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, bool flag=true, int iter=-1)
	Update objective function. More...
Real	value (const Vector< Real > &x, Real &tol)
	Compute value. More...
void	gradient (Vector< Real > &g, const Vector< Real > &x, Real &tol)
	Compute gradient. More...
void	hessVec (Vector< Real > &hv, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
	Apply Hessian approximation to vector. More...
void	precond (Vector< Real > &Pv, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
	Apply preconditioner to vector. More...
Public Member Functions inherited from ROL::Objective< Real >
virtual	~Objective ()
virtual Real	dirDeriv (const Vector< Real > &x, const Vector< Real > &d, Real &tol)
	Compute directional derivative. More...
virtual void	invHessVec (Vector< Real > &hv, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
	Apply inverse Hessian approximation to vector. More...
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. More...
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. More...
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. More...
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. More...
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. More...
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. More...
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. More...
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. More...
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. More...
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. More...
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_
std::map< std::vector< Real > , Real >	value_storage_
std::map< std::vector< Real > , Ptr< Vector< 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 54 of file ROL_RiskNeutralObjective.hpp.

Constructor & Destructor Documentation

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

Definition at line 119 of file ROL_RiskNeutralObjective.hpp.

References ROL::RiskNeutralObjective< Real >::gradient_storage_, and ROL::RiskNeutralObjective< Real >::value_storage_.

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

Definition at line 131 of file ROL_RiskNeutralObjective.hpp.

References ROL::RiskNeutralObjective< Real >::gradient_storage_, and ROL::RiskNeutralObjective< Real >::value_storage_.

template<class Real >

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

inline

Definition at line 142 of file ROL_RiskNeutralObjective.hpp.

References ROL::RiskNeutralObjective< Real >::gradient_storage_, and ROL::RiskNeutralObjective< Real >::value_storage_.

Member Function Documentation

template<class Real >

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

inlineprivate

Definition at line 72 of file ROL_RiskNeutralObjective.hpp.

References ROL::Vector< Real >::dual(), ROL::RiskNeutralObjective< Real >::firstUpdate_, ROL::RiskNeutralObjective< Real >::gradient_, ROL::RiskNeutralObjective< Real >::pointDual_, and ROL::RiskNeutralObjective< Real >::sumDual_.

Referenced by ROL::RiskNeutralObjective< Real >::gradient(), ROL::RiskNeutralObjective< Real >::hessVec(), ROL::RiskNeutralObjective< Real >::update(), and ROL::RiskNeutralObjective< Real >::value().

template<class Real >

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

inlineprivate

Definition at line 81 of file ROL_RiskNeutralObjective.hpp.

References ROL::RiskNeutralObjective< Real >::ParametrizedObjective_, ROL::RiskNeutralObjective< Real >::storage_, and ROL::RiskNeutralObjective< Real >::value_storage_.

Referenced by ROL::RiskNeutralObjective< Real >::value().

template<class Real >

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

inlineprivate

Definition at line 95 of file ROL_RiskNeutralObjective.hpp.

References ROL::Vector< Real >::clone(), ROL::RiskNeutralObjective< Real >::gradient_storage_, ROL::RiskNeutralObjective< Real >::ParametrizedObjective_, ROL::Vector< Real >::set(), and ROL::RiskNeutralObjective< Real >::storage_.

Referenced by ROL::RiskNeutralObjective< Real >::gradient().

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

Definition at line 111 of file ROL_RiskNeutralObjective.hpp.

References ROL::RiskNeutralObjective< Real >::ParametrizedObjective_.

Referenced by ROL::RiskNeutralObjective< Real >::hessVec().

template<class Real >

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

inlinevirtual

Update objective function.

This function updates the objective function at new iterations.

Parameters

[in]	x	is the new iterate.
[in]	flag	is true if the iterate has changed.
[in]	iter	is the outer algorithm iterations count.

Reimplemented from ROL::Objective< Real >.

Definition at line 152 of file ROL_RiskNeutralObjective.hpp.

References ROL::RiskNeutralObjective< Real >::gradient_, ROL::RiskNeutralObjective< Real >::gradient_storage_, ROL::RiskNeutralObjective< Real >::GradientSampler_, ROL::RiskNeutralObjective< Real >::HessianSampler_, ROL::RiskNeutralObjective< Real >::initialize(), ROL::RiskNeutralObjective< Real >::ParametrizedObjective_, ROL::RiskNeutralObjective< Real >::storage_, ROL::RiskNeutralObjective< Real >::value_, ROL::RiskNeutralObjective< Real >::value_storage_, and ROL::RiskNeutralObjective< Real >::ValueSampler_.

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]	x	is the current iterate.
[in]	tol	is a tolerance for inexact objective function computation.

Implements ROL::Objective< Real >.

Definition at line 171 of file ROL_RiskNeutralObjective.hpp.

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

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]	g	is the gradient.
[in]	x	is the current iterate.
[in]	tol	is 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 192 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().

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]	hv	is the the action of the Hessian on \(v\).
[in]	v	is the direction vector.
[in]	x	is the current iterate.
[in]	tol	is a tolerance for inexact objective function computation.

Reimplemented from ROL::Objective< Real >.

Definition at line 218 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().

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]	Pv	is the action of the Hessian preconditioner on \(v\).
[in]	v	is the direction vector.
[in]	x	is the current iterate.
[in]	tol	is a tolerance for inexact objective function computation.

Reimplemented from ROL::Objective< Real >.

Definition at line 229 of file ROL_RiskNeutralObjective.hpp.

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

Member Data Documentation

template<class Real >

Ptr<Objective<Real> > ROL::RiskNeutralObjective< Real >::ParametrizedObjective_

private

Definition at line 56 of file ROL_RiskNeutralObjective.hpp.

Referenced by ROL::RiskNeutralObjective< Real >::getGradient(), ROL::RiskNeutralObjective< Real >::getHessVec(), ROL::RiskNeutralObjective< Real >::getValue(), and ROL::RiskNeutralObjective< Real >::update().

template<class Real >

Ptr<SampleGenerator<Real> > ROL::RiskNeutralObjective< Real >::ValueSampler_

private

Definition at line 57 of file ROL_RiskNeutralObjective.hpp.

Referenced by ROL::RiskNeutralObjective< Real >::update(), and ROL::RiskNeutralObjective< Real >::value().

template<class Real >

Ptr<SampleGenerator<Real> > ROL::RiskNeutralObjective< Real >::GradientSampler_

private

Definition at line 58 of file ROL_RiskNeutralObjective.hpp.

Referenced by ROL::RiskNeutralObjective< Real >::gradient(), and ROL::RiskNeutralObjective< Real >::update().

template<class Real >

Ptr<SampleGenerator<Real> > ROL::RiskNeutralObjective< Real >::HessianSampler_

private

Definition at line 59 of file ROL_RiskNeutralObjective.hpp.

Referenced by ROL::RiskNeutralObjective< Real >::hessVec(), and ROL::RiskNeutralObjective< Real >::update().

template<class Real >

Real ROL::RiskNeutralObjective< Real >::value_

private

Definition at line 61 of file ROL_RiskNeutralObjective.hpp.

Referenced by ROL::RiskNeutralObjective< Real >::update(), and ROL::RiskNeutralObjective< Real >::value().

template<class Real >

Ptr<Vector<Real> > ROL::RiskNeutralObjective< Real >::gradient_

private

Definition at line 62 of file ROL_RiskNeutralObjective.hpp.

Referenced by ROL::RiskNeutralObjective< Real >::gradient(), ROL::RiskNeutralObjective< Real >::initialize(), and ROL::RiskNeutralObjective< Real >::update().

template<class Real >

Ptr<Vector<Real> > ROL::RiskNeutralObjective< Real >::pointDual_

private

Definition at line 63 of file ROL_RiskNeutralObjective.hpp.

Referenced by ROL::RiskNeutralObjective< Real >::gradient(), ROL::RiskNeutralObjective< Real >::hessVec(), and ROL::RiskNeutralObjective< Real >::initialize().

template<class Real >

Ptr<Vector<Real> > ROL::RiskNeutralObjective< Real >::sumDual_

private

Definition at line 64 of file ROL_RiskNeutralObjective.hpp.

Referenced by ROL::RiskNeutralObjective< Real >::gradient(), ROL::RiskNeutralObjective< Real >::hessVec(), and ROL::RiskNeutralObjective< Real >::initialize().

template<class Real >

bool ROL::RiskNeutralObjective< Real >::firstUpdate_

private

Definition at line 66 of file ROL_RiskNeutralObjective.hpp.

Referenced by ROL::RiskNeutralObjective< Real >::initialize().

template<class Real >

bool ROL::RiskNeutralObjective< Real >::storage_

private

Definition at line 67 of file ROL_RiskNeutralObjective.hpp.

Referenced by ROL::RiskNeutralObjective< Real >::getGradient(), ROL::RiskNeutralObjective< Real >::getValue(), and ROL::RiskNeutralObjective< Real >::update().

template<class Real >

std::map<std::vector<Real>,Real> ROL::RiskNeutralObjective< Real >::value_storage_

private

Definition at line 69 of file ROL_RiskNeutralObjective.hpp.

Referenced by ROL::RiskNeutralObjective< Real >::getValue(), ROL::RiskNeutralObjective< Real >::RiskNeutralObjective(), and ROL::RiskNeutralObjective< Real >::update().

template<class Real >

std::map<std::vector<Real>,Ptr<Vector<Real> > > ROL::RiskNeutralObjective< Real >::gradient_storage_

private

Definition at line 70 of file ROL_RiskNeutralObjective.hpp.

Referenced by ROL::RiskNeutralObjective< Real >::getGradient(), ROL::RiskNeutralObjective< Real >::RiskNeutralObjective(), and ROL::RiskNeutralObjective< Real >::update().

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

• ROL_RiskNeutralObjective.hpp