ROL
ROL_ExpectationQuadRegret.hpp
Go to the documentation of this file.
1 // @HEADER
2 // *****************************************************************************
3 // Rapid Optimization Library (ROL) Package
4 //
5 // Copyright 2014 NTESS and the ROL contributors.
6 // SPDX-License-Identifier: BSD-3-Clause
7 // *****************************************************************************
8 // @HEADER
9 
10 #ifndef ROL_EXPECTATIONQUADREGRET_HPP
11 #define ROL_EXPECTATIONQUADREGRET_HPP
12 
13 #include "ROL_ExpectationQuad.hpp"
15 #include "ROL_Types.hpp"
16 
52 namespace ROL {
53 
54 template<class Real>
56 private:
57  Ptr<ExpectationQuad<Real>> eq_;
58 
64 
67 
72 
73 public:
75  : RandVarFunctional<Real>(), eq_(eq) {}
76 
79  void checkRegret(void) {
80  eq_->check();
81  }
82 
84  const Vector<Real> &x,
85  const std::vector<Real> &xstat,
86  Real &tol) {
87  Real val = computeValue(obj,x,tol);
88  val_ += weight_ * eq_->regret(val,0);
89  }
90 
92  const Vector<Real> &x,
93  const std::vector<Real> &xstat,
94  Real &tol) {
95  Real val = computeValue(obj,x,tol);
96  Real r = eq_->regret(val,1);
97  if (std::abs(r) >= ROL_EPSILON<Real>()) {
98  computeGradient(*dualVector_,obj,x,tol);
99  g_->axpy(weight_*r,*dualVector_);
100  }
101  }
102 
104  const Vector<Real> &v,
105  const std::vector<Real> &vstat,
106  const Vector<Real> &x,
107  const std::vector<Real> &xstat,
108  Real &tol) {
109  Real val = computeValue(obj,x,tol);
110  Real r1 = eq_->regret(val,1);
111  Real r2 = eq_->regret(val,2);
112  if (std::abs(r2) >= ROL_EPSILON<Real>()) {
113  Real gv = computeGradVec(*dualVector_,obj,v,x,tol);
114  hv_->axpy(weight_*r2*gv,*dualVector_);
115  }
116  if (std::abs(r1) >= ROL_EPSILON<Real>()) {
117  computeHessVec(*dualVector_,obj,v,x,tol);
118  hv_->axpy(weight_*r1,*dualVector_);
119  }
120  }
121 
122  Real getValue(const Vector<Real> &x,
123  const std::vector<Real> &xstat,
124  SampleGenerator<Real> &sampler) {
125  Real val(0);
126  sampler.sumAll(&val_,&val,1);
127  return val;
128  }
129 
131  std::vector<Real> &gstat,
132  const Vector<Real> &x,
133  const std::vector<Real> &xstat,
134  SampleGenerator<Real> &sampler) {
135  sampler.sumAll(*g_,g);
136  }
137 
139  std::vector<Real> &hvstat,
140  const Vector<Real> &v,
141  const std::vector<Real> &vstat,
142  const Vector<Real> &x,
143  const std::vector<Real> &xstat,
144  SampleGenerator<Real> &sampler) {
145  sampler.sumAll(*hv_,hv);
146  }
147 };
148 
149 }
150 
151 #endif
Provides the interface to evaluate objective functions.
void computeHessVec(Vector< Real > &hv, Objective< Real > &obj, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
Ptr< Vector< Real > > g_
Provides a general interface for risk and error measures generated through the expectation risk quadr...
Real computeValue(Objective< Real > &obj, const Vector< Real > &x, Real &tol)
Real getValue(const Vector< Real > &x, const std::vector< Real > &xstat, SampleGenerator< Real > &sampler)
Return risk measure value.
Ptr< Vector< Real > > hv_
Contains definitions of custom data types in ROL.
Ptr< Vector< Real > > dualVector_
Defines the linear algebra or vector space interface.
Definition: ROL_Vector.hpp:46
Provides a general interface for regret measures generated through the expectation risk quadrangle...
void sumAll(Real *input, Real *output, int dim) const
void getGradient(Vector< Real > &g, std::vector< Real > &gstat, const Vector< Real > &x, const std::vector< Real > &xstat, SampleGenerator< Real > &sampler)
Return risk measure (sub)gradient.
Ptr< ExpectationQuad< Real > > eq_
void updateValue(Objective< Real > &obj, const Vector< Real > &x, const std::vector< Real > &xstat, Real &tol)
Update internal storage for value computation.
void updateGradient(Objective< Real > &obj, const Vector< Real > &x, const std::vector< Real > &xstat, Real &tol)
Update internal risk measure storage for gradient computation.
ExpectationQuadRegret(const Ptr< ExpectationQuad< Real >> &eq)
void updateHessVec(Objective< Real > &obj, const Vector< Real > &v, const std::vector< Real > &vstat, const Vector< Real > &x, const std::vector< Real > &xstat, Real &tol)
Update internal risk measure storage for Hessian-time-a-vector computation.
void computeGradient(Vector< Real > &g, Objective< Real > &obj, const Vector< Real > &x, Real &tol)
Real computeGradVec(Vector< Real > &g, Objective< Real > &obj, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
Provides the interface to implement any functional that maps a random variable to a (extended) real n...
void getHessVec(Vector< Real > &hv, std::vector< Real > &hvstat, const Vector< Real > &v, const std::vector< Real > &vstat, const Vector< Real > &x, const std::vector< Real > &xstat, SampleGenerator< Real > &sampler)
Return risk measure Hessian-times-a-vector.
void checkRegret(void)
Run derivative tests for the scalar regret function.