/usr/include/trilinos/ROL_LinearCombinationObjective.hpp is in libtrilinos-rol-dev 12.12.1-5.
This file is owned by root:root, with mode 0o644.
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// ************************************************************************
//
//               Rapid Optimization Library (ROL) Package
//                 Copyright (2014) Sandia Corporation
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#ifndef ROL_LINEARCOMBINATIONOBJECTIVE_H
#define ROL_LINEARCOMBINATIONOBJECTIVE_H
#include "ROL_Objective.hpp"
#include "Teuchos_RCP.hpp"
namespace ROL {
template <class Real>
class LinearCombinationObjective : public Objective<Real> {
private:
  const std::vector<Teuchos::RCP<Objective<Real> > > obj_;
  std::vector<Real> weights_;
  size_t size_;
  Teuchos::RCP<Vector<Real> > xdual_;
  bool initialized_;
public:
  LinearCombinationObjective(const std::vector<Teuchos::RCP<Objective<Real> > > &obj)
    : Objective<Real>(), obj_(obj),
      xdual_(Teuchos::null), initialized_(false) {
    size_ = obj_.size();
    weights_.clear(); weights_.assign(size_,static_cast<Real>(1));
  }
  LinearCombinationObjective(const std::vector<Real> &weights,
                             const std::vector<Teuchos::RCP<Objective<Real> > > &obj)
    : Objective<Real>(), obj_(obj), weights_(weights), size_(weights.size()),
      xdual_(Teuchos::null), initialized_(false) {}
  void update(const Vector<Real> &x, bool flag = true, int iter = -1) {
    for (size_t i=0; i<size_; ++i) {
      obj_[i]->update(x,flag,iter);
    }
  }
  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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