Provides the interface for the progressive hedging probability objective. More...

#include <ROL_PH_ProbObjective.hpp>

Inheritance diagram for ROL::PH_ProbObjective< Real >:

Public Member Functions
	PH_ProbObjective (const Ptr< Objective< Real >> &obj, ParameterList &parlist)

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

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 void	precond (Vector< Real > &Pv, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
	Apply preconditioner 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...

Private Member Functions
void	getValue (const Vector< Real > &x, Real &tol)

void	getGradient (const Vector< Real > &x, Real &tol)

Real	smoothHeaviside (const Real x, const int deriv=0) const

Private Attributes
const Ptr< Objective< Real > >	obj_

Real	threshold_

Real	eps_

bool	isValueComputed_

Real	val_

bool	isGradientInitialized_

bool	isGradientComputed_

Ptr< Vector< Real > >	g_

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::PH_ProbObjective< Real >

Provides the interface for the progressive hedging probability objective.

Definition at line 58 of file ROL_PH_ProbObjective.hpp.

Constructor & Destructor Documentation

template<class Real >

ROL::PH_ProbObjective< Real >::PH_ProbObjective	(	const Ptr< Objective< Real >> &	obj,
		ParameterList &	parlist
	)

inline

Definition at line 109 of file ROL_PH_ProbObjective.hpp.

References ROL::PH_ProbObjective< Real >::eps_, and ROL::PH_ProbObjective< Real >::threshold_.

Member Function Documentation

template<class Real >

void ROL::PH_ProbObjective< Real >::getValue	(	const Vector< Real > &	x,
		Real &	tol
	)

inlineprivate

Definition at line 71 of file ROL_PH_ProbObjective.hpp.

References ROL::PH_ProbObjective< Real >::isValueComputed_, ROL::PH_ProbObjective< Real >::obj_, and ROL::PH_ProbObjective< Real >::val_.

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

template<class Real >

void ROL::PH_ProbObjective< Real >::getGradient	(	const Vector< Real > &	x,
		Real &	tol
	)

inlineprivate

Definition at line 78 of file ROL_PH_ProbObjective.hpp.

References ROL::Vector< Real >::dual(), ROL::PH_ProbObjective< Real >::g_, ROL::PH_ProbObjective< Real >::isGradientComputed_, ROL::PH_ProbObjective< Real >::isGradientInitialized_, and ROL::PH_ProbObjective< Real >::obj_.

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

template<class Real >

Real ROL::PH_ProbObjective< Real >::smoothHeaviside	(	const Real	x,
		const int	deriv = `0`
	)		const

inlineprivate

Definition at line 89 of file ROL_PH_ProbObjective.hpp.

References ROL::PH_ProbObjective< Real >::eps_.

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

template<class Real >

void ROL::PH_ProbObjective< 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 120 of file ROL_PH_ProbObjective.hpp.

References ROL::PH_ProbObjective< Real >::isGradientComputed_, ROL::PH_ProbObjective< Real >::isValueComputed_, and ROL::PH_ProbObjective< Real >::obj_.

template<class Real >

Real ROL::PH_ProbObjective< 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 126 of file ROL_PH_ProbObjective.hpp.

References ROL::PH_ProbObjective< Real >::getValue(), ROL::PH_ProbObjective< Real >::smoothHeaviside(), ROL::PH_ProbObjective< Real >::threshold_, and ROL::PH_ProbObjective< Real >::val_.

template<class Real >

void ROL::PH_ProbObjective< 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 135 of file ROL_PH_ProbObjective.hpp.

References ROL::PH_ProbObjective< Real >::g_, ROL::PH_ProbObjective< Real >::getGradient(), ROL::PH_ProbObjective< Real >::getValue(), ROL::Vector< Real >::scale(), ROL::Vector< Real >::set(), ROL::PH_ProbObjective< Real >::smoothHeaviside(), ROL::PH_ProbObjective< Real >::threshold_, ROL::PH_ProbObjective< Real >::val_, and ROL::Vector< Real >::zero().

template<class Real >

void ROL::PH_ProbObjective< 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.