Inheritance diagram for ROL::TypeP::InexactNewtonAlgorithm< Real >::NewtonObj:

Public Member Functions
	NewtonObj (const Ptr< Objective< Real >> &obj, const Vector< Real > &x, const Vector< Real > &g)

void	update (const Vector< Real > &x, UpdateType type, int iter)
	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...

int	numHessVec (bool reset=true)

void	setData (const Vector< Real > &x, const Vector< Real > &g)

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

	Objective ()

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

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 void	prox (Vector< Real > &Pv, const Vector< Real > &v, Real t, Real &tol)

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 Attributes
const Ptr< Objective< Real > >	obj_

const Ptr< Vector< Real > >	x_

const Ptr< Vector< Real > >	g_

Ptr< Vector< Real > >	pwa_

Ptr< Vector< Real > >	dwa_

Ptr< Vector< Real > >	Hx_

bool	isHessApplied_

int	nhess_

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

Detailed Description

template<typename Real>
class ROL::TypeP::InexactNewtonAlgorithm< Real >::NewtonObj

Definition at line 83 of file ROL_TypeP_InexactNewtonAlgorithm.hpp.

Constructor & Destructor Documentation

template<typename Real >

ROL::TypeP::InexactNewtonAlgorithm< Real >::NewtonObj::NewtonObj	(	const Ptr< Objective< Real >> &	obj,
		const Vector< Real > &	x,
		const Vector< Real > &	g
	)

inline

Definition at line 93 of file ROL_TypeP_InexactNewtonAlgorithm.hpp.

Member Function Documentation

template<typename Real >

void ROL::TypeP::InexactNewtonAlgorithm< Real >::NewtonObj::update	(	const Vector< Real > &	x,
		UpdateType	type,
		int	iter
	)

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 96 of file ROL_TypeP_InexactNewtonAlgorithm.hpp.

References ROL::TypeP::InexactNewtonAlgorithm< Real >::NewtonObj::isHessApplied_.

template<typename Real >

Real ROL::TypeP::InexactNewtonAlgorithm< Real >::NewtonObj::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 99 of file ROL_TypeP_InexactNewtonAlgorithm.hpp.

template<typename Real >

void ROL::TypeP::InexactNewtonAlgorithm< Real >::NewtonObj::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 111 of file ROL_TypeP_InexactNewtonAlgorithm.hpp.

References ROL::TypeP::InexactNewtonAlgorithm< Real >::NewtonObj::g_, ROL::TypeP::InexactNewtonAlgorithm< Real >::NewtonObj::Hx_, ROL::TypeP::InexactNewtonAlgorithm< Real >::NewtonObj::isHessApplied_, ROL::TypeP::InexactNewtonAlgorithm< Real >::NewtonObj::nhess_, ROL::TypeP::InexactNewtonAlgorithm< Real >::NewtonObj::obj_, ROL::Vector< Real >::plus(), ROL::TypeP::InexactNewtonAlgorithm< Real >::NewtonObj::pwa_, ROL::Vector< Real >::set(), and ROL::TypeP::InexactNewtonAlgorithm< Real >::NewtonObj::x_.

template<typename Real >

void ROL::TypeP::InexactNewtonAlgorithm< Real >::NewtonObj::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.