static PetscErrorCode TSStep_Alpha(TS ts)
{
TS_Alpha *th = (TS_Alpha*)ts->data;
PetscInt its,lits,reject;
PetscReal next_time_step;
SNESConvergedReason snesreason = SNES_CONVERGED_ITERATING;
PetscErrorCode ierr;
PetscFunctionBegin;
if (ts->steps == 0) {
ierr = VecSet(th->V0,0.0);CHKERRQ(ierr);
} else {
ierr = VecCopy(th->V1,th->V0);CHKERRQ(ierr);
}
ierr = VecCopy(ts->vec_sol,th->X0);CHKERRQ(ierr);
next_time_step = ts->time_step;
for (reject=0; reject<ts->max_reject; reject++,ts->reject++) {
ts->time_step = next_time_step;
th->stage_time = ts->ptime + th->Alpha_f*ts->time_step;
th->shift = th->Alpha_m/(th->Alpha_f*th->Gamma*ts->time_step);
ierr = TSPreStep(ts);CHKERRQ(ierr);
ierr = TSPreStage(ts,th->stage_time);CHKERRQ(ierr);
/* predictor */
ierr = VecCopy(th->X0,th->X1);CHKERRQ(ierr);
/* solve R(X,V) = 0 */
ierr = SNESSolve(ts->snes,PETSC_NULL,th->X1);CHKERRQ(ierr);
/* V1 = (1-1/Gamma)*V0 + 1/(Gamma*dT)*(X1-X0) */
ierr = VecWAXPY(th->V1,-1,th->X0,th->X1);CHKERRQ(ierr);
ierr = VecAXPBY(th->V1,1-1/th->Gamma,1/(th->Gamma*ts->time_step),th->V0);CHKERRQ(ierr);
/* nonlinear solve convergence */
ierr = SNESGetConvergedReason(ts->snes,&snesreason);CHKERRQ(ierr);
if (snesreason < 0 && !th->adapt) break;
ierr = SNESGetIterationNumber(ts->snes,&its);CHKERRQ(ierr);
ierr = SNESGetLinearSolveIterations(ts->snes,&lits);CHKERRQ(ierr);
ts->snes_its += its; ts->ksp_its += lits;
ierr = PetscInfo3(ts,"step=%D, nonlinear solve iterations=%D, linear solve iterations=%D\n",ts->steps,its,lits);CHKERRQ(ierr);
/* time step adaptativity */
if (!th->adapt) break;
else {
PetscReal t1 = ts->ptime + ts->time_step;
PetscBool stepok = (reject==0) ? PETSC_TRUE : PETSC_FALSE;
ierr = th->adapt(ts,t1,th->X1,th->V1,&next_time_step,&stepok,th->adaptctx);CHKERRQ(ierr);
ierr = PetscInfo5(ts,"Step %D (t=%G,dt=%G) %s, next dt=%G\n",ts->steps,ts->ptime,ts->time_step,stepok?"accepted":"rejected",next_time_step);CHKERRQ(ierr);
if (stepok) break;
}
}
if (snesreason < 0 && ts->max_snes_failures > 0 && ++ts->num_snes_failures >= ts->max_snes_failures) {
ts->reason = TS_DIVERGED_NONLINEAR_SOLVE;
ierr = PetscInfo2(ts,"Step=%D, nonlinear solve solve failures %D greater than current TS allowed, stopping solve\n",ts->steps,ts->num_snes_failures);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
if (reject >= ts->max_reject) {
ts->reason = TS_DIVERGED_STEP_REJECTED;
ierr = PetscInfo2(ts,"Step=%D, step rejections %D greater than current TS allowed, stopping solve\n",ts->steps,reject);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
ierr = VecCopy(th->X1,ts->vec_sol);CHKERRQ(ierr);
ts->ptime += ts->time_step;
ts->time_step = next_time_step;
ts->steps++;
PetscFunctionReturn(0);
}
static PetscErrorCode SNESLineSearchApply_BT(SNESLineSearch linesearch)
{
PetscBool changed_y,changed_w;
PetscErrorCode ierr;
Vec X,F,Y,W,G;
SNES snes;
PetscReal fnorm, xnorm, ynorm, gnorm;
PetscReal lambda,lambdatemp,lambdaprev,minlambda,maxstep,initslope,alpha,stol;
PetscReal t1,t2,a,b,d;
PetscReal f;
PetscReal g,gprev;
PetscBool domainerror;
PetscViewer monitor;
PetscInt max_its,count;
SNESLineSearch_BT *bt;
Mat jac;
PetscErrorCode (*objective)(SNES,Vec,PetscReal*,void*);
PetscFunctionBegin;
ierr = SNESLineSearchGetVecs(linesearch, &X, &F, &Y, &W, &G);CHKERRQ(ierr);
ierr = SNESLineSearchGetNorms(linesearch, &xnorm, &fnorm, &ynorm);CHKERRQ(ierr);
ierr = SNESLineSearchGetLambda(linesearch, &lambda);CHKERRQ(ierr);
ierr = SNESLineSearchGetSNES(linesearch, &snes);CHKERRQ(ierr);
ierr = SNESLineSearchGetMonitor(linesearch, &monitor);CHKERRQ(ierr);
ierr = SNESLineSearchGetTolerances(linesearch,&minlambda,&maxstep,NULL,NULL,NULL,&max_its);CHKERRQ(ierr);
ierr = SNESGetTolerances(snes,NULL,NULL,&stol,NULL,NULL);CHKERRQ(ierr);
ierr = SNESGetObjective(snes,&objective,NULL);CHKERRQ(ierr);
bt = (SNESLineSearch_BT*)linesearch->data;
alpha = bt->alpha;
ierr = SNESGetJacobian(snes, &jac, NULL, NULL, NULL);CHKERRQ(ierr);
if (!jac && !objective) SETERRQ(PetscObjectComm((PetscObject)linesearch), PETSC_ERR_USER, "SNESLineSearchBT requires a Jacobian matrix");
/* precheck */
ierr = SNESLineSearchPreCheck(linesearch,X,Y,&changed_y);CHKERRQ(ierr);
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_TRUE);CHKERRQ(ierr);
ierr = VecNormBegin(Y, NORM_2, &ynorm);CHKERRQ(ierr);
ierr = VecNormBegin(X, NORM_2, &xnorm);CHKERRQ(ierr);
ierr = VecNormEnd(Y, NORM_2, &ynorm);CHKERRQ(ierr);
ierr = VecNormEnd(X, NORM_2, &xnorm);CHKERRQ(ierr);
if (ynorm == 0.0) {
if (monitor) {
ierr = PetscViewerASCIIAddTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
ierr = PetscViewerASCIIPrintf(monitor," Line search: Initial direction and size is 0\n");CHKERRQ(ierr);
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
}
ierr = VecCopy(X,W);CHKERRQ(ierr);
ierr = VecCopy(F,G);CHKERRQ(ierr);
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_FALSE);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
if (ynorm > maxstep) { /* Step too big, so scale back */
if (monitor) {
ierr = PetscViewerASCIIAddTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
ierr = PetscViewerASCIIPrintf(monitor," Line search: Scaling step by %14.12e old ynorm %14.12e\n", (double)(maxstep/ynorm),(double)ynorm);CHKERRQ(ierr);
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
}
ierr = VecScale(Y,maxstep/(ynorm));CHKERRQ(ierr);
ynorm = maxstep;
}
/* if the SNES has an objective set, use that instead of the function value */
if (objective) {
ierr = SNESComputeObjective(snes,X,&f);CHKERRQ(ierr);
} else {
f = fnorm*fnorm;
}
/* compute the initial slope */
if (objective) {
/* slope comes from the function (assumed to be the gradient of the objective */
ierr = VecDotRealPart(Y,F,&initslope);CHKERRQ(ierr);
} else {
/* slope comes from the normal equations */
ierr = MatMult(jac,Y,W);CHKERRQ(ierr);
ierr = VecDotRealPart(F,W,&initslope);CHKERRQ(ierr);
if (initslope > 0.0) initslope = -initslope;
if (initslope == 0.0) initslope = -1.0;
}
ierr = VecWAXPY(W,-lambda,Y,X);CHKERRQ(ierr);
if (linesearch->ops->viproject) {
ierr = (*linesearch->ops->viproject)(snes, W);CHKERRQ(ierr);
}
if (snes->nfuncs >= snes->max_funcs) {
ierr = PetscInfo(snes,"Exceeded maximum function evaluations, while checking full step length!\n");CHKERRQ(ierr);
snes->reason = SNES_DIVERGED_FUNCTION_COUNT;
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_FALSE);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
if (objective) {
ierr = SNESComputeObjective(snes,W,&g);CHKERRQ(ierr);
} else {
ierr = (*linesearch->ops->snesfunc)(snes,W,G);CHKERRQ(ierr);
ierr = SNESGetFunctionDomainError(snes, &domainerror);CHKERRQ(ierr);
if (domainerror) {
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_FALSE);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
if (linesearch->ops->vinorm) {
gnorm = fnorm;
ierr = (*linesearch->ops->vinorm)(snes, G, W, &gnorm);CHKERRQ(ierr);
} else {
ierr = VecNorm(G,NORM_2,&gnorm);CHKERRQ(ierr);
}
g = PetscSqr(gnorm);
}
if (PetscIsInfOrNanReal(g)) {
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_FALSE);CHKERRQ(ierr);
ierr = PetscInfo(monitor,"Aborted due to Nan or Inf in function evaluation\n");CHKERRQ(ierr);
PetscFunctionReturn(0);
}
if (!objective) {
ierr = PetscInfo2(snes,"Initial fnorm %14.12e gnorm %14.12e\n", (double)fnorm, (double)gnorm);CHKERRQ(ierr);
}
if (.5*g <= .5*f + lambda*alpha*initslope) { /* Sufficient reduction or step tolerance convergence */
if (monitor) {
ierr = PetscViewerASCIIAddTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
if (!objective) {
ierr = PetscViewerASCIIPrintf(monitor," Line search: Using full step: fnorm %14.12e gnorm %14.12e\n", (double)fnorm, (double)gnorm);CHKERRQ(ierr);
} else {
ierr = PetscViewerASCIIPrintf(monitor," Line search: Using full step: obj0 %14.12e obj %14.12e\n", (double)f, (double)g);CHKERRQ(ierr);
}
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
}
} else {
/* Since the full step didn't work and the step is tiny, quit */
if (stol*xnorm > ynorm) {
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_FALSE);CHKERRQ(ierr);
ierr = PetscInfo2(monitor,"Aborted due to ynorm < stol*xnorm (%14.12e < %14.12e) and inadequate full step.\n",ynorm,stol*xnorm);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
/* Fit points with quadratic */
lambdatemp = -initslope/(g - f - 2.0*lambda*initslope);
lambdaprev = lambda;
gprev = g;
if (lambdatemp > .5*lambda) lambdatemp = .5*lambda;
if (lambdatemp <= .1*lambda) lambda = .1*lambda;
else lambda = lambdatemp;
ierr = VecWAXPY(W,-lambda,Y,X);CHKERRQ(ierr);
if (linesearch->ops->viproject) {
ierr = (*linesearch->ops->viproject)(snes, W);CHKERRQ(ierr);
}
if (snes->nfuncs >= snes->max_funcs) {
ierr = PetscInfo1(snes,"Exceeded maximum function evaluations, while attempting quadratic backtracking! %D \n",snes->nfuncs);CHKERRQ(ierr);
snes->reason = SNES_DIVERGED_FUNCTION_COUNT;
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_FALSE);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
if (objective) {
ierr = SNESComputeObjective(snes,W,&g);CHKERRQ(ierr);
} else {
ierr = (*linesearch->ops->snesfunc)(snes,W,G);CHKERRQ(ierr);
ierr = SNESGetFunctionDomainError(snes, &domainerror);CHKERRQ(ierr);
if (domainerror) PetscFunctionReturn(0);
if (linesearch->ops->vinorm) {
gnorm = fnorm;
ierr = (*linesearch->ops->vinorm)(snes, G, W, &gnorm);CHKERRQ(ierr);
} else {
ierr = VecNorm(G,NORM_2,&gnorm);CHKERRQ(ierr);
g = gnorm*gnorm;
}
}
if (PetscIsInfOrNanReal(g)) {
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_FALSE);CHKERRQ(ierr);
ierr = PetscInfo(monitor,"Aborted due to Nan or Inf in function evaluation\n");CHKERRQ(ierr);
PetscFunctionReturn(0);
}
if (monitor) {
ierr = PetscViewerASCIIAddTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
if (!objective) {
ierr = PetscViewerASCIIPrintf(monitor," Line search: gnorm after quadratic fit %14.12e\n",(double)gnorm);CHKERRQ(ierr);
} else {
ierr = PetscViewerASCIIPrintf(monitor," Line search: obj after quadratic fit %14.12e\n",(double)g);CHKERRQ(ierr);
}
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
}
if (.5*g < .5*f + lambda*alpha*initslope) { /* sufficient reduction */
if (monitor) {
ierr = PetscViewerASCIIAddTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
ierr = PetscViewerASCIIPrintf(monitor," Line search: Quadratically determined step, lambda=%18.16e\n",(double)lambda);CHKERRQ(ierr);
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
}
} else {
/* Fit points with cubic */
for (count = 0; count < max_its; count++) {
if (lambda <= minlambda) {
if (monitor) {
ierr = PetscViewerASCIIAddTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
ierr = PetscViewerASCIIPrintf(monitor," Line search: unable to find good step length! After %D tries \n",count);CHKERRQ(ierr);
if (!objective) {
ierr = PetscViewerASCIIPrintf(monitor,
" Line search: fnorm=%18.16e, gnorm=%18.16e, ynorm=%18.16e, minlambda=%18.16e, lambda=%18.16e, initial slope=%18.16e\n",
(double)fnorm, (double)gnorm, (double)ynorm, (double)minlambda, (double)lambda, (double)initslope);CHKERRQ(ierr);
} else {
ierr = PetscViewerASCIIPrintf(monitor,
" Line search: obj(0)=%18.16e, obj=%18.16e, ynorm=%18.16e, minlambda=%18.16e, lambda=%18.16e, initial slope=%18.16e\n",
(double)f, (double)g, (double)ynorm, (double)minlambda, (double)lambda, (double)initslope);CHKERRQ(ierr);
}
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
}
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_FALSE);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
if (linesearch->order == SNES_LINESEARCH_ORDER_CUBIC) {
t1 = .5*(g - f) - lambda*initslope;
t2 = .5*(gprev - f) - lambdaprev*initslope;
a = (t1/(lambda*lambda) - t2/(lambdaprev*lambdaprev))/(lambda-lambdaprev);
b = (-lambdaprev*t1/(lambda*lambda) + lambda*t2/(lambdaprev*lambdaprev))/(lambda-lambdaprev);
d = b*b - 3*a*initslope;
if (d < 0.0) d = 0.0;
if (a == 0.0) lambdatemp = -initslope/(2.0*b);
else lambdatemp = (-b + PetscSqrtReal(d))/(3.0*a);
} else if (linesearch->order == SNES_LINESEARCH_ORDER_QUADRATIC) {
lambdatemp = -initslope/(g - f - 2.0*initslope);
} else SETERRQ(PetscObjectComm((PetscObject)linesearch), PETSC_ERR_SUP, "unsupported line search order for type bt");
lambdaprev = lambda;
gprev = g;
if (lambdatemp > .5*lambda) lambdatemp = .5*lambda;
if (lambdatemp <= .1*lambda) lambda = .1*lambda;
else lambda = lambdatemp;
ierr = VecWAXPY(W,-lambda,Y,X);CHKERRQ(ierr);
if (linesearch->ops->viproject) {
ierr = (*linesearch->ops->viproject)(snes,W);CHKERRQ(ierr);
}
if (snes->nfuncs >= snes->max_funcs) {
ierr = PetscInfo1(snes,"Exceeded maximum function evaluations, while looking for good step length! %D \n",count);CHKERRQ(ierr);
if (!objective) {
ierr = PetscInfo5(snes,"fnorm=%18.16e, gnorm=%18.16e, ynorm=%18.16e, lambda=%18.16e, initial slope=%18.16e\n",
(double)fnorm,(double)gnorm,(double)ynorm,(double)lambda,(double)initslope);CHKERRQ(ierr);
}
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_FALSE);CHKERRQ(ierr);
snes->reason = SNES_DIVERGED_FUNCTION_COUNT;
PetscFunctionReturn(0);
}
if (objective) {
ierr = SNESComputeObjective(snes,W,&g);CHKERRQ(ierr);
} else {
ierr = (*linesearch->ops->snesfunc)(snes,W,G);CHKERRQ(ierr);
ierr = SNESGetFunctionDomainError(snes, &domainerror);CHKERRQ(ierr);
if (domainerror) {
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_FALSE);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
if (linesearch->ops->vinorm) {
gnorm = fnorm;
ierr = (*linesearch->ops->vinorm)(snes, G, W, &gnorm);CHKERRQ(ierr);
} else {
ierr = VecNorm(G,NORM_2,&gnorm);CHKERRQ(ierr);
g = gnorm*gnorm;
}
}
if (PetscIsInfOrNanReal(gnorm)) {
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_FALSE);CHKERRQ(ierr);
ierr = PetscInfo(monitor,"Aborted due to Nan or Inf in function evaluation\n");CHKERRQ(ierr);
PetscFunctionReturn(0);
}
if (.5*g < .5*f + lambda*alpha*initslope) { /* is reduction enough? */
if (monitor) {
ierr = PetscViewerASCIIAddTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
if (!objective) {
if (linesearch->order == SNES_LINESEARCH_ORDER_CUBIC) {
ierr = PetscViewerASCIIPrintf(monitor," Line search: Cubically determined step, current gnorm %14.12e lambda=%18.16e\n",(double)gnorm,(double)lambda);CHKERRQ(ierr);
} else {
ierr = PetscViewerASCIIPrintf(monitor," Line search: Quadratically determined step, current gnorm %14.12e lambda=%18.16e\n",(double)gnorm,(double)lambda);CHKERRQ(ierr);
}
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
} else {
if (linesearch->order == SNES_LINESEARCH_ORDER_CUBIC) {
ierr = PetscViewerASCIIPrintf(monitor," Line search: Cubically determined step, obj %14.12e lambda=%18.16e\n",(double)g,(double)lambda);CHKERRQ(ierr);
} else {
ierr = PetscViewerASCIIPrintf(monitor," Line search: Quadratically determined step, obj %14.12e lambda=%18.16e\n",(double)g,(double)lambda);CHKERRQ(ierr);
}
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
}
}
break;
} else if (monitor) {
ierr = PetscViewerASCIIAddTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
if (!objective) {
if (linesearch->order == SNES_LINESEARCH_ORDER_CUBIC) {
ierr = PetscViewerASCIIPrintf(monitor," Line search: Cubic step no good, shrinking lambda, current gnorm %12.12e lambda=%18.16e\n",(double)gnorm,(double)lambda);CHKERRQ(ierr);
} else {
ierr = PetscViewerASCIIPrintf(monitor," Line search: Quadratic step no good, shrinking lambda, current gnorm %12.12e lambda=%18.16e\n",(double)gnorm,(double)lambda);CHKERRQ(ierr);
}
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
} else {
if (linesearch->order == SNES_LINESEARCH_ORDER_CUBIC) {
ierr = PetscViewerASCIIPrintf(monitor," Line search: Cubic step no good, shrinking lambda, obj %12.12e lambda=%18.16e\n",(double)g,(double)lambda);CHKERRQ(ierr);
} else {
ierr = PetscViewerASCIIPrintf(monitor," Line search: Quadratic step no good, shrinking lambda, obj %12.12e lambda=%18.16e\n",(double)g,(double)lambda);CHKERRQ(ierr);
}
ierr = PetscViewerASCIISubtractTab(monitor,((PetscObject)linesearch)->tablevel);CHKERRQ(ierr);
}
}
}
}
}
/* postcheck */
ierr = SNESLineSearchPostCheck(linesearch,X,Y,W,&changed_y,&changed_w);CHKERRQ(ierr);
if (changed_y) {
ierr = VecWAXPY(W,-lambda,Y,X);CHKERRQ(ierr);
if (linesearch->ops->viproject) {
ierr = (*linesearch->ops->viproject)(snes, W);CHKERRQ(ierr);
}
}
if (changed_y || changed_w || objective) { /* recompute the function norm if the step has changed or the objective isn't the norm */
ierr = (*linesearch->ops->snesfunc)(snes,W,G);CHKERRQ(ierr);
ierr = SNESGetFunctionDomainError(snes, &domainerror);CHKERRQ(ierr);
if (domainerror) {
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_FALSE);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
if (linesearch->ops->vinorm) {
gnorm = fnorm;
ierr = (*linesearch->ops->vinorm)(snes, G, W, &gnorm);CHKERRQ(ierr);
} else {
ierr = VecNorm(G,NORM_2,&gnorm);CHKERRQ(ierr);
}
ierr = VecNorm(Y,NORM_2,&ynorm);CHKERRQ(ierr);
if (PetscIsInfOrNanReal(gnorm)) {
ierr = SNESLineSearchSetSuccess(linesearch, PETSC_FALSE);CHKERRQ(ierr);
ierr = PetscInfo(monitor,"Aborted due to Nan or Inf in function evaluation\n");CHKERRQ(ierr);
PetscFunctionReturn(0);
}
}
/* copy the solution over */
ierr = VecCopy(W, X);CHKERRQ(ierr);
ierr = VecCopy(G, F);CHKERRQ(ierr);
ierr = VecNorm(X, NORM_2, &xnorm);CHKERRQ(ierr);
ierr = SNESLineSearchSetLambda(linesearch, lambda);CHKERRQ(ierr);
ierr = SNESLineSearchSetNorms(linesearch, xnorm, gnorm, ynorm);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
PetscErrorCode SNESDiffParameterCompute_More(SNES snes,void *nePv,Vec x,Vec p,double *fnoise,double *hopt)
{
DIFFPAR_MORE *neP = (DIFFPAR_MORE*)nePv;
Vec w, xp, fvec; /* work vectors to use in computing h */
double zero = 0.0, hl, hu, h, fnoise_s, fder2_s;
PetscScalar alpha;
PetscScalar fval[7], tab[7][7], eps[7], f = -1;
double rerrf = -1., fder2;
PetscErrorCode ierr;
PetscInt iter, k, i, j, info;
PetscInt nf = 7; /* number of function evaluations */
PetscInt fcount;
MPI_Comm comm;
FILE *fp;
PetscBool noise_test = PETSC_FALSE;
PetscFunctionBegin;
ierr = PetscObjectGetComm((PetscObject)snes,&comm);CHKERRQ(ierr);
/* Call to SNESSetUp() just to set data structures in SNES context */
if (!snes->setupcalled) {ierr = SNESSetUp(snes);CHKERRQ(ierr);}
w = neP->workv[0];
xp = neP->workv[1];
fvec = neP->workv[2];
fp = neP->fp;
/* Initialize parameters */
hl = zero;
hu = zero;
h = neP->h_first_try;
fnoise_s = zero;
fder2_s = zero;
fcount = neP->function_count;
/* We have 5 tries to attempt to compute a good hopt value */
ierr = SNESGetIterationNumber(snes,&i);CHKERRQ(ierr);
ierr = PetscFPrintf(comm,fp,"\n ------- SNES iteration %D ---------\n",i);CHKERRQ(ierr);
for (iter=0; iter<5; iter++) {
neP->h_first_try = h;
/* Compute the nf function values needed to estimate the noise from
the difference table */
for (k=0; k<nf; k++) {
alpha = h * (k+1 - (nf+1)/2);
ierr = VecWAXPY(xp,alpha,p,x);CHKERRQ(ierr);
ierr = SNESComputeFunction(snes,xp,fvec);CHKERRQ(ierr);
neP->function_count++;
ierr = VecDot(fvec,w,&fval[k]);CHKERRQ(ierr);
}
f = fval[(nf+1)/2 - 1];
/* Construct the difference table */
for (i=0; i<nf; i++) tab[i][0] = fval[i];
for (j=0; j<6; j++) {
for (i=0; i<nf-j; i++) {
tab[i][j+1] = tab[i+1][j] - tab[i][j];
}
}
/* Print the difference table */
ierr = PetscFPrintf(comm,fp,"Difference Table: iter = %D\n",iter);CHKERRQ(ierr);
for (i=0; i<nf; i++) {
for (j=0; j<nf-i; j++) {
ierr = PetscFPrintf(comm,fp," %10.2e ",tab[i][j]);CHKERRQ(ierr);
}
ierr = PetscFPrintf(comm,fp,"\n");CHKERRQ(ierr);
}
/* Call the noise estimator */
ierr = SNESNoise_dnest_(&nf,fval,&h,fnoise,&fder2,hopt,&info,eps);CHKERRQ(ierr);
/* Output statements */
rerrf = *fnoise/PetscAbsScalar(f);
if (info == 1) {ierr = PetscFPrintf(comm,fp,"%s\n","Noise detected");CHKERRQ(ierr);}
if (info == 2) {ierr = PetscFPrintf(comm,fp,"%s\n","Noise not detected; h is too small");CHKERRQ(ierr);}
if (info == 3) {ierr = PetscFPrintf(comm,fp,"%s\n","Noise not detected; h is too large");CHKERRQ(ierr);}
if (info == 4) {ierr = PetscFPrintf(comm,fp,"%s\n","Noise detected, but unreliable hopt");CHKERRQ(ierr);}
ierr = PetscFPrintf(comm,fp,"Approximate epsfcn %g %g %g %g %g %g\n",(double)eps[0],(double)eps[1],(double)eps[2],(double)eps[3],(double)eps[4],(double)eps[5]);CHKERRQ(ierr);
ierr = PetscFPrintf(comm,fp,"h = %g, fnoise = %g, fder2 = %g, rerrf = %g, hopt = %g\n\n",(double)h, (double)*fnoise, (double)fder2, (double)rerrf, (double)*hopt);CHKERRQ(ierr);
/* Save fnoise and fder2. */
if (*fnoise) fnoise_s = *fnoise;
if (fder2) fder2_s = fder2;
/* Check for noise detection. */
if (fnoise_s && fder2_s) {
*fnoise = fnoise_s;
fder2 = fder2_s;
*hopt = 1.68*sqrt(*fnoise/PetscAbsScalar(fder2));
goto theend;
} else {
/* Update hl and hu, and determine new h */
if (info == 2 || info == 4) {
hl = h;
if (hu == zero) h = 100*h;
else h = PetscMin(100*h,0.1*hu);
} else if (info == 3) {
hu = h;
h = PetscMax(1.0e-3,sqrt(hl/hu))*hu;
}
}
}
theend:
if (*fnoise < neP->fnoise_min) {
ierr = PetscFPrintf(comm,fp,"Resetting fnoise: fnoise1 = %g, fnoise_min = %g\n",(double)*fnoise,(double)neP->fnoise_min);CHKERRQ(ierr);
*fnoise = neP->fnoise_min;
neP->fnoise_resets++;
}
if (*hopt < neP->hopt_min) {
ierr = PetscFPrintf(comm,fp,"Resetting hopt: hopt1 = %g, hopt_min = %g\n",(double)*hopt,(double)neP->hopt_min);CHKERRQ(ierr);
*hopt = neP->hopt_min;
neP->hopt_resets++;
}
ierr = PetscFPrintf(comm,fp,"Errors in derivative:\n");CHKERRQ(ierr);
ierr = PetscFPrintf(comm,fp,"f = %g, fnoise = %g, fder2 = %g, hopt = %g\n",(double)f,(double)*fnoise,(double)fder2,(double)*hopt);CHKERRQ(ierr);
/* For now, compute h **each** MV Mult!! */
/*
ierr = PetscOptionsHasName(NULL,"-matrix_free_jorge_each_mvp",&flg);CHKERRQ(ierr);
if (!flg) {
Mat mat;
ierr = SNESGetJacobian(snes,&mat,NULL,NULL);CHKERRQ(ierr);
ierr = SNESDefaultMatrixFreeSetParameters2(mat,PETSC_DEFAULT,PETSC_DEFAULT,*hopt);CHKERRQ(ierr);
}
*/
fcount = neP->function_count - fcount;
ierr = PetscInfo5(snes,"fct_now = %D, fct_cum = %D, rerrf=%g, sqrt(noise)=%g, h_more=%g\n",fcount,neP->function_count,(double)rerrf,(double)PetscSqrtReal(*fnoise),(double)*hopt);CHKERRQ(ierr);
ierr = PetscOptionsGetBool(NULL,"-noise_test",&noise_test,NULL);CHKERRQ(ierr);
if (noise_test) {
ierr = JacMatMultCompare(snes,x,p,*hopt);CHKERRQ(ierr);
}
PetscFunctionReturn(0);
}
PetscErrorCode MatRARtSymbolic_SeqAIJ_SeqAIJ(Mat A,Mat R,PetscReal fill,Mat *C)
{
PetscErrorCode ierr;
Mat P;
PetscInt *rti,*rtj;
Mat_RARt *rart;
PetscContainer container;
MatTransposeColoring matcoloring;
ISColoring iscoloring;
Mat Rt_dense,RARt_dense;
PetscLogDouble GColor=0.0,MCCreate=0.0,MDenCreate=0.0,t0,tf,etime=0.0;
Mat_SeqAIJ *c;
PetscFunctionBegin;
ierr = PetscGetTime(&t0);CHKERRQ(ierr);
/* create symbolic P=Rt */
ierr = MatGetSymbolicTranspose_SeqAIJ(R,&rti,&rtj);CHKERRQ(ierr);
ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,R->cmap->n,R->rmap->n,rti,rtj,PETSC_NULL,&P);CHKERRQ(ierr);
/* get symbolic C=Pt*A*P */
ierr = MatPtAPSymbolic_SeqAIJ_SeqAIJ(A,P,fill,C);CHKERRQ(ierr);
(*C)->rmap->bs = R->rmap->bs;
(*C)->cmap->bs = R->rmap->bs;
/* create a supporting struct */
ierr = PetscNew(Mat_RARt,&rart);CHKERRQ(ierr);
/* attach the supporting struct to C */
ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr);
ierr = PetscContainerSetPointer(container,rart);CHKERRQ(ierr);
ierr = PetscContainerSetUserDestroy(container,PetscContainerDestroy_Mat_RARt);CHKERRQ(ierr);
ierr = PetscObjectCompose((PetscObject)(*C),"Mat_RARt",(PetscObject)container);CHKERRQ(ierr);
ierr = PetscContainerDestroy(&container);CHKERRQ(ierr);
ierr = PetscGetTime(&tf);CHKERRQ(ierr);
etime += tf - t0;
/* Create MatTransposeColoring from symbolic C=R*A*R^T */
c=(Mat_SeqAIJ*)(*C)->data;
ierr = PetscGetTime(&t0);CHKERRQ(ierr);
ierr = MatGetColoring(*C,MATCOLORINGLF,&iscoloring);CHKERRQ(ierr);
ierr = PetscGetTime(&tf);CHKERRQ(ierr);
GColor += tf - t0;
ierr = PetscGetTime(&t0);CHKERRQ(ierr);
ierr = MatTransposeColoringCreate(*C,iscoloring,&matcoloring);CHKERRQ(ierr);
rart->matcoloring = matcoloring;
ierr = ISColoringDestroy(&iscoloring);CHKERRQ(ierr);
ierr = PetscGetTime(&tf);CHKERRQ(ierr);
MCCreate += tf - t0;
ierr = PetscGetTime(&t0);CHKERRQ(ierr);
/* Create Rt_dense */
ierr = MatCreate(PETSC_COMM_SELF,&Rt_dense);CHKERRQ(ierr);
ierr = MatSetSizes(Rt_dense,A->cmap->n,matcoloring->ncolors,A->cmap->n,matcoloring->ncolors);CHKERRQ(ierr);
ierr = MatSetType(Rt_dense,MATSEQDENSE);CHKERRQ(ierr);
ierr = MatSeqDenseSetPreallocation(Rt_dense,PETSC_NULL);CHKERRQ(ierr);
Rt_dense->assembled = PETSC_TRUE;
rart->Rt = Rt_dense;
/* Create RARt_dense = R*A*Rt_dense */
ierr = MatCreate(PETSC_COMM_SELF,&RARt_dense);CHKERRQ(ierr);
ierr = MatSetSizes(RARt_dense,(*C)->rmap->n,matcoloring->ncolors,(*C)->rmap->n,matcoloring->ncolors);CHKERRQ(ierr);
ierr = MatSetType(RARt_dense,MATSEQDENSE);CHKERRQ(ierr);
ierr = MatSeqDenseSetPreallocation(RARt_dense,PETSC_NULL);CHKERRQ(ierr);
rart->RARt = RARt_dense;
/* Allocate work array to store columns of A*R^T used in MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqDense() */
ierr = PetscMalloc(A->rmap->n*4*sizeof(PetscScalar),&rart->work);CHKERRQ(ierr);
ierr = PetscGetTime(&tf);CHKERRQ(ierr);
MDenCreate += tf - t0;
rart->destroy = (*C)->ops->destroy;
(*C)->ops->destroy = MatDestroy_SeqAIJ_RARt;
/* clean up */
ierr = MatRestoreSymbolicTranspose_SeqAIJ(R,&rti,&rtj);CHKERRQ(ierr);
ierr = MatDestroy(&P);CHKERRQ(ierr);
#if defined(PETSC_USE_INFO)
{
PetscReal density= (PetscReal)(c->nz)/(RARt_dense->rmap->n*RARt_dense->cmap->n);
ierr = PetscInfo6(*C,"RARt_den %D %D; Rt_den %D %D, (RARt->nz %D)/(m*ncolors)=%g\n",RARt_dense->rmap->n,RARt_dense->cmap->n,Rt_dense->rmap->n,Rt_dense->cmap->n,c->nz,density);CHKERRQ(ierr);
ierr = PetscInfo5(*C,"Sym = GetColor %g + MColorCreate %g + MDenCreate %g + other %g = %g\n",GColor,MCCreate,MDenCreate,etime,GColor+MCCreate+MDenCreate+etime);CHKERRQ(ierr);
}
#endif
PetscFunctionReturn(0);
}
