#include <ROL_AlmostSureConstraint.hpp>

Inheritance diagram for ROL::AlmostSureConstraint< Real >:

Public Member Functions
virtual	~AlmostSureConstraint ()

	AlmostSureConstraint (const Ptr< SampleGenerator< Real >> &sampler, const Ptr< Constraint< Real >> &con)

void	update (const Vector< Real > &x, bool flag=true, int iter=-1)
	Update constraint functions. x is the optimization variable, flag = true if optimization variable is changed, iter is the outer algorithm iterations count. More...

void	update (const Vector< Real > &x, UpdateType type, int iter=-1)
	Update constraint function. More...

void	value (Vector< Real > &c, const Vector< Real > &x, Real &tol)
	Evaluate the constraint operator \(c:\mathcal{X} \rightarrow \mathcal{C}\) at \(x\). More...

void	applyJacobian (Vector< Real > &jv, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
	Apply the constraint Jacobian at \(x\), \(c'(x) \in L(\mathcal{X}, \mathcal{C})\), to vector \(v\). More...

void	applyAdjointJacobian (Vector< Real > &ajv, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
	Apply the adjoint of the the constraint Jacobian at \(x\), \(c'(x)^* \in L(\mathcal{C}^, \mathcal{X}^)\), to vector \(v\). More...

void	applyAdjointHessian (Vector< Real > &ahuv, const Vector< Real > &u, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
	Apply the derivative of the adjoint of the constraint Jacobian at \(x\) to vector \(u\) in direction \(v\), according to \( v \mapsto c''(x)(v,\cdot)^*u \). More...

void	applyPreconditioner (Vector< Real > &Pv, const Vector< Real > &v, const Vector< Real > &x, const Vector< Real > &g, Real &tol)
	Apply a constraint preconditioner at \(x\), \(P(x) \in L(\mathcal{C}, \mathcal{C}^)\), to vector \(v\). Ideally, this preconditioner satisfies the following relationship: \[ \left[c'(x) \circ R \circ c'(x)^ \circ P(x)\right] v = v \,, \] where R is the appropriate Riesz map in \(L(\mathcal{X}^*, \mathcal{X})\). It is used by the solveAugmentedSystem method. More...

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

	Constraint (void)

virtual void	applyAdjointJacobian (Vector< Real > &ajv, const Vector< Real > &v, const Vector< Real > &x, const Vector< Real > &dualv, Real &tol)
	Apply the adjoint of the the constraint Jacobian at \(x\), \(c'(x)^* \in L(\mathcal{C}^, \mathcal{X}^)\), to vector \(v\). More...

virtual std::vector< Real >	solveAugmentedSystem (Vector< Real > &v1, Vector< Real > &v2, const Vector< Real > &b1, const Vector< Real > &b2, const Vector< Real > &x, Real &tol)
	Approximately solves the augmented system \[ \begin{pmatrix} I & c'(x)^* \\ c'(x) & 0 \end{pmatrix} \begin{pmatrix} v_{1} \\ v_{2} \end{pmatrix} = \begin{pmatrix} b_{1} \\ b_{2} \end{pmatrix} \] where \(v_{1} \in \mathcal{X}\), \(v_{2} \in \mathcal{C}^\), \(b_{1} \in \mathcal{X}^\), \(b_{2} \in \mathcal{C}\), \(I : \mathcal{X} \rightarrow \mathcal{X}^\) is an identity or Riesz operator, and \(0 : \mathcal{C}^ \rightarrow \mathcal{C}\) is a zero operator. More...

void	activate (void)
	Turn on constraints. More...

void	deactivate (void)
	Turn off constraints. More...

bool	isActivated (void)
	Check if constraints are on. More...

virtual std::vector < std::vector< Real > >	checkApplyJacobian (const Vector< Real > &x, const Vector< Real > &v, const Vector< Real > &jv, const std::vector< Real > &steps, const bool printToStream=true, std::ostream &outStream=std::cout, const int order=1)
	Finite-difference check for the constraint Jacobian application. More...

virtual std::vector < std::vector< Real > >	checkApplyJacobian (const Vector< Real > &x, const Vector< Real > &v, const Vector< Real > &jv, const bool printToStream=true, std::ostream &outStream=std::cout, const int numSteps=ROL_NUM_CHECKDERIV_STEPS, const int order=1)
	Finite-difference check for the constraint Jacobian application. More...

virtual std::vector < std::vector< Real > >	checkApplyAdjointJacobian (const Vector< Real > &x, const Vector< Real > &v, const Vector< Real > &c, const Vector< Real > &ajv, const bool printToStream=true, std::ostream &outStream=std::cout, const int numSteps=ROL_NUM_CHECKDERIV_STEPS)
	Finite-difference check for the application of the adjoint of constraint Jacobian. More...

virtual Real	checkAdjointConsistencyJacobian (const Vector< Real > &w, const Vector< Real > &v, const Vector< Real > &x, const bool printToStream=true, std::ostream &outStream=std::cout)

virtual Real	checkAdjointConsistencyJacobian (const Vector< Real > &w, const Vector< Real > &v, const Vector< Real > &x, const Vector< Real > &dualw, const Vector< Real > &dualv, const bool printToStream=true, std::ostream &outStream=std::cout)

virtual std::vector < std::vector< Real > >	checkApplyAdjointHessian (const Vector< Real > &x, const Vector< Real > &u, const Vector< Real > &v, const Vector< Real > &hv, const std::vector< Real > &step, const bool printToScreen=true, std::ostream &outStream=std::cout, const int order=1)
	Finite-difference check for the application of the adjoint of constraint Hessian. More...

virtual std::vector < std::vector< Real > >	checkApplyAdjointHessian (const Vector< Real > &x, const Vector< Real > &u, const Vector< Real > &v, const Vector< Real > &hv, const bool printToScreen=true, std::ostream &outStream=std::cout, const int numSteps=ROL_NUM_CHECKDERIV_STEPS, const int order=1)
	Finite-difference check for the application of the adjoint of constraint Hessian. More...

virtual void	setParameter (const std::vector< Real > &param)

Private Attributes
const Ptr< SampleGenerator < Real > >	sampler_

const Ptr< Constraint< Real > >	con_

Ptr< Vector< Real > >	scratch1_

Ptr< Vector< Real > >	scratch2_

bool	isInitialized_

Additional Inherited Members
Protected Member Functions inherited from ROL::Constraint< Real >
const std::vector< Real >	getParameter (void) const

Detailed Description

template<class Real>
class ROL::AlmostSureConstraint< Real >

Definition at line 21 of file ROL_AlmostSureConstraint.hpp.

Constructor & Destructor Documentation

template<class Real >

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

inlinevirtual

Definition at line 31 of file ROL_AlmostSureConstraint.hpp.

template<class Real >

ROL::AlmostSureConstraint< Real >::AlmostSureConstraint	(	const Ptr< SampleGenerator< Real >> &	sampler,
		const Ptr< Constraint< Real >> &	con
	)

inline

Definition at line 33 of file ROL_AlmostSureConstraint.hpp.

Member Function Documentation

template<class Real >

void ROL::AlmostSureConstraint< Real >::update	(	const Vector< Real > &	x,
		bool	flag = `true`,
		int	iter = `-1`
	)

inlinevirtual

Update constraint functions. x is the optimization variable, flag = true if optimization variable is changed, iter is the outer algorithm iterations count.

Reimplemented from ROL::Constraint< Real >.

Definition at line 37 of file ROL_AlmostSureConstraint.hpp.

References ROL::AlmostSureConstraint< Real >::con_.

template<class Real >

void ROL::AlmostSureConstraint< Real >::update	(	const Vector< Real > &	x,
		UpdateType	type,
		int	iter = `-1`
	)

inlinevirtual

Update constraint function.

This function updates the constraint function at new iterations.

Parameters

[in]	x	is the new iterate.
[in]	type	is the type of update requested.
[in]	iter	is the outer algorithm iterations count.

Reimplemented from ROL::Constraint< Real >.

Definition at line 40 of file ROL_AlmostSureConstraint.hpp.

References ROL::AlmostSureConstraint< Real >::con_.

template<class Real >

void ROL::AlmostSureConstraint< Real >::value	(	Vector< Real > &	c,
		const Vector< Real > &	x,
		Real &	tol
	)

inlinevirtual

Evaluate the constraint operator \(c:\mathcal{X} \rightarrow \mathcal{C}\) at \(x\).

Parameters

[out]	c	is the result of evaluating the constraint operator at x; a constraint-space vector
[in]	x	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, \(\mathsf{c} = c(x)\), where \(\mathsf{c} \in \mathcal{C}\), \(\mathsf{x} \in \mathcal{X}\).

Implements ROL::Constraint< Real >.

Definition at line 44 of file ROL_AlmostSureConstraint.hpp.

References ROL::AlmostSureConstraint< Real >::con_, ROL::SimulatedVector< Real >::get(), ROL::AlmostSureConstraint< Real >::sampler_, and ROL::Vector< Real >::zero().

template<class Real >

void ROL::AlmostSureConstraint< Real >::applyJacobian	(	Vector< Real > &	jv,
		const Vector< Real > &	v,
		const Vector< Real > &	x,
		Real &	tol
	)

inlinevirtual

Apply the constraint Jacobian at \(x\), \(c'(x) \in L(\mathcal{X}, \mathcal{C})\), to vector \(v\).

  @param[out]      jv  is the result of applying the constraint Jacobian to @b v at @b x; a constraint-space vector
  @param[in]       v   is an optimization-space vector
  @param[in]       x   is the constraint argument; an optimization-space vector
  @param[in,out]   tol is a tolerance for inexact evaluations; currently unused

  On return, \form#91, where

\(v \in \mathcal{X}\), \(\mathsf{jv} \in \mathcal{C}\).

The default implementation is a finite-difference approximation.

Reimplemented from ROL::Constraint< Real >.

Definition at line 59 of file ROL_AlmostSureConstraint.hpp.

References ROL::AlmostSureConstraint< Real >::con_, ROL::SimulatedVector< Real >::get(), ROL::AlmostSureConstraint< Real >::sampler_, and ROL::Vector< Real >::zero().

template<class Real >

void ROL::AlmostSureConstraint< Real >::applyAdjointJacobian	(	Vector< Real > &	ajv,
		const Vector< Real > &	v,
		const Vector< Real > &	x,
		Real &	tol
	)

inlinevirtual

Apply the adjoint of the the constraint Jacobian at \(x\), \(c'(x)^* \in L(\mathcal{C}^*, \mathcal{X}^*)\), to vector \(v\).

  @param[out]      ajv is the result of applying the adjoint of the constraint Jacobian to @b v at @b x; a dual optimization-space vector
  @param[in]       v   is a dual constraint-space vector
  @param[in]       x   is the constraint argument; an optimization-space vector
  @param[in,out]   tol is a tolerance for inexact evaluations; currently unused

  On return, \form#95, where

\(v \in \mathcal{C}^*\), \(\mathsf{ajv} \in \mathcal{X}^*\).

The default implementation is a finite-difference approximation.

Reimplemented from ROL::Constraint< Real >.

Definition at line 75 of file ROL_AlmostSureConstraint.hpp.

References ROL::Vector< Real >::clone(), ROL::AlmostSureConstraint< Real >::con_, ROL::SimulatedVector< Real >::get(), ROL::AlmostSureConstraint< Real >::isInitialized_, ROL::AlmostSureConstraint< Real >::sampler_, ROL::AlmostSureConstraint< Real >::scratch1_, ROL::AlmostSureConstraint< Real >::scratch2_, and ROL::Vector< Real >::zero().

template<class Real >

void ROL::AlmostSureConstraint< Real >::applyAdjointHessian	(	Vector< Real > &	ahuv,
		const Vector< Real > &	u,
		const Vector< Real > &	v,
		const Vector< Real > &	x,
		Real &	tol
	)

inlinevirtual

Apply the derivative of the adjoint of the constraint Jacobian at \(x\) to vector \(u\) in direction \(v\), according to \( v \mapsto c''(x)(v,\cdot)^*u \).

  @param[out]      ahuv is the result of applying the derivative of the adjoint of the constraint Jacobian at @b x to vector @b u in direction @b v; a dual optimization-space vector
  @param[in]       u    is the direction vector; a dual constraint-space vector
  @param[in]       v    is an optimization-space vector
  @param[in]       x    is the constraint argument; an optimization-space vector
  @param[in,out]   tol  is a tolerance for inexact evaluations; currently unused

  On return, \form#100, where

\(u \in \mathcal{C}^*\), \(v \in \mathcal{X}\), and \(\mathsf{ahuv} \in \mathcal{X}^*\).

The default implementation is a finite-difference approximation based on the adjoint Jacobian.

Reimplemented from ROL::Constraint< Real >.

Definition at line 99 of file ROL_AlmostSureConstraint.hpp.

References ROL::Vector< Real >::clone(), ROL::AlmostSureConstraint< Real >::con_, ROL::SimulatedVector< Real >::get(), ROL::AlmostSureConstraint< Real >::isInitialized_, ROL::AlmostSureConstraint< Real >::sampler_, ROL::AlmostSureConstraint< Real >::scratch1_, ROL::AlmostSureConstraint< Real >::scratch2_, and ROL::Vector< Real >::zero().

template<class Real >

void ROL::AlmostSureConstraint< Real >::applyPreconditioner	(	Vector< Real > &	pv,
		const Vector< Real > &	v,
		const Vector< Real > &	x,
		const Vector< Real > &	g,
		Real &	tol
	)

inlinevirtual

Apply a constraint preconditioner at \(x\), \(P(x) \in L(\mathcal{C}, \mathcal{C}^*)\), to vector \(v\). Ideally, this preconditioner satisfies the following relationship:

\[ \left[c'(x) \circ R \circ c'(x)^* \circ P(x)\right] v = v \,, \]

where R is the appropriate Riesz map in \(L(\mathcal{X}^*, \mathcal{X})\). It is used by the solveAugmentedSystem method.

  @param[out]      pv  is the result of applying the constraint preconditioner to @b v at @b x; a dual constraint-space vector
  @param[in]       v   is a constraint-space vector
  @param[in]       x   is the preconditioner argument; an optimization-space vector
  @param[in]       g   is the preconditioner argument; a dual optimization-space vector, unused
  @param[in,out]   tol is a tolerance for inexact evaluations

  On return, \form#114, where

\(v \in \mathcal{C}\), \(\mathsf{pv} \in \mathcal{C}^*\).

The default implementation is the Riesz map in \(L(\mathcal{C}, \mathcal{C}^*)\).

Reimplemented from ROL::Constraint< Real >.

Definition at line 124 of file ROL_AlmostSureConstraint.hpp.

References ROL::AlmostSureConstraint< Real >::con_, ROL::SimulatedVector< Real >::get(), ROL::AlmostSureConstraint< Real >::sampler_, ROL::AlmostSureConstraint< Real >::scratch1_, ROL::AlmostSureConstraint< Real >::scratch2_, and ROL::Vector< Real >::zero().