Provides the implementation of the buffered probability of exceedance. More...

#include <ROL_BPOE.hpp>

Inheritance diagram for ROL::BPOE< Real >:

Public Member Functions
	BPOE (const Real threshold, const Real order=1)

	BPOE (Teuchos::ParameterList &parlist)

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...

Real	getValue (SampleGenerator< Real > &sampler)
	Return risk measure value. More...

void	update (const Real val, const Vector< Real > &g, const Real weight)
	Update internal risk measure storage for gradient computation. More...

void	getGradient (Vector< Real > &g, SampleGenerator< Real > &sampler)
	Return risk measure (sub)gradient. 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...

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 Attributes
Real	threshold_

Real	order_

Real	xvar_

Real	vvar_

std::vector< Real >	hvec_

Teuchos::RCP< Vector< Real > >	dualVec1_

Teuchos::RCP< Vector< Real > >	dualVec2_

bool	firstReset_

Additional Inherited Members
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::BPOE< Real >

Provides the implementation of the buffered probability of exceedance.

Let \((\Omega,\mathcal{F},\mathbb{P})\) be a complete 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.

ROL's BPOE class inherits from ROL::RiskMeasure which is written in a way to exploit parallel sampling.

Definition at line 66 of file ROL_BPOE.hpp.

Constructor & Destructor Documentation

◆ BPOE() [1/2]

template<class Real >

ROL::BPOE< Real >::BPOE	(	const Real	threshold,
		const Real	order = `1`
	)

inline

Definition at line 79 of file ROL_BPOE.hpp.

◆ BPOE() [2/2]

template<class Real >

ROL::BPOE< Real >::BPOE ( Teuchos::ParameterList & parlist )

inline

Definition at line 84 of file ROL_BPOE.hpp.

Member Function Documentation

◆ reset() [1/2]

template<class Real >

void ROL::BPOE< Real >::reset	(	Teuchos::RCP< Vector< Real > > &	x0,
		const Vector< Real > &	x
	)

inlinevirtual

Reset internal risk measure storage. Called for value and gradient computation.

Parameters

[out]	x0	is a user-provided optimization vector
[in]	x	is a (potentially) augmented risk vector

On input, \(x\) carries \(x_0\) and any statistics (scalars) associated with the risk measure.

Reimplemented from ROL::RiskMeasure< Real >.

Definition at line 90 of file ROL_BPOE.hpp.

References ROL::RiskMeasure< Real >::reset().

Referenced by ROL::BPOE< Real >::reset().

◆ reset() [2/2]

template<class Real >

void ROL::BPOE< Real >::reset	(	Teuchos::RCP< Vector< Real > > &	x0,
		const Vector< Real > &	x,
		Teuchos::RCP< Vector< Real > > &	v0,
		const Vector< Real > &	v
	)

inlinevirtual

Reset internal risk measure storage. Called for Hessian-times-a-vector computation.

Parameters

[out]	x0	is a user-provided optimization vector
[in]	x	is a (potentially) augmented risk vector
[out]	v0	is a user-provided direction vector
[in]	v	is a (potentially) augmented risk vector

On input, \(x\) carries \(x_0\) and any statistics (scalars) associated with the risk measure. Similarly, \(v\) carries \(v_0\) and any statistics (scalars) associated with the risk measure.

Reimplemented from ROL::RiskMeasure< Real >.

Definition at line 95 of file ROL_BPOE.hpp.

References ROL::BPOE< Real >::reset().

◆ update() [1/3]

template<class Real >

void ROL::BPOE< Real >::update	(	const Real	val,
		const Real	weight
	)

inlinevirtual

Update internal risk measure 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::RiskMeasure< Real >.

Definition at line 112 of file ROL_BPOE.hpp.

References ROL::BPOE< Real >::threshold_.

◆ getValue()

template<class Real >

Real ROL::BPOE< Real >::getValue ( 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::RiskMeasure< Real >.

Definition at line 121 of file ROL_BPOE.hpp.

References ROL::SampleGenerator< Real >::sumAll().

◆ update() [2/3]

template<class Real >

void ROL::BPOE< Real >::update	(	const Real	val,
		const Vector< Real > &	g,
		const Real	weight
	)

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::RiskMeasure< Real >.

Definition at line 128 of file ROL_BPOE.hpp.

References ROL::BPOE< Real >::threshold_.

◆ getGradient()

template<class Real >

void ROL::BPOE< Real >::getGradient	(	Vector< Real > &	g,
		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::RiskMeasure< Real >.

Definition at line 140 of file ROL_BPOE.hpp.

References ROL::SampleGenerator< Real >::sumAll().

◆ update() [3/3]

template<class Real >

void ROL::BPOE< Real >::update	(	const Real	val,
		const Vector< Real > &	g,
		const Real	gv,
		const Vector< Real > &	hv,
		const Real	weight
	)

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::RiskMeasure< Real >.

Definition at line 159 of file ROL_BPOE.hpp.

References ROL::BPOE< Real >::threshold_.

◆ getHessVec()

template<class Real >

void ROL::BPOE< Real >::getHessVec	(	Vector< Real > &	hv,
		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::RiskMeasure< Real >.

Definition at line 182 of file ROL_BPOE.hpp.

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

Member Data Documentation

◆ threshold_

template<class Real >

Real ROL::BPOE< Real >::threshold_

private

Definition at line 68 of file ROL_BPOE.hpp.

Referenced by ROL::BPOE< Real >::update().

◆ order_

template<class Real >

Real ROL::BPOE< Real >::order_

private

Definition at line 69 of file ROL_BPOE.hpp.

Referenced by ROL::BPOE< Real >::getHessVec().

◆ xvar_

template<class Real >

Real ROL::BPOE< Real >::xvar_

private

Definition at line 71 of file ROL_BPOE.hpp.

◆ vvar_

template<class Real >

Real ROL::BPOE< Real >::vvar_

private

Definition at line 71 of file ROL_BPOE.hpp.

◆ hvec_

template<class Real >

std::vector<Real> ROL::BPOE< Real >::hvec_

private

Definition at line 73 of file ROL_BPOE.hpp.

◆ dualVec1_

template<class Real >

Teuchos::RCP<Vector<Real> > ROL::BPOE< Real >::dualVec1_

private

Definition at line 74 of file ROL_BPOE.hpp.

◆ dualVec2_

template<class Real >

Teuchos::RCP<Vector<Real> > ROL::BPOE< Real >::dualVec2_

private

Definition at line 74 of file ROL_BPOE.hpp.

◆ firstReset_

template<class Real >

bool ROL::BPOE< Real >::firstReset_

private

Definition at line 76 of file ROL_BPOE.hpp.

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

ROL_BPOE.hpp

Public Member Functions

Private Attributes

Additional Inherited Members

Detailed Description

template<class Real> class ROL::BPOE< Real >

Constructor & Destructor Documentation

◆ BPOE() [1/2]

◆ BPOE() [2/2]

Member Function Documentation

◆ reset() [1/2]

◆ reset() [2/2]

◆ update() [1/3]

◆ getValue()

◆ update() [2/3]

◆ getGradient()

◆ update() [3/3]

◆ getHessVec()

Member Data Documentation

◆ threshold_

◆ order_

◆ xvar_

◆ vvar_

◆ hvec_

◆ dualVec1_

◆ dualVec2_

◆ firstReset_

template<class Real>
class ROL::BPOE< Real >