Provides the interface to implement any functional that maps a random variable to a (extended) real number. More...

#include <ROL_RandVarFunctional.hpp>

Inheritance diagram for ROL::RandVarFunctional< Real >:

Public Member Functions
virtual	~RandVarFunctional ()

	RandVarFunctional (void)

void	useStorage (bool storage)

void	useHessVecStorage (bool storage)

virtual void	setStorage (const Ptr< ScalarController< Real > > &value_storage, const Ptr< VectorController< Real > > &gradient_storage)

virtual void	setHessVecStorage (const Ptr< ScalarController< Real > > &gradvec_storage, const Ptr< VectorController< Real > > &hessvec_storage)

virtual void	resetStorage (bool flag=true)
	Reset internal storage.

virtual void	resetStorage (UpdateType type)

virtual void	initialize (const Vector< Real > &x)
	Initialize temporary variables.

virtual void	setSample (const std::vector< Real > &point, const Real weight)

virtual Real	computeStatistic (const Ptr< const std::vector< Real > > &xstat) const
	Compute statistic.

virtual void	updateValue (Objective< Real > &obj, const Vector< Real > &x, const std::vector< Real > &xstat, Real &tol)
	Update internal storage for value computation.

virtual void	updateGradient (Objective< Real > &obj, const Vector< Real > &x, const std::vector< Real > &xstat, Real &tol)
	Update internal risk measure storage for gradient computation.

virtual void	updateHessVec (Objective< Real > &obj, const Vector< Real > &v, const std::vector< Real > &vstat, const Vector< Real > &x, const std::vector< Real > &xstat, Real &tol)
	Update internal risk measure storage for Hessian-time-a-vector computation.

virtual Real	getValue (const Vector< Real > &x, const std::vector< Real > &xstat, SampleGenerator< Real > &sampler)
	Return risk measure value.

virtual void	getGradient (Vector< Real > &g, std::vector< Real > &gstat, const Vector< Real > &x, const std::vector< Real > &xstat, SampleGenerator< Real > &sampler)
	Return risk measure (sub)gradient.

virtual void	getHessVec (Vector< Real > &hv, std::vector< Real > &hvstat, const Vector< Real > &v, const std::vector< Real > &vstat, const Vector< Real > &x, const std::vector< Real > &xstat, SampleGenerator< Real > &sampler)
	Return risk measure Hessian-times-a-vector.

Protected Member Functions
Real	computeValue (Objective< Real > &obj, const Vector< Real > &x, Real &tol)

void	computeGradient (Vector< Real > &g, Objective< Real > &obj, const Vector< Real > &x, Real &tol)

Real	computeGradVec (Vector< Real > &g, Objective< Real > &obj, const Vector< Real > &v, const Vector< Real > &x, Real &tol)

void	computeHessVec (Vector< Real > &hv, Objective< Real > &obj, const Vector< Real > &v, const Vector< Real > &x, Real &tol)

Protected Attributes
Real	val_

Real	gv_

Ptr< Vector< Real > >	g_

Ptr< Vector< Real > >	hv_

Ptr< Vector< Real > >	dualVector_

bool	firstReset_

std::vector< Real >	point_

Real	weight_

Private Attributes
bool	storage_

bool	storage_hessvec_

Ptr< ScalarController< Real > >	value_storage_

Ptr< VectorController< Real > >	gradient_storage_

Ptr< ScalarController< Real > >	gradvec_storage_

Ptr< VectorController< Real > >	hessvec_storage_

Detailed Description

template<class Real>
class ROL::RandVarFunctional< Real >

Provides the interface to implement any functional that maps a random variable to a (extended) real number.

Let \((\Omega,\mathcal{F},\mathbb{P})\) be a probability space. Here, \(\Omega\) is the set of outcomes, \(\mathcal{F}\subseteq 2^\Omega\) is a \(\sigma\)-algebra of events and \(\mathbb{P}:\mathcal{F}\to[0,1]\) is a probability measure. Moreover, let \(\mathcal{X}\) be a class of random variables. A `‘random variable functional’' is an extended real-valued functional that associates numerical values to random variables, i.e., \(\mathcal{R}:\mathcal{X}\to\mathbb{R}\cup\{+\infty\}\). In most cases, \(\mathcal{X} = L^p(\Omega,\mathcal{F},\mathbb{P})\) for some \(1\le p\le \infty\).

ROL's random variable functional base class is written in a way to exploit parallel sampling. General risk measures may depend on global information such as the expected value of a random variable, \(\mathbb{E}[X]\). Thus, ROL::RandVarFunctional contains functions to update intermediate information and to compute desired quantities such as values, gradients and Hessians applied to vectors.

Definition at line 80 of file ROL_RandVarFunctional.hpp.

Constructor & Destructor Documentation

◆ ~RandVarFunctional()

template<class Real>

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

inlinevirtual

Definition at line 172 of file ROL_RandVarFunctional.hpp.

◆ RandVarFunctional()

template<class Real>

ROL::RandVarFunctional< Real >::RandVarFunctional ( void )

inline

Definition at line 174 of file ROL_RandVarFunctional.hpp.

References firstReset_, gradient_storage_, gradvec_storage_, gv_, hessvec_storage_, point_, storage_, storage_hessvec_, val_, and value_storage_.

Referenced by ROL::BPOE< Real >::BPOE(), ROL::BPOE< Real >::BPOE(), ROL::CoherentEntropicRisk< Real >::CoherentEntropicRisk(), ROL::ConvexCombinationRiskMeasure< Real >::ConvexCombinationRiskMeasure(), ROL::CVaR< Real >::CVaR(), ROL::CVaR< Real >::CVaR(), ROL::EntropicRisk< Real >::EntropicRisk(), ROL::EntropicRisk< Real >::EntropicRisk(), ROL::ExpectationQuadDeviation< Real >::ExpectationQuadDeviation(), ROL::ExpectationQuadError< Real >::ExpectationQuadError(), ROL::ExpectationQuadRegret< Real >::ExpectationQuadRegret(), ROL::ExpectationQuadRisk< Real >::ExpectationQuadRisk(), ROL::FDivergence< Real >::FDivergence(), ROL::FDivergence< Real >::FDivergence(), ROL::HMCR< Real >::HMCR(), ROL::HMCR< Real >::HMCR(), ROL::KLDivergence< Real >::KLDivergence(), ROL::KLDivergence< Real >::KLDivergence(), ROL::MeanDeviation< Real >::MeanDeviation(), ROL::MeanDeviation< Real >::MeanDeviation(), ROL::MeanDeviation< Real >::MeanDeviation(), ROL::MeanDeviationFromTarget< Real >::MeanDeviationFromTarget(), ROL::MeanDeviationFromTarget< Real >::MeanDeviationFromTarget(), ROL::MeanDeviationFromTarget< Real >::MeanDeviationFromTarget(), ROL::MeanSemiDeviation< Real >::MeanSemiDeviation(), ROL::MeanSemiDeviation< Real >::MeanSemiDeviation(), ROL::MeanSemiDeviationFromTarget< Real >::MeanSemiDeviationFromTarget(), ROL::MeanSemiDeviationFromTarget< Real >::MeanSemiDeviationFromTarget(), ROL::MeanVariance< Real >::MeanVariance(), ROL::MeanVariance< Real >::MeanVariance(), ROL::MeanVariance< Real >::MeanVariance(), ROL::MeanVarianceFromTarget< Real >::MeanVarianceFromTarget(), ROL::MeanVarianceFromTarget< Real >::MeanVarianceFromTarget(), ROL::MeanVarianceFromTarget< Real >::MeanVarianceFromTarget(), ROL::MixedCVaR< Real >::MixedCVaR(), ROL::MixedCVaR< Real >::MixedCVaR(), ROL::PD_RandVarFunctional< Real >::PD_RandVarFunctional(), ROL::QuantileRadius< Real >::QuantileRadius(), ROL::QuantileRadius< Real >::QuantileRadius(), ROL::SmoothedPOE< Real >::SmoothedPOE(), ROL::SmoothedPOE< Real >::SmoothedPOE(), ROL::SpectralRisk< Real >::SpectralRisk(), ROL::SpectralRisk< Real >::SpectralRisk(), ROL::SpectralRisk< Real >::SpectralRisk(), and ROL::SpectralRisk< Real >::SpectralRisk().

Member Function Documentation

◆ computeValue()

template<class Real>

Real ROL::RandVarFunctional< Real >::computeValue	(	Objective< Real > &	obj,
		const Vector< Real > &	x,
		Real &	tol )

inlineprotected

Definition at line 101 of file ROL_RandVarFunctional.hpp.

References point_, ROL::Objective< Real >::setParameter(), storage_, ROL::Objective< Real >::value(), and value_storage_.

◆ computeGradient()

template<class Real>

void ROL::RandVarFunctional< Real >::computeGradient	(	Vector< Real > &	g,
		Objective< Real > &	obj,
		const Vector< Real > &	x,
		Real &	tol )

inlineprotected

Definition at line 119 of file ROL_RandVarFunctional.hpp.

References ROL::Objective< Real >::gradient(), gradient_storage_, point_, ROL::Objective< Real >::setParameter(), and storage_.

◆ computeGradVec()

template<class Real>

Real ROL::RandVarFunctional< Real >::computeGradVec	(	Vector< Real > &	g,
		Objective< Real > &	obj,
		const Vector< Real > &	v,
		const Vector< Real > &	x,
		Real &	tol )

inlineprotected

Definition at line 135 of file ROL_RandVarFunctional.hpp.

References ROL::Vector< Real >::apply(), computeGradient(), gradvec_storage_, point_, and storage_hessvec_.

◆ computeHessVec()

template<class Real>

void ROL::RandVarFunctional< Real >::computeHessVec	(	Vector< Real > &	hv,
		Objective< Real > &	obj,
		const Vector< Real > &	v,
		const Vector< Real > &	x,
		Real &	tol )

inlineprotected

Definition at line 155 of file ROL_RandVarFunctional.hpp.

References ROL::Objective< Real >::hessVec(), hessvec_storage_, point_, ROL::Objective< Real >::setParameter(), and storage_hessvec_.

◆ useStorage()

template<class Real>

void ROL::RandVarFunctional< Real >::useStorage ( bool storage )

inline

Definition at line 182 of file ROL_RandVarFunctional.hpp.

References gradient_storage_, storage_, and value_storage_.

Referenced by setStorage(), and useHessVecStorage().

◆ useHessVecStorage()

template<class Real>

void ROL::RandVarFunctional< Real >::useHessVecStorage ( bool storage )

inline

Definition at line 194 of file ROL_RandVarFunctional.hpp.

References gradvec_storage_, hessvec_storage_, storage_hessvec_, and useStorage().

Referenced by setHessVecStorage().

◆ setStorage()

template<class Real>

virtual void ROL::RandVarFunctional< Real >::setStorage	(	const Ptr< ScalarController< Real > > &	value_storage,
		const Ptr< VectorController< Real > > &	gradient_storage )

inlinevirtual

Reimplemented in ROL::MeanDeviation< Real >, ROL::MeanSemiDeviation< Real >, ROL::MeanVariance< Real >, ROL::PD_BPOE< Real >, ROL::PD_CVaR< Real >, ROL::PD_HMCR2< Real >, ROL::PD_MeanSemiDeviation< Real >, ROL::PD_MeanSemiDeviationFromTarget< Real >, ROL::PD_RandVarFunctional< Real >, and ROL::SpectralRisk< Real >.

Definition at line 207 of file ROL_RandVarFunctional.hpp.

References gradient_storage_, useStorage(), and value_storage_.

Referenced by ROL::ConvexCombinationRiskMeasure< Real >::initializeCCRM(), ROL::MeanVariance< Real >::initializeMV(), ROL::MeanDeviation< Real >::initializeStorage(), ROL::MeanSemiDeviation< Real >::initializeStorage(), ROL::PD_BPOE< Real >::initializeStorage(), ROL::PD_CVaR< Real >::initializeStorage(), ROL::PD_HMCR2< Real >::initializeStorage(), ROL::PD_MeanSemiDeviation< Real >::initializeStorage(), ROL::PD_MeanSemiDeviationFromTarget< Real >::initializeStorage(), ROL::MeanDeviation< Real >::setStorage(), ROL::MeanSemiDeviation< Real >::setStorage(), ROL::MeanVariance< Real >::setStorage(), ROL::PD_RandVarFunctional< Real >::setStorage(), and ROL::SpectralRisk< Real >::setStorage().

◆ setHessVecStorage()

template<class Real>

virtual void ROL::RandVarFunctional< Real >::setHessVecStorage	(	const Ptr< ScalarController< Real > > &	gradvec_storage,
		const Ptr< VectorController< Real > > &	hessvec_storage )

inlinevirtual

Reimplemented in ROL::MeanDeviation< Real >, ROL::MeanSemiDeviation< Real >, ROL::MeanVariance< Real >, ROL::PD_BPOE< Real >, ROL::PD_CVaR< Real >, ROL::PD_HMCR2< Real >, ROL::PD_MeanSemiDeviation< Real >, ROL::PD_MeanSemiDeviationFromTarget< Real >, ROL::PD_RandVarFunctional< Real >, and ROL::SpectralRisk< Real >.

Definition at line 214 of file ROL_RandVarFunctional.hpp.

References gradvec_storage_, hessvec_storage_, and useHessVecStorage().

Referenced by ROL::ConvexCombinationRiskMeasure< Real >::initializeCCRM(), ROL::MeanVariance< Real >::initializeMV(), ROL::MeanDeviation< Real >::initializeStorage(), ROL::MeanSemiDeviation< Real >::initializeStorage(), ROL::PD_BPOE< Real >::initializeStorage(), ROL::PD_CVaR< Real >::initializeStorage(), ROL::PD_HMCR2< Real >::initializeStorage(), ROL::PD_MeanSemiDeviation< Real >::initializeStorage(), ROL::PD_MeanSemiDeviationFromTarget< Real >::initializeStorage(), ROL::MeanDeviation< Real >::setHessVecStorage(), ROL::MeanSemiDeviation< Real >::setHessVecStorage(), ROL::MeanVariance< Real >::setHessVecStorage(), ROL::PD_RandVarFunctional< Real >::setHessVecStorage(), and ROL::SpectralRisk< Real >::setHessVecStorage().

◆ resetStorage() [1/2]

template<class Real>

virtual void ROL::RandVarFunctional< Real >::resetStorage ( bool flag = true )

inlinevirtual

Reset internal storage.

  @param[in]   x  is a vector used for initializing storage

Reimplemented in ROL::ConvexCombinationRiskMeasure< Real >, and ROL::SpectralRisk< Real >.

Definition at line 225 of file ROL_RandVarFunctional.hpp.

References gradient_storage_, gradvec_storage_, hessvec_storage_, storage_, storage_hessvec_, and value_storage_.

Referenced by ROL::ConvexCombinationRiskMeasure< Real >::resetStorage(), ROL::ConvexCombinationRiskMeasure< Real >::resetStorage(), ROL::SpectralRisk< Real >::resetStorage(), and ROL::SpectralRisk< Real >::resetStorage().

◆ resetStorage() [2/2]

template<class Real>

virtual void ROL::RandVarFunctional< Real >::resetStorage ( UpdateType type )

inlinevirtual

Reimplemented in ROL::ConvexCombinationRiskMeasure< Real >, and ROL::SpectralRisk< Real >.

Definition at line 237 of file ROL_RandVarFunctional.hpp.

References gradient_storage_, gradvec_storage_, hessvec_storage_, storage_, storage_hessvec_, and value_storage_.

◆ initialize()

template<class Real>

virtual void ROL::RandVarFunctional< Real >::initialize ( const Vector< Real > & x )

inlinevirtual

Initialize temporary variables.

  @param[in]   x  is a vector used for initializing storage

Reimplemented in ROL::BPOE< Real >, ROL::CoherentEntropicRisk< Real >, ROL::ConvexCombinationRiskMeasure< Real >, ROL::FDivergence< Real >, ROL::HMCR< Real >, ROL::KLDivergence< Real >, ROL::MeanDeviation< Real >, ROL::MeanDeviationFromTarget< Real >, ROL::MeanSemiDeviation< Real >, ROL::MixedCVaR< Real >, ROL::PD_BPOE< Real >, ROL::PD_CVaR< Real >, ROL::PD_HMCR2< Real >, ROL::PD_MeanSemiDeviation< Real >, ROL::PD_MeanSemiDeviationFromTarget< Real >, ROL::PD_RandVarFunctional< Real >, ROL::QuantileRadius< Real >, and ROL::SpectralRisk< Real >.

Definition at line 252 of file ROL_RandVarFunctional.hpp.

References ROL::Vector< Real >::clone(), ROL::Vector< Real >::dual(), dualVector_, firstReset_, g_, gradvec_storage_, gv_, hessvec_storage_, hv_, storage_hessvec_, val_, and zero.

◆ setSample()

template<class Real>

virtual void ROL::RandVarFunctional< Real >::setSample	(	const std::vector< Real > &	point,
		const Real	weight )

inlinevirtual

Reimplemented in ROL::ConvexCombinationRiskMeasure< Real >, and ROL::SpectralRisk< Real >.

Definition at line 270 of file ROL_RandVarFunctional.hpp.

References point_, and weight_.

Referenced by ROL::ConvexCombinationRiskMeasure< Real >::setSample(), and ROL::SpectralRisk< Real >::setSample().

◆ computeStatistic()

template<class Real>

virtual Real ROL::RandVarFunctional< Real >::computeStatistic ( const Ptr< const std::vector< Real > > & xstat ) const

inlinevirtual

Compute statistic.

Parameters

[in] xstat is a ROL::Ptr to a std::vector containing the statistic vector

Definition at line 280 of file ROL_RandVarFunctional.hpp.

◆ updateValue()

template<class Real>

virtual void ROL::RandVarFunctional< Real >::updateValue	(	Objective< Real > &	obj,
		const Vector< Real > &	x,
		const std::vector< Real > &	xstat,
		Real &	tol )

inlinevirtual

Update internal storage for value computation.

Parameters

[in]	val	is the value of the random variable objective function at the current sample point
[in]	weight	is the weight associated with the current sample point

Reimplemented in ROL::BPOE< Real >, ROL::CoherentEntropicRisk< Real >, ROL::ConvexCombinationRiskMeasure< Real >, ROL::CVaR< Real >, ROL::EntropicRisk< Real >, ROL::ExpectationQuadDeviation< Real >, ROL::ExpectationQuadError< Real >, ROL::ExpectationQuadRegret< Real >, ROL::ExpectationQuadRisk< Real >, ROL::FDivergence< Real >, ROL::HMCR< Real >, ROL::KLDivergence< Real >, ROL::MeanDeviation< Real >, ROL::MeanDeviationFromTarget< Real >, ROL::MeanSemiDeviation< Real >, ROL::MeanSemiDeviationFromTarget< Real >, ROL::MeanVariance< Real >, ROL::MeanVarianceFromTarget< Real >, ROL::MixedCVaR< Real >, ROL::PD_BPOE< Real >, ROL::PD_CVaR< Real >, ROL::PD_HMCR2< Real >, ROL::PD_MeanSemiDeviation< Real >, ROL::PD_MeanSemiDeviationFromTarget< Real >, ROL::QuantileRadius< Real >, ROL::SmoothedPOE< Real >, and ROL::SpectralRisk< Real >.

Definition at line 295 of file ROL_RandVarFunctional.hpp.

References computeValue(), val_, and weight_.

◆ updateGradient()

template<class Real>

virtual void ROL::RandVarFunctional< Real >::updateGradient	(	Objective< Real > &	obj,
		const Vector< Real > &	x,
		const std::vector< Real > &	xstat,
		Real &	tol )

inlinevirtual

Update internal risk measure storage for gradient computation.

Parameters

[in]	val	is the value of the random variable objective function at the current sample point
[in]	g	is the gradient of the random variable objective function at the current sample point
[in]	weight	is the weight associated with the current sample point

Reimplemented in ROL::BPOE< Real >, ROL::CoherentEntropicRisk< Real >, ROL::ConvexCombinationRiskMeasure< Real >, ROL::CVaR< Real >, ROL::EntropicRisk< Real >, ROL::ExpectationQuadDeviation< Real >, ROL::ExpectationQuadError< Real >, ROL::ExpectationQuadRegret< Real >, ROL::ExpectationQuadRisk< Real >, ROL::FDivergence< Real >, ROL::HMCR< Real >, ROL::KLDivergence< Real >, ROL::MeanDeviation< Real >, ROL::MeanDeviationFromTarget< Real >, ROL::MeanSemiDeviation< Real >, ROL::MeanSemiDeviationFromTarget< Real >, ROL::MeanVariance< Real >, ROL::MeanVarianceFromTarget< Real >, ROL::MixedCVaR< Real >, ROL::PD_BPOE< Real >, ROL::PD_CVaR< Real >, ROL::PD_HMCR2< Real >, ROL::PD_MeanSemiDeviation< Real >, ROL::PD_MeanSemiDeviationFromTarget< Real >, ROL::QuantileRadius< Real >, ROL::SmoothedPOE< Real >, and ROL::SpectralRisk< Real >.

Definition at line 312 of file ROL_RandVarFunctional.hpp.

References computeGradient(), dualVector_, g_, and weight_.

◆ updateHessVec()

template<class Real>

virtual void ROL::RandVarFunctional< Real >::updateHessVec	(	Objective< Real > &	obj,
		const Vector< Real > &	v,
		const std::vector< Real > &	vstat,
		const Vector< Real > &	x,
		const std::vector< Real > &	xstat,
		Real &	tol )

inlinevirtual

Update internal risk measure storage for Hessian-time-a-vector computation.

Parameters

[in]	val	is the value of the random variable objective function at the current sample point
[in]	g	is the gradient of the random variable objective function at the current sample point
[in]	gv	is the gradient of the random variable objective function at the current sample point applied to the vector v0
[in]	hv	is the Hessian of the random variable objective function at the current sample point applied to the vector v0
[in]	weight	is the weight associated with the current sample point

Reimplemented in ROL::BPOE< Real >, ROL::CoherentEntropicRisk< Real >, ROL::ConvexCombinationRiskMeasure< Real >, ROL::CVaR< Real >, ROL::EntropicRisk< Real >, ROL::ExpectationQuadDeviation< Real >, ROL::ExpectationQuadError< Real >, ROL::ExpectationQuadRegret< Real >, ROL::ExpectationQuadRisk< Real >, ROL::FDivergence< Real >, ROL::HMCR< Real >, ROL::KLDivergence< Real >, ROL::MeanDeviation< Real >, ROL::MeanDeviationFromTarget< Real >, ROL::MeanSemiDeviation< Real >, ROL::MeanSemiDeviationFromTarget< Real >, ROL::MeanVariance< Real >, ROL::MeanVarianceFromTarget< Real >, ROL::MixedCVaR< Real >, ROL::PD_BPOE< Real >, ROL::PD_CVaR< Real >, ROL::PD_HMCR2< Real >, ROL::PD_MeanSemiDeviation< Real >, ROL::PD_MeanSemiDeviationFromTarget< Real >, ROL::QuantileRadius< Real >, ROL::SmoothedPOE< Real >, and ROL::SpectralRisk< Real >.

Definition at line 335 of file ROL_RandVarFunctional.hpp.

References computeHessVec(), dualVector_, hv_, and weight_.

◆ getValue()

template<class Real>

virtual Real ROL::RandVarFunctional< Real >::getValue	(	const Vector< Real > &	x,
		const std::vector< Real > &	xstat,
		SampleGenerator< Real > &	sampler )

inlinevirtual

Return risk measure value.

Parameters

[in] sampler is the ROL::SampleGenerator used to sample the objective function

Upon return, getValue returns \(\mathcal{R}(f(x_0))\) where \(f(x_0)\) denotes the random variable objective function evaluated at \(x_0\).

Reimplemented in ROL::BPOE< Real >, ROL::CoherentEntropicRisk< Real >, ROL::ConvexCombinationRiskMeasure< Real >, ROL::CVaR< Real >, ROL::EntropicRisk< Real >, ROL::ExpectationQuadDeviation< Real >, ROL::ExpectationQuadError< Real >, ROL::ExpectationQuadRegret< Real >, ROL::ExpectationQuadRisk< Real >, ROL::FDivergence< Real >, ROL::HMCR< Real >, ROL::KLDivergence< Real >, ROL::MeanDeviation< Real >, ROL::MeanDeviationFromTarget< Real >, ROL::MeanSemiDeviation< Real >, ROL::MeanSemiDeviationFromTarget< Real >, ROL::MeanVariance< Real >, ROL::MixedCVaR< Real >, ROL::PD_BPOE< Real >, ROL::PD_CVaR< Real >, ROL::PD_HMCR2< Real >, ROL::PD_MeanSemiDeviation< Real >, ROL::PD_MeanSemiDeviationFromTarget< Real >, ROL::QuantileRadius< Real >, ROL::SmoothedPOE< Real >, and ROL::SpectralRisk< Real >.

Definition at line 353 of file ROL_RandVarFunctional.hpp.

References ROL::SampleGenerator< Real >::sumAll(), and val_.

◆ getGradient()

template<class Real>

virtual void ROL::RandVarFunctional< Real >::getGradient	(	Vector< Real > &	g,
		std::vector< Real > &	gstat,
		const Vector< Real > &	x,
		const std::vector< Real > &	xstat,
		SampleGenerator< Real > &	sampler )

inlinevirtual

Return risk measure (sub)gradient.

Parameters

[out]	g	is the (sub)gradient of the risk measure
[in]	sampler	is the ROL::SampleGenerator used to sample the objective function

Upon return, getGradient returns \(\theta\in\partial\mathcal{R}(f(x_0))\) where \(f(x_0)\) denotes the random variable objective function evaluated at \(x_0\) and \(\partial\mathcal{R}(X)\) denotes the subdifferential of \(\mathcal{R}\) at \(X\).

Reimplemented in ROL::BPOE< Real >, ROL::CoherentEntropicRisk< Real >, ROL::ConvexCombinationRiskMeasure< Real >, ROL::CVaR< Real >, ROL::EntropicRisk< Real >, ROL::ExpectationQuadDeviation< Real >, ROL::ExpectationQuadError< Real >, ROL::ExpectationQuadRegret< Real >, ROL::ExpectationQuadRisk< Real >, ROL::FDivergence< Real >, ROL::HMCR< Real >, ROL::KLDivergence< Real >, ROL::MeanDeviation< Real >, ROL::MeanDeviationFromTarget< Real >, ROL::MeanSemiDeviation< Real >, ROL::MeanSemiDeviationFromTarget< Real >, ROL::MeanVariance< Real >, ROL::MixedCVaR< Real >, ROL::PD_BPOE< Real >, ROL::PD_CVaR< Real >, ROL::PD_HMCR2< Real >, ROL::PD_MeanSemiDeviation< Real >, ROL::PD_MeanSemiDeviationFromTarget< Real >, ROL::QuantileRadius< Real >, ROL::SmoothedPOE< Real >, and ROL::SpectralRisk< Real >.

Definition at line 372 of file ROL_RandVarFunctional.hpp.

References g_, and ROL::SampleGenerator< Real >::sumAll().

◆ getHessVec()

template<class Real>

virtual void ROL::RandVarFunctional< Real >::getHessVec	(	Vector< Real > &	hv,
		std::vector< Real > &	hvstat,
		const Vector< Real > &	v,
		const std::vector< Real > &	vstat,
		const Vector< Real > &	x,
		const std::vector< Real > &	xstat,
		SampleGenerator< Real > &	sampler )

inlinevirtual

Return risk measure Hessian-times-a-vector.

Parameters

[out]	hv	is the Hessian-times-a-vector of the risk measure
[in]	sampler	is the ROL::SampleGenerator used to sample the objective function

Upon return, getHessVec returns \(\nabla^2 \mathcal{R}(f(x_0))v_0\) (if available) where \(f(x_0)\) denotes the random variable objective function evaluated at \(x_0\).

Reimplemented in ROL::BPOE< Real >, ROL::CoherentEntropicRisk< Real >, ROL::ConvexCombinationRiskMeasure< Real >, ROL::CVaR< Real >, ROL::EntropicRisk< Real >, ROL::ExpectationQuadDeviation< Real >, ROL::ExpectationQuadError< Real >, ROL::ExpectationQuadRegret< Real >, ROL::ExpectationQuadRisk< Real >, ROL::FDivergence< Real >, ROL::HMCR< Real >, ROL::KLDivergence< Real >, ROL::MeanDeviation< Real >, ROL::MeanDeviationFromTarget< Real >, ROL::MeanSemiDeviation< Real >, ROL::MeanSemiDeviationFromTarget< Real >, ROL::MeanVariance< Real >, ROL::MixedCVaR< Real >, ROL::PD_BPOE< Real >, ROL::PD_CVaR< Real >, ROL::PD_HMCR2< Real >, ROL::PD_MeanSemiDeviation< Real >, ROL::PD_MeanSemiDeviationFromTarget< Real >, ROL::QuantileRadius< Real >, ROL::SmoothedPOE< Real >, and ROL::SpectralRisk< Real >.

Definition at line 391 of file ROL_RandVarFunctional.hpp.

References hv_, and ROL::SampleGenerator< Real >::sumAll().

Member Data Documentation

◆ storage_

template<class Real>

bool ROL::RandVarFunctional< Real >::storage_

private

Definition at line 82 of file ROL_RandVarFunctional.hpp.

Referenced by computeGradient(), computeValue(), RandVarFunctional(), resetStorage(), resetStorage(), and useStorage().

◆ storage_hessvec_

template<class Real>

bool ROL::RandVarFunctional< Real >::storage_hessvec_

private

Definition at line 83 of file ROL_RandVarFunctional.hpp.

Referenced by computeGradVec(), computeHessVec(), initialize(), RandVarFunctional(), resetStorage(), resetStorage(), and useHessVecStorage().

◆ value_storage_

template<class Real>

Ptr<ScalarController<Real> > ROL::RandVarFunctional< Real >::value_storage_

private

Definition at line 84 of file ROL_RandVarFunctional.hpp.

Referenced by computeValue(), RandVarFunctional(), resetStorage(), resetStorage(), setStorage(), and useStorage().

◆ gradient_storage_

template<class Real>

Ptr<VectorController<Real> > ROL::RandVarFunctional< Real >::gradient_storage_

private

Definition at line 85 of file ROL_RandVarFunctional.hpp.

Referenced by computeGradient(), RandVarFunctional(), resetStorage(), resetStorage(), setStorage(), and useStorage().

◆ gradvec_storage_

template<class Real>

Ptr<ScalarController<Real> > ROL::RandVarFunctional< Real >::gradvec_storage_

private

Definition at line 86 of file ROL_RandVarFunctional.hpp.

Referenced by computeGradVec(), initialize(), RandVarFunctional(), resetStorage(), resetStorage(), setHessVecStorage(), and useHessVecStorage().

◆ hessvec_storage_

template<class Real>

Ptr<VectorController<Real> > ROL::RandVarFunctional< Real >::hessvec_storage_

private

Definition at line 87 of file ROL_RandVarFunctional.hpp.

Referenced by computeHessVec(), initialize(), RandVarFunctional(), resetStorage(), resetStorage(), setHessVecStorage(), and useHessVecStorage().

◆ val_

template<class Real>

Real ROL::RandVarFunctional< Real >::val_

protected

Definition at line 90 of file ROL_RandVarFunctional.hpp.

◆ gv_

template<class Real>

Real ROL::RandVarFunctional< Real >::gv_

protected

Definition at line 91 of file ROL_RandVarFunctional.hpp.

Referenced by ROL::BPOE< Real >::getGradient(), ROL::CoherentEntropicRisk< Real >::getGradient(), ROL::PD_HMCR2< Real >::getGradient(), ROL::CoherentEntropicRisk< Real >::getHessVec(), ROL::EntropicRisk< Real >::getHessVec(), ROL::KLDivergence< Real >::getHessVec(), ROL::MeanDeviation< Real >::getHessVec(), ROL::MeanSemiDeviation< Real >::getHessVec(), ROL::MeanVariance< Real >::getHessVec(), ROL::PD_HMCR2< Real >::getHessVec(), ROL::PD_MeanSemiDeviation< Real >::getHessVec(), initialize(), RandVarFunctional(), ROL::BPOE< Real >::updateGradient(), ROL::CoherentEntropicRisk< Real >::updateGradient(), ROL::PD_HMCR2< Real >::updateGradient(), ROL::CoherentEntropicRisk< Real >::updateHessVec(), ROL::EntropicRisk< Real >::updateHessVec(), ROL::KLDivergence< Real >::updateHessVec(), ROL::MeanDeviation< Real >::updateHessVec(), ROL::MeanSemiDeviation< Real >::updateHessVec(), ROL::MeanVariance< Real >::updateHessVec(), ROL::PD_HMCR2< Real >::updateHessVec(), and ROL::PD_MeanSemiDeviation< Real >::updateHessVec().

◆ g_

template<class Real>

Ptr<Vector<Real> > ROL::RandVarFunctional< Real >::g_

protected

Definition at line 92 of file ROL_RandVarFunctional.hpp.

◆ hv_

template<class Real>

Ptr<Vector<Real> > ROL::RandVarFunctional< Real >::hv_

protected

Definition at line 93 of file ROL_RandVarFunctional.hpp.

◆ dualVector_

template<class Real>

Ptr<Vector<Real> > ROL::RandVarFunctional< Real >::dualVector_

protected

Definition at line 94 of file ROL_RandVarFunctional.hpp.

◆ firstReset_

template<class Real>

bool ROL::RandVarFunctional< Real >::firstReset_

protected

Definition at line 95 of file ROL_RandVarFunctional.hpp.

Referenced by initialize(), and RandVarFunctional().

◆ point_

template<class Real>

std::vector<Real> ROL::RandVarFunctional< Real >::point_

protected

◆ weight_

template<class Real>

Real ROL::RandVarFunctional< Real >::weight_

protected

Definition at line 98 of file ROL_RandVarFunctional.hpp.

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

ROL_RandVarFunctional.hpp

Public Member Functions

Protected Member Functions

Protected Attributes

Private Attributes

Detailed Description

Constructor & Destructor Documentation

◆ ~RandVarFunctional()

◆ RandVarFunctional()

Member Function Documentation

◆ computeValue()

◆ computeGradient()

◆ computeGradVec()

◆ computeHessVec()

◆ useStorage()

◆ useHessVecStorage()

◆ setStorage()

◆ setHessVecStorage()

◆ resetStorage() [1/2]

◆ resetStorage() [2/2]

◆ initialize()

◆ setSample()

◆ computeStatistic()

◆ updateValue()

◆ updateGradient()

◆ updateHessVec()

◆ getValue()

◆ getGradient()

◆ getHessVec()

Member Data Documentation

◆ storage_

◆ storage_hessvec_

◆ value_storage_

◆ gradient_storage_

◆ gradvec_storage_

◆ hessvec_storage_

◆ val_

◆ gv_

◆ g_

◆ hv_

◆ dualVector_

◆ firstReset_

◆ point_

◆ weight_