PETSC_EXTERN void PETSC_STDCALL vecstepboundinfo_(Vec X,Vec DX,Vec XL,Vec XU,PetscReal *boundmin,PetscReal *wolfemin,PetscReal *boundmax, int *__ierr ){
*__ierr = VecStepBoundInfo(
(Vec)PetscToPointer((X) ),
(Vec)PetscToPointer((DX) ),
(Vec)PetscToPointer((XL) ),
(Vec)PetscToPointer((XU) ),boundmin,wolfemin,boundmax);
}
static PetscErrorCode TaoLineSearchApply_MT(TaoLineSearch ls, Vec x, PetscReal *f, Vec g, Vec s)
{
PetscErrorCode ierr;
TaoLineSearch_MT *mt;
PetscReal xtrapf = 4.0;
PetscReal finit, width, width1, dginit, fm, fxm, fym, dgm, dgxm, dgym;
PetscReal dgx, dgy, dg, dg2, fx, fy, stx, sty, dgtest;
PetscReal ftest1=0.0, ftest2=0.0;
PetscInt i, stage1,n1,n2,nn1,nn2;
PetscReal bstepmin1, bstepmin2, bstepmax;
PetscBool g_computed=PETSC_FALSE; /* to prevent extra gradient computation */
PetscFunctionBegin;
PetscValidHeaderSpecific(ls,TAOLINESEARCH_CLASSID,1);
PetscValidHeaderSpecific(x,VEC_CLASSID,2);
PetscValidScalarPointer(f,3);
PetscValidHeaderSpecific(g,VEC_CLASSID,4);
PetscValidHeaderSpecific(s,VEC_CLASSID,5);
/* comm,type,size checks are done in interface TaoLineSearchApply */
mt = (TaoLineSearch_MT*)(ls->data);
ls->reason = TAOLINESEARCH_CONTINUE_ITERATING;
/* Check work vector */
if (!mt->work) {
ierr = VecDuplicate(x,&mt->work);CHKERRQ(ierr);
mt->x = x;
ierr = PetscObjectReference((PetscObject)mt->x);CHKERRQ(ierr);
} else if (x != mt->x) {
ierr = VecDestroy(&mt->work);CHKERRQ(ierr);
ierr = VecDuplicate(x,&mt->work);CHKERRQ(ierr);
ierr = PetscObjectDereference((PetscObject)mt->x);CHKERRQ(ierr);
mt->x = x;
ierr = PetscObjectReference((PetscObject)mt->x);CHKERRQ(ierr);
}
if (ls->bounded) {
/* Compute step length needed to make all variables equal a bound */
/* Compute the smallest steplength that will make one nonbinding variable
equal the bound */
ierr = VecGetLocalSize(ls->upper,&n1);CHKERRQ(ierr);
ierr = VecGetLocalSize(mt->x, &n2);CHKERRQ(ierr);
ierr = VecGetSize(ls->upper,&nn1);CHKERRQ(ierr);
ierr = VecGetSize(mt->x,&nn2);CHKERRQ(ierr);
if (n1 != n2 || nn1 != nn2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Variable vector not compatible with bounds vector");
ierr = VecScale(s,-1.0);CHKERRQ(ierr);
ierr = VecBoundGradientProjection(s,x,ls->lower,ls->upper,s);CHKERRQ(ierr);
ierr = VecScale(s,-1.0);CHKERRQ(ierr);
ierr = VecStepBoundInfo(x,s,ls->lower,ls->upper,&bstepmin1,&bstepmin2,&bstepmax);CHKERRQ(ierr);
ls->stepmax = PetscMin(bstepmax,1.0e15);
}
ierr = VecDot(g,s,&dginit);CHKERRQ(ierr);
if (PetscIsInfOrNanReal(dginit)) {
ierr = PetscInfo1(ls,"Initial Line Search step * g is Inf or Nan (%g)\n",(double)dginit);CHKERRQ(ierr);
ls->reason=TAOLINESEARCH_FAILED_INFORNAN;
PetscFunctionReturn(0);
}
if (dginit >= 0.0) {
ierr = PetscInfo1(ls,"Initial Line Search step * g is not descent direction (%g)\n",(double)dginit);CHKERRQ(ierr);
ls->reason = TAOLINESEARCH_FAILED_ASCENT;
PetscFunctionReturn(0);
}
/* Initialization */
mt->bracket = 0;
stage1 = 1;
finit = *f;
dgtest = ls->ftol * dginit;
width = ls->stepmax - ls->stepmin;
width1 = width * 2.0;
ierr = VecCopy(x,mt->work);CHKERRQ(ierr);
/* Variable dictionary:
stx, fx, dgx - the step, function, and derivative at the best step
sty, fy, dgy - the step, function, and derivative at the other endpoint
of the interval of uncertainty
step, f, dg - the step, function, and derivative at the current step */
stx = 0.0;
fx = finit;
dgx = dginit;
sty = 0.0;
fy = finit;
dgy = dginit;
ls->step=ls->initstep;
for (i=0; i< ls->max_funcs; i++) {
/* Set min and max steps to correspond to the interval of uncertainty */
if (mt->bracket) {
ls->stepmin = PetscMin(stx,sty);
ls->stepmax = PetscMax(stx,sty);
} else {
ls->stepmin = stx;
ls->stepmax = ls->step + xtrapf * (ls->step - stx);
}
/* Force the step to be within the bounds */
ls->step = PetscMax(ls->step,ls->stepmin);
ls->step = PetscMin(ls->step,ls->stepmax);
/* If an unusual termination is to occur, then let step be the lowest
point obtained thus far */
if ((stx!=0) && (((mt->bracket) && (ls->step <= ls->stepmin || ls->step >= ls->stepmax)) || ((mt->bracket) && (ls->stepmax - ls->stepmin <= ls->rtol * ls->stepmax)) ||
((ls->nfeval+ls->nfgeval) >= ls->max_funcs - 1) || (mt->infoc == 0))) {
ls->step = stx;
}
ierr = VecCopy(x,mt->work);CHKERRQ(ierr);
ierr = VecAXPY(mt->work,ls->step,s);CHKERRQ(ierr); /* W = X + step*S */
if (ls->bounded) {
ierr = VecMedian(ls->lower, mt->work, ls->upper, mt->work);CHKERRQ(ierr);
}
if (ls->usegts) {
ierr = TaoLineSearchComputeObjectiveAndGTS(ls,mt->work,f,&dg);CHKERRQ(ierr);
g_computed=PETSC_FALSE;
} else {
ierr = TaoLineSearchComputeObjectiveAndGradient(ls,mt->work,f,g);CHKERRQ(ierr);
g_computed=PETSC_TRUE;
if (ls->bounded) {
ierr = VecDot(g,x,&dg);CHKERRQ(ierr);
ierr = VecDot(g,mt->work,&dg2);CHKERRQ(ierr);
dg = (dg2 - dg)/ls->step;
} else {
ierr = VecDot(g,s,&dg);CHKERRQ(ierr);
}
}
if (0 == i) {
ls->f_fullstep=*f;
}
if (PetscIsInfOrNanReal(*f) || PetscIsInfOrNanReal(dg)) {
/* User provided compute function generated Not-a-Number, assume
domain violation and set function value and directional
derivative to infinity. */
*f = PETSC_INFINITY;
dg = PETSC_INFINITY;
}
ftest1 = finit + ls->step * dgtest;
if (ls->bounded) {
ftest2 = finit + ls->step * dgtest * ls->ftol;
}
/* Convergence testing */
if (((*f - ftest1 <= 1.0e-10 * PetscAbsReal(finit)) && (PetscAbsReal(dg) + ls->gtol*dginit <= 0.0))) {
ierr = PetscInfo(ls, "Line search success: Sufficient decrease and directional deriv conditions hold\n");CHKERRQ(ierr);
ls->reason = TAOLINESEARCH_SUCCESS;
break;
}
/* Check Armijo if beyond the first breakpoint */
if (ls->bounded && (*f <= ftest2) && (ls->step >= bstepmin2)) {
ierr = PetscInfo(ls,"Line search success: Sufficient decrease.\n");CHKERRQ(ierr);
ls->reason = TAOLINESEARCH_SUCCESS;
break;
}
/* Checks for bad cases */
if (((mt->bracket) && (ls->step <= ls->stepmin||ls->step >= ls->stepmax)) || (!mt->infoc)) {
ierr = PetscInfo(ls,"Rounding errors may prevent further progress. May not be a step satisfying\n");CHKERRQ(ierr);
ierr = PetscInfo(ls,"sufficient decrease and curvature conditions. Tolerances may be too small.\n");CHKERRQ(ierr);
ls->reason = TAOLINESEARCH_HALTED_OTHER;
break;
}
if ((ls->step == ls->stepmax) && (*f <= ftest1) && (dg <= dgtest)) {
ierr = PetscInfo1(ls,"Step is at the upper bound, stepmax (%g)\n",(double)ls->stepmax);CHKERRQ(ierr);
ls->reason = TAOLINESEARCH_HALTED_UPPERBOUND;
break;
}
if ((ls->step == ls->stepmin) && (*f >= ftest1) && (dg >= dgtest)) {
ierr = PetscInfo1(ls,"Step is at the lower bound, stepmin (%g)\n",(double)ls->stepmin);CHKERRQ(ierr);
ls->reason = TAOLINESEARCH_HALTED_LOWERBOUND;
break;
}
if ((mt->bracket) && (ls->stepmax - ls->stepmin <= ls->rtol*ls->stepmax)){
ierr = PetscInfo1(ls,"Relative width of interval of uncertainty is at most rtol (%g)\n",(double)ls->rtol);CHKERRQ(ierr);
ls->reason = TAOLINESEARCH_HALTED_RTOL;
break;
}
/* In the first stage, we seek a step for which the modified function
has a nonpositive value and nonnegative derivative */
if ((stage1) && (*f <= ftest1) && (dg >= dginit * PetscMin(ls->ftol, ls->gtol))) {
stage1 = 0;
}
/* A modified function is used to predict the step only if we
have not obtained a step for which the modified function has a
nonpositive function value and nonnegative derivative, and if a
lower function value has been obtained but the decrease is not
sufficient */
if ((stage1) && (*f <= fx) && (*f > ftest1)) {
fm = *f - ls->step * dgtest; /* Define modified function */
fxm = fx - stx * dgtest; /* and derivatives */
fym = fy - sty * dgtest;
dgm = dg - dgtest;
dgxm = dgx - dgtest;
dgym = dgy - dgtest;
/* if (dgxm * (ls->step - stx) >= 0.0) */
/* Update the interval of uncertainty and compute the new step */
ierr = Tao_mcstep(ls,&stx,&fxm,&dgxm,&sty,&fym,&dgym,&ls->step,&fm,&dgm);CHKERRQ(ierr);
fx = fxm + stx * dgtest; /* Reset the function and */
fy = fym + sty * dgtest; /* gradient values */
dgx = dgxm + dgtest;
dgy = dgym + dgtest;
} else {
/* Update the interval of uncertainty and compute the new step */
ierr = Tao_mcstep(ls,&stx,&fx,&dgx,&sty,&fy,&dgy,&ls->step,f,&dg);CHKERRQ(ierr);
}
/* Force a sufficient decrease in the interval of uncertainty */
if (mt->bracket) {
if (PetscAbsReal(sty - stx) >= 0.66 * width1) ls->step = stx + 0.5*(sty - stx);
width1 = width;
width = PetscAbsReal(sty - stx);
}
}
if ((ls->nfeval+ls->nfgeval) > ls->max_funcs) {
ierr = PetscInfo2(ls,"Number of line search function evals (%D) > maximum (%D)\n",(ls->nfeval+ls->nfgeval),ls->max_funcs);CHKERRQ(ierr);
ls->reason = TAOLINESEARCH_HALTED_MAXFCN;
}
/* Finish computations */
ierr = PetscInfo2(ls,"%D function evals in line search, step = %g\n",(ls->nfeval+ls->nfgeval),(double)ls->step);CHKERRQ(ierr);
/* Set new solution vector and compute gradient if needed */
ierr = VecCopy(mt->work,x);CHKERRQ(ierr);
if (!g_computed) {
ierr = TaoLineSearchComputeGradient(ls,mt->work,g);CHKERRQ(ierr);
}
PetscFunctionReturn(0);
}
static PetscErrorCode TaoLineSearchApply_GPCG(TaoLineSearch ls, Vec x, PetscReal *f, Vec g, Vec s)
{
TaoLineSearch_GPCG *neP = (TaoLineSearch_GPCG *)ls->data;
PetscErrorCode ierr;
PetscInt i;
PetscBool g_computed=PETSC_FALSE; /* to prevent extra gradient computation */
PetscReal d1,finit,actred,prered,rho, gdx;
PetscFunctionBegin;
/* ls->stepmin - lower bound for step */
/* ls->stepmax - upper bound for step */
/* ls->rtol - relative tolerance for an acceptable step */
/* ls->ftol - tolerance for sufficient decrease condition */
/* ls->gtol - tolerance for curvature condition */
/* ls->nfeval - number of function evaluations */
/* ls->nfeval - number of function/gradient evaluations */
/* ls->max_funcs - maximum number of function evaluations */
ls->reason = TAOLINESEARCH_CONTINUE_ITERATING;
ls->step = ls->initstep;
if (!neP->W2) {
ierr = VecDuplicate(x,&neP->W2);CHKERRQ(ierr);
ierr = VecDuplicate(x,&neP->W1);CHKERRQ(ierr);
ierr = VecDuplicate(x,&neP->Gold);CHKERRQ(ierr);
neP->x = x;
ierr = PetscObjectReference((PetscObject)neP->x);CHKERRQ(ierr);
} else if (x != neP->x) {
ierr = VecDestroy(&neP->x);CHKERRQ(ierr);
ierr = VecDestroy(&neP->W1);CHKERRQ(ierr);
ierr = VecDestroy(&neP->W2);CHKERRQ(ierr);
ierr = VecDestroy(&neP->Gold);CHKERRQ(ierr);
ierr = VecDuplicate(x,&neP->W1);CHKERRQ(ierr);
ierr = VecDuplicate(x,&neP->W2);CHKERRQ(ierr);
ierr = VecDuplicate(x,&neP->Gold);CHKERRQ(ierr);
ierr = PetscObjectDereference((PetscObject)neP->x);CHKERRQ(ierr);
neP->x = x;
ierr = PetscObjectReference((PetscObject)neP->x);CHKERRQ(ierr);
}
ierr = VecDot(g,s,&gdx);CHKERRQ(ierr);
if (gdx > 0) {
ierr = PetscInfo1(ls,"Line search error: search direction is not descent direction. dot(g,s) = %g\n",(double)gdx);CHKERRQ(ierr);
ls->reason = TAOLINESEARCH_FAILED_ASCENT;
PetscFunctionReturn(0);
}
ierr = VecCopy(x,neP->W2);CHKERRQ(ierr);
ierr = VecCopy(g,neP->Gold);CHKERRQ(ierr);
if (ls->bounded) {
/* Compute the smallest steplength that will make one nonbinding variable equal the bound */
ierr = VecStepBoundInfo(x,s,ls->lower,ls->upper,&rho,&actred,&d1);CHKERRQ(ierr);
ls->step = PetscMin(ls->step,d1);
}
rho=0; actred=0;
if (ls->step < 0) {
ierr = PetscInfo1(ls,"Line search error: initial step parameter %g< 0\n",(double)ls->step);CHKERRQ(ierr);
ls->reason = TAOLINESEARCH_HALTED_OTHER;
PetscFunctionReturn(0);
}
/* Initialization */
finit = *f;
for (i=0; i< ls->max_funcs; i++) {
/* Force the step to be within the bounds */
ls->step = PetscMax(ls->step,ls->stepmin);
ls->step = PetscMin(ls->step,ls->stepmax);
ierr = VecCopy(x,neP->W2);CHKERRQ(ierr);
ierr = VecAXPY(neP->W2,ls->step,s);CHKERRQ(ierr);
if (ls->bounded) {
/* Make sure new vector is numerically within bounds */
ierr = VecMedian(neP->W2,ls->lower,ls->upper,neP->W2);CHKERRQ(ierr);
}
/* Gradient is not needed here. Unless there is a separate
gradient routine, compute it here anyway to prevent recomputing at
the end of the line search */
if (ls->hasobjective) {
ierr = TaoLineSearchComputeObjective(ls,neP->W2,f);CHKERRQ(ierr);
g_computed=PETSC_FALSE;
} else if (ls->usegts){
ierr = TaoLineSearchComputeObjectiveAndGTS(ls,neP->W2,f,&gdx);CHKERRQ(ierr);
g_computed=PETSC_FALSE;
} else {
ierr = TaoLineSearchComputeObjectiveAndGradient(ls,neP->W2,f,g);CHKERRQ(ierr);
g_computed=PETSC_TRUE;
}
if (0 == i) {
ls->f_fullstep = *f;
}
actred = *f - finit;
ierr = VecCopy(neP->W2,neP->W1);CHKERRQ(ierr);
ierr = VecAXPY(neP->W1,-1.0,x);CHKERRQ(ierr); /* W1 = W2 - X */
ierr = VecDot(neP->W1,neP->Gold,&prered);CHKERRQ(ierr);
if (fabs(prered)<1.0e-100) prered=1.0e-12;
rho = actred/prered;
/*
If sufficient progress has been obtained, accept the
point. Otherwise, backtrack.
*/
if (actred > 0) {
ierr = PetscInfo(ls,"Step resulted in ascent, rejecting.\n");CHKERRQ(ierr);
ls->step = (ls->step)/2;
} else if (rho > ls->ftol){
break;
} else{
ls->step = (ls->step)/2;
}
/* Convergence testing */
if (ls->step <= ls->stepmin || ls->step >= ls->stepmax) {
ls->reason = TAOLINESEARCH_HALTED_OTHER;
ierr = PetscInfo(ls,"Rounding errors may prevent further progress. May not be a step satisfying\n");CHKERRQ(ierr);
ierr = PetscInfo(ls,"sufficient decrease and curvature conditions. Tolerances may be too small.\n");CHKERRQ(ierr);
break;
}
if (ls->step == ls->stepmax) {
ierr = PetscInfo1(ls,"Step is at the upper bound, stepmax (%g)\n",(double)ls->stepmax);CHKERRQ(ierr);
ls->reason = TAOLINESEARCH_HALTED_UPPERBOUND;
break;
}
if (ls->step == ls->stepmin) {
ierr = PetscInfo1(ls,"Step is at the lower bound, stepmin (%g)\n",(double)ls->stepmin);CHKERRQ(ierr);
ls->reason = TAOLINESEARCH_HALTED_LOWERBOUND;
break;
}
if ((ls->nfeval+ls->nfgeval) >= ls->max_funcs) {
ierr = PetscInfo2(ls,"Number of line search function evals (%D) > maximum (%D)\n",ls->nfeval+ls->nfgeval,ls->max_funcs);CHKERRQ(ierr);
ls->reason = TAOLINESEARCH_HALTED_MAXFCN;
break;
}
if ((neP->bracket) && (ls->stepmax - ls->stepmin <= ls->rtol*ls->stepmax)){
ierr = PetscInfo1(ls,"Relative width of interval of uncertainty is at most rtol (%g)\n",(double)ls->rtol);CHKERRQ(ierr);
ls->reason = TAOLINESEARCH_HALTED_RTOL;
break;
}
}
ierr = PetscInfo2(ls,"%D function evals in line search, step = %g\n",ls->nfeval+ls->nfgeval,(double)ls->step);CHKERRQ(ierr);
/* set new solution vector and compute gradient if necessary */
ierr = VecCopy(neP->W2, x);CHKERRQ(ierr);
if (ls->reason == TAOLINESEARCH_CONTINUE_ITERATING) {
ls->reason = TAOLINESEARCH_SUCCESS;
}
if (!g_computed) {
ierr = TaoLineSearchComputeGradient(ls,x,g);CHKERRQ(ierr);
}
PetscFunctionReturn(0);
}
static PetscErrorCode TaoSolve_IPM(Tao tao)
{
PetscErrorCode ierr;
TAO_IPM *ipmP = (TAO_IPM*)tao->data;
TaoConvergedReason reason = TAO_CONTINUE_ITERATING;
PetscInt its,i;
PetscScalar stepsize=1.0;
PetscScalar step_s,step_l,alpha,tau,sigma,phi_target;
PetscFunctionBegin;
/* Push initial point away from bounds */
ierr = IPMInitializeBounds(tao);CHKERRQ(ierr);
ierr = IPMPushInitialPoint(tao);CHKERRQ(ierr);
ierr = VecCopy(tao->solution,ipmP->rhs_x);CHKERRQ(ierr);
ierr = IPMEvaluate(tao);CHKERRQ(ierr);
ierr = IPMComputeKKT(tao);CHKERRQ(ierr);
ierr = TaoMonitor(tao,tao->niter++,ipmP->kkt_f,ipmP->phi,0.0,1.0,&reason);CHKERRQ(ierr);
while (reason == TAO_CONTINUE_ITERATING) {
tao->ksp_its=0;
ierr = IPMUpdateK(tao);CHKERRQ(ierr);
/*
rhs.x = -rd
rhs.lame = -rpe
rhs.lami = -rpi
rhs.com = -com
*/
ierr = VecCopy(ipmP->rd,ipmP->rhs_x);CHKERRQ(ierr);
if (ipmP->me > 0) {
ierr = VecCopy(ipmP->rpe,ipmP->rhs_lamdae);CHKERRQ(ierr);
}
if (ipmP->nb > 0) {
ierr = VecCopy(ipmP->rpi,ipmP->rhs_lamdai);CHKERRQ(ierr);
ierr = VecCopy(ipmP->complementarity,ipmP->rhs_s);CHKERRQ(ierr);
}
ierr = IPMGatherRHS(tao,ipmP->bigrhs,ipmP->rhs_x,ipmP->rhs_lamdae,ipmP->rhs_lamdai,ipmP->rhs_s);CHKERRQ(ierr);
ierr = VecScale(ipmP->bigrhs,-1.0);CHKERRQ(ierr);
/* solve K * step = rhs */
ierr = KSPSetOperators(tao->ksp,ipmP->K,ipmP->K);CHKERRQ(ierr);
ierr = KSPSolve(tao->ksp,ipmP->bigrhs,ipmP->bigstep);CHKERRQ(ierr);
ierr = IPMScatterStep(tao,ipmP->bigstep,tao->stepdirection,ipmP->ds,ipmP->dlamdae,ipmP->dlamdai);CHKERRQ(ierr);
ierr = KSPGetIterationNumber(tao->ksp,&its);CHKERRQ(ierr);
tao->ksp_its += its;
tao->ksp_tot_its+=its;
/* Find distance along step direction to closest bound */
if (ipmP->nb > 0) {
ierr = VecStepBoundInfo(ipmP->s,ipmP->ds,ipmP->Zero_nb,ipmP->Inf_nb,&step_s,NULL,NULL);CHKERRQ(ierr);
ierr = VecStepBoundInfo(ipmP->lamdai,ipmP->dlamdai,ipmP->Zero_nb,ipmP->Inf_nb,&step_l,NULL,NULL);CHKERRQ(ierr);
alpha = PetscMin(step_s,step_l);
alpha = PetscMin(alpha,1.0);
ipmP->alpha1 = alpha;
} else {
ipmP->alpha1 = alpha = 1.0;
}
/* x_aff = x + alpha*d */
ierr = VecCopy(tao->solution,ipmP->save_x);CHKERRQ(ierr);
if (ipmP->me > 0) {
ierr = VecCopy(ipmP->lamdae,ipmP->save_lamdae);CHKERRQ(ierr);
}
if (ipmP->nb > 0) {
ierr = VecCopy(ipmP->lamdai,ipmP->save_lamdai);CHKERRQ(ierr);
ierr = VecCopy(ipmP->s,ipmP->save_s);CHKERRQ(ierr);
}
ierr = VecAXPY(tao->solution,alpha,tao->stepdirection);CHKERRQ(ierr);
if (ipmP->me > 0) {
ierr = VecAXPY(ipmP->lamdae,alpha,ipmP->dlamdae);CHKERRQ(ierr);
}
if (ipmP->nb > 0) {
ierr = VecAXPY(ipmP->lamdai,alpha,ipmP->dlamdai);CHKERRQ(ierr);
ierr = VecAXPY(ipmP->s,alpha,ipmP->ds);CHKERRQ(ierr);
}
/* Recompute kkt to find centering parameter sigma = (new_mu/old_mu)^3 */
if (ipmP->mu == 0.0) {
sigma = 0.0;
} else {
sigma = 1.0/ipmP->mu;
}
ierr = IPMComputeKKT(tao);CHKERRQ(ierr);
sigma *= ipmP->mu;
sigma*=sigma*sigma;
/* revert kkt info */
ierr = VecCopy(ipmP->save_x,tao->solution);CHKERRQ(ierr);
if (ipmP->me > 0) {
ierr = VecCopy(ipmP->save_lamdae,ipmP->lamdae);CHKERRQ(ierr);
}
if (ipmP->nb > 0) {
ierr = VecCopy(ipmP->save_lamdai,ipmP->lamdai);CHKERRQ(ierr);
ierr = VecCopy(ipmP->save_s,ipmP->s);CHKERRQ(ierr);
}
ierr = IPMComputeKKT(tao);CHKERRQ(ierr);
/* update rhs with new complementarity vector */
if (ipmP->nb > 0) {
ierr = VecCopy(ipmP->complementarity,ipmP->rhs_s);CHKERRQ(ierr);
ierr = VecScale(ipmP->rhs_s,-1.0);CHKERRQ(ierr);
ierr = VecShift(ipmP->rhs_s,sigma*ipmP->mu);CHKERRQ(ierr);
}
ierr = IPMGatherRHS(tao,ipmP->bigrhs,NULL,NULL,NULL,ipmP->rhs_s);CHKERRQ(ierr);
/* solve K * step = rhs */
ierr = KSPSetOperators(tao->ksp,ipmP->K,ipmP->K);CHKERRQ(ierr);
ierr = KSPSolve(tao->ksp,ipmP->bigrhs,ipmP->bigstep);CHKERRQ(ierr);
ierr = IPMScatterStep(tao,ipmP->bigstep,tao->stepdirection,ipmP->ds,ipmP->dlamdae,ipmP->dlamdai);CHKERRQ(ierr);
ierr = KSPGetIterationNumber(tao->ksp,&its);CHKERRQ(ierr);
tao->ksp_its += its;
tao->ksp_tot_its+=its;
if (ipmP->nb > 0) {
/* Get max step size and apply frac-to-boundary */
tau = PetscMax(ipmP->taumin,1.0-ipmP->mu);
tau = PetscMin(tau,1.0);
if (tau != 1.0) {
ierr = VecScale(ipmP->s,tau);CHKERRQ(ierr);
ierr = VecScale(ipmP->lamdai,tau);CHKERRQ(ierr);
}
ierr = VecStepBoundInfo(ipmP->s,ipmP->ds,ipmP->Zero_nb,ipmP->Inf_nb,&step_s,NULL,NULL);CHKERRQ(ierr);
ierr = VecStepBoundInfo(ipmP->lamdai,ipmP->dlamdai,ipmP->Zero_nb,ipmP->Inf_nb,&step_l,NULL,NULL);CHKERRQ(ierr);
if (tau != 1.0) {
ierr = VecCopy(ipmP->save_s,ipmP->s);CHKERRQ(ierr);
ierr = VecCopy(ipmP->save_lamdai,ipmP->lamdai);CHKERRQ(ierr);
}
alpha = PetscMin(step_s,step_l);
alpha = PetscMin(alpha,1.0);
} else {
alpha = 1.0;
}
ipmP->alpha2 = alpha;
/* TODO make phi_target meaningful */
phi_target = ipmP->dec * ipmP->phi;
for (i=0; i<11;i++) {
ierr = VecAXPY(tao->solution,alpha,tao->stepdirection);CHKERRQ(ierr);
if (ipmP->nb > 0) {
ierr = VecAXPY(ipmP->s,alpha,ipmP->ds);CHKERRQ(ierr);
ierr = VecAXPY(ipmP->lamdai,alpha,ipmP->dlamdai);CHKERRQ(ierr);
}
if (ipmP->me > 0) {
ierr = VecAXPY(ipmP->lamdae,alpha,ipmP->dlamdae);CHKERRQ(ierr);
}
/* update dual variables */
if (ipmP->me > 0) {
ierr = VecCopy(ipmP->lamdae,tao->DE);CHKERRQ(ierr);
}
ierr = IPMEvaluate(tao);CHKERRQ(ierr);
ierr = IPMComputeKKT(tao);CHKERRQ(ierr);
if (ipmP->phi <= phi_target) break;
alpha /= 2.0;
}
ierr = TaoMonitor(tao,tao->niter,ipmP->kkt_f,ipmP->phi,0.0,stepsize,&reason);CHKERRQ(ierr);
tao->niter++;
}
PetscFunctionReturn(0);
}
