ROL_RiskMeasure.hpp

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#ifndef ROL_RISKMEASURE_HPP
#define ROL_RISKMEASURE_HPP

#include "ROL_Vector.hpp"

namespace ROL {

template<class Real>
class RiskMeasure {
protected:
  Real val_;
  Real gv_;
  Teuchos::RCP<Vector<Real> > g_;
  Teuchos::RCP<Vector<Real> > hv_;
  bool firstReset_;

public:
  virtual ~RiskMeasure() {}

  RiskMeasure(void) : firstReset_(true) {}

  // Reset risk measure storage.  Called for value and gradient computation.
  virtual void reset(Teuchos::RCP<Vector<Real> > &x0, const Vector<Real> &x) {
    // Create memory for class members
    if ( firstReset_ ) {
      g_  = (x.dual()).clone();
      hv_ = (x.dual()).clone();
      firstReset_ = false;
    }
    // Zero member variables
    val_ = 0.0; gv_ = 0.0;
    g_->zero(); hv_->zero();
    // Get vector component of x.  This is important for CVaR.
    x0 = Teuchos::rcp(&const_cast<Vector<Real> &>(x),false);
  }

  // Reset risk measure storage.  Called for Hessian-times-a-vector computation.
  virtual void reset(Teuchos::RCP<Vector<Real> > &x0, const Vector<Real> &x,
                     Teuchos::RCP<Vector<Real> > &v0, const Vector<Real> &v) {
    reset(x0,x);
    // Get vector component of v.  This is important for CVaR.
    v0 = Teuchos::rcp(&const_cast<Vector<Real> &>(v),false);
  }

  virtual void update(const Real val, const Real weight) {
    val_ += weight * val;
  }

  virtual void update(const Real val, const Vector<Real> &g, const Real weight) {
    g_->axpy(weight,g);
  }

  virtual void update(const Real val, const Vector<Real> &g, const Real gv, const Vector<Real> &hv,
                      const Real weight) {
    hv_->axpy(weight,hv);
  }

  virtual Real getValue(SampleGenerator<Real> &sampler) {
    Real val = 0.0;
    sampler.sumAll(&val_,&val,1);
    return val;
  }

  virtual void getGradient(Vector<Real> &g, SampleGenerator<Real> &sampler) {
    sampler.sumAll(*g_,g);
  }

  virtual void getHessVec(Vector<Real> &hv, SampleGenerator<Real> &sampler) {
    sampler.sumAll(*hv_,hv);
  }
};

}

#endif