Provides an interface for a convex combination of risk measures. More...

#include <ROL_ConvexCombinationRiskMeasure.hpp>

Inheritance diagram for ROL::ConvexCombinationRiskMeasure< Real >:

Public Member Functions
	ConvexCombinationRiskMeasure (ROL::ParameterList &parlist)
	Constructor. More...

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

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

void	resetStorage (UpdateType type)

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

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

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

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

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. More...

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. More...

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. More...

Public Member Functions inherited from ROL::RandVarFunctional< Real >
virtual	~RandVarFunctional ()

	RandVarFunctional (void)

	weight_ (0)

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

Private Types
typedef std::vector< Real > ::size_type	uint

Private Member Functions
void	initializeCCRM (void)

void	checkInputs (void)

Private Attributes
std::vector< Real >	lambda_

std::vector< ROL::Ptr < RandVarFunctional< Real > > >	risk_

uint	size_

std::vector< int >	statVec_

Ptr< ScalarController< Real > >	values_

Ptr< ScalarController< Real > >	gradvecs_

Ptr< VectorController< Real > >	gradients_

Ptr< VectorController< Real > >	hessvecs_

Additional Inherited Members
Protected Member Functions inherited from ROL::RandVarFunctional< Real >
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 inherited from ROL::RandVarFunctional< Real >
Real	val_

Real	gv_

Ptr< Vector< Real > >	g_

Ptr< Vector< Real > >	hv_

Ptr< Vector< Real > >	dualVector_

bool	firstReset_

std::vector< Real >	point_

Real	weight_

Detailed Description

template<class Real>
class ROL::ConvexCombinationRiskMeasure< Real >

Provides an interface for a convex combination of risk measures.

This function provides the capability to produce a convex combination of risk measure, i.e.,

\[ \mathcal{R}(X) = \sum_{k=1}^n \lambda_k \mathcal{R}_k(X) \]

where \(\mathcal{R}_k\) are risk measures and \(\lambda_k \ge 0\) with \(\lambda_1 + \ldots + \lambda_n = 1\). In general, \(\mathcal{R}\) is not law-invariant or coherent unless each \(\mathcal{R}_k\) is.

Definition at line 34 of file ROL_ConvexCombinationRiskMeasure.hpp.

Member Typedef Documentation

template<class Real >

typedef std::vector<Real>::size_type ROL::ConvexCombinationRiskMeasure< Real >::uint

private

Definition at line 36 of file ROL_ConvexCombinationRiskMeasure.hpp.

Constructor & Destructor Documentation

template<class Real >

ROL::ConvexCombinationRiskMeasure< Real >::ConvexCombinationRiskMeasure ( ROL::ParameterList & parlist )

inline

Constructor.

Parameters

[in] parlist is a parameter list specifying inputs

parlist should contain sublists "SOL"->"Risk Measure"->"Convex Combination Risk Measure" and within the "Convex Combination Risk Measure" sublist should have the following parameters

"Convex Combination Parameters" (greater than 0 and sum to 1)
Sublists labeled 1 to n with risk measure definitions.

Definition at line 92 of file ROL_ConvexCombinationRiskMeasure.hpp.

References ROL::ConvexCombinationRiskMeasure< Real >::checkInputs(), ROL::ConvexCombinationRiskMeasure< Real >::lambda_, ROL::ConvexCombinationRiskMeasure< Real >::risk_, ROL::RiskMeasureInfo(), ROL::ConvexCombinationRiskMeasure< Real >::size_, and ROL::ConvexCombinationRiskMeasure< Real >::statVec_.

Member Function Documentation

template<class Real >

void ROL::ConvexCombinationRiskMeasure< Real >::initializeCCRM ( void )

inlineprivate

Definition at line 51 of file ROL_ConvexCombinationRiskMeasure.hpp.

References ROL::ConvexCombinationRiskMeasure< Real >::gradients_, ROL::ConvexCombinationRiskMeasure< Real >::gradvecs_, ROL::ConvexCombinationRiskMeasure< Real >::hessvecs_, ROL::ConvexCombinationRiskMeasure< Real >::risk_, ROL::RandVarFunctional< Real >::setHessVecStorage(), ROL::RandVarFunctional< Real >::setStorage(), ROL::ConvexCombinationRiskMeasure< Real >::size_, and ROL::ConvexCombinationRiskMeasure< Real >::values_.

Referenced by ROL::ConvexCombinationRiskMeasure< Real >::checkInputs().

template<class Real >

void ROL::ConvexCombinationRiskMeasure< Real >::checkInputs ( void )

inlineprivate

Definition at line 65 of file ROL_ConvexCombinationRiskMeasure.hpp.

References ROL::ConvexCombinationRiskMeasure< Real >::initializeCCRM(), ROL::ConvexCombinationRiskMeasure< Real >::lambda_, ROL::ConvexCombinationRiskMeasure< Real >::risk_, and zero.

Referenced by ROL::ConvexCombinationRiskMeasure< Real >::ConvexCombinationRiskMeasure().

template<class Real >

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

inlinevirtual

Reimplemented from ROL::RandVarFunctional< Real >.

Definition at line 124 of file ROL_ConvexCombinationRiskMeasure.hpp.

References ROL::ConvexCombinationRiskMeasure< Real >::risk_, ROL::RandVarFunctional< Real >::setSample(), and ROL::ConvexCombinationRiskMeasure< Real >::size_.

template<class Real >

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

inlinevirtual

Reset internal storage.

Parameters

[in] x is a vector used for initializing storage

Reimplemented from ROL::RandVarFunctional< Real >.

Definition at line 131 of file ROL_ConvexCombinationRiskMeasure.hpp.

References ROL::RandVarFunctional< Real >::resetStorage(), ROL::ConvexCombinationRiskMeasure< Real >::risk_, and ROL::ConvexCombinationRiskMeasure< Real >::size_.

template<class Real >

void ROL::ConvexCombinationRiskMeasure< Real >::resetStorage ( UpdateType type )

inlinevirtual

Reimplemented from ROL::RandVarFunctional< Real >.

Definition at line 137 of file ROL_ConvexCombinationRiskMeasure.hpp.

References ROL::RandVarFunctional< Real >::resetStorage(), ROL::ConvexCombinationRiskMeasure< Real >::risk_, and ROL::ConvexCombinationRiskMeasure< Real >::size_.

template<class Real >

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

inlinevirtual

Initialize temporary variables.

Parameters

[in] x is a vector used for initializing storage

Reimplemented from ROL::RandVarFunctional< Real >.

Definition at line 145 of file ROL_ConvexCombinationRiskMeasure.hpp.

References ROL::RandVarFunctional< Real >::initialize(), ROL::ConvexCombinationRiskMeasure< Real >::risk_, and ROL::ConvexCombinationRiskMeasure< Real >::size_.

template<class Real >

void ROL::ConvexCombinationRiskMeasure< 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 from ROL::RandVarFunctional< Real >.

Definition at line 152 of file ROL_ConvexCombinationRiskMeasure.hpp.

References ROL::ConvexCombinationRiskMeasure< Real >::risk_, ROL::ConvexCombinationRiskMeasure< Real >::size_, and ROL::ConvexCombinationRiskMeasure< Real >::statVec_.

template<class Real >

Real ROL::ConvexCombinationRiskMeasure< 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 from ROL::RandVarFunctional< Real >.

Definition at line 168 of file ROL_ConvexCombinationRiskMeasure.hpp.

References ROL::ConvexCombinationRiskMeasure< Real >::lambda_, ROL::ConvexCombinationRiskMeasure< Real >::risk_, ROL::ConvexCombinationRiskMeasure< Real >::size_, and ROL::ConvexCombinationRiskMeasure< Real >::statVec_.

template<class Real >

void ROL::ConvexCombinationRiskMeasure< 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 from ROL::RandVarFunctional< Real >.

Definition at line 185 of file ROL_ConvexCombinationRiskMeasure.hpp.

References ROL::ConvexCombinationRiskMeasure< Real >::risk_, ROL::ConvexCombinationRiskMeasure< Real >::size_, and ROL::ConvexCombinationRiskMeasure< Real >::statVec_.

template<class Real >

void ROL::ConvexCombinationRiskMeasure< 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 from ROL::RandVarFunctional< Real >.

Definition at line 201 of file ROL_ConvexCombinationRiskMeasure.hpp.

References ROL::Vector< Real >::axpy(), ROL::RandVarFunctional< Real >::g_, ROL::ConvexCombinationRiskMeasure< Real >::lambda_, ROL::ConvexCombinationRiskMeasure< Real >::risk_, ROL::ConvexCombinationRiskMeasure< Real >::size_, and ROL::ConvexCombinationRiskMeasure< Real >::statVec_.

template<class Real >

void ROL::ConvexCombinationRiskMeasure< 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 from ROL::RandVarFunctional< Real >.

Definition at line 225 of file ROL_ConvexCombinationRiskMeasure.hpp.

References ROL::ConvexCombinationRiskMeasure< Real >::risk_, ROL::ConvexCombinationRiskMeasure< Real >::size_, and ROL::ConvexCombinationRiskMeasure< Real >::statVec_.

template<class Real >

void ROL::ConvexCombinationRiskMeasure< 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 from ROL::RandVarFunctional< Real >.

Definition at line 245 of file ROL_ConvexCombinationRiskMeasure.hpp.

References ROL::Vector< Real >::axpy(), ROL::RandVarFunctional< Real >::hv_, ROL::ConvexCombinationRiskMeasure< Real >::lambda_, ROL::ConvexCombinationRiskMeasure< Real >::risk_, ROL::ConvexCombinationRiskMeasure< Real >::size_, and ROL::ConvexCombinationRiskMeasure< Real >::statVec_.