PetscErrorCode MatMult_SMF(Mat mat,Vec a,Vec y)
{
MatSubMatFreeCtx ctx;
PetscErrorCode ierr;
PetscFunctionBegin;
ierr = MatShellGetContext(mat,(void **)&ctx);CHKERRQ(ierr);
ierr = VecCopy(a,ctx->VR);CHKERRQ(ierr);
ierr = VecISSet(ctx->VR,ctx->Cols,0.0);CHKERRQ(ierr);
ierr = MatMult(ctx->A,ctx->VR,y);CHKERRQ(ierr);
ierr = VecISSet(y,ctx->Rows,0.0);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
PetscErrorCode TaoSolve_BNTR(Tao tao)
{
PetscErrorCode ierr;
TAO_BNK *bnk = (TAO_BNK *)tao->data;
KSPConvergedReason ksp_reason;
PetscReal oldTrust, prered, actred, steplen, resnorm;
PetscBool cgTerminate, needH = PETSC_TRUE, stepAccepted, shift = PETSC_FALSE;
PetscInt stepType, nDiff;
PetscFunctionBegin;
/* Initialize the preconditioner, KSP solver and trust radius/line search */
tao->reason = TAO_CONTINUE_ITERATING;
ierr = TaoBNKInitialize(tao, bnk->init_type, &needH);CHKERRQ(ierr);
if (tao->reason != TAO_CONTINUE_ITERATING) PetscFunctionReturn(0);
/* Have not converged; continue with Newton method */
while (tao->reason == TAO_CONTINUE_ITERATING) {
/* Call general purpose update function */
if (tao->ops->update) {
ierr = (*tao->ops->update)(tao, tao->niter, tao->user_update);CHKERRQ(ierr);
}
++tao->niter;
if (needH && bnk->inactive_idx) {
/* Take BNCG steps (if enabled) to trade-off Hessian evaluations for more gradient evaluations */
ierr = TaoBNKTakeCGSteps(tao, &cgTerminate);CHKERRQ(ierr);
if (cgTerminate) {
tao->reason = bnk->bncg->reason;
PetscFunctionReturn(0);
}
/* Compute the hessian and update the BFGS preconditioner at the new iterate */
ierr = (*bnk->computehessian)(tao);CHKERRQ(ierr);
needH = PETSC_FALSE;
}
/* Store current solution before it changes */
bnk->fold = bnk->f;
ierr = VecCopy(tao->solution, bnk->Xold);CHKERRQ(ierr);
ierr = VecCopy(tao->gradient, bnk->Gold);CHKERRQ(ierr);
ierr = VecCopy(bnk->unprojected_gradient, bnk->unprojected_gradient_old);CHKERRQ(ierr);
/* Enter into trust region loops */
stepAccepted = PETSC_FALSE;
while (!stepAccepted && tao->reason == TAO_CONTINUE_ITERATING) {
tao->ksp_its=0;
/* Use the common BNK kernel to compute the Newton step (for inactive variables only) */
ierr = (*bnk->computestep)(tao, shift, &ksp_reason, &stepType);CHKERRQ(ierr);
/* Temporarily accept the step and project it into the bounds */
ierr = VecAXPY(tao->solution, 1.0, tao->stepdirection);CHKERRQ(ierr);
ierr = TaoBoundSolution(tao->solution, tao->XL,tao->XU, 0.0, &nDiff, tao->solution);CHKERRQ(ierr);
/* Check if the projection changed the step direction */
if (nDiff > 0) {
/* Projection changed the step, so we have to recompute the step and
the predicted reduction. Leave the trust radius unchanged. */
ierr = VecCopy(tao->solution, tao->stepdirection);CHKERRQ(ierr);
ierr = VecAXPY(tao->stepdirection, -1.0, bnk->Xold);CHKERRQ(ierr);
ierr = TaoBNKRecomputePred(tao, tao->stepdirection, &prered);CHKERRQ(ierr);
} else {
/* Step did not change, so we can just recover the pre-computed prediction */
ierr = KSPCGGetObjFcn(tao->ksp, &prered);CHKERRQ(ierr);
}
prered = -prered;
/* Compute the actual reduction and update the trust radius */
ierr = TaoComputeObjective(tao, tao->solution, &bnk->f);CHKERRQ(ierr);
if (PetscIsInfOrNanReal(bnk->f)) SETERRQ(PETSC_COMM_SELF,1, "User provided compute function generated Inf or NaN");
actred = bnk->fold - bnk->f;
oldTrust = tao->trust;
ierr = TaoBNKUpdateTrustRadius(tao, prered, actred, bnk->update_type, stepType, &stepAccepted);CHKERRQ(ierr);
if (stepAccepted) {
/* Step is good, evaluate the gradient and flip the need-Hessian switch */
steplen = 1.0;
needH = PETSC_TRUE;
++bnk->newt;
ierr = TaoComputeGradient(tao, tao->solution, bnk->unprojected_gradient);CHKERRQ(ierr);
ierr = TaoBNKEstimateActiveSet(tao, bnk->as_type);CHKERRQ(ierr);
ierr = VecCopy(bnk->unprojected_gradient, tao->gradient);CHKERRQ(ierr);
ierr = VecISSet(tao->gradient, bnk->active_idx, 0.0);CHKERRQ(ierr);
ierr = TaoGradientNorm(tao, tao->gradient, NORM_2, &bnk->gnorm);CHKERRQ(ierr);
} else {
/* Step is bad, revert old solution and re-solve with new radius*/
steplen = 0.0;
needH = PETSC_FALSE;
bnk->f = bnk->fold;
ierr = VecCopy(bnk->Xold, tao->solution);CHKERRQ(ierr);
ierr = VecCopy(bnk->Gold, tao->gradient);CHKERRQ(ierr);
ierr = VecCopy(bnk->unprojected_gradient_old, bnk->unprojected_gradient);CHKERRQ(ierr);
if (oldTrust == tao->trust) {
/* Can't change the radius anymore so just terminate */
tao->reason = TAO_DIVERGED_TR_REDUCTION;
}
}
/* Check for termination */
ierr = VecFischer(tao->solution, bnk->unprojected_gradient, tao->XL, tao->XU, bnk->W);CHKERRQ(ierr);
ierr = VecNorm(bnk->W, NORM_2, &resnorm);CHKERRQ(ierr);
if (PetscIsInfOrNanReal(resnorm)) SETERRQ(PETSC_COMM_SELF,1, "User provided compute function generated Inf or NaN");
ierr = TaoLogConvergenceHistory(tao, bnk->f, resnorm, 0.0, tao->ksp_its);CHKERRQ(ierr);
ierr = TaoMonitor(tao, tao->niter, bnk->f, resnorm, 0.0, steplen);CHKERRQ(ierr);
ierr = (*tao->ops->convergencetest)(tao, tao->cnvP);CHKERRQ(ierr);
}
}
PetscFunctionReturn(0);
}
PETSC_EXTERN void PETSC_STDCALL vecisset_(Vec V,IS S,PetscScalar *c, int *__ierr ){
*__ierr = VecISSet(
(Vec)PetscToPointer((V) ),
(IS)PetscToPointer((S) ),*c);
}
