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

Provides an interface for the Chebyshev-Kusuoka risk measure. More...

#include <ROL_ChebyshevKusuoka.hpp>

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

Public Member Functions

 ChebyshevKusuoka (Teuchos::ParameterList &parlist)
 Constructor. More...
 
 ChebyshevKusuoka (const Real lower, const Real upper, const int nQuad, const int wType, const Teuchos::RCP< PlusFunction< Real > > &pf)
 Constructor. More...
 
- Public Member Functions inherited from ROL::SpectralRisk< Real >
 SpectralRisk (void)
 
 SpectralRisk (const Teuchos::RCP< Distribution< Real > > &dist, const int nQuad, const Teuchos::RCP< PlusFunction< Real > > &pf)
 
 SpectralRisk (Teuchos::ParameterList &parlist)
 
 SpectralRisk (const std::vector< Real > &pts, const std::vector< Real > &wts, const Teuchos::RCP< PlusFunction< Real > > &pf)
 
Real computeStatistic (const Vector< Real > &x) const
 
void reset (Teuchos::RCP< Vector< Real > > &x0, const Vector< Real > &x)
 Reset internal risk measure storage. Called for value and gradient computation. More...
 
void reset (Teuchos::RCP< Vector< Real > > &x0, const Vector< Real > &x, Teuchos::RCP< Vector< Real > > &v0, const Vector< Real > &v)
 Reset internal risk measure storage. Called for Hessian-times-a-vector computation. More...
 
void update (const Real val, const Real weight)
 Update internal risk measure storage for value computation. More...
 
void update (const Real val, const Vector< Real > &g, const Real weight)
 Update internal risk measure storage for gradient computation. More...
 
void update (const Real val, const Vector< Real > &g, const Real gv, const Vector< Real > &hv, const Real weight)
 Update internal risk measure storage for Hessian-time-a-vector computation. More...
 
Real getValue (SampleGenerator< Real > &sampler)
 Return risk measure value. More...
 
void getGradient (Vector< Real > &g, SampleGenerator< Real > &sampler)
 Return risk measure (sub)gradient. More...
 
void getHessVec (Vector< Real > &hv, SampleGenerator< Real > &sampler)
 Return risk measure Hessian-times-a-vector. More...
 
- Public Member Functions inherited from ROL::RiskMeasure< Real >
virtual ~RiskMeasure ()
 
 RiskMeasure (void)
 

Private Member Functions

void checkInputs (void) const
 
void initialize (void)
 

Private Attributes

Teuchos::RCP< PlusFunction< Real > > plusFunction_
 
Real lower_
 
Real upper_
 
int nQuad_
 
int wType_
 
std::vector< Real > wts_
 
std::vector< Real > pts_
 

Additional Inherited Members

- Protected Member Functions inherited from ROL::SpectralRisk< Real >
void buildMixedQuantile (const std::vector< Real > &pts, const std::vector< Real > &wts, const Teuchos::RCP< PlusFunction< Real > > &pf)
 
void buildQuadFromDist (std::vector< Real > &pts, std::vector< Real > &wts, const int nQuad, const Teuchos::RCP< Distribution< Real > > &dist) const
 
void printQuad (const std::vector< Real > &pts, const std::vector< Real > &wts, const bool print=false) const
 
- Protected Attributes inherited from ROL::RiskMeasure< Real >
Real val_
 
Real gv_
 
Teuchos::RCP< Vector< Real > > g_
 
Teuchos::RCP< Vector< Real > > hv_
 
Teuchos::RCP< Vector< Real > > dualVector_
 
bool firstReset_
 

Detailed Description

template<class Real>
class ROL::ChebyshevKusuoka< Real >

Provides an interface for the Chebyshev-Kusuoka risk measure.

The Chebyshev-Kusuoka risk measure is defined as

\[ \mathcal{R}(X) = \int_{\alpha_0}^{\alpha_1} w(\alpha) \mathrm{CVaR}_{\alpha}(X) \,\mathrm{d}\alpha \]

where \(0\le \alpha_0 < \alpha_1 < 1\) and the conditional value-at-risk (CVaR) with confidence level \(0\le \alpha < 1\) is

\[ \mathrm{CVaR}_\alpha(X) = \inf_{t\in\mathbb{R}} \left\{ t + \frac{1}{1-\alpha} \mathbb{E}\left[(X-t)_+\right] \right\}, \quad (x)_+ = \max\{0,x\}. \]

There are three choices of weight functions \(w\): (i) the first weight function generates the Chebyshev polynomials of the first kind and has the specific form

\[ w(x) = \frac{1}{\sqrt{(x-\alpha_0)(\alpha_1-x)}}; \]

(ii) the second weight function generates the Chebyshev polynomials of the second kind and has the specific form

\[ w(x) = \sqrt{(x-\alpha_0)(\alpha_1-x)}; \]

and (iii) the third weight function is related again to the Chebyshev polynomials of the first kind and has the specific form

\[ w(x) = \sqrt{\frac{x-\alpha_0}{\alpha_1-x}}. \]

As defined, \(\mathcal{R}\) is a law-invariant coherent risk measure.

ROL implements \(\mathcal{R}\) by approximating the integral with the appropriate Gauss-Chebyshev quadrature rule. The corresponding quadrature points and weights are then used to construct a ROL::MixedQuantileQuadrangle risk measure. When using derivative-based optimization, the user can provide a smooth approximation of \((\cdot)_+\) using the ROL::PlusFunction class.

Definition at line 97 of file ROL_ChebyshevKusuoka.hpp.

Constructor & Destructor Documentation

◆ ChebyshevKusuoka() [1/2]

template<class Real>
ROL::ChebyshevKusuoka< Real >::ChebyshevKusuoka ( Teuchos::ParameterList &  parlist)
inline

Constructor.

Parameters
[in]parlistis a parameter list specifying inputs

parlist should contain sublists "SOL"->"Risk Measure"->"Chebyshev-Kusuoka" and the "Chebyshev-Kusuoka" sublist should have the following parameters

  • "Lower Bound" (between 0 and 1)
  • "Upper Bound" (between 0 and 1, greater than "Lower Bound")
  • "Weight Type" (either 1, 2, or 3)
  • "Number of Quadrature Points"
  • A sublist for plus function information.

Definition at line 158 of file ROL_ChebyshevKusuoka.hpp.

References ROL::ChebyshevKusuoka< Real >::checkInputs(), ROL::ChebyshevKusuoka< Real >::initialize(), ROL::ChebyshevKusuoka< Real >::lower_, ROL::ChebyshevKusuoka< Real >::nQuad_, ROL::ChebyshevKusuoka< Real >::plusFunction_, ROL::ChebyshevKusuoka< Real >::upper_, and ROL::ChebyshevKusuoka< Real >::wType_.

◆ ChebyshevKusuoka() [2/2]

template<class Real>
ROL::ChebyshevKusuoka< Real >::ChebyshevKusuoka ( const Real  lower,
const Real  upper,
const int  nQuad,
const int  wType,
const Teuchos::RCP< PlusFunction< Real > > &  pf 
)
inline

Constructor.

Parameters
[in]loweris the lower confidence level (between 0 and 1)
[in]upperis the upper confidence level (between 0 and 1, greater than lower)
[in]nQuadis the number of quadrature points
[in]wTypeis the weight type (either 1, 2, or 3)
[in]pfis the plus function or an approximation

Definition at line 181 of file ROL_ChebyshevKusuoka.hpp.

References ROL::ChebyshevKusuoka< Real >::checkInputs(), and ROL::ChebyshevKusuoka< Real >::initialize().

Member Function Documentation

◆ checkInputs()

template<class Real>
void ROL::ChebyshevKusuoka< Real >::checkInputs ( void  ) const
inlineprivate

◆ initialize()

template<class Real>
void ROL::ChebyshevKusuoka< Real >::initialize ( void  )
inlineprivate

Member Data Documentation

◆ plusFunction_

template<class Real>
Teuchos::RCP<PlusFunction<Real> > ROL::ChebyshevKusuoka< Real >::plusFunction_
private

◆ lower_

template<class Real>
Real ROL::ChebyshevKusuoka< Real >::lower_
private

◆ upper_

template<class Real>
Real ROL::ChebyshevKusuoka< Real >::upper_
private

◆ nQuad_

template<class Real>
int ROL::ChebyshevKusuoka< Real >::nQuad_
private

◆ wType_

template<class Real>
int ROL::ChebyshevKusuoka< Real >::wType_
private

◆ wts_

template<class Real>
std::vector<Real> ROL::ChebyshevKusuoka< Real >::wts_
private

Definition at line 105 of file ROL_ChebyshevKusuoka.hpp.

Referenced by ROL::ChebyshevKusuoka< Real >::initialize().

◆ pts_

template<class Real>
std::vector<Real> ROL::ChebyshevKusuoka< Real >::pts_
private

Definition at line 106 of file ROL_ChebyshevKusuoka.hpp.

Referenced by ROL::ChebyshevKusuoka< Real >::initialize().


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