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// ************************************************************************
//
// Rapid Optimization Library (ROL) Package
// Copyright (2014) Sandia Corporation
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#ifndef ROL_SLACKLESSOBJECTIVE_HPP
#define ROL_SLACKLESSOBJECTIVE_HPP
#include "ROL_Objective.hpp"
#include "ROL_PartitionedVector.hpp"
/** @ingroup func_group
* \class ROL::SlacklessObjective
* \brief This class strips out the slack variables from objective evaluations
* to create the new objective \f$ F(x,s) = f(x) \f$
*/
namespace ROL {
template<class Real>
class SlacklessObjective : public Objective<Real> {
typedef ROL::PartitionedVector<Real> PV;
typedef typename PV::size_type size_type;
private:
const static size_type OPT = 0;
const static size_type SLACK = 1;
Teuchos::RCP<Objective<Real> > obj_;
Teuchos::RCP<Vector<Real> > getOpt( Vector<Real> &xs ) {
return Teuchos::dyn_cast<PV>(xs).get(OPT);
}
Teuchos::RCP<const Vector<Real> > getOpt( const Vector<Real> &xs ) {
return Teuchos::dyn_cast<const PV>(xs).get(OPT);
}
void zeroSlack( Vector<Real> &x ) {
Teuchos::dyn_cast<PV>(x).get(SLACK)->zero();
}
public:
SlacklessObjective( const Teuchos::RCP<Objective<Real> > &obj ) : obj_(obj) {}
~SlacklessObjective() {}
void update( const Vector<Real> &x, bool flag = true, int iter = -1 ) {
obj_->update( *getOpt(x), flag, iter );
}
Real value( const Vector<Real> &x, Real &tol ) {
return obj_->value( *getOpt(x), tol );
}
void gradient( Vector<Real> &g, const Vector<Real> &x, Real &tol ) {
zeroSlack(g);
obj_->gradient(*getOpt(g),*getOpt(x),tol);
}
Real dirDeriv( const Vector<Real> &x, const Vector<Real> &d, Real &tol ) {
return obj_->dirDeriv(*getOpt(x),*getOpt(d),tol);
}
void hessVec( Vector<Real> &hv, const Vector<Real> &v, const Vector<Real> &x, Real &tol ) {
zeroSlack(hv);
obj_->hessVec(*getOpt(hv),*getOpt(v),*getOpt(x),tol);
}
void invHessVec( Vector<Real> &ihv, const Vector<Real> &v, const Vector<Real> &x, Real &tol ) {
zeroSlack(ihv);
obj_->invHessVec( *getOpt(ihv), *getOpt(v), *getOpt(x), tol );
}
void precond( Vector<Real> &Pv, const Vector<Real> &v, const Vector<Real> &x, Real &tol ) {
zeroSlack(Pv);
obj_->precond( *getOpt(Pv), *getOpt(v), *getOpt(x), tol );
}
// Definitions for parametrized (stochastic) objective functions
public:
void setParameter(const std::vector<Real> ¶m) {
Objective<Real>::setParameter(param);
obj_->setParameter(param);
}
}; // class SlacklessObjective
} // namespace ROL
#endif // ROL__SLACKLESSOBJECTIVE_HPP
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