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

#include <ROL_MeanValueConstraint.hpp>

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

Public Member Functions

 MeanValueConstraint (const Ptr< Constraint< Real > > &con, const Ptr< SampleGenerator< Real > > &sampler)
 
void update (const Vector< Real > &x, bool flag=true, int iter=-1) override
 Update constraint functions.
x is the optimization variable, flag = true if optimization variable is changed, iter is the outer algorithm iterations count.
 
void update (const Vector< Real > &x, UpdateType type, int iter=-1) override
 Update constraint function.
 
void value (Vector< Real > &c, const Vector< Real > &x, Real &tol) override
 Evaluate the constraint operator \(c:\mathcal{X} \rightarrow \mathcal{C}\) at \(x\).
 
void applyJacobian (Vector< Real > &jv, const Vector< Real > &v, const Vector< Real > &x, Real &tol) override
 Apply the constraint Jacobian at \(x\), \(c'(x) \in L(\mathcal{X}, \mathcal{C})\), to vector \(v\).
 
void applyAdjointJacobian (Vector< Real > &ajv, const Vector< Real > &v, const Vector< Real > &x, Real &tol) override
 Apply the adjoint of the the constraint Jacobian at \(x\), \(c'(x)^* \in L(\mathcal{C}^*, \mathcal{X}^*)\), to vector \(v\).
 
void applyAdjointHessian (Vector< Real > &ahuv, const Vector< Real > &u, const Vector< Real > &v, const Vector< Real > &x, Real &tol) override
 Apply the derivative of the adjoint of the constraint Jacobian at \(x\) to vector \(u\) in direction \(v\), according to \( v \mapsto c''(x)(v,\cdot)^*u \).
 
- Public Member Functions inherited from ROL::Constraint< Real >
virtual ~Constraint (void)
 
 Constraint (void)
 
virtual void update (const Vector< Real > &x, UpdateType type, int iter=-1)
 Update constraint function.
 
virtual 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.
 
virtual void value (Vector< Real > &c, const Vector< Real > &x, Real &tol)=0
 Evaluate the constraint operator \(c:\mathcal{X} \rightarrow \mathcal{C}\) at \(x\).
 
virtual 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 \(v\).
 
virtual 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 \(v\).
 
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 \(v\).
 
virtual 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 \( v \mapsto c''(x)(v,\cdot)^*u \).
 
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
 
virtual 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:
 
void activate (void)
 Turn on constraints.
 
void deactivate (void)
 Turn off constraints.
 
bool isActivated (void)
 Check if constraints are on.
 
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.
 
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.
 
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.
 
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.
 
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.
 
virtual void setParameter (const std::vector< Real > &param)
 

Private Member Functions

std::vector< Real > computeSampleMean (const Ptr< SampleGenerator< Real > > &sampler) const
 

Private Attributes

const Ptr< Constraint< Real > > con_
 

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::MeanValueConstraint< Real >

Definition at line 53 of file ROL_MeanValueConstraint.hpp.

Constructor & Destructor Documentation

◆ MeanValueConstraint()

template<typename Real >
ROL::MeanValueConstraint< Real >::MeanValueConstraint ( const Ptr< Constraint< Real > > &  con,
const Ptr< SampleGenerator< Real > > &  sampler 
)

Member Function Documentation

◆ update() [1/2]

template<typename Real >
void ROL::MeanValueConstraint< Real >::update ( const Vector< Real > &  x,
bool  flag = true,
int  iter = -1 
)
overridevirtual

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 58 of file ROL_MeanValueConstraint_Def.hpp.

◆ update() [2/2]

template<typename Real >
void ROL::MeanValueConstraint< Real >::update ( const Vector< Real > &  x,
UpdateType  type,
int  iter = -1 
)
overridevirtual

Update constraint function.

This function updates the constraint function at new iterations.

Parameters
[in]xis the new iterate.
[in]typeis the type of update requested.
[in]iteris the outer algorithm iterations count.

Reimplemented from ROL::Constraint< Real >.

Definition at line 63 of file ROL_MeanValueConstraint_Def.hpp.

◆ value()

template<typename Real >
void ROL::MeanValueConstraint< Real >::value ( Vector< Real > &  c,
const Vector< Real > &  x,
Real &  tol 
)
overridevirtual

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

Parameters
[out]cis the result of evaluating the constraint operator at x; a constraint-space vector
[in]xis the constraint argument; an optimization-space vector
[in,out]tolis 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 68 of file ROL_MeanValueConstraint_Def.hpp.

◆ applyJacobian()

template<typename Real >
void ROL::MeanValueConstraint< Real >::applyJacobian ( Vector< Real > &  jv,
const Vector< Real > &  v,
const Vector< Real > &  x,
Real &  tol 
)
overridevirtual

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

Parameters
[out]jvis the result of applying the constraint Jacobian to v at x; a constraint-space vector
[in]vis an optimization-space vector
[in]xis the constraint argument; an optimization-space vector
[in,out]tolis a tolerance for inexact evaluations; currently unused

On return, \(\mathsf{jv} = c'(x)v\), 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 73 of file ROL_MeanValueConstraint_Def.hpp.

◆ applyAdjointJacobian()

template<typename Real >
void ROL::MeanValueConstraint< Real >::applyAdjointJacobian ( Vector< Real > &  ajv,
const Vector< Real > &  v,
const Vector< Real > &  x,
Real &  tol 
)
overridevirtual

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

Parameters
[out]ajvis the result of applying the adjoint of the constraint Jacobian to v at x; a dual optimization-space vector
[in]vis a dual constraint-space vector
[in]xis the constraint argument; an optimization-space vector
[in,out]tolis a tolerance for inexact evaluations; currently unused

On return, \(\mathsf{ajv} = c'(x)^*v\), 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 78 of file ROL_MeanValueConstraint_Def.hpp.

◆ applyAdjointHessian()

template<typename Real >
void ROL::MeanValueConstraint< Real >::applyAdjointHessian ( Vector< Real > &  ahuv,
const Vector< Real > &  u,
const Vector< Real > &  v,
const Vector< Real > &  x,
Real &  tol 
)
overridevirtual

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

Parameters
[out]ahuvis the result of applying the derivative of the adjoint of the constraint Jacobian at x to vector u in direction v; a dual optimization-space vector
[in]uis the direction vector; a dual constraint-space vector
[in]vis an optimization-space vector
[in]xis the constraint argument; an optimization-space vector
[in,out]tolis a tolerance for inexact evaluations; currently unused

On return, \( \mathsf{ahuv} = c''(x)(v,\cdot)^*u \), 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 83 of file ROL_MeanValueConstraint_Def.hpp.

◆ computeSampleMean()

template<typename Real >
std::vector< Real > ROL::MeanValueConstraint< Real >::computeSampleMean ( const Ptr< SampleGenerator< Real > > &  sampler) const
private

Member Data Documentation

◆ con_

template<class Real >
const Ptr<Constraint<Real> > ROL::MeanValueConstraint< Real >::con_
private

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