ROL::StochasticObjective< Real > Class Template Reference

#include <ROL_StochasticObjective.hpp>

Inheritance diagram for ROL::StochasticObjective< Real >:

Public Member Functions
virtual	~StochasticObjective ()
	StochasticObjective (const Ptr< Objective< Real >> &obj, const Ptr< RandVarFunctional< Real >> &rvf, const Ptr< SampleGenerator< Real >> &vsampler, const Ptr< SampleGenerator< Real >> &gsampler, const Ptr< SampleGenerator< Real >> &hsampler, const bool storage=true, const int comp=0, const int index=0)
	StochasticObjective (const Ptr< Objective< Real >> &obj, const Ptr< RandVarFunctional< Real >> &rvf, const Ptr< SampleGenerator< Real >> &vsampler, const Ptr< SampleGenerator< Real >> &gsampler, const bool storage=true, const int comp=0, const int index=0)
	StochasticObjective (const Ptr< Objective< Real >> &obj, const Ptr< RandVarFunctional< Real >> &rvf, const Ptr< SampleGenerator< Real >> &sampler, const bool storage=true, const int comp=0, const int index=0)
	StochasticObjective (const Ptr< Objective< Real >> &obj, ParameterList &parlist, const Ptr< SampleGenerator< Real >> &vsampler, const Ptr< SampleGenerator< Real >> &gsampler, const Ptr< SampleGenerator< Real >> &hsampler, const int comp=0, const int index=0)
	StochasticObjective (const Ptr< Objective< Real >> &obj, ROL::ParameterList &parlist, const Ptr< SampleGenerator< Real >> &vsampler, const Ptr< SampleGenerator< Real >> &gsampler, const int comp=0, const int index=0)
	StochasticObjective (const Ptr< Objective< Real >> &obj, ROL::ParameterList &parlist, const Ptr< SampleGenerator< Real >> &sampler, const int comp=0, const int index=0)
Real	computeStatistic (const Vector< Real > &x) const
void	setIndex (int ind)
void	update (const Vector< Real > &x, UpdateType type, int iter=-1)
	Update objective function. More...
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...
virtual void	precond (Vector< Real > &Pv, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
	Apply preconditioner to vector. More...
Public Member Functions inherited from ROL::Objective< Real >
virtual	~Objective ()
	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	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 Member Functions
Ptr< const Vector< Real > >	getConstVector (const Vector< Real > &x) const
Ptr< Vector< Real > >	getVector (Vector< Real > &x) const
Ptr< const std::vector< Real > >	getConstStat (const Vector< Real > &x) const
Ptr< std::vector< Real > >	getStat (Vector< Real > &x) const

Private Attributes
Ptr< Objective< Real > >	obj_
Ptr< RandVarFunctional< Real > >	rvf_
Ptr< SampleGenerator< Real > >	vsampler_
Ptr< SampleGenerator< Real > >	gsampler_
Ptr< SampleGenerator< Real > >	hsampler_
const int	comp_
int	index_

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::StochasticObjective< Real >

Definition at line 22 of file ROL_StochasticObjective.hpp.

Constructor & Destructor Documentation

template<class Real >

virtual ROL::StochasticObjective< Real >::~StochasticObjective ( )

inlinevirtual

Definition at line 65 of file ROL_StochasticObjective.hpp.

template<class Real >

ROL::StochasticObjective< Real >::StochasticObjective ( const Ptr< Objective< Real >> &  obj, const Ptr< RandVarFunctional< Real >> &  rvf, const Ptr< SampleGenerator< Real >> &  vsampler, const Ptr< SampleGenerator< Real >> &  gsampler, const Ptr< SampleGenerator< Real >> &  hsampler, const bool  storage = true, const int  comp = 0, const int  index = 0  )

inline

Definition at line 67 of file ROL_StochasticObjective.hpp.

template<class Real >

ROL::StochasticObjective< Real >::StochasticObjective ( const Ptr< Objective< Real >> &  obj, const Ptr< RandVarFunctional< Real >> &  rvf, const Ptr< SampleGenerator< Real >> &  vsampler, const Ptr< SampleGenerator< Real >> &  gsampler, const bool  storage = true, const int  comp = 0, const int  index = 0  )

inline

Definition at line 80 of file ROL_StochasticObjective.hpp.

template<class Real >

ROL::StochasticObjective< Real >::StochasticObjective ( const Ptr< Objective< Real >> &  obj, const Ptr< RandVarFunctional< Real >> &  rvf, const Ptr< SampleGenerator< Real >> &  sampler, const bool  storage = true, const int  comp = 0, const int  index = 0  )

inline

Definition at line 88 of file ROL_StochasticObjective.hpp.

template<class Real >

ROL::StochasticObjective< Real >::StochasticObjective ( const Ptr< Objective< Real >> &  obj, ParameterList &  parlist, const Ptr< SampleGenerator< Real >> &  vsampler, const Ptr< SampleGenerator< Real >> &  gsampler, const Ptr< SampleGenerator< Real >> &  hsampler, const int  comp = 0, const int  index = 0  )

inline

Definition at line 95 of file ROL_StochasticObjective.hpp.

References ROL::StochasticObjective< Real >::rvf_.

template<class Real >

ROL::StochasticObjective< Real >::StochasticObjective ( const Ptr< Objective< Real >> &  obj, ROL::ParameterList &  parlist, const Ptr< SampleGenerator< Real >> &  vsampler, const Ptr< SampleGenerator< Real >> &  gsampler, const int  comp = 0, const int  index = 0  )

inline

Definition at line 117 of file ROL_StochasticObjective.hpp.

template<class Real >

ROL::StochasticObjective< Real >::StochasticObjective ( const Ptr< Objective< Real >> &  obj, ROL::ParameterList &  parlist, const Ptr< SampleGenerator< Real >> &  sampler, const int  comp = 0, const int  index = 0  )

inline

Definition at line 124 of file ROL_StochasticObjective.hpp.

Member Function Documentation

template<class Real >

Ptr<const Vector<Real> > ROL::StochasticObjective< Real >::getConstVector ( const Vector< Real > &  x ) const

inlineprivate

Definition at line 36 of file ROL_StochasticObjective.hpp.

References ROL::RiskVector< Real >::getVector().

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

template<class Real >

Ptr<Vector<Real> > ROL::StochasticObjective< Real >::getVector ( Vector< Real > &  x ) const

inlineprivate

Definition at line 41 of file ROL_StochasticObjective.hpp.

References ROL::RiskVector< Real >::getVector().

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

template<class Real >

Ptr<const std::vector<Real> > ROL::StochasticObjective< Real >::getConstStat ( const Vector< Real > &  x ) const

inlineprivate

Definition at line 46 of file ROL_StochasticObjective.hpp.

References ROL::StochasticObjective< Real >::comp_, ROL::RiskVector< Real >::getStatistic(), and ROL::StochasticObjective< Real >::index_.

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

template<class Real >

Ptr<std::vector<Real> > ROL::StochasticObjective< Real >::getStat ( Vector< Real > &  x ) const

inlineprivate

Definition at line 55 of file ROL_StochasticObjective.hpp.

References ROL::StochasticObjective< Real >::comp_, ROL::RiskVector< Real >::getStatistic(), and ROL::StochasticObjective< Real >::index_.

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

template<class Real >

Real ROL::StochasticObjective< Real >::computeStatistic ( const Vector< Real > &  x ) const

inline

Definition at line 130 of file ROL_StochasticObjective.hpp.

References ROL::StochasticObjective< Real >::getConstStat(), and ROL::StochasticObjective< Real >::rvf_.

template<class Real >

void ROL::StochasticObjective< Real >::setIndex ( int  ind )

inline

Definition at line 135 of file ROL_StochasticObjective.hpp.

References ROL::StochasticObjective< Real >::index_.

template<class Real >

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

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 139 of file ROL_StochasticObjective.hpp.

References ROL::StochasticObjective< Real >::getConstVector(), ROL::StochasticObjective< Real >::gsampler_, ROL::StochasticObjective< Real >::hsampler_, ROL::StochasticObjective< Real >::obj_, ROL::Revert, ROL::StochasticObjective< Real >::rvf_, ROL::Trial, and ROL::StochasticObjective< Real >::vsampler_.

template<class Real >

void ROL::StochasticObjective< 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 153 of file ROL_StochasticObjective.hpp.

References ROL::StochasticObjective< Real >::getConstVector(), ROL::StochasticObjective< Real >::gsampler_, ROL::StochasticObjective< Real >::hsampler_, ROL::StochasticObjective< Real >::obj_, ROL::StochasticObjective< Real >::rvf_, and ROL::StochasticObjective< Real >::vsampler_.

template<class Real >

Real ROL::StochasticObjective< 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 167 of file ROL_StochasticObjective.hpp.

References ROL::StochasticObjective< Real >::getConstStat(), ROL::StochasticObjective< Real >::getConstVector(), ROL::StochasticObjective< Real >::obj_, ROL::StochasticObjective< Real >::rvf_, and ROL::StochasticObjective< Real >::vsampler_.

template<class Real >

void ROL::StochasticObjective< 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 180 of file ROL_StochasticObjective.hpp.

References ROL::StochasticObjective< Real >::getConstStat(), ROL::StochasticObjective< Real >::getConstVector(), ROL::StochasticObjective< Real >::getStat(), ROL::StochasticObjective< Real >::getVector(), ROL::StochasticObjective< Real >::gsampler_, ROL::StochasticObjective< Real >::obj_, ROL::StochasticObjective< Real >::rvf_, and ROL::Vector< Real >::zero().

template<class Real >

void ROL::StochasticObjective< 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 194 of file ROL_StochasticObjective.hpp.

References ROL::StochasticObjective< Real >::getConstStat(), ROL::StochasticObjective< Real >::getConstVector(), ROL::StochasticObjective< Real >::getStat(), ROL::StochasticObjective< Real >::getVector(), ROL::StochasticObjective< Real >::hsampler_, ROL::StochasticObjective< Real >::obj_, ROL::StochasticObjective< Real >::rvf_, and ROL::Vector< Real >::zero().

template<class Real >

virtual void ROL::StochasticObjective< 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.

Reimplemented from ROL::Objective< Real >.

Definition at line 211 of file ROL_StochasticObjective.hpp.

References ROL::Vector< Real >::dual(), and ROL::Vector< Real >::set().

Member Data Documentation

template<class Real >

Ptr<Objective<Real> > ROL::StochasticObjective< Real >::obj_

private

Definition at line 25 of file ROL_StochasticObjective.hpp.

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

template<class Real >

Ptr<RandVarFunctional<Real> > ROL::StochasticObjective< Real >::rvf_

private

Definition at line 26 of file ROL_StochasticObjective.hpp.

Referenced by ROL::StochasticObjective< Real >::computeStatistic(), ROL::StochasticObjective< Real >::gradient(), ROL::StochasticObjective< Real >::hessVec(), ROL::StochasticObjective< Real >::StochasticObjective(), ROL::StochasticObjective< Real >::update(), and ROL::StochasticObjective< Real >::value().

template<class Real >

Ptr<SampleGenerator<Real> > ROL::StochasticObjective< Real >::vsampler_

private

Definition at line 29 of file ROL_StochasticObjective.hpp.

Referenced by ROL::StochasticObjective< Real >::update(), and ROL::StochasticObjective< Real >::value().

template<class Real >

Ptr<SampleGenerator<Real> > ROL::StochasticObjective< Real >::gsampler_

private

Definition at line 30 of file ROL_StochasticObjective.hpp.

Referenced by ROL::StochasticObjective< Real >::gradient(), and ROL::StochasticObjective< Real >::update().

template<class Real >

Ptr<SampleGenerator<Real> > ROL::StochasticObjective< Real >::hsampler_

private

Definition at line 31 of file ROL_StochasticObjective.hpp.

Referenced by ROL::StochasticObjective< Real >::hessVec(), and ROL::StochasticObjective< Real >::update().

template<class Real >

const int ROL::StochasticObjective< Real >::comp_

private

Definition at line 33 of file ROL_StochasticObjective.hpp.

Referenced by ROL::StochasticObjective< Real >::getConstStat(), and ROL::StochasticObjective< Real >::getStat().

template<class Real >

int ROL::StochasticObjective< Real >::index_

private

Definition at line 34 of file ROL_StochasticObjective.hpp.

Referenced by ROL::StochasticObjective< Real >::getConstStat(), ROL::StochasticObjective< Real >::getStat(), and ROL::StochasticObjective< Real >::setIndex().

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The documentation for this class was generated from the following file:

• ROL_StochasticObjective.hpp