/* collective on KSP */
PetscErrorCode KSPPlotEigenContours_Private(KSP ksp,PetscInt neig,const PetscReal *r,const PetscReal *c)
{
PetscErrorCode ierr;
PetscReal xmin,xmax,ymin,ymax,*xloc,*yloc,*value,px0,py0,rscale,iscale;
PetscInt M,N,i,j;
PetscMPIInt rank;
PetscViewer viewer;
PetscDraw draw;
PetscDrawAxis drawaxis;
PetscFunctionBegin;
ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)ksp),&rank);CHKERRQ(ierr);
if (rank) PetscFunctionReturn(0);
M = 80;
N = 80;
xmin = r[0]; xmax = r[0];
ymin = c[0]; ymax = c[0];
for (i=1; i<neig; i++) {
xmin = PetscMin(xmin,r[i]);
xmax = PetscMax(xmax,r[i]);
ymin = PetscMin(ymin,c[i]);
ymax = PetscMax(ymax,c[i]);
}
ierr = PetscMalloc3(M,&xloc,N,&yloc,M*N,&value);CHKERRQ(ierr);
for (i=0; i<M; i++) xloc[i] = xmin - 0.1*(xmax-xmin) + 1.2*(xmax-xmin)*i/(M-1);
for (i=0; i<N; i++) yloc[i] = ymin - 0.1*(ymax-ymin) + 1.2*(ymax-ymin)*i/(N-1);
ierr = PolyEval(neig,r,c,0,0,&px0,&py0);CHKERRQ(ierr);
rscale = px0/(PetscSqr(px0)+PetscSqr(py0));
iscale = -py0/(PetscSqr(px0)+PetscSqr(py0));
for (j=0; j<N; j++) {
for (i=0; i<M; i++) {
PetscReal px,py,tx,ty,tmod;
ierr = PolyEval(neig,r,c,xloc[i],yloc[j],&px,&py);CHKERRQ(ierr);
tx = px*rscale - py*iscale;
ty = py*rscale + px*iscale;
tmod = PetscSqr(tx) + PetscSqr(ty); /* modulus of the complex polynomial */
if (tmod > 1) tmod = 1.0;
if (tmod > 0.5 && tmod < 1) tmod = 0.5;
if (tmod > 0.2 && tmod < 0.5) tmod = 0.2;
if (tmod > 0.05 && tmod < 0.2) tmod = 0.05;
if (tmod < 1e-3) tmod = 1e-3;
value[i+j*M] = PetscLogReal(tmod) / PetscLogReal(10.0);
}
}
ierr = PetscViewerDrawOpen(PETSC_COMM_SELF,0,"Iteratively Computed Eigen-contours",PETSC_DECIDE,PETSC_DECIDE,450,450,&viewer);CHKERRQ(ierr);
ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr);
ierr = PetscDrawTensorContour(draw,M,N,NULL,NULL,value);CHKERRQ(ierr);
if (0) {
ierr = PetscDrawAxisCreate(draw,&drawaxis);CHKERRQ(ierr);
ierr = PetscDrawAxisSetLimits(drawaxis,xmin,xmax,ymin,ymax);CHKERRQ(ierr);
ierr = PetscDrawAxisSetLabels(drawaxis,"Eigen-counters","real","imag");CHKERRQ(ierr);
ierr = PetscDrawAxisDraw(drawaxis);CHKERRQ(ierr);
ierr = PetscDrawAxisDestroy(&drawaxis);CHKERRQ(ierr);
}
ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr);
ierr = PetscFree3(xloc,yloc,value);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
int main(int argc, char **argv)
{
PetscErrorCode ierr; /* Error code */
char ptype[256] = "hull1972a1"; /* Problem specification */
PetscInt n_refine = 1; /* Number of refinement levels for convergence analysis */
PetscReal refine_fac = 2.0; /* Refinement factor for dt */
PetscReal dt_initial = 0.01; /* Initial default value of dt */
PetscReal dt;
PetscReal tfinal = 20.0; /* Final time for the time-integration */
PetscInt maxiter = 100000; /* Maximum number of time-integration iterations */
PetscReal *error; /* Array to store the errors for convergence analysis */
PetscMPIInt size; /* No of processors */
PetscBool flag; /* Flag denoting availability of exact solution */
PetscInt r;
/* Initialize program */
PetscInitialize(&argc,&argv,(char*)0,help);
/* Check if running with only 1 proc */
ierr = MPI_Comm_size(PETSC_COMM_WORLD,&size);CHKERRQ(ierr);
if (size>1) SETERRQ(PETSC_COMM_WORLD,PETSC_ERR_SUP,"Only for sequential runs");
ierr = PetscOptionsString("-problem","Problem specification","<hull1972a1>",
ptype,ptype,sizeof(ptype),NULL);CHKERRQ(ierr);
ierr = PetscOptionsInt("-refinement_levels","Number of refinement levels for convergence analysis",
"<1>",n_refine,&n_refine,NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-refinement_factor","Refinement factor for dt","<2.0>",
refine_fac,&refine_fac,NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-dt","Time step size (for convergence analysis, initial time step)",
"<0.01>",dt_initial,&dt_initial,NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-final_time","Final time for the time-integration","<20.0>",
tfinal,&tfinal,NULL);CHKERRQ(ierr);
ierr = PetscMalloc1(n_refine,&error);CHKERRQ(ierr);
for (r = 0,dt = dt_initial; r < n_refine; r++) {
error[r] = 0;
if (r > 0) dt /= refine_fac;
ierr = PetscPrintf(PETSC_COMM_WORLD,"Solving ODE \"%s\" with dt %f, final time %f and system size %D.\n",ptype,(double)dt,(double)tfinal,GetSize(&ptype[0]));
ierr = SolveODE(&ptype[0],dt,tfinal,maxiter,&error[r],&flag);
if (flag) {
/* If exact solution available for the specified ODE */
if (r > 0) {
PetscReal conv_rate = (PetscLogReal(error[r]) - PetscLogReal(error[r-1])) / (-PetscLogReal(refine_fac));
ierr = PetscPrintf(PETSC_COMM_WORLD,"Error = %E,\tConvergence rate = %f\n.",(double)error[r],(double)conv_rate);CHKERRQ(ierr);
} else {
ierr = PetscPrintf(PETSC_COMM_WORLD,"Error = %E.\n",error[r]);CHKERRQ(ierr);
}
}
}
ierr = PetscFree(error);CHKERRQ(ierr);
/* Exit */
PetscFinalize();
return(0);
}
static PetscErrorCode KSPSolve_AGMRES(KSP ksp)
{
PetscErrorCode ierr;
PetscInt its;
KSP_AGMRES *agmres = (KSP_AGMRES*)ksp->data;
PetscBool guess_zero = ksp->guess_zero;
PetscReal res_old, res;
PetscInt test;
PetscFunctionBegin;
ierr = PetscObjectSAWsTakeAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->its = 0;
ierr = PetscObjectSAWsGrantAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->reason = KSP_CONVERGED_ITERATING;
if (!agmres->HasShifts) { /* Compute Shifts for the Newton basis */
ierr = KSPComputeShifts_DGMRES(ksp);CHKERRQ(ierr);
}
/* NOTE: At this step, the initial guess is not equal to zero since one cycle of the classical GMRES is performed to compute the shifts */
ierr = (*ksp->converged)(ksp,0,ksp->rnorm,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
while (!ksp->reason) {
ierr = KSPInitialResidual(ksp,ksp->vec_sol,VEC_TMP,VEC_TMP_MATOP,VEC_V(0),ksp->vec_rhs);CHKERRQ(ierr);
if ((ksp->pc_side == PC_LEFT) && agmres->r && agmres->DeflPrecond) {
ierr = KSPDGMRESApplyDeflation_DGMRES(ksp, VEC_V(0), VEC_TMP);CHKERRQ(ierr);
ierr = VecCopy(VEC_TMP, VEC_V(0));CHKERRQ(ierr);
agmres->matvecs += 1;
}
ierr = VecNormalize(VEC_V(0),&(ksp->rnorm));CHKERRQ(ierr);
KSPCheckNorm(ksp,ksp->rnorm);
res_old = ksp->rnorm; /* Record the residual norm to test if deflation is needed */
ksp->ops->buildsolution = KSPBuildSolution_AGMRES;
ierr = KSPAGMRESCycle(&its,ksp);CHKERRQ(ierr);
if (ksp->its >= ksp->max_it) {
if (!ksp->reason) ksp->reason = KSP_DIVERGED_ITS;
break;
}
/* compute the eigenvectors to augment the subspace : use an adaptive strategy */
res = ksp->rnorm;
if (!ksp->reason && agmres->neig > 0) {
test = agmres->max_k * PetscLogReal(ksp->rtol/res) / PetscLogReal(res/res_old); /* estimate the remaining number of steps */
if ((test > agmres->smv*(ksp->max_it-ksp->its)) || agmres->force) {
if (!agmres->force && ((test > agmres->bgv*(ksp->max_it-ksp->its)) && ((agmres->r + 1) < agmres->max_neig))) {
agmres->neig += 1; /* Augment the number of eigenvalues to deflate if the convergence is too slow */
}
ierr = KSPDGMRESComputeDeflationData_DGMRES(ksp,&agmres->neig);CHKERRQ(ierr);
}
}
ksp->guess_zero = PETSC_FALSE; /* every future call to KSPInitialResidual() will have nonzero guess */
}
ksp->guess_zero = guess_zero; /* restore if user has provided nonzero initial guess */
PetscFunctionReturn(0);
}
PetscErrorCode FormPsiAndExactSoln(DM da) {
ObsCtx *user;
PetscErrorCode ierr;
DMDALocalInfo info;
PetscInt i,j;
DM coordDA;
Vec coordinates;
DMDACoor2d **coords;
PetscReal **psi, **uexact, r;
const PetscReal afree = 0.69797, A = 0.68026, B = 0.47152;
PetscFunctionBeginUser;
ierr = DMGetApplicationContext(da,&user);CHKERRQ(ierr);
ierr = DMDAGetLocalInfo(da,&info); CHKERRQ(ierr);
ierr = DMGetCoordinateDM(da, &coordDA);CHKERRQ(ierr);
ierr = DMGetCoordinates(da, &coordinates);CHKERRQ(ierr);
ierr = DMDAVecGetArray(coordDA, coordinates, &coords);CHKERRQ(ierr);
ierr = DMDAVecGetArray(da, user->psi, &psi);CHKERRQ(ierr);
ierr = DMDAVecGetArray(da, user->uexact, &uexact);CHKERRQ(ierr);
for (j=info.ys; j<info.ys+info.ym; j++) {
for (i=info.xs; i<info.xs+info.xm; i++) {
r = PetscSqrtReal(pow(coords[j][i].x,2) + pow(coords[j][i].y,2));
if (r <= 1.0) psi[j][i] = PetscSqrtReal(1.0 - r * r);
else psi[j][i] = -1.0;
if (r <= afree) uexact[j][i] = psi[j][i]; /* on the obstacle */
else uexact[j][i] = - A * PetscLogReal(r) + B; /* solves the laplace eqn */
}
}
ierr = DMDAVecRestoreArray(da, user->psi, &psi);CHKERRQ(ierr);
ierr = DMDAVecRestoreArray(da, user->uexact, &uexact);CHKERRQ(ierr);
ierr = DMDAVecRestoreArray(coordDA, coordinates, &coords);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
PetscErrorCode stdNormalArray(PetscReal *eps, PetscInt numdim, PetscRandom ran)
{
PetscInt i;
PetscScalar u1,u2;
PetscReal t;
PetscErrorCode ierr;
PetscFunctionBegin;
for (i=0; i<numdim; i+=2) {
ierr = PetscRandomGetValue(ran,&u1);CHKERRQ(ierr);
ierr = PetscRandomGetValue(ran,&u2);CHKERRQ(ierr);
t = PetscSqrtReal(-2*PetscLogReal(PetscRealPart(u1)));
eps[i] = t * PetscCosReal(2*PETSC_PI*PetscRealPart(u2));
eps[i+1] = t * PetscSinReal(2*PETSC_PI*PetscRealPart(u2));
}
PetscFunctionReturn(0);
}
//FORMPSI
PetscErrorCode FormPsiAndInitialGuess(DM da,Vec U0,PetscBool feasible, ObsCtx *user)
{
PetscErrorCode ierr;
PetscInt i,j;
PetscReal **psi, **u0, **uexact,
x, y, r,
pi = PETSC_PI, afree = 0.69797, A = 0.68026, B = 0.47152;
DMDALocalInfo info;
PetscFunctionBeginUser;
ierr = DMDAGetLocalInfo(da,&info); CHKERRQ(ierr);
ierr = DMDAVecGetArray(da, user->psi, &psi);CHKERRQ(ierr);
ierr = DMDAVecGetArray(da, U0, &u0);CHKERRQ(ierr);
ierr = DMDAVecGetArray(da, user->g, &uexact);CHKERRQ(ierr);
for (j=info.ys; j<info.ys+info.ym; j++) {
y = -2.0 + j * user->dy;
for (i=info.xs; i<info.xs+info.xm; i++) {
x = -2.0 + i * user->dx;
r = PetscSqrtReal(x * x + y * y);
if (r <= 1.0)
psi[j][i] = PetscSqrtReal(1.0 - r * r);
else
psi[j][i] = -1.0;
if (r <= afree)
uexact[j][i] = psi[j][i]; /* on the obstacle */
else
uexact[j][i] = - A * PetscLogReal(r) + B; /* solves the laplace eqn */
if (feasible) {
if (i == 0 || j == 0 || i == info.mx-1 || j == info.my-1)
u0[j][i] = uexact[j][i];
else
u0[j][i] = uexact[j][i] + PetscCosReal(pi*x/4.0)*PetscCosReal(pi*y/4.0);
} else
u0[j][i] = 0.;
}
}
ierr = DMDAVecRestoreArray(da, user->psi, &psi);CHKERRQ(ierr);
ierr = DMDAVecRestoreArray(da, U0, &u0);CHKERRQ(ierr);
ierr = DMDAVecRestoreArray(da, user->g, &uexact);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
/*
PEPBuildDiagonalScaling - compute two diagonal matrices to be applied for balancing
in polynomial eigenproblems.
*/
PetscErrorCode PEPBuildDiagonalScaling(PEP pep)
{
PetscErrorCode ierr;
PetscInt it,i,j,k,nmat,nr,e,nz,lst,lend,nc=0,*cols,emax,emin,emaxl,eminl;
const PetscInt *cidx,*ridx;
Mat M,*T,A;
PetscMPIInt n;
PetscBool cont=PETSC_TRUE,flg=PETSC_FALSE;
PetscScalar *array,*Dr,*Dl,t;
PetscReal l2,d,*rsum,*aux,*csum,w=1.0;
MatStructure str;
MatInfo info;
PetscFunctionBegin;
l2 = 2*PetscLogReal(2.0);
nmat = pep->nmat;
ierr = PetscMPIIntCast(pep->n,&n);
ierr = STGetMatStructure(pep->st,&str);CHKERRQ(ierr);
ierr = PetscMalloc1(nmat,&T);CHKERRQ(ierr);
for (k=0;k<nmat;k++) {
ierr = STGetTOperators(pep->st,k,&T[k]);CHKERRQ(ierr);
}
/* Form local auxiliar matrix M */
ierr = PetscObjectTypeCompareAny((PetscObject)T[0],&cont,MATMPIAIJ,MATSEQAIJ);CHKERRQ(ierr);
if (!cont) SETERRQ(PetscObjectComm((PetscObject)T[0]),PETSC_ERR_SUP,"Only for MPIAIJ or SEQAIJ matrix types");
ierr = PetscObjectTypeCompare((PetscObject)T[0],MATMPIAIJ,&cont);CHKERRQ(ierr);
if (cont) {
ierr = MatMPIAIJGetLocalMat(T[0],MAT_INITIAL_MATRIX,&M);CHKERRQ(ierr);
flg = PETSC_TRUE;
} else {
ierr = MatDuplicate(T[0],MAT_COPY_VALUES,&M);CHKERRQ(ierr);
}
ierr = MatGetInfo(M,MAT_LOCAL,&info);CHKERRQ(ierr);
nz = info.nz_used;
ierr = MatSeqAIJGetArray(M,&array);CHKERRQ(ierr);
for (i=0;i<nz;i++) {
t = PetscAbsScalar(array[i]);
array[i] = t*t;
}
ierr = MatSeqAIJRestoreArray(M,&array);CHKERRQ(ierr);
for (k=1;k<nmat;k++) {
if (flg) {
ierr = MatMPIAIJGetLocalMat(T[k],MAT_INITIAL_MATRIX,&A);CHKERRQ(ierr);
} else {
if (str==SAME_NONZERO_PATTERN) {
ierr = MatCopy(T[k],A,SAME_NONZERO_PATTERN);CHKERRQ(ierr);
} else {
ierr = MatDuplicate(T[k],MAT_COPY_VALUES,&A);CHKERRQ(ierr);
}
}
ierr = MatGetInfo(A,MAT_LOCAL,&info);CHKERRQ(ierr);
nz = info.nz_used;
ierr = MatSeqAIJGetArray(A,&array);CHKERRQ(ierr);
for (i=0;i<nz;i++) {
t = PetscAbsScalar(array[i]);
array[i] = t*t;
}
ierr = MatSeqAIJRestoreArray(A,&array);CHKERRQ(ierr);
w *= pep->slambda*pep->slambda*pep->sfactor;
ierr = MatAXPY(M,w,A,str);CHKERRQ(ierr);
if (flg || str!=SAME_NONZERO_PATTERN || k==nmat-2) {
ierr = MatDestroy(&A);CHKERRQ(ierr);
}
}
ierr = MatGetRowIJ(M,0,PETSC_FALSE,PETSC_FALSE,&nr,&ridx,&cidx,&cont);CHKERRQ(ierr);
if (!cont) SETERRQ(PetscObjectComm((PetscObject)T[0]), PETSC_ERR_SUP,"It is not possible to compute scaling diagonals for these PEP matrices");
ierr = MatGetInfo(M,MAT_LOCAL,&info);CHKERRQ(ierr);
nz = info.nz_used;
ierr = VecGetOwnershipRange(pep->Dl,&lst,&lend);CHKERRQ(ierr);
ierr = PetscMalloc4(nr,&rsum,pep->n,&csum,pep->n,&aux,PetscMin(pep->n-lend+lst,nz),&cols);CHKERRQ(ierr);
ierr = VecSet(pep->Dr,1.0);CHKERRQ(ierr);
ierr = VecSet(pep->Dl,1.0);CHKERRQ(ierr);
ierr = VecGetArray(pep->Dl,&Dl);CHKERRQ(ierr);
ierr = VecGetArray(pep->Dr,&Dr);CHKERRQ(ierr);
ierr = MatSeqAIJGetArray(M,&array);CHKERRQ(ierr);
ierr = PetscMemzero(aux,pep->n*sizeof(PetscReal));CHKERRQ(ierr);
for (j=0;j<nz;j++) {
/* Search non-zero columns outsize lst-lend */
if (aux[cidx[j]]==0 && (cidx[j]<lst || lend<=cidx[j])) cols[nc++] = cidx[j];
/* Local column sums */
aux[cidx[j]] += PetscAbsScalar(array[j]);
}
for (it=0;it<pep->sits && cont;it++) {
emaxl = 0; eminl = 0;
/* Column sum */
if (it>0) { /* it=0 has been already done*/
ierr = MatSeqAIJGetArray(M,&array);CHKERRQ(ierr);
ierr = PetscMemzero(aux,pep->n*sizeof(PetscReal));CHKERRQ(ierr);
for (j=0;j<nz;j++) aux[cidx[j]] += PetscAbsScalar(array[j]);
ierr = MatSeqAIJRestoreArray(M,&array);CHKERRQ(ierr);
}
ierr = MPI_Allreduce(aux,csum,n,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)pep->Dr));
/* Update Dr */
for (j=lst;j<lend;j++) {
d = PetscLogReal(csum[j])/l2;
e = -(PetscInt)((d < 0)?(d-0.5):(d+0.5));
d = PetscPowReal(2.0,e);
Dr[j-lst] *= d;
aux[j] = d*d;
emaxl = PetscMax(emaxl,e);
eminl = PetscMin(eminl,e);
}
for (j=0;j<nc;j++) {
d = PetscLogReal(csum[cols[j]])/l2;
e = -(PetscInt)((d < 0)?(d-0.5):(d+0.5));
d = PetscPowReal(2.0,e);
aux[cols[j]] = d*d;
emaxl = PetscMax(emaxl,e);
eminl = PetscMin(eminl,e);
}
/* Scale M */
ierr = MatSeqAIJGetArray(M,&array);CHKERRQ(ierr);
for (j=0;j<nz;j++) {
array[j] *= aux[cidx[j]];
}
ierr = MatSeqAIJRestoreArray(M,&array);CHKERRQ(ierr);
/* Row sum */
ierr = PetscMemzero(rsum,nr*sizeof(PetscReal));CHKERRQ(ierr);
ierr = MatSeqAIJGetArray(M,&array);CHKERRQ(ierr);
for (i=0;i<nr;i++) {
for (j=ridx[i];j<ridx[i+1];j++) rsum[i] += PetscAbsScalar(array[j]);
/* Update Dl */
d = PetscLogReal(rsum[i])/l2;
e = -(PetscInt)((d < 0)?(d-0.5):(d+0.5));
d = PetscPowReal(2.0,e);
Dl[i] *= d;
/* Scale M */
for (j=ridx[i];j<ridx[i+1];j++) array[j] *= d*d;
emaxl = PetscMax(emaxl,e);
eminl = PetscMin(eminl,e);
}
ierr = MatSeqAIJRestoreArray(M,&array);CHKERRQ(ierr);
/* Compute global max and min */
ierr = MPI_Allreduce(&emaxl,&emax,1,MPIU_INT,MPIU_MAX,PetscObjectComm((PetscObject)pep->Dl));
ierr = MPI_Allreduce(&eminl,&emin,1,MPIU_INT,MPIU_MIN,PetscObjectComm((PetscObject)pep->Dl));
if (emax<=emin+2) cont = PETSC_FALSE;
}
ierr = VecRestoreArray(pep->Dr,&Dr);CHKERRQ(ierr);
ierr = VecRestoreArray(pep->Dl,&Dl);CHKERRQ(ierr);
/* Free memory*/
ierr = MatDestroy(&M);CHKERRQ(ierr);
ierr = PetscFree4(rsum,csum,aux,cols);CHKERRQ(ierr);
ierr = PetscFree(T);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
int main(int Argc,char **Args)
{
PetscBool flg;
PetscInt n = -6;
PetscScalar rho = 1.0;
PetscReal h;
PetscReal beta = 1.0;
DM da;
PetscRandom rctx;
PetscMPIInt comm_size;
Mat H,HtH;
PetscInt x, y, xs, ys, xm, ym;
PetscReal r1, r2;
PetscScalar uxy1, uxy2;
MatStencil sxy, sxy_m;
PetscScalar val, valconj;
Vec b, Htb,xvec;
KSP kspmg;
PC pcmg;
PetscErrorCode ierr;
PetscInt ix[1] = {0};
PetscScalar vals[1] = {1.0};
PetscInitialize(&Argc,&Args,(char*)0,help);
ierr = PetscOptionsGetInt(NULL,"-size",&n,&flg);CHKERRQ(ierr);
ierr = PetscOptionsGetReal(NULL,"-beta",&beta,&flg);CHKERRQ(ierr);
ierr = PetscOptionsGetScalar(NULL,"-rho",&rho,&flg);CHKERRQ(ierr);
/* Set the fudge parameters, we scale the whole thing by 1/(2*h) later */
h = 1.;
rho *= 1./(2.*h);
/* Geometry info */
ierr = DMDACreate2d(PETSC_COMM_WORLD, DMDA_BOUNDARY_PERIODIC,DMDA_BOUNDARY_PERIODIC, DMDA_STENCIL_STAR, n, n,
PETSC_DECIDE, PETSC_DECIDE, 2 /* this is the # of dof's */,
1, NULL, NULL, &da);CHKERRQ(ierr);
/* Random numbers */
ierr = PetscRandomCreate(PETSC_COMM_WORLD,&rctx);CHKERRQ(ierr);
ierr = PetscRandomSetFromOptions(rctx);CHKERRQ(ierr);
/* Single or multi processor ? */
ierr = MPI_Comm_size(PETSC_COMM_WORLD,&comm_size);CHKERRQ(ierr);
/* construct matrix */
ierr = DMSetMatType(da,MATAIJ);CHKERRQ(ierr);
ierr = DMCreateMatrix(da, &H);CHKERRQ(ierr);
/* get local corners for this processor */
ierr = DMDAGetCorners(da,&xs,&ys,0,&xm,&ym,0);CHKERRQ(ierr);
/* Assemble the matrix */
for (x=xs; x<xs+xm; x++) {
for (y=ys; y<ys+ym; y++) {
/* each lattice point sets only the *forward* pointing parameters (right, down),
i.e. Nabla_1^+ and Nabla_2^+.
In this way we can use only local random number creation. That means
we also have to set the corresponding backward pointing entries. */
/* Compute some normally distributed random numbers via Box-Muller */
ierr = PetscRandomGetValueReal(rctx, &r1);CHKERRQ(ierr);
r1 = 1.-r1; /* to change from [0,1) to (0,1], which we need for the log */
ierr = PetscRandomGetValueReal(rctx, &r2);CHKERRQ(ierr);
PetscReal R = PetscSqrtReal(-2.*PetscLogReal(r1));
PetscReal c = PetscCosReal(2.*PETSC_PI*r2);
PetscReal s = PetscSinReal(2.*PETSC_PI*r2);
/* use those to set the field */
uxy1 = PetscExpScalar(((PetscScalar) (R*c/beta))*PETSC_i);
uxy2 = PetscExpScalar(((PetscScalar) (R*s/beta))*PETSC_i);
sxy.i = x; sxy.j = y; /* the point where we are */
/* center action */
sxy.c = 0; /* spin 0, 0 */
ierr = MatSetValuesStencil(H, 1, &sxy, 1, &sxy, &rho, ADD_VALUES);CHKERRQ(ierr);
sxy.c = 1; /* spin 1, 1 */
val = -rho;
ierr = MatSetValuesStencil(H, 1, &sxy, 1, &sxy, &val, ADD_VALUES);CHKERRQ(ierr);
sxy_m.i = x+1; sxy_m.j = y; /* right action */
sxy.c = 0; sxy_m.c = 0; /* spin 0, 0 */
val = -uxy1; valconj = PetscConj(val);
ierr = MatSetValuesStencil(H, 1, &sxy_m, 1, &sxy, &val, ADD_VALUES);CHKERRQ(ierr);
ierr = MatSetValuesStencil(H, 1, &sxy, 1, &sxy_m, &valconj, ADD_VALUES);CHKERRQ(ierr);
sxy.c = 0; sxy_m.c = 1; /* spin 0, 1 */
val = -uxy1; valconj = PetscConj(val);
ierr = MatSetValuesStencil(H, 1, &sxy_m, 1, &sxy, &val, ADD_VALUES);CHKERRQ(ierr);
ierr = MatSetValuesStencil(H, 1, &sxy, 1, &sxy_m, &valconj, ADD_VALUES);CHKERRQ(ierr);
sxy.c = 1; sxy_m.c = 0; /* spin 1, 0 */
val = uxy1; valconj = PetscConj(val);
ierr = MatSetValuesStencil(H, 1, &sxy_m, 1, &sxy, &val, ADD_VALUES);CHKERRQ(ierr);
ierr = MatSetValuesStencil(H, 1, &sxy, 1, &sxy_m, &valconj, ADD_VALUES);CHKERRQ(ierr);
sxy.c = 1; sxy_m.c = 1; /* spin 1, 1 */
val = uxy1; valconj = PetscConj(val);
ierr = MatSetValuesStencil(H, 1, &sxy_m, 1, &sxy, &val, ADD_VALUES);CHKERRQ(ierr);
ierr = MatSetValuesStencil(H, 1, &sxy, 1, &sxy_m, &valconj, ADD_VALUES);CHKERRQ(ierr);
sxy_m.i = x; sxy_m.j = y+1; /* down action */
sxy.c = 0; sxy_m.c = 0; /* spin 0, 0 */
val = -uxy2; valconj = PetscConj(val);
ierr = MatSetValuesStencil(H, 1, &sxy_m, 1, &sxy, &val, ADD_VALUES);CHKERRQ(ierr);
ierr = MatSetValuesStencil(H, 1, &sxy, 1, &sxy_m, &valconj, ADD_VALUES);CHKERRQ(ierr);
sxy.c = 0; sxy_m.c = 1; /* spin 0, 1 */
val = -PETSC_i*uxy2; valconj = PetscConj(val);
ierr = MatSetValuesStencil(H, 1, &sxy_m, 1, &sxy, &val, ADD_VALUES);CHKERRQ(ierr);
ierr = MatSetValuesStencil(H, 1, &sxy, 1, &sxy_m, &valconj, ADD_VALUES);CHKERRQ(ierr);
sxy.c = 1; sxy_m.c = 0; /* spin 1, 0 */
val = -PETSC_i*uxy2; valconj = PetscConj(val);
ierr = MatSetValuesStencil(H, 1, &sxy_m, 1, &sxy, &val, ADD_VALUES);CHKERRQ(ierr);
ierr = MatSetValuesStencil(H, 1, &sxy, 1, &sxy_m, &valconj, ADD_VALUES);CHKERRQ(ierr);
sxy.c = 1; sxy_m.c = 1; /* spin 1, 1 */
val = PetscConj(uxy2); valconj = PetscConj(val);
ierr = MatSetValuesStencil(H, 1, &sxy_m, 1, &sxy, &val, ADD_VALUES);CHKERRQ(ierr);
ierr = MatSetValuesStencil(H, 1, &sxy, 1, &sxy_m, &valconj, ADD_VALUES);CHKERRQ(ierr);
}
}
ierr = MatAssemblyBegin(H, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
ierr = MatAssemblyEnd(H, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
/* scale H */
ierr = MatScale(H, 1./(2.*h));CHKERRQ(ierr);
/* it looks like H is Hermetian */
/* construct normal equations */
ierr = MatMatMult(H, H, MAT_INITIAL_MATRIX, 1., &HtH);CHKERRQ(ierr);
/* permutation matrix to check whether H and HtH are identical to the ones in the paper */
/* Mat perm; */
/* ierr = DMCreateMatrix(da, &perm);CHKERRQ(ierr); */
/* PetscInt row, col; */
/* PetscScalar one = 1.0; */
/* for (PetscInt i=0; i<n; i++) { */
/* for (PetscInt j=0; j<n; j++) { */
/* row = (i*n+j)*2; col = i*n+j; */
/* ierr = MatSetValues(perm, 1, &row, 1, &col, &one, INSERT_VALUES);CHKERRQ(ierr); */
/* row = (i*n+j)*2+1; col = i*n+j + n*n; */
/* ierr = MatSetValues(perm, 1, &row, 1, &col, &one, INSERT_VALUES);CHKERRQ(ierr); */
/* } */
/* } */
/* ierr = MatAssemblyBegin(perm, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); */
/* ierr = MatAssemblyEnd(perm, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); */
/* Mat Hperm; */
/* ierr = MatPtAP(H, perm, MAT_INITIAL_MATRIX, 1.0, &Hperm);CHKERRQ(ierr); */
/* ierr = PetscPrintf(PETSC_COMM_WORLD, "Matrix H after construction\n");CHKERRQ(ierr); */
/* ierr = MatView(Hperm, PETSC_VIEWER_STDOUT_(PETSC_COMM_WORLD));CHKERRQ(ierr); */
/* Mat HtHperm; */
/* ierr = MatPtAP(HtH, perm, MAT_INITIAL_MATRIX, 1.0, &HtHperm);CHKERRQ(ierr); */
/* ierr = PetscPrintf(PETSC_COMM_WORLD, "Matrix HtH:\n");CHKERRQ(ierr); */
/* ierr = MatView(HtHperm, PETSC_VIEWER_STDOUT_(PETSC_COMM_WORLD));CHKERRQ(ierr); */
/* right hand side */
ierr = DMCreateGlobalVector(da, &b);CHKERRQ(ierr);
ierr = VecSet(b,0.0);CHKERRQ(ierr);
ierr = VecSetValues(b, 1, ix, vals, INSERT_VALUES);CHKERRQ(ierr);
ierr = VecAssemblyBegin(b);CHKERRQ(ierr);
ierr = VecAssemblyEnd(b);CHKERRQ(ierr);
/* ierr = VecSetRandom(b, rctx);CHKERRQ(ierr); */
ierr = VecDuplicate(b, &Htb);CHKERRQ(ierr);
ierr = MatMultTranspose(H, b, Htb);CHKERRQ(ierr);
/* construct solver */
ierr = KSPCreate(PETSC_COMM_WORLD,&kspmg);CHKERRQ(ierr);
ierr = KSPSetType(kspmg, KSPCG);CHKERRQ(ierr);
ierr = KSPGetPC(kspmg,&pcmg);CHKERRQ(ierr);
ierr = PCSetType(pcmg,PCASA);CHKERRQ(ierr);
/* maybe user wants to override some of the choices */
ierr = KSPSetFromOptions(kspmg);CHKERRQ(ierr);
ierr = KSPSetOperators(kspmg, HtH, HtH, DIFFERENT_NONZERO_PATTERN);CHKERRQ(ierr);
ierr = DMDASetRefinementFactor(da, 3, 3, 3);CHKERRQ(ierr);
ierr = PCSetDM(pcmg,da);CHKERRQ(ierr);
ierr = PCASASetTolerances(pcmg, 1.e-6, 1.e-10,PETSC_DEFAULT,PETSC_DEFAULT);CHKERRQ(ierr);
ierr = VecDuplicate(b, &xvec);CHKERRQ(ierr);
ierr = VecSet(xvec, 0.0);CHKERRQ(ierr);
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Solve the linear system
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
ierr = KSPSolve(kspmg, Htb, xvec);CHKERRQ(ierr);
/* ierr = VecView(xvec, PETSC_VIEWER_STDOUT_(PETSC_COMM_WORLD));CHKERRQ(ierr); */
ierr = KSPDestroy(&kspmg);CHKERRQ(ierr);
ierr = VecDestroy(&xvec);CHKERRQ(ierr);
/* seems to be destroyed by KSPDestroy */
ierr = VecDestroy(&b);CHKERRQ(ierr);
ierr = VecDestroy(&Htb);CHKERRQ(ierr);
ierr = MatDestroy(&HtH);CHKERRQ(ierr);
ierr = MatDestroy(&H);CHKERRQ(ierr);
ierr = DMDestroy(&da);CHKERRQ(ierr);
ierr = PetscRandomDestroy(&rctx);CHKERRQ(ierr);
ierr = PetscFinalize();
return 0;
}
int main(int argc,char **argv)
{
PetscDrawLG lg;
PetscErrorCode ierr;
PetscInt Mx = 100,i;
PetscReal x,hx = .1/Mx,pause,xx[3],yy[3];
PetscDraw draw;
const char *const legend[] = {"(1 - u^2)^2","1 - u^2","-(1 - u)log(1 - u)"};
PetscDrawAxis axis;
PetscDrawViewPorts *ports;
PetscFunctionBegin;
ierr = PetscInitialize(&argc,&argv,0,help);if (ierr) return ierr;
ierr = PetscViewerDrawResize(PETSC_VIEWER_DRAW_(PETSC_COMM_WORLD),1200,800);CHKERRQ(ierr);
ierr = PetscViewerDrawGetDrawLG(PETSC_VIEWER_DRAW_(PETSC_COMM_WORLD),0,&lg);CHKERRQ(ierr);
ierr = PetscDrawLGGetDraw(lg,&draw);CHKERRQ(ierr);
ierr = PetscDrawCheckResizedWindow(draw);CHKERRQ(ierr);
ierr = PetscDrawViewPortsCreateRect(draw,1,2,&ports);CHKERRQ(ierr);
ierr = PetscDrawLGGetAxis(lg,&axis);CHKERRQ(ierr);
ierr = PetscDrawLGReset(lg);CHKERRQ(ierr);
/*
Plot the energies
*/
ierr = PetscDrawLGSetDimension(lg,3);CHKERRQ(ierr);
ierr = PetscDrawViewPortsSet(ports,1);CHKERRQ(ierr);
x = .9;
for (i=0; i<Mx; i++) {
xx[0] = xx[1] = xx[2] = x;
yy[0] = (1.-x*x)*(1. - x*x);
yy[1] = (1. - x*x);
yy[2] = -(1.-x)*PetscLogReal(1.-x);
ierr = PetscDrawLGAddPoint(lg,xx,yy);CHKERRQ(ierr);
x += hx;
}
ierr = PetscDrawGetPause(draw,&pause);CHKERRQ(ierr);
ierr = PetscDrawSetPause(draw,0.0);CHKERRQ(ierr);
ierr = PetscDrawAxisSetLabels(axis,"Energy","","");CHKERRQ(ierr);
ierr = PetscDrawLGSetLegend(lg,legend);CHKERRQ(ierr);
ierr = PetscDrawLGDraw(lg);CHKERRQ(ierr);
/*
Plot the forces
*/
ierr = PetscDrawViewPortsSet(ports,0);CHKERRQ(ierr);
ierr = PetscDrawLGReset(lg);CHKERRQ(ierr);
x = .9;
for (i=0; i<Mx; i++) {
xx[0] = xx[1] = xx[2] = x;
yy[0] = x*x*x - x;
yy[1] = -x;
yy[2] = 1.0 + PetscLogReal(1. - x);
ierr = PetscDrawLGAddPoint(lg,xx,yy);CHKERRQ(ierr);
x += hx;
}
ierr = PetscDrawAxisSetLabels(axis,"Derivative","","");CHKERRQ(ierr);
ierr = PetscDrawLGSetLegend(lg,NULL);CHKERRQ(ierr);
ierr = PetscDrawLGDraw(lg);CHKERRQ(ierr);
ierr = PetscDrawSetPause(draw,pause);CHKERRQ(ierr);
ierr = PetscDrawPause(draw);CHKERRQ(ierr);
ierr = PetscDrawViewPortsDestroy(ports);CHKERRQ(ierr);
ierr = PetscFinalize();
return ierr;
}
static void func9(PetscReal x, PetscReal *val)
{
*val = PetscLogReal(PetscCosReal(x));
}
static void func8(PetscReal x, PetscReal *val)
{
*val = PetscLogReal(x)*PetscLogReal(x);
}
PetscErrorCode DSFunction_EXP_NHEP_PADE(DS ds)
{
#if defined(PETSC_MISSING_LAPACK_GESV) || defined(SLEPC_MISSING_LAPACK_LANGE)
PetscFunctionBegin;
SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GESV/LANGE - Lapack routines are unavailable");
#else
PetscErrorCode ierr;
PetscBLASInt n,ld,ld2,*ipiv,info,inc=1;
PetscInt j,k,odd;
const PetscInt p=MAX_PADE;
PetscReal c[MAX_PADE+1],s;
PetscScalar scale,mone=-1.0,one=1.0,two=2.0,zero=0.0;
PetscScalar *A,*A2,*Q,*P,*W,*aux;
PetscFunctionBegin;
ierr = PetscBLASIntCast(ds->n,&n);CHKERRQ(ierr);
ierr = PetscBLASIntCast(ds->ld,&ld);CHKERRQ(ierr);
ld2 = ld*ld;
ierr = DSAllocateWork_Private(ds,0,ld,ld);CHKERRQ(ierr);
ipiv = ds->iwork;
if (!ds->mat[DS_MAT_W]) { ierr = DSAllocateMat_Private(ds,DS_MAT_W);CHKERRQ(ierr); }
if (!ds->mat[DS_MAT_Z]) { ierr = DSAllocateMat_Private(ds,DS_MAT_Z);CHKERRQ(ierr); }
A = ds->mat[DS_MAT_A];
A2 = ds->mat[DS_MAT_Z];
Q = ds->mat[DS_MAT_Q];
P = ds->mat[DS_MAT_F];
W = ds->mat[DS_MAT_W];
/* Pade' coefficients */
c[0] = 1.0;
for (k=1;k<=p;k++) {
c[k] = c[k-1]*(p+1-k)/(k*(2*p+1-k));
}
/* Scaling */
s = LAPACKlange_("I",&n,&n,A,&ld,ds->rwork);
if (s>0.5) {
s = PetscMax(0,(int)(PetscLogReal(s)/PetscLogReal(2.0)) + 2);
scale = PetscPowReal(2.0,(-1)*s);
PetscStackCallBLAS("BLASscal",BLASscal_(&ld2,&scale,A,&inc));
}
/* Horner evaluation */
PetscStackCallBLAS("BLASgemm",BLASgemm_("N","N",&n,&n,&n,&one,A,&ld,A,&ld,&zero,A2,&ld));
ierr = PetscMemzero(Q,ld*ld*sizeof(PetscScalar));CHKERRQ(ierr);
ierr = PetscMemzero(P,ld*ld*sizeof(PetscScalar));CHKERRQ(ierr);
for (j=0;j<n;j++) {
Q[j+j*ld] = c[p];
P[j+j*ld] = c[p-1];
}
odd = 1;
for (k=p-1;k>0;k--) {
if (odd==1) {
PetscStackCallBLAS("BLASgemm",BLASgemm_("N","N",&n,&n,&n,&one,Q,&ld,A2,&ld,&zero,W,&ld));
aux = Q;
Q = W;
W = aux;
for (j=0;j<n;j++)
Q[j+j*ld] = Q[j+j*ld] + c[k-1];
} else {
PetscStackCallBLAS("BLASgemm",BLASgemm_("N","N",&n,&n,&n,&one,P,&ld,A2,&ld,&zero,W,&ld));
aux = P;
P = W;
W = aux;
for (j=0;j<n;j++)
P[j+j*ld] = P[j+j*ld] + c[k-1];
}
odd = 1-odd;
}
if (odd==1) {
PetscStackCallBLAS("BLASgemm",BLASgemm_("N","N",&n,&n,&n,&one,Q,&ld,A,&ld,&zero,W,&ld));
aux = Q;
Q = W;
W = aux;
PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&ld2,&mone,P,&inc,Q,&inc));
PetscStackCallBLAS("LAPACKgesv",LAPACKgesv_(&n,&n,Q,&ld,ipiv,P,&ld,&info));
PetscStackCallBLAS("BLASscal",BLASscal_(&ld2,&two,P,&inc));
for (j=0;j<n;j++)
P[j+j*ld] = P[j+j*ld] + 1.0;
PetscStackCallBLAS("BLASscal",BLASscal_(&ld2,&mone,P,&inc));
} else {
PetscStackCallBLAS("BLASgemm",BLASgemm_("N","N",&n,&n,&n,&one,P,&ld,A,&ld,&zero,W,&ld));
aux = P;
P = W;
W = aux;
PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&ld2,&mone,P,&inc,Q,&inc));
PetscStackCallBLAS("LAPACKgesv",LAPACKgesv_(&n,&n,Q,&ld,ipiv,P,&ld,&info));
PetscStackCallBLAS("BLASscal",BLASscal_(&ld2,&two,P,&inc));
for (j=0;j<n;j++)
P[j+j*ld] = P[j+j*ld] + 1.0;
}
for (k=1;k<=s;k++) {
PetscStackCallBLAS("BLASgemm",BLASgemm_("N","N",&n,&n,&n,&one,P,&ld,P,&ld,&zero,W,&ld));
ierr = PetscMemcpy(P,W,ld2*sizeof(PetscScalar));CHKERRQ(ierr);
}
if (P!=ds->mat[DS_MAT_F]) {
ierr = PetscMemcpy(ds->mat[DS_MAT_F],P,ld2*sizeof(PetscScalar));CHKERRQ(ierr);
}
PetscFunctionReturn(0);
#endif
}
static void func8(PetscReal x, PetscReal *val)
{
if (x == 0.0) *val = PETSC_INFINITY;
else *val = PetscLogReal(x)*PetscLogReal(x);
}
static void func5(PetscReal x, PetscReal *val)
{
if (x == 0.0) *val = 0.0;
else *val = PetscSqrtReal(x)*PetscLogReal(x);
}
/*
FormFunction - Evaluates nonlinear function, F(x).
Input Parameters:
. ts - the TS context
. X - input vector
. ptr - optional user-defined context, as set by SNESSetFunction()
Output Parameter:
. F - function vector
*/
PetscErrorCode FormFunction(TS ts,PetscReal ftime,Vec X,Vec Xdot,Vec F,void *ptr)
{
DM da;
PetscErrorCode ierr;
PetscInt i,Mx,xs,xm;
PetscReal hx,sx;
Field *x,*xdot,*f;
Vec localX,localXdot;
UserCtx *ctx = (UserCtx*)ptr;
PetscFunctionBegin;
ierr = TSGetDM(ts,&da);CHKERRQ(ierr);
ierr = DMGetLocalVector(da,&localX);CHKERRQ(ierr);
ierr = DMGetLocalVector(da,&localXdot);CHKERRQ(ierr);
ierr = DMDAGetInfo(da,PETSC_IGNORE,&Mx,PETSC_IGNORE,PETSC_IGNORE,PETSC_IGNORE,PETSC_IGNORE,
PETSC_IGNORE,PETSC_IGNORE,PETSC_IGNORE,PETSC_IGNORE,PETSC_IGNORE,PETSC_IGNORE,PETSC_IGNORE);
hx = 1.0/(PetscReal)Mx; sx = 1.0/(hx*hx);
/*
Scatter ghost points to local vector,using the 2-step process
DMGlobalToLocalBegin(),DMGlobalToLocalEnd().
By placing code between these two statements, computations can be
done while messages are in transition.
*/
ierr = DMGlobalToLocalBegin(da,X,INSERT_VALUES,localX);CHKERRQ(ierr);
ierr = DMGlobalToLocalEnd(da,X,INSERT_VALUES,localX);CHKERRQ(ierr);
ierr = DMGlobalToLocalBegin(da,Xdot,INSERT_VALUES,localXdot);CHKERRQ(ierr);
ierr = DMGlobalToLocalEnd(da,Xdot,INSERT_VALUES,localXdot);CHKERRQ(ierr);
/*
Get pointers to vector data
*/
ierr = DMDAVecGetArrayRead(da,localX,&x);CHKERRQ(ierr);
ierr = DMDAVecGetArrayRead(da,localXdot,&xdot);CHKERRQ(ierr);
ierr = DMDAVecGetArray(da,F,&f);CHKERRQ(ierr);
/*
Get local grid boundaries
*/
ierr = DMDAGetCorners(da,&xs,NULL,NULL,&xm,NULL,NULL);CHKERRQ(ierr);
/*
Compute function over the locally owned part of the grid
*/
for (i=xs; i<xs+xm; i++) {
f[i].w = x[i].w + ctx->kappa*(x[i-1].u + x[i+1].u - 2.0*x[i].u)*sx;
if (ctx->cahnhillard) {
switch (ctx->energy) {
case 1: /* double well */
f[i].w += -x[i].u*x[i].u*x[i].u + x[i].u;
break;
case 2: /* double obstacle */
f[i].w += x[i].u;
break;
case 3: /* logarithmic */
if (PetscRealPart(x[i].u) < -1.0 + 2.0*ctx->tol) f[i].w += .5*ctx->theta*(-PetscLogReal(ctx->tol) + PetscLogScalar((1.0-x[i].u)/2.0)) + ctx->theta_c*x[i].u;
else if (PetscRealPart(x[i].u) > 1.0 - 2.0*ctx->tol) f[i].w += .5*ctx->theta*(-PetscLogScalar((1.0+x[i].u)/2.0) + PetscLogReal(ctx->tol)) + ctx->theta_c*x[i].u;
else f[i].w += .5*ctx->theta*(-PetscLogScalar((1.0+x[i].u)/2.0) + PetscLogScalar((1.0-x[i].u)/2.0)) + ctx->theta_c*x[i].u;
break;
}
}
f[i].u = xdot[i].u - (x[i-1].w + x[i+1].w - 2.0*x[i].w)*sx;
}
/*
Restore vectors
*/
ierr = DMDAVecRestoreArrayRead(da,localXdot,&xdot);CHKERRQ(ierr);
ierr = DMDAVecRestoreArrayRead(da,localX,&x);CHKERRQ(ierr);
ierr = DMDAVecRestoreArray(da,F,&f);CHKERRQ(ierr);
ierr = DMRestoreLocalVector(da,&localX);CHKERRQ(ierr);
ierr = DMRestoreLocalVector(da,&localXdot);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
