/usr/include/trilinos/ROL_LinearCombinationObjective.hpp is in libtrilinos-rol-dev 12.10.1-3.
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// Rapid Optimization Library (ROL) Package
// Copyright (2014) Sandia Corporation
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// @HEADER
#ifndef ROL_LINEARCOMBINATIONOBJECTIVE_H
#define ROL_LINEARCOMBINATIONOBJECTIVE_H
#include "ROL_Objective.hpp"
#include "ROL_Vector.hpp"
#include "Teuchos_RCP.hpp"
namespace ROL {
template <class Real>
class LinearCombinationObjective : public Objective<Real> {
private:
const std::vector<Real> weights_;
std::vector<Teuchos::RCP<Objective<Real> > > obj_;
size_t size_;
Teuchos::RCP<Vector<Real> > xdual_;
bool initialized_;
public:
LinearCombinationObjective(const std::vector<Real> &weights,
const std::vector<Teuchos::RCP<Objective<Real> > > &obj)
: Objective<Real>(), weights_(weights), obj_(obj), size_(weights.size()),
xdual_(Teuchos::null), initialized_(false) {}
Real value( const Vector<Real> &x, Real &tol ) {
Real val = 0.;
for (size_t i = 0; i < size_; i++) {
val += weights_[i]*obj_[i]->value(x,tol);
}
return val;
}
void gradient( Vector<Real> &g, const Vector<Real> &x, Real &tol ) {
if (!initialized_) {
xdual_ = g.clone();
initialized_ = true;
}
g.zero();
for (size_t i = 0; i < size_; i++) {
obj_[i]->gradient(*xdual_,x,tol);
g.axpy(weights_[i],*xdual_);
}
}
void hessVec( Vector<Real> &hv, const Vector<Real> &v, const Vector<Real> &x, Real &tol ) {
if (!initialized_) {
xdual_ = hv.clone();
initialized_ = true;
}
hv.zero();
for (size_t i = 0; i < size_; i++) {
obj_[i]->hessVec(*xdual_,v,x,tol);
hv.axpy(weights_[i],*xdual_);
}
}
// Definitions for parametrized (stochastic) objective functions
public:
void setParameter(const std::vector<Real> ¶m) {
Objective<Real>::setParameter(param);
for (size_t i = 0; i < size_; ++i) {
obj_[i]->setParameter(param);
}
}
}; // class LinearCombinationObjective
} // namespace ROL
#endif
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