#include <ROL_Constraint_SerialSimOpt.hpp>

Inheritance diagram for ROL::ROL::NonlinearLeastSquaresObjective< Real >:

Public Member Functions
	NonlinearLeastSquaresObjective (const Ptr< Constraint< Real > > &con, const Vector< Real > &optvec, const Vector< Real > &convec, const bool GNH=false)
	Constructor.
void	update (const Vector< Real > &x, UpdateType type, int iter=-1) override
	Update objective function.
void	update (const Vector< Real > &x, bool flag=true, int iter=-1) override
	Update objective function.
Real	value (const Vector< Real > &x, Real &tol) override
	Compute value.
void	gradient (Vector< Real > &g, const Vector< Real > &x, Real &tol) override
	Compute gradient.
void	hessVec (Vector< Real > &hv, const Vector< Real > &v, const Vector< Real > &x, Real &tol) override
	Apply Hessian approximation to vector.
void	precond (Vector< Real > &Pv, const Vector< Real > &v, const Vector< Real > &x, Real &tol) override
	Apply preconditioner to vector.
void	setParameter (const std::vector< Real > &param) override
Public Member Functions inherited from ROL::ROL::Objective< Real >
virtual	~Objective ()
	Objective ()
virtual Real	dirDeriv (const Vector< Real > &x, const Vector< Real > &d, Real &tol)
	Compute directional derivative.
virtual void	invHessVec (Vector< Real > &hv, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
	Apply inverse Hessian approximation to vector.
virtual void	prox (Vector< Real > &Pv, const Vector< Real > &v, Real t, Real &tol)
	Compute the proximity operator.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.

Private Attributes
const Ptr< Constraint< Real > >	con_
const bool	GaussNewtonHessian_
Ptr< Vector< Real > >	c1_
Ptr< Vector< Real > >	c2_
Ptr< Vector< Real > >	c1dual_
Ptr< Vector< Real > >	x_

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

Detailed Description

template<typename Real>
class ROL::ROL::NonlinearLeastSquaresObjective< Real >

Definition at line 39 of file ROL_Constraint_SerialSimOpt.hpp.

Constructor & Destructor Documentation

◆ NonlinearLeastSquaresObjective()

template<typename Real>

ROL::ROL::NonlinearLeastSquaresObjective< Real >::NonlinearLeastSquaresObjective	(	const Ptr< Constraint< Real > > &	con,
		const Vector< Real > &	optvec,
		const Vector< Real > &	convec,
		const bool	GNH = false )

Constructor.

This function constructs a nonlinear least squares objective function.

Parameters

[in]	con	is the nonlinear equation to be solved.
[in]	vec	is a constraint space vector used for cloning.
[in]	GHN	is a flag dictating whether or not to use the Gauss-Newton Hessian.

Definition at line 16 of file ROL_NonlinearLeastSquaresObjective_Def.hpp.

References c1_, c1dual_, c2_, ROL::ROL::Vector< Real >::clone(), con_, ROL::ROL::Vector< Real >::dual(), GaussNewtonHessian_, and x_.

Member Function Documentation

◆ update() [1/2]

template<typename Real>

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

overridevirtual

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::ROL::Objective< Real >.

Definition at line 27 of file ROL_NonlinearLeastSquaresObjective_Def.hpp.

References c1_, c1dual_, con_, and ROL::ROL::ROL_EPSILON().

◆ update() [2/2]

template<typename Real>

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

overridevirtual

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::ROL::Objective< Real >.

Definition at line 35 of file ROL_NonlinearLeastSquaresObjective_Def.hpp.

References c1_, c1dual_, con_, and ROL::ROL::ROL_EPSILON().

◆ value()

template<typename Real>

Real ROL::ROL::NonlinearLeastSquaresObjective< Real >::value	(	const Vector< Real > &	x,
		Real &	tol )

overridevirtual

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::ROL::Objective< Real >.

Definition at line 43 of file ROL_NonlinearLeastSquaresObjective_Def.hpp.

References c1_.

◆ gradient()

template<typename Real>

void ROL::ROL::NonlinearLeastSquaresObjective< Real >::gradient	(	Vector< Real > &	g,
		const Vector< Real > &	x,
		Real &	tol )

overridevirtual

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::ROL::Objective< Real >.

Definition at line 49 of file ROL_NonlinearLeastSquaresObjective_Def.hpp.

References c1dual_, and con_.

◆ hessVec()

template<typename Real>

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

overridevirtual

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::ROL::Objective< Real >.

Definition at line 54 of file ROL_NonlinearLeastSquaresObjective_Def.hpp.

References c1dual_, c2_, con_, GaussNewtonHessian_, ROL::ROL::Vector< Real >::plus(), and x_.

◆ precond()

template<typename Real>

void ROL::ROL::NonlinearLeastSquaresObjective< Real >::precond	(	Vector< Real > &	Pv,
		const Vector< Real > &	v,
		const Vector< Real > &	x,
		Real &	tol )

overridevirtual

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.