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

Reduce the input of a linear constraint based on the active set associated with a vector \(x\), i.e., let \(\mathcal{I}\) denote the inactive set associated with \(x\) and the bounds \(\ell\le u\), then. More...

#include <ROL_ReducedLinearConstraint.hpp>

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

Public Member Functions

 ReducedLinearConstraint (const Ptr< Constraint< Real >> &con, const Ptr< BoundConstraint< Real >> &bnd, const Ptr< const Vector< Real >> &x)
 
void setX (const Ptr< const Vector< Real >> &x)
 
void value (Vector< Real > &c, const Vector< Real > &x, Real &tol) override
 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) override
 Apply the constraint Jacobian at \(x\), \(c'(x) \in L(\mathcal{X}, \mathcal{C})\), to vector \(v\). More...
 
void applyAdjointJacobian (Vector< Real > &jv, 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 \(v\). More...
 
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 \( v \mapsto c''(x)(v,\cdot)^*u \). More...
 
- 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. More...
 
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. More...
 
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...

 
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:

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

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

 
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< Constraint< Real > > con_
 
const Ptr< BoundConstraint
< Real > > 
bnd_
 
Ptr< const Vector< Real > > x_
 
const Ptr< Vector< Real > > prim_
 

Additional Inherited Members

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

Detailed Description

template<typename Real>
class ROL::ReducedLinearConstraint< Real >

Reduce the input of a linear constraint based on the active set associated with a vector \(x\), i.e., let \(\mathcal{I}\) denote the inactive set associated with \(x\) and the bounds \(\ell\le u\), then.

\[ C(v) = c(v_\mathcal{I}), \]

  where \form#122 denotes the vector that is equal to

\(v\) on \(\mathcal{I}\) and zero otherwise.

Definition at line 33 of file ROL_ReducedLinearConstraint.hpp.

Constructor & Destructor Documentation

template<typename Real >
ROL::ReducedLinearConstraint< Real >::ReducedLinearConstraint ( const Ptr< Constraint< Real >> &  con,
const Ptr< BoundConstraint< Real >> &  bnd,
const Ptr< const Vector< Real >> &  x 
)

Definition at line 16 of file ROL_ReducedLinearConstraint_Def.hpp.

Member Function Documentation

template<typename Real >
void ROL::ReducedLinearConstraint< Real >::setX ( const Ptr< const Vector< Real >> &  x)

Definition at line 22 of file ROL_ReducedLinearConstraint_Def.hpp.

template<typename Real >
void ROL::ReducedLinearConstraint< 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 27 of file ROL_ReducedLinearConstraint_Def.hpp.

References zero.

template<typename Real >
void ROL::ReducedLinearConstraint< 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 \(v\).

  @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 35 of file ROL_ReducedLinearConstraint_Def.hpp.

References zero.

template<typename Real >
void ROL::ReducedLinearConstraint< 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 \(v\).

  @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 45 of file ROL_ReducedLinearConstraint_Def.hpp.

References zero.

template<typename Real >
void ROL::ReducedLinearConstraint< 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 \( v \mapsto c''(x)(v,\cdot)^*u \).

  @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 54 of file ROL_ReducedLinearConstraint_Def.hpp.

References ROL::Vector< Real >::zero().

Member Data Documentation

template<typename Real >
const Ptr<Constraint<Real> > ROL::ReducedLinearConstraint< Real >::con_
private

Definition at line 35 of file ROL_ReducedLinearConstraint.hpp.

template<typename Real >
const Ptr<BoundConstraint<Real> > ROL::ReducedLinearConstraint< Real >::bnd_
private

Definition at line 36 of file ROL_ReducedLinearConstraint.hpp.

template<typename Real >
Ptr<const Vector<Real> > ROL::ReducedLinearConstraint< Real >::x_
private

Definition at line 37 of file ROL_ReducedLinearConstraint.hpp.

template<typename Real >
const Ptr<Vector<Real> > ROL::ReducedLinearConstraint< Real >::prim_
private

Definition at line 38 of file ROL_ReducedLinearConstraint.hpp.


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