This class strips out the slack variables from objective evaluations to create the new objective \( F(x,s) = f(x) \). More...

#include <ROL_SlacklessObjective.hpp>

Inheritance diagram for ROL::SlacklessObjective< Real >:

Public Member Functions
	SlacklessObjective (const ROL::Ptr< Objective< Real > > &obj)

	~SlacklessObjective ()

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...

Real	dirDeriv (const Vector< Real > &x, const Vector< Real > &d, Real &tol)
	Compute directional derivative. More...

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

void	invHessVec (Vector< Real > &ihv, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
	Apply inverse 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...

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

Public Member Functions inherited from ROL::Objective< Real >
virtual	~Objective ()

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
ROL::Ptr< Vector< Real > >	getOpt (Vector< Real > &xs)

ROL::Ptr< const Vector< Real > >	getOpt (const Vector< Real > &xs)

void	zeroSlack (Vector< Real > &x)

Private Attributes
ROL::Ptr< Objective< Real > >	obj_

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::SlacklessObjective< Real >

This class strips out the slack variables from objective evaluations to create the new objective \( F(x,s) = f(x) \).

Definition at line 59 of file ROL_SlacklessObjective.hpp.

Constructor & Destructor Documentation

template<class Real >

ROL::SlacklessObjective< Real >::SlacklessObjective ( const ROL::Ptr< Objective< Real > > & obj )

inline

Definition at line 81 of file ROL_SlacklessObjective.hpp.

template<class Real >

ROL::SlacklessObjective< Real >::~SlacklessObjective ( )

inline

Definition at line 82 of file ROL_SlacklessObjective.hpp.

Member Function Documentation

template<class Real >

ROL::Ptr<Vector<Real> > ROL::SlacklessObjective< Real >::getOpt ( Vector< Real > & xs )

inlineprivate

Definition at line 63 of file ROL_SlacklessObjective.hpp.

Referenced by ROL::SlacklessObjective< Real >::dirDeriv(), ROL::SlacklessObjective< Real >::gradient(), ROL::SlacklessObjective< Real >::hessVec(), ROL::SlacklessObjective< Real >::invHessVec(), ROL::SlacklessObjective< Real >::precond(), ROL::SlacklessObjective< Real >::update(), and ROL::SlacklessObjective< Real >::value().

template<class Real >

ROL::Ptr<const Vector<Real> > ROL::SlacklessObjective< Real >::getOpt ( const Vector< Real > & xs )

inlineprivate

Definition at line 67 of file ROL_SlacklessObjective.hpp.

template<class Real >

void ROL::SlacklessObjective< Real >::zeroSlack ( Vector< Real > & x )

inlineprivate

Definition at line 71 of file ROL_SlacklessObjective.hpp.

References ROL::PartitionedVector< Real >::get(), and ROL::PartitionedVector< Real >::numVectors().

Referenced by ROL::SlacklessObjective< Real >::gradient(), ROL::SlacklessObjective< Real >::hessVec(), ROL::SlacklessObjective< Real >::invHessVec(), and ROL::SlacklessObjective< Real >::precond().

template<class Real >

void ROL::SlacklessObjective< 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 84 of file ROL_SlacklessObjective.hpp.

References ROL::SlacklessObjective< Real >::getOpt(), and ROL::SlacklessObjective< Real >::obj_.

template<class Real >

Real ROL::SlacklessObjective< 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 88 of file ROL_SlacklessObjective.hpp.

References ROL::SlacklessObjective< Real >::getOpt(), and ROL::SlacklessObjective< Real >::obj_.

template<class Real >

void ROL::SlacklessObjective< 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 92 of file ROL_SlacklessObjective.hpp.

References ROL::SlacklessObjective< Real >::getOpt(), ROL::SlacklessObjective< Real >::obj_, and ROL::SlacklessObjective< Real >::zeroSlack().

template<class Real >

Real ROL::SlacklessObjective< Real >::dirDeriv	(	const Vector< Real > &	x,
		const Vector< Real > &	d,
		Real &	tol
	)

inlinevirtual

Compute directional derivative.

This function returns the directional derivative of the objective function in the \(d\) direction.

Parameters

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

Reimplemented from ROL::Objective< Real >.

Definition at line 97 of file ROL_SlacklessObjective.hpp.

References ROL::SlacklessObjective< Real >::getOpt(), and ROL::SlacklessObjective< Real >::obj_.

template<class Real >

void ROL::SlacklessObjective< 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 101 of file ROL_SlacklessObjective.hpp.

References ROL::SlacklessObjective< Real >::getOpt(), ROL::SlacklessObjective< Real >::obj_, and ROL::SlacklessObjective< Real >::zeroSlack().

template<class Real >

void ROL::SlacklessObjective< Real >::invHessVec	(	Vector< Real > &	hv,
		const Vector< Real > &	v,
		const Vector< Real > &	x,
		Real &	tol
	)

inlinevirtual

Apply inverse Hessian approximation to vector.

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

Parameters

[out]	hv	is the action of the inverse 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 106 of file ROL_SlacklessObjective.hpp.

References ROL::SlacklessObjective< Real >::getOpt(), ROL::SlacklessObjective< Real >::obj_, and ROL::SlacklessObjective< Real >::zeroSlack().

template<class Real >

void ROL::SlacklessObjective< 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.