)
{
PetscErrorCode ierr;
char type[256];
PetscBool flg;
PetscFunctionBegin;
PetscValidHeaderSpecific(pf,PF_CLASSID,1);
ierr = PetscObjectOptionsBegin((PetscObject)pf);CHKERRQ(ierr);
ierr = PetscOptionsList("-pf_type","Type of function","PFSetType",PFList,0,type,256,&flg);CHKERRQ(ierr);
if (flg) {
ierr = PFSetType(pf,type,PETSC_NULL);CHKERRQ(ierr);
}
if (pf->ops->setfromoptions) {
ierr = (*pf->ops->setfromoptions)(pf);CHKERRQ(ierr);
}
/* process any options handlers added with PetscObjectAddOptionsHandler() */
ierr = PetscObjectProcessOptionsHandlers((PetscObject)pf);CHKERRQ(ierr);
ierr = PetscOptionsEnd();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
/*@
PetscDrawLGView - Prints a line graph.
Collective on PetscDrawLG
Input Parameter:
. lg - the line graph context
Level: beginner
.seealso: PetscDrawLGCreate()
.keywords: draw, line, graph
@*/
PetscErrorCode PetscDrawLGView(PetscDrawLG lg,PetscViewer viewer)
{
PetscReal xmin=lg->xmin, xmax=lg->xmax, ymin=lg->ymin, ymax=lg->ymax;
PetscInt i, j, dim = lg->dim, nopts = lg->nopts;
PetscErrorCode ierr;
PetscFunctionBegin;
PetscValidHeaderSpecific(lg,PETSC_DRAWLG_CLASSID,1);
if (nopts < 1) PetscFunctionReturn(0);
if (xmin > xmax || ymin > ymax) PetscFunctionReturn(0);
if (!viewer){
ierr = PetscViewerASCIIGetStdout(PetscObjectComm((PetscObject)lg),&viewer);CHKERRQ(ierr);
}
ierr = PetscObjectPrintClassNamePrefixType((PetscObject)lg,viewer);CHKERRQ(ierr);
for (i = 0; i < dim; i++) {
ierr = PetscViewerASCIIPrintf(viewer, "Line %D>\n", i);CHKERRQ(ierr);
for (j = 0; j < nopts; j++) {
ierr = PetscViewerASCIIPrintf(viewer, " X: %g Y: %g\n", (double)lg->x[j*dim+i], (double)lg->y[j*dim+i]);CHKERRQ(ierr);
}
}
PetscFunctionReturn(0);
}
/*@
MatHasOperation - Determines whether the given matrix supports the particular
operation.
Not Collective
Input Parameters:
+ mat - the matrix
- op - the operation, for example, MATOP_GET_DIAGONAL
Output Parameter:
. has - either PETSC_TRUE or PETSC_FALSE
Level: advanced
Notes:
See the file include/petscmat.h for a complete list of matrix
operations, which all have the form MATOP_<OPERATION>, where
<OPERATION> is the name (in all capital letters) of the
user-level routine. E.g., MatNorm() -> MATOP_NORM.
.keywords: matrix, has, operation
.seealso: MatCreateShell()
@*/
PetscErrorCode MatHasOperation(Mat mat,MatOperation op,PetscBool *has)
{
PetscFunctionBegin;
PetscValidHeaderSpecific(mat,MAT_CLASSID,1);
PetscValidType(mat,1);
PetscValidPointer(has,3);
if (((void**)mat->ops)[op]) *has = PETSC_TRUE;
else {
if (op == MATOP_GET_SUBMATRIX) {
PetscErrorCode ierr;
PetscMPIInt size;
ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr);
if (size == 1) {
ierr = MatHasOperation(mat,MATOP_GET_SUBMATRICES,has);CHKERRQ(ierr);
} else {
*has = PETSC_FALSE;
}
} else {
*has = PETSC_FALSE;
}
}
PetscFunctionReturn(0);
}
PetscErrorCode DMCompositeGetGlobalISs(DM dm,IS *is[])
{
PetscErrorCode ierr;
PetscInt cnt = 0,*idx,i;
struct DMCompositeLink *next;
PetscMPIInt rank;
DM_Composite *com = (DM_Composite*)dm->data;
PetscFunctionBegin;
PetscValidHeaderSpecific(dm,DM_CLASSID,1);
ierr = PetscMalloc((com->nDM)*sizeof(IS),is);CHKERRQ(ierr);
next = com->next;
ierr = MPI_Comm_rank(((PetscObject)dm)->comm,&rank);CHKERRQ(ierr);
/* loop over packed objects, handling one at at time */
while (next) {
ierr = PetscMalloc(next->n*sizeof(PetscInt),&idx);CHKERRQ(ierr);
for (i=0; i<next->n; i++) idx[i] = next->grstart + i;
ierr = ISCreateGeneral(((PetscObject)dm)->comm,next->n,idx,PETSC_OWN_POINTER,&(*is)[cnt]);CHKERRQ(ierr);
cnt++;
next = next->next;
}
PetscFunctionReturn(0);
}
/*@C
MatSchurComplementGetSubmatrices - Get the individual submatrices in the Schur complement
Collective on Mat
Input Parameters:
+ N - the matrix obtained with MatCreateSchurComplement()
- A,B,C,D - the four parts of the original matrix (D is optional)
Note:
D is optional, and thus can be PETSC_NULL
Level: intermediate
.seealso: MatCreateNormal(), MatMult(), MatCreate(), MatSchurComplementGetKSP(), MatCreateSchurComplement(), MatSchurComplementUpdate()
@*/
PetscErrorCode MatSchurComplementGetSubmatrices(Mat N,Mat *A,Mat *Ap,Mat *B,Mat *C,Mat *D)
{
Mat_SchurComplement *Na = (Mat_SchurComplement *) N->data;
PetscErrorCode ierr;
PetscBool flg;
PetscFunctionBegin;
PetscValidHeaderSpecific(N,MAT_CLASSID,1);
ierr = PetscObjectTypeCompare((PetscObject)N,MATSCHURCOMPLEMENT,&flg);CHKERRQ(ierr);
if (flg) {
if (A) *A = Na->A;
if (Ap) *Ap = Na->Ap;
if (B) *B = Na->B;
if (C) *C = Na->C;
if (D) *D = Na->D;
} else {
if (A) *A = 0;
if (Ap) *Ap = 0;
if (B) *B = 0;
if (C) *C = 0;
if (D) *D = 0;
}
PetscFunctionReturn(0);
}
/*@
NEPSetDimensions - Sets the number of eigenvalues to compute
and the dimension of the subspace.
Logically Collective on NEP
Input Parameters:
+ nep - the nonlinear eigensolver context
. nev - number of eigenvalues to compute
. ncv - the maximum dimension of the subspace to be used by the solver
- mpd - the maximum dimension allowed for the projected problem
Options Database Keys:
+ -nep_nev <nev> - Sets the number of eigenvalues
. -nep_ncv <ncv> - Sets the dimension of the subspace
- -nep_mpd <mpd> - Sets the maximum projected dimension
Notes:
Use PETSC_DEFAULT for ncv and mpd to assign a reasonably good value, which is
dependent on the solution method.
The parameters ncv and mpd are intimately related, so that the user is advised
to set one of them at most. Normal usage is that
(a) in cases where nev is small, the user sets ncv (a reasonable default is 2*nev); and
(b) in cases where nev is large, the user sets mpd.
The value of ncv should always be between nev and (nev+mpd), typically
ncv=nev+mpd. If nev is not too large, mpd=nev is a reasonable choice, otherwise
a smaller value should be used.
Level: intermediate
.seealso: NEPGetDimensions()
@*/
PetscErrorCode NEPSetDimensions(NEP nep,PetscInt nev,PetscInt ncv,PetscInt mpd)
{
PetscFunctionBegin;
PetscValidHeaderSpecific(nep,NEP_CLASSID,1);
PetscValidLogicalCollectiveInt(nep,nev,2);
PetscValidLogicalCollectiveInt(nep,ncv,3);
PetscValidLogicalCollectiveInt(nep,mpd,4);
if (nev<1) SETERRQ(PetscObjectComm((PetscObject)nep),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of nev. Must be > 0");
nep->nev = nev;
if (ncv == PETSC_DECIDE || ncv == PETSC_DEFAULT) {
nep->ncv = 0;
} else {
if (ncv<1) SETERRQ(PetscObjectComm((PetscObject)nep),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of ncv. Must be > 0");
nep->ncv = ncv;
}
if (mpd == PETSC_DECIDE || mpd == PETSC_DEFAULT) {
nep->mpd = 0;
} else {
if (mpd<1) SETERRQ(PetscObjectComm((PetscObject)nep),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of mpd. Must be > 0");
nep->mpd = mpd;
}
nep->state = NEP_STATE_INITIAL;
PetscFunctionReturn(0);
}