#include <ROL_SimulatedObjectiveCVaR.hpp>

Inheritance diagram for ROL::SimulatedObjectiveCVaR< Real >:

Public Member Functions
virtual	~SimulatedObjectiveCVaR ()

	SimulatedObjectiveCVaR (const ROL::Ptr< SampleGenerator< Real > > &sampler, const ROL::Ptr< Objective_SimOpt< Real > > &pobj, const ROL::Ptr< PlusFunction< Real > > &pfunc, const Real &alpha)

void	update (const Vector< Real > &x, bool flag=true, int iter=-1)
	Update objective function. More...

void	update (const Vector< Real > &x, UpdateType type, int iter=-1)
	Update objective function. More...

Real	value (const Vector< Real > &x, Real &tol)
	Compute value. More...

virtual void	gradient (Vector< Real > &g, const Vector< Real > &x, Real &tol)
	Compute gradient. More...

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. More...

virtual void	hessVec (Vector< Real > &hv, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
	Apply Hessian approximation to vector. 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 void	precond (Vector< Real > &Pv, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
	Apply preconditioner to vector. More...

virtual void	prox (Vector< Real > &Pv, const Vector< Real > &v, Real t, Real &tol)
	Compute the proximity operator. More...

virtual void	proxJacVec (Vector< Real > &Jv, const Vector< Real > &v, const Vector< Real > &x, Real t, Real &tol)
	Apply the Jacobian of the proximity operator. 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 std::vector < std::vector< Real > >	checkProxJacVec (const Vector< Real > &x, const Vector< Real > &v, Real t=Real(1), bool printToStream=true, std::ostream &outStream=std::cout, int numSteps=ROL_NUM_CHECKDERIV_STEPS)
	Finite-difference proximity operator Jacobian-applied-to-vector check. More...

virtual void	setParameter (const std::vector< Real > &param)

Private Attributes
const ROL::Ptr < SampleGenerator< Real > >	sampler_

const ROL::Ptr < Objective_SimOpt< Real > >	pobj_

const ROL::Ptr< PlusFunction < Real > >	pfunc_

const Real	alpha_

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::SimulatedObjectiveCVaR< Real >

Definition at line 21 of file ROL_SimulatedObjectiveCVaR.hpp.

Constructor & Destructor Documentation

template<class Real >

virtual ROL::SimulatedObjectiveCVaR< Real >::~SimulatedObjectiveCVaR ( )

inlinevirtual

Definition at line 30 of file ROL_SimulatedObjectiveCVaR.hpp.

template<class Real >

ROL::SimulatedObjectiveCVaR< Real >::SimulatedObjectiveCVaR	(	const ROL::Ptr< SampleGenerator< Real > > &	sampler,
		const ROL::Ptr< Objective_SimOpt< Real > > &	pobj,
		const ROL::Ptr< PlusFunction< Real > > &	pfunc,
		const Real &	alpha
	)

inline

Definition at line 32 of file ROL_SimulatedObjectiveCVaR.hpp.

Member Function Documentation

template<class Real >

void ROL::SimulatedObjectiveCVaR< 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 38 of file ROL_SimulatedObjectiveCVaR.hpp.

References ROL::SimulatedObjectiveCVaR< Real >::pobj_.

template<class Real >

void ROL::SimulatedObjectiveCVaR< Real >::update	(	const Vector< Real > &	x,
		UpdateType	type,
		int	iter = `-1`
	)

inlinevirtual

Update objective function.

This function updates the objective function at new iterations.

Parameters

[in]	x	is the new iterate.
[in]	type	is the type of update requested.
[in]	iter	is the outer algorithm iterations count.

Reimplemented from ROL::Objective< Real >.

Definition at line 42 of file ROL_SimulatedObjectiveCVaR.hpp.

References ROL::SimulatedObjectiveCVaR< Real >::pobj_.

template<class Real >

Real ROL::SimulatedObjectiveCVaR< 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 46 of file ROL_SimulatedObjectiveCVaR.hpp.

References ROL::SimulatedObjectiveCVaR< Real >::alpha_, ROL::SimulatedVector< Real >::get(), ROL::Vector_SimOpt< Real >::get_1(), ROL::Vector_SimOpt< Real >::get_2(), ROL::RiskVector< Real >::getStatistic(), ROL::RiskVector< Real >::getVector(), ROL::SimulatedVector< Real >::numVectors(), ROL::SimulatedObjectiveCVaR< Real >::pfunc_, ROL::SimulatedObjectiveCVaR< Real >::pobj_, and ROL::SimulatedObjectiveCVaR< Real >::sampler_.

template<class Real >

virtual void ROL::SimulatedObjectiveCVaR< 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 78 of file ROL_SimulatedObjectiveCVaR.hpp.

References ROL::SimulatedObjectiveCVaR< Real >::alpha_, ROL::SimulatedVector< Real >::get(), ROL::Vector_SimOpt< Real >::get_1(), ROL::Vector_SimOpt< Real >::get_2(), ROL::RiskVector< Real >::getStatistic(), ROL::RiskVector< Real >::getVector(), ROL::SimulatedVector< Real >::numVectors(), ROL::SimulatedObjectiveCVaR< Real >::pfunc_, ROL::SimulatedObjectiveCVaR< Real >::pobj_, ROL::SimulatedObjectiveCVaR< Real >::sampler_, ROL::RiskVector< Real >::setStatistic(), and ROL::Vector< Real >::zero().