ROL
ROL_StochasticConstraint.hpp
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43 
44 #ifndef ROL_STOCHASTIC_CONSTRAINT_H
45 #define ROL_STOCHASTIC_CONSTRAINT_H
46 
49 #include "ROL_Types.hpp"
50 
51 namespace ROL {
52 
53 template <class Real>
54 class StochasticConstraint : public Constraint<Real> {
55 private:
56  Ptr<StochasticObjective<Real>> robj_;
57  Ptr<Constraint<Real>> con_;
58  Ptr<SampleGenerator<Real>> sampler_;
59 
60 public:
62  const Ptr<SampleGenerator<Real>> &sampler,
63  ROL::ParameterList &parlist,
64  const int index = 0)
65  : sampler_(sampler) {
66  robj_ = makePtr<StochasticObjective<Real>>(obj,parlist,sampler,1,index);
67  con_ = makePtr<ConstraintFromObjective<Real>>(robj_);
68  }
69 
71  const Ptr<SampleGenerator<Real>> &sampler,
72  ROL::ParameterList &parlist,
73  const int index = 0)
74  : sampler_(sampler) {
75  try {
76  Ptr<ConstraintFromObjective<Real>> cfo
77  = dynamicPtrCast<ConstraintFromObjective<Real>>(con);
78  robj_ = makePtr<StochasticObjective<Real>>(cfo->getObjective(),
79  parlist,sampler,1,index);
80  con_ = makePtr<ConstraintFromObjective<Real>>(robj_);
81  }
82  catch (std::exception &e) {
83  throw Exception::NotImplemented(">>> ROL::StochasticConstraint: Input constraint must be a ConstraintFromObjective!");
84  }
85  }
86 
87  Real computeStatistic(const Vector<Real> &x) const {
88  return robj_->computeStatistic(x);
89  }
90 
91  void update(const Vector<Real> &x, bool flag = true, int iter = -1) {
92  con_->update(x,flag,iter);
93  }
94 
95  void value(Vector<Real> &c, const Vector<Real> &x, Real &tol) {
96  con_->value(c,x,tol);
97  }
98 
99  void applyJacobian(Vector<Real> &jv, const Vector<Real> &v, const Vector<Real> &x, Real &tol) {
100  con_->applyJacobian(jv,v,x,tol);
101  }
102 
103  void applyAdjointJacobian(Vector<Real> &ajv, const Vector<Real> &v, const Vector<Real> &x, Real &tol) {
104  con_->applyAdjointJacobian(ajv,v,x,tol);
105  }
106 
107  void applyAdjointHessian(Vector<Real> &ahuv, const Vector<Real> &u, const Vector<Real> &v, const Vector<Real> &x, Real &tol) {
108  con_->applyAdjointHessian(ahuv,u,v,x,tol);
109  }
110 
111 }; // class StochasticConstraint
112 
113 } // namespace ROL
114 
115 #endif
Provides the interface to evaluate objective functions.
void applyJacobian(Vector< Real > &jv, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
Apply the constraint Jacobian at , , to vector .
StochasticConstraint(const Ptr< Constraint< Real >> &con, const Ptr< SampleGenerator< Real >> &sampler, ROL::ParameterList &parlist, const int index=0)
Contains definitions of custom data types in ROL.
Defines the linear algebra or vector space interface.
Definition: ROL_Vector.hpp:80
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 to vector in direction ...
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 ...
Ptr< SampleGenerator< Real > > sampler_
void applyAdjointJacobian(Vector< Real > &ajv, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
Apply the adjoint of the the constraint Jacobian at , , to vector .
void value(Vector< Real > &c, const Vector< Real > &x, Real &tol)
Evaluate the constraint operator at .
StochasticConstraint(const Ptr< Objective< Real >> &obj, const Ptr< SampleGenerator< Real >> &sampler, ROL::ParameterList &parlist, const int index=0)
Ptr< StochasticObjective< Real > > robj_
Real computeStatistic(const Vector< Real > &x) const
Defines the general constraint operator interface.