ROL
ROL_MixedCVaR.hpp
Go to the documentation of this file.
1// @HEADER
2// ************************************************************************
3//
4// Rapid Optimization Library (ROL) Package
5// Copyright (2014) Sandia Corporation
6//
7// Under terms of Contract DE-AC04-94AL85000, there is a non-exclusive
8// license for use of this work by or on behalf of the U.S. Government.
9//
10// Redistribution and use in source and binary forms, with or without
11// modification, are permitted provided that the following conditions are
12// met:
13//
14// 1. Redistributions of source code must retain the above copyright
15// notice, this list of conditions and the following disclaimer.
16//
17// 2. Redistributions in binary form must reproduce the above copyright
18// notice, this list of conditions and the following disclaimer in the
19// documentation and/or other materials provided with the distribution.
20//
21// 3. Neither the name of the Corporation nor the names of the
22// contributors may be used to endorse or promote products derived from
23// this software without specific prior written permission.
24//
25// THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
26// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
27// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
28// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
29// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
30// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
31// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
32// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
33// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
34// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
35// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
36//
37// Questions? Contact lead developers:
38// Drew Kouri (dpkouri@sandia.gov) and
39// Denis Ridzal (dridzal@sandia.gov)
40//
41// ************************************************************************
42// @HEADER
43
44#ifndef ROL_MIXEDQUANTILEQUADRANGLE_HPP
45#define ROL_MIXEDQUANTILEQUADRANGLE_HPP
46
48#include "ROL_PlusFunction.hpp"
49
50#include "ROL_ParameterList.hpp"
51
85namespace ROL {
86
87template<class Real>
88class MixedCVaR : public RandVarFunctional<Real> {
89private:
90 ROL::Ptr<PlusFunction<Real> > plusFunction_;
91 std::vector<Real> prob_;
92 std::vector<Real> coeff_;
93 std::vector<Real> vec_;
94 int size_;
95
96 using RandVarFunctional<Real>::val_;
97 using RandVarFunctional<Real>::gv_;
98 using RandVarFunctional<Real>::g_;
99 using RandVarFunctional<Real>::hv_;
101
102 using RandVarFunctional<Real>::point_;
103 using RandVarFunctional<Real>::weight_;
104
109
110 void initializeMCVAR(void) {
111 size_ = prob_.size();
112 vec_.clear(); vec_.resize(size_,static_cast<Real>(0));
113 }
114
115 void checkInputs(void) {
116 int pSize = prob_.size(), cSize = coeff_.size();
117 ROL_TEST_FOR_EXCEPTION((pSize!=cSize),std::invalid_argument,
118 ">>> ERROR (ROL::MixedCVaR): Probability and coefficient arrays have different sizes!");
119 Real sum(0), zero(0), one(1);
120 for (int i = 0; i < pSize; i++) {
121 ROL_TEST_FOR_EXCEPTION((prob_[i]>one || prob_[i]<zero), std::invalid_argument,
122 ">>> ERROR (ROL::MixedCVaR): Element of probability array out of range!");
123 ROL_TEST_FOR_EXCEPTION((coeff_[i]>one || coeff_[i]<zero), std::invalid_argument,
124 ">>> ERROR (ROL::MixedCVaR): Element of coefficient array out of range!");
125 sum += coeff_[i];
126 }
127 ROL_TEST_FOR_EXCEPTION((std::abs(sum-one) > std::sqrt(ROL_EPSILON<Real>())),std::invalid_argument,
128 ">>> ERROR (ROL::MixedCVaR): Coefficients do not sum to one!");
129 ROL_TEST_FOR_EXCEPTION(plusFunction_ == ROL::nullPtr, std::invalid_argument,
130 ">>> ERROR (ROL::MixedCVaR): PlusFunction pointer is null!");
132 }
133
134public:
135
136 MixedCVaR( ROL::ParameterList &parlist )
137 : RandVarFunctional<Real>() {
138 ROL::ParameterList &list
139 = parlist.sublist("SOL").sublist("Risk Measure").sublist("Mixed CVaR");
140 // Grab probability and coefficient arrays
141 prob_ = ROL::getArrayFromStringParameter<Real>(list,"Probability Array");
142 coeff_ = ROL::getArrayFromStringParameter<Real>(list,"Coefficient Array");
143 plusFunction_ = ROL::makePtr<PlusFunction<Real>>(list);
144 // Check inputs
145 checkInputs();
146 }
147
148 MixedCVaR(const std::vector<Real> &prob,
149 const std::vector<Real> &coeff,
150 const ROL::Ptr<PlusFunction<Real> > &pf )
151 : RandVarFunctional<Real>(), plusFunction_(pf), prob_(prob), coeff_(coeff) {
152 checkInputs();
153 }
154
155 void initialize(const Vector<Real> &x) {
157 vec_.assign(size_,static_cast<Real>(0));
158 }
159
160 Real computeStatistic(const Ptr<std::vector<Real>> &xstat) const {
161 Real stat(0);
162 if (xstat != nullPtr) {
163 for (int i = 0; i < size_; ++i) {
164 stat = coeff_[i]*(*xstat)[i];
165 }
166 }
167 return stat;
168 }
169
171 const Vector<Real> &x,
172 const std::vector<Real> &xstat,
173 Real &tol) {
174 Real pf(0), one(1);
175 Real val = computeValue(obj,x,tol);
176 for (int i = 0; i < size_; i++) {
177 pf = plusFunction_->evaluate(val-xstat[i],0);
178 val_ += weight_*coeff_[i]/(one-prob_[i])*pf;
179 }
180 }
181
182 Real getValue(const Vector<Real> &x,
183 const std::vector<Real> &xstat,
184 SampleGenerator<Real> &sampler) {
185 Real cvar(0);
186 sampler.sumAll(&val_,&cvar,1);
187 for (int i = 0; i < size_; i++) {
188 cvar += coeff_[i]*xstat[i];
189 }
190 return cvar;
191 }
192
194 const Vector<Real> &x,
195 const std::vector<Real> &xstat,
196 Real &tol) {
197 Real pf(0), c(0), one(1);
198 Real val = computeValue(obj,x,tol);
199 for (int i = 0; i < size_; i++) {
200 pf = plusFunction_->evaluate(val-xstat[i],1);
201 c = weight_*coeff_[i]/(one-prob_[i])*pf;
202 if (std::abs(c) >= ROL_EPSILON<Real>()) {
203 vec_[i] -= c;
204 computeGradient(*dualVector_,obj,x,tol);
205 g_->axpy(c,*dualVector_);
206 }
207 }
208 }
209
211 std::vector<Real> &gstat,
212 const Vector<Real> &x,
213 const std::vector<Real> &xstat,
214 SampleGenerator<Real> &sampler) {
215 sampler.sumAll(&vec_[0],&gstat[0],size_);
216 for (int i = 0; i < size_; i++) {
217 gstat[i] += coeff_[i];
218 }
219 sampler.sumAll(*g_,g);
220 }
221
223 const Vector<Real> &v,
224 const std::vector<Real> &vstat,
225 const Vector<Real> &x,
226 const std::vector<Real> &xstat,
227 Real &tol) {
228 Real pf1(0), pf2(0), c(0), one(1);
229 Real val = computeValue(obj,x,tol);
230 for (int i = 0; i < size_; i++) {
231 pf1 = plusFunction_->evaluate(val-xstat[i],1);
232 pf2 = plusFunction_->evaluate(val-xstat[i],2);
233 if (std::abs(pf2) >= ROL_EPSILON<Real>()) {
234 Real gv = computeGradVec(*dualVector_,obj,v,x,tol);
235 c = weight_*coeff_[i]/(one-prob_[i])*pf2*(gv-vstat[i]);
236 vec_[i] -= c;
237 hv_->axpy(c,*dualVector_);
238 }
239 if (std::abs(pf1) >= ROL_EPSILON<Real>()) {
240 c = weight_*coeff_[i]/(one-prob_[i])*pf1;
241 computeHessVec(*dualVector_,obj,v,x,tol);
243 }
244 }
245 }
246
248 std::vector<Real> &hvstat,
249 const Vector<Real> &v,
250 const std::vector<Real> &vstat,
251 const Vector<Real> &x,
252 const std::vector<Real> &xstat,
253 SampleGenerator<Real> &sampler) {
254 sampler.sumAll(&vec_[0],&hvstat[0],size_);
255 sampler.sumAll(*hv_,hv);
256 }
257};
258
259}
260
261#endif
Objective_SerialSimOpt(const Ptr< Obj > &obj, const V &ui) z0 zero)()
Provides an interface for a convex combination of conditional value-at-risks.
MixedCVaR(ROL::ParameterList &parlist)
void updateValue(Objective< Real > &obj, const Vector< Real > &x, const std::vector< Real > &xstat, Real &tol)
Update internal storage for value computation.
std::vector< Real > prob_
std::vector< Real > coeff_
MixedCVaR(const std::vector< Real > &prob, const std::vector< Real > &coeff, const ROL::Ptr< PlusFunction< Real > > &pf)
void checkInputs(void)
std::vector< Real > vec_
Real computeStatistic(const Ptr< std::vector< Real > > &xstat) const
void updateGradient(Objective< Real > &obj, const Vector< Real > &x, const std::vector< Real > &xstat, Real &tol)
Update internal risk measure storage for gradient computation.
void initializeMCVAR(void)
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 initialize(const Vector< Real > &x)
Initialize temporary variables.
ROL::Ptr< PlusFunction< Real > > plusFunction_
Real getValue(const Vector< Real > &x, const std::vector< Real > &xstat, SampleGenerator< Real > &sampler)
Return risk measure value.
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.
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.
Provides the interface to evaluate objective functions.
Provides the interface to implement any functional that maps a random variable to a (extended) real n...
Real computeValue(Objective< Real > &obj, const Vector< Real > &x, Real &tol)
virtual void initialize(const Vector< Real > &x)
Initialize temporary variables.
void computeHessVec(Vector< Real > &hv, Objective< Real > &obj, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
void computeGradient(Vector< Real > &g, Objective< Real > &obj, const Vector< Real > &x, Real &tol)
Ptr< Vector< Real > > dualVector_
Real computeGradVec(Vector< Real > &g, Objective< Real > &obj, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
void sumAll(Real *input, Real *output, int dim) const
Defines the linear algebra or vector space interface.