ROL
ROL_RiskNeutralConstraint.hpp
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43
44#ifndef ROL_RISKNEUTRALCONSTRAINT_HPP
45#define ROL_RISKNEUTRALCONSTRAINT_HPP
46
47#include "ROL_Ptr.hpp"
48#include "ROL_Vector.hpp"
49#include "ROL_Constraint.hpp"
51
52namespace ROL {
53
54template<class Real>
55class RiskNeutralConstraint : public Constraint<Real> {
56private:
57 const Ptr<Constraint<Real>> con_;
58 const Ptr<SampleGenerator<Real>> xsampler_;
59 const Ptr<BatchManager<Real>> cbman_;
60
61 Ptr<Vector<Real>> conVec_;
62 Ptr<Vector<Real>> optVec_;
63
65
66 void init(const Vector<Real> &c, const Vector<Real> &x) {
67 if (!initialized_) {
68 conVec_ = c.clone();
69 optVec_ = x.dual().clone();
70 initialized_ = true;
71 }
72 }
73
74public:
76 const Ptr<SampleGenerator<Real>> &xsampler,
77 const Ptr<BatchManager<Real>> &cbman)
78 : con_(con), xsampler_(xsampler), cbman_(cbman), initialized_(false) {}
79
80 void update( const Vector<Real> &x, bool flag = true, int iter = -1 ) {
81 con_->update(x,flag,iter);
82 }
83
84 void update( const Vector<Real> &x, UpdateType type, int iter = -1 ) {
85 con_->update(x,type,iter);
86 }
87
88 void value(Vector<Real> &c, const Vector<Real> &x, Real &tol ) {
89 init(c,x);
90 conVec_->zero();
91 for ( int i = 0; i < xsampler_->numMySamples(); ++i ) {
92 con_->setParameter(xsampler_->getMyPoint(i));
93 con_->value(c,x,tol);
94 conVec_->axpy(xsampler_->getMyWeight(i),c);
95 }
96 c.zero();
97 cbman_->sumAll(*conVec_,c);
98 }
99
100 void applyJacobian(Vector<Real> &jv, const Vector<Real> &v, const Vector<Real> &x, Real &tol) {
101 init(jv,x);
102 conVec_->zero();
103 for ( int i = 0; i < xsampler_->numMySamples(); ++i ) {
104 con_->setParameter(xsampler_->getMyPoint(i));
105 con_->applyJacobian(jv,v,x,tol);
106 conVec_->axpy(xsampler_->getMyWeight(i),jv);
107 }
108 jv.zero();
109 cbman_->sumAll(*conVec_,jv);
110 }
111
112 void applyAdjointJacobian(Vector<Real> &ajv, const Vector<Real> &v, const Vector<Real> &x, Real &tol) {
113 init(v.dual(),x);
114 optVec_->zero();
115 for ( int i = 0; i < xsampler_->numMySamples(); ++i ) {
116 con_->setParameter(xsampler_->getMyPoint(i));
117 con_->applyAdjointJacobian(ajv,v,x,tol);
118 optVec_->axpy(xsampler_->getMyWeight(i),ajv);
119 }
120 ajv.zero();
121 xsampler_->sumAll(*optVec_,ajv);
122 }
123
124 void applyAdjointHessian(Vector<Real> &ahuv, const Vector<Real> &u, const Vector<Real> &v, const Vector<Real> &x, Real &tol) {
125 init(u.dual(),x);
126 optVec_->zero();
127 for ( int i = 0; i < xsampler_->numMySamples(); ++i ) {
128 con_->setParameter(xsampler_->getMyPoint(i));
129 con_->applyAdjointHessian(ahuv,u,v,x,tol);
130 optVec_->axpy(xsampler_->getMyWeight(i),ahuv);
131 }
132 ahuv.zero();
133 xsampler_->sumAll(*optVec_,ahuv);
134 }
135
136};
137
138}
139
140#endif
Defines the general constraint operator interface.
RiskNeutralConstraint(const Ptr< Constraint< Real > > &con, const Ptr< SampleGenerator< Real > > &xsampler, const Ptr< BatchManager< Real > > &cbman)
const Ptr< Constraint< Real > > con_
void value(Vector< Real > &c, const Vector< Real > &x, Real &tol)
Evaluate the constraint operator at .
void init(const Vector< Real > &c, const Vector< Real > &x)
const Ptr< BatchManager< Real > > cbman_
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 i...
void applyJacobian(Vector< Real > &jv, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
Apply the constraint Jacobian at , , to vector .
void update(const Vector< Real > &x, UpdateType type, int iter=-1)
Update constraint function.
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 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 ,...
const Ptr< SampleGenerator< Real > > xsampler_
Defines the linear algebra or vector space interface.
Definition: ROL_Vector.hpp:84
virtual const Vector & dual() const
Return dual representation of , for example, the result of applying a Riesz map, or change of basis,...
Definition: ROL_Vector.hpp:226
virtual void zero()
Set to zero vector.
Definition: ROL_Vector.hpp:167
virtual ROL::Ptr< Vector > clone() const =0
Clone to make a new (uninitialized) vector.