ROL
Public Member Functions | Private Attributes | List of all members
ROL::RiskAverseObjective< Real > Class Template Reference

#include <ROL_RiskAverseObjective.hpp>

+ Inheritance diagram for ROL::RiskAverseObjective< Real >:

Public Member Functions

virtual ~RiskAverseObjective ()
 
 RiskAverseObjective (ParametrizedObjective< Real > &pObj, RiskMeasure< Real > &rm, SampleGenerator< Real > &vsampler, SampleGenerator< Real > &gsampler, bool storage=true)
 
 RiskAverseObjective (ParametrizedObjective< Real > &pObj, RiskMeasure< Real > &rm, SampleGenerator< Real > &sampler, bool storage=true)
 
virtual void update (const Vector< Real > &x, bool flag=true, int iter=-1)
 Update objective function. More...
 
virtual Real value (const Vector< Real > &x, Real &tol)
 Compute value. More...
 
virtual void gradient (Vector< Real > &g, const Vector< Real > &x, Real &tol)
 Compute gradient. More...
 
virtual 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 ()
 
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

Teuchos::RCP
< ParametrizedObjective< Real > > 
pObj_
 
Teuchos::RCP< SampleGenerator
< Real > > 
vsampler_
 
Teuchos::RCP< SampleGenerator
< Real > > 
gsampler_
 
Teuchos::RCP< RiskMeasure< Real > > rm_
 
bool storage_
 
std::map< std::vector< Real >
, Real > 
value_storage_
 
std::map< std::vector< Real >
, Teuchos::RCP< Vector< Real > > > 
gradient_storage_
 

Detailed Description

template<class Real>
class ROL::RiskAverseObjective< Real >

Definition at line 57 of file ROL_RiskAverseObjective.hpp.

Constructor & Destructor Documentation

template<class Real >
virtual ROL::RiskAverseObjective< Real >::~RiskAverseObjective ( )
inlinevirtual

Definition at line 71 of file ROL_RiskAverseObjective.hpp.

template<class Real >
ROL::RiskAverseObjective< Real >::RiskAverseObjective ( ParametrizedObjective< Real > &  pObj,
RiskMeasure< Real > &  rm,
SampleGenerator< Real > &  vsampler,
SampleGenerator< Real > &  gsampler,
bool  storage = true 
)
inline
template<class Real >
ROL::RiskAverseObjective< Real >::RiskAverseObjective ( ParametrizedObjective< Real > &  pObj,
RiskMeasure< Real > &  rm,
SampleGenerator< Real > &  sampler,
bool  storage = true 
)
inline

Member Function Documentation

template<class Real >
virtual void ROL::RiskAverseObjective< 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]xis the new iterate.
[in]flagis true if the iterate has changed.
[in]iteris the outer algorithm iterations count.

Reimplemented from ROL::Objective< Real >.

Definition at line 102 of file ROL_RiskAverseObjective.hpp.

References ROL::RiskAverseObjective< Real >::gradient_storage_, ROL::RiskAverseObjective< Real >::gsampler_, ROL::RiskAverseObjective< Real >::pObj_, ROL::RiskAverseObjective< Real >::storage_, ROL::RiskAverseObjective< Real >::value_storage_, and ROL::RiskAverseObjective< Real >::vsampler_.

template<class Real >
virtual Real ROL::RiskAverseObjective< Real >::value ( const Vector< Real > &  x,
Real &  tol 
)
inlinevirtual

Compute value.

This function returns the objective function value.

Parameters
[in]xis the current iterate.
[in]tolis a tolerance for inexact objective function computation.

Implements ROL::Objective< Real >.

Definition at line 116 of file ROL_RiskAverseObjective.hpp.

References ROL::RiskAverseObjective< Real >::pObj_, ROL::RiskAverseObjective< Real >::rm_, ROL::RiskAverseObjective< Real >::storage_, ROL::RiskAverseObjective< Real >::value_storage_, and ROL::RiskAverseObjective< Real >::vsampler_.

template<class Real >
virtual void ROL::RiskAverseObjective< Real >::gradient ( Vector< Real > &  g,
const Vector< Real > &  x,
Real &  tol 
)
inlinevirtual

Compute gradient.

This function returns the objective function gradient.

Parameters
[out]gis the gradient.
[in]xis the current iterate.
[in]tolis 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 136 of file ROL_RiskAverseObjective.hpp.

References ROL::RiskAverseObjective< Real >::gradient_storage_, ROL::RiskAverseObjective< Real >::gsampler_, ROL::RiskAverseObjective< Real >::pObj_, ROL::RiskAverseObjective< Real >::rm_, ROL::RiskAverseObjective< Real >::storage_, ROL::RiskAverseObjective< Real >::value_storage_, and ROL::Vector< Real >::zero().

template<class Real >
virtual void ROL::RiskAverseObjective< 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]hvis the the action of the Hessian on \(v\).
[in]vis the direction vector.
[in]xis the current iterate.
[in]tolis a tolerance for inexact objective function computation.

Reimplemented from ROL::Objective< Real >.

Definition at line 170 of file ROL_RiskAverseObjective.hpp.

References ROL::RiskAverseObjective< Real >::gradient_storage_, ROL::RiskAverseObjective< Real >::gsampler_, ROL::RiskAverseObjective< Real >::pObj_, ROL::RiskAverseObjective< Real >::rm_, ROL::RiskAverseObjective< Real >::storage_, ROL::RiskAverseObjective< Real >::value_storage_, and ROL::Vector< Real >::zero().

template<class Real >
virtual void ROL::RiskAverseObjective< 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]Pvis the action of the Hessian preconditioner on \(v\).
[in]vis the direction vector.
[in]xis the current iterate.
[in]tolis a tolerance for inexact objective function computation.

Reimplemented from ROL::Objective< Real >.

Definition at line 209 of file ROL_RiskAverseObjective.hpp.

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

Member Data Documentation

template<class Real >
Teuchos::RCP<ParametrizedObjective<Real> > ROL::RiskAverseObjective< Real >::pObj_
private
template<class Real >
Teuchos::RCP<SampleGenerator<Real> > ROL::RiskAverseObjective< Real >::vsampler_
private
template<class Real >
Teuchos::RCP<SampleGenerator<Real> > ROL::RiskAverseObjective< Real >::gsampler_
private
template<class Real >
Teuchos::RCP<RiskMeasure<Real> > ROL::RiskAverseObjective< Real >::rm_
private
template<class Real >
bool ROL::RiskAverseObjective< Real >::storage_
private
template<class Real >
std::map<std::vector<Real>,Real> ROL::RiskAverseObjective< Real >::value_storage_
private
template<class Real >
std::map<std::vector<Real>,Teuchos::RCP<Vector<Real> > > ROL::RiskAverseObjective< Real >::gradient_storage_
private

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