ROL
Public Member Functions | Private Member Functions | Private Attributes | List of all members
ROL::RiskNeutralObjective< Real > Class Template Reference

#include <ROL_RiskNeutralObjective.hpp>

+ Inheritance diagram for ROL::RiskNeutralObjective< Real >:

Public Member Functions

 RiskNeutralObjective (const Ptr< Objective< Real > > &pObj, const Ptr< SampleGenerator< Real > > &vsampler, const Ptr< SampleGenerator< Real > > &gsampler, const Ptr< SampleGenerator< Real > > &hsampler, const bool storage=true)
 
 RiskNeutralObjective (const Ptr< Objective< Real > > &pObj, const Ptr< SampleGenerator< Real > > &vsampler, const Ptr< SampleGenerator< Real > > &gsampler, const bool storage=true)
 
 RiskNeutralObjective (const Ptr< Objective< Real > > &pObj, const Ptr< SampleGenerator< Real > > &sampler, const bool storage=true)
 
void update (const Vector< Real > &x, UpdateType type, int iter=-1)
 Update objective function.
 
void update (const Vector< Real > &x, bool flag=true, int iter=-1)
 Update objective function.
 
Real value (const Vector< Real > &x, Real &tol)
 Compute value.
 
void gradient (Vector< Real > &g, const Vector< Real > &x, Real &tol)
 Compute gradient.
 
void hessVec (Vector< Real > &hv, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
 Apply Hessian approximation to vector.
 
void precond (Vector< Real > &Pv, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
 Apply preconditioner to vector.
 
- Public Member Functions inherited from ROL::Objective< Real >
virtual ~Objective ()
 
 Objective ()
 
virtual Real dirDeriv (const Vector< Real > &x, const Vector< Real > &d, Real &tol)
 Compute directional derivative.
 
virtual void invHessVec (Vector< Real > &hv, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
 Apply inverse Hessian approximation to vector.
 
virtual std::vector< std::vector< Real > > checkGradient (const Vector< Real > &x, const Vector< Real > &d, const bool printToStream=true, std::ostream &outStream=std::cout, const int numSteps=ROL_NUM_CHECKDERIV_STEPS, const int order=1)
 Finite-difference gradient check.
 
virtual std::vector< std::vector< Real > > checkGradient (const Vector< Real > &x, const Vector< Real > &g, const Vector< Real > &d, const bool printToStream=true, std::ostream &outStream=std::cout, const int numSteps=ROL_NUM_CHECKDERIV_STEPS, const int order=1)
 Finite-difference gradient check.
 
virtual std::vector< std::vector< Real > > checkGradient (const Vector< Real > &x, const Vector< Real > &d, const std::vector< Real > &steps, const bool printToStream=true, std::ostream &outStream=std::cout, const int order=1)
 Finite-difference gradient check with specified step sizes.
 
virtual std::vector< std::vector< Real > > checkGradient (const Vector< Real > &x, const Vector< Real > &g, const Vector< Real > &d, const std::vector< Real > &steps, const bool printToStream=true, std::ostream &outStream=std::cout, const int order=1)
 Finite-difference gradient check with specified step sizes.
 
virtual std::vector< std::vector< Real > > checkHessVec (const Vector< Real > &x, const Vector< Real > &v, const bool printToStream=true, std::ostream &outStream=std::cout, const int numSteps=ROL_NUM_CHECKDERIV_STEPS, const int order=1)
 Finite-difference Hessian-applied-to-vector check.
 
virtual std::vector< std::vector< Real > > checkHessVec (const Vector< Real > &x, const Vector< Real > &hv, const Vector< Real > &v, const bool printToStream=true, std::ostream &outStream=std::cout, const int numSteps=ROL_NUM_CHECKDERIV_STEPS, const int order=1)
 Finite-difference Hessian-applied-to-vector check.
 
virtual std::vector< std::vector< Real > > checkHessVec (const Vector< Real > &x, const Vector< Real > &v, const std::vector< Real > &steps, const bool printToStream=true, std::ostream &outStream=std::cout, const int order=1)
 Finite-difference Hessian-applied-to-vector check with specified step sizes.
 
virtual std::vector< std::vector< Real > > checkHessVec (const Vector< Real > &x, const Vector< Real > &hv, const Vector< Real > &v, const std::vector< Real > &steps, const bool printToStream=true, std::ostream &outStream=std::cout, const int order=1)
 Finite-difference Hessian-applied-to-vector check with specified step sizes.
 
virtual std::vector< Real > checkHessSym (const Vector< Real > &x, const Vector< Real > &v, const Vector< Real > &w, const bool printToStream=true, std::ostream &outStream=std::cout)
 Hessian symmetry check.
 
virtual std::vector< Real > checkHessSym (const Vector< Real > &x, const Vector< Real > &hv, const Vector< Real > &v, const Vector< Real > &w, const bool printToStream=true, std::ostream &outStream=std::cout)
 Hessian symmetry check.
 
virtual void setParameter (const std::vector< Real > &param)
 

Private Member Functions

void initialize (const Vector< Real > &x)
 
void getValue (Real &val, const Vector< Real > &x, const std::vector< Real > &param, Real &tol)
 
void getGradient (Vector< Real > &g, const Vector< Real > &x, const std::vector< Real > &param, Real &tol)
 
void getHessVec (Vector< Real > &hv, const Vector< Real > &v, const Vector< Real > &x, const std::vector< Real > &param, Real &tol)
 

Private Attributes

Ptr< Objective< Real > > ParametrizedObjective_
 
Ptr< SampleGenerator< Real > > ValueSampler_
 
Ptr< SampleGenerator< Real > > GradientSampler_
 
Ptr< SampleGenerator< Real > > HessianSampler_
 
Real value_
 
Ptr< Vector< Real > > gradient_
 
Ptr< Vector< Real > > pointDual_
 
Ptr< Vector< Real > > sumDual_
 
bool firstUpdate_
 
bool storage_
 
Ptr< ScalarController< Real > > value_storage_
 
Ptr< VectorController< Real > > gradient_storage_
 

Additional Inherited Members

- Protected Member Functions inherited from ROL::Objective< Real >
const std::vector< Real > getParameter (void) const
 

Detailed Description

template<class Real>
class ROL::RiskNeutralObjective< Real >

Definition at line 56 of file ROL_RiskNeutralObjective.hpp.

Constructor & Destructor Documentation

◆ RiskNeutralObjective() [1/3]

template<class Real >
ROL::RiskNeutralObjective< Real >::RiskNeutralObjective ( const Ptr< Objective< Real > > & pObj,
const Ptr< SampleGenerator< Real > > & vsampler,
const Ptr< SampleGenerator< Real > > & gsampler,
const Ptr< SampleGenerator< Real > > & hsampler,
const bool storage = true )
inline

◆ RiskNeutralObjective() [2/3]

template<class Real >
ROL::RiskNeutralObjective< Real >::RiskNeutralObjective ( const Ptr< Objective< Real > > & pObj,
const Ptr< SampleGenerator< Real > > & vsampler,
const Ptr< SampleGenerator< Real > > & gsampler,
const bool storage = true )
inline

◆ RiskNeutralObjective() [3/3]

template<class Real >
ROL::RiskNeutralObjective< Real >::RiskNeutralObjective ( const Ptr< Objective< Real > > & pObj,
const Ptr< SampleGenerator< Real > > & sampler,
const bool storage = true )
inline

Member Function Documentation

◆ initialize()

template<class Real >
void ROL::RiskNeutralObjective< Real >::initialize ( const Vector< Real > & x)
inlineprivate

◆ getValue()

template<class Real >
void ROL::RiskNeutralObjective< Real >::getValue ( Real & val,
const Vector< Real > & x,
const std::vector< Real > & param,
Real & tol )
inlineprivate

◆ getGradient()

template<class Real >
void ROL::RiskNeutralObjective< Real >::getGradient ( Vector< Real > & g,
const Vector< Real > & x,
const std::vector< Real > & param,
Real & tol )
inlineprivate

◆ getHessVec()

template<class Real >
void ROL::RiskNeutralObjective< Real >::getHessVec ( Vector< Real > & hv,
const Vector< Real > & v,
const Vector< Real > & x,
const std::vector< Real > & param,
Real & tol )
inlineprivate

◆ update() [1/2]

template<class Real >
void ROL::RiskNeutralObjective< Real >::update ( const Vector< Real > & x,
UpdateType type,
int iter = -1 )
inlinevirtual

◆ update() [2/2]

template<class Real >
void ROL::RiskNeutralObjective< Real >::update ( const Vector< Real > & x,
bool flag = true,
int iter = -1 )
inlinevirtual

◆ value()

template<class Real >
Real ROL::RiskNeutralObjective< Real >::value ( const Vector< Real > & x,
Real & tol )
inlinevirtual

Compute value.

This function returns the objective function value.

Parameters
[in]xis the current iterate.
[in]tolis a tolerance for inexact objective function computation.

Implements ROL::Objective< Real >.

Definition at line 192 of file ROL_RiskNeutralObjective.hpp.

References ROL::RiskNeutralObjective< Real >::getValue(), ROL::RiskNeutralObjective< Real >::initialize(), ROL::RiskNeutralObjective< Real >::value_, and ROL::RiskNeutralObjective< Real >::ValueSampler_.

◆ gradient()

template<class Real >
void ROL::RiskNeutralObjective< Real >::gradient ( Vector< Real > & g,
const Vector< Real > & x,
Real & tol )
inlinevirtual

Compute gradient.

This function returns the objective function gradient.

Parameters
[out]gis the gradient.
[in]xis the current iterate.
[in]tolis a tolerance for inexact objective function computation.

The default implementation is a finite-difference approximation based on the function value. This requires the definition of a basis \(\{\phi_i\}\) for the optimization vectors x and the definition of a basis \(\{\psi_j\}\) for the dual optimization vectors (gradient vectors g). The bases must be related through the Riesz map, i.e., \( R \{\phi_i\} = \{\psi_j\}\), and this must be reflected in the implementation of the ROL::Vector::dual() method.

Reimplemented from ROL::Objective< Real >.

Definition at line 213 of file ROL_RiskNeutralObjective.hpp.

References ROL::RiskNeutralObjective< Real >::getGradient(), ROL::RiskNeutralObjective< Real >::gradient_, ROL::RiskNeutralObjective< Real >::GradientSampler_, ROL::RiskNeutralObjective< Real >::initialize(), ROL::RiskNeutralObjective< Real >::pointDual_, ROL::Vector< Real >::set(), ROL::RiskNeutralObjective< Real >::sumDual_, and ROL::Vector< Real >::zero().

◆ hessVec()

template<class Real >
void ROL::RiskNeutralObjective< Real >::hessVec ( Vector< Real > & hv,
const Vector< Real > & v,
const Vector< Real > & x,
Real & tol )
inlinevirtual

Apply Hessian approximation to vector.

This function applies the Hessian of the objective function to the vector \(v\).

Parameters
[out]hvis the the action of the Hessian on \(v\).
[in]vis the direction vector.
[in]xis the current iterate.
[in]tolis a tolerance for inexact objective function computation.

Reimplemented from ROL::Objective< Real >.

Definition at line 239 of file ROL_RiskNeutralObjective.hpp.

References ROL::RiskNeutralObjective< Real >::getHessVec(), ROL::RiskNeutralObjective< Real >::HessianSampler_, ROL::RiskNeutralObjective< Real >::initialize(), ROL::RiskNeutralObjective< Real >::pointDual_, ROL::RiskNeutralObjective< Real >::sumDual_, and ROL::Vector< Real >::zero().

◆ precond()

template<class Real >
void ROL::RiskNeutralObjective< Real >::precond ( Vector< Real > & Pv,
const Vector< Real > & v,
const Vector< Real > & x,
Real & tol )
inlinevirtual

Apply preconditioner to vector.

This function applies a preconditioner for the Hessian of the objective function to the vector \(v\).

Parameters
[out]Pvis the action of the Hessian preconditioner on \(v\).
[in]vis the direction vector.
[in]xis the current iterate.
[in]tolis a tolerance for inexact objective function computation.

Reimplemented from ROL::Objective< Real >.

Definition at line 250 of file ROL_RiskNeutralObjective.hpp.

References ROL::Vector< Real >::dual(), and ROL::Vector< Real >::set().

Member Data Documentation

◆ ParametrizedObjective_

template<class Real >
Ptr<Objective<Real> > ROL::RiskNeutralObjective< Real >::ParametrizedObjective_
private

◆ ValueSampler_

template<class Real >
Ptr<SampleGenerator<Real> > ROL::RiskNeutralObjective< Real >::ValueSampler_
private

◆ GradientSampler_

template<class Real >
Ptr<SampleGenerator<Real> > ROL::RiskNeutralObjective< Real >::GradientSampler_
private

◆ HessianSampler_

template<class Real >
Ptr<SampleGenerator<Real> > ROL::RiskNeutralObjective< Real >::HessianSampler_
private

◆ value_

template<class Real >
Real ROL::RiskNeutralObjective< Real >::value_
private

◆ gradient_

template<class Real >
Ptr<Vector<Real> > ROL::RiskNeutralObjective< Real >::gradient_
private

◆ pointDual_

template<class Real >
Ptr<Vector<Real> > ROL::RiskNeutralObjective< Real >::pointDual_
private

◆ sumDual_

template<class Real >
Ptr<Vector<Real> > ROL::RiskNeutralObjective< Real >::sumDual_
private

◆ firstUpdate_

template<class Real >
bool ROL::RiskNeutralObjective< Real >::firstUpdate_
private

◆ storage_

template<class Real >
bool ROL::RiskNeutralObjective< Real >::storage_
private

◆ value_storage_

template<class Real >
Ptr<ScalarController<Real> > ROL::RiskNeutralObjective< Real >::value_storage_
private

◆ gradient_storage_

template<class Real >
Ptr<VectorController<Real> > ROL::RiskNeutralObjective< Real >::gradient_storage_
private

The documentation for this class was generated from the following file: