#include <ROL_Constraint_SerialSimOpt.hpp>

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

Public Member Functions
	NonlinearLeastSquaresObjective_SimOpt (const ROL::Ptr< Constraint_SimOpt< Real > > &con, const Vector< Real > &uvec, const Vector< Real > &zvec, const Vector< Real > &cvec, const bool GNH=false)
	Constructor. More...

void	update (const Vector< Real > &u, 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 > &u, Real &tol)
	Compute gradient. More...

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

void	precond (Vector< Real > &pv, const Vector< Real > &v, const Vector< Real > &u, 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 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 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 Attributes
const ROL::Ptr < Constraint_SimOpt< Real > >	con_

const bool	GaussNewtonHessian_

ROL::Ptr< Vector< Real > >	c1_

ROL::Ptr< Vector< Real > >	c2_

ROL::Ptr< Vector< Real > >	cdual_

ROL::Ptr< Vector< Real > >	udual_

ROL::Ptr< Vector< Real > >	z_

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::ROL::NonlinearLeastSquaresObjective_SimOpt< Real >

Definition at line 77 of file ROL_Constraint_SerialSimOpt.hpp.

Constructor & Destructor Documentation

template<class Real >

ROL::ROL::NonlinearLeastSquaresObjective_SimOpt< Real >::NonlinearLeastSquaresObjective_SimOpt	(	const ROL::Ptr< Constraint_SimOpt< Real > > &	con,
		const Vector< Real > &	uvec,
		const Vector< Real > &	zvec,
		const Vector< Real > &	cvec,
		const bool	GNH = `false`
	)

inline

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 92 of file ROL_Constraint_SerialSimOpt.hpp.

Member Function Documentation

template<class Real >

void ROL::ROL::NonlinearLeastSquaresObjective_SimOpt< 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 105 of file ROL_Constraint_SerialSimOpt.hpp.

template<class Real >

Real ROL::ROL::NonlinearLeastSquaresObjective_SimOpt< 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 112 of file ROL_Constraint_SerialSimOpt.hpp.

template<class Real >

void ROL::ROL::NonlinearLeastSquaresObjective_SimOpt< 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 117 of file ROL_Constraint_SerialSimOpt.hpp.

template<class Real >

void ROL::ROL::NonlinearLeastSquaresObjective_SimOpt< 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 121 of file ROL_Constraint_SerialSimOpt.hpp.

template<class Real >

void ROL::ROL::NonlinearLeastSquaresObjective_SimOpt< 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.