ROL
ROL_GenMoreauYosidaCVaR.hpp
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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_GENMOREAUYOSIDACVAR_HPP
11#define ROL_GENMOREAUYOSIDACVAR_HPP
12
13#include "ROL_ExpectationQuad.hpp"
14
68namespace ROL {
69
70template<class Real>
71class GenMoreauYosidaCVaR : public ExpectationQuad<Real> {
72private:
73
74 Real prob_;
75 Real lam_;
76 Real eps_;
77
78 Real alpha_;
79 Real beta_;
80
81 Real omp_;
82 Real oma_;
83 Real bmo_;
84 Real lb_;
85 Real ub_;
86
87 void parseParameterList(ROL::ParameterList &parlist) {
88 std::string type = parlist.sublist("SOL").get("Type","Risk Averse");
89 ROL::ParameterList list;
90 if (type == "Risk Averse") {
91 list = parlist.sublist("SOL").sublist("Risk Measure").sublist("Generalized Moreau-Yosida CVaR");
92 }
93 else if (type == "Error") {
94 list = parlist.sublist("SOL").sublist("Error Measure").sublist("Generalized Moreau-Yosida-Koenker-Bassett");
95 }
96 else if (type == "Deviation") {
97 list = parlist.sublist("SOL").sublist("Deviation Measure").sublist("Generalized Moreau-Yosida CVaR");
98 }
99 else if (type == "Regret") {
100 list = parlist.sublist("SOL").sublist("Regret Measure").sublist("Generalized Moreau-Yosida Mean Absolute Loss");
101 }
102 prob_ = list.get<Real>("Confidence Level");
103 lam_ = list.get<Real>("Convex Combination Parameter");
104 eps_ = list.get<Real>("Smoothing Parameter");
105 }
106
107 void checkInputs(void) const {
108 Real zero(0), one(1);
109 ROL_TEST_FOR_EXCEPTION((prob_ <= zero) || (prob_ >= one), std::invalid_argument,
110 ">>> ERROR (ROL::GenMoreauYosidaCVaR): Confidence level must be between 0 and 1!");
111 ROL_TEST_FOR_EXCEPTION((lam_ < zero) || (lam_ > one), std::invalid_argument,
112 ">>> ERROR (ROL::GenMoreauYosidaCVaR): Convex combination parameter must be positive!");
113 ROL_TEST_FOR_EXCEPTION((eps_ <= zero), std::invalid_argument,
114 ">>> ERROR (ROL::GenMoreauYosidaCVaR): Smoothing parameter must be positive!");
115 }
116
117 void setParameters(void) {
118 const Real one(1);
119 omp_ = one-prob_;
120 alpha_ = lam_;
121 beta_ = (one-alpha_*prob_)/omp_;
122 oma_ = one-alpha_;
123 bmo_ = beta_-one;
124 lb_ = -eps_*oma_;
125 ub_ = eps_*bmo_;
126 }
127
128public:
134 GenMoreauYosidaCVaR(Real prob, Real eps )
135 : ExpectationQuad<Real>(), prob_(prob), lam_(0), eps_(eps) {
136 checkInputs();
137 setParameters();
138 }
139
146 GenMoreauYosidaCVaR(Real prob, Real lam, Real eps )
147 : ExpectationQuad<Real>(), prob_(prob), lam_(lam), eps_(eps) {
148 checkInputs();
149 setParameters();
150 }
151
162 GenMoreauYosidaCVaR(ROL::ParameterList &parlist)
163 : ExpectationQuad<Real>() {
164 parseParameterList(parlist);
165 checkInputs();
166 setParameters();
167 }
168
169 Real error(Real x, int deriv = 0) {
170 Real zero(0), one(1);
171 Real X = ((deriv==0) ? x : ((deriv==1) ? one : zero));
172 return regret(x,deriv) - X;
173 }
174
175 Real regret(Real x, int deriv = 0) {
176 Real zero(0), half(0.5), one(1), reg(0);
177 if ( x <= lb_ ) {
178 reg = ((deriv == 0) ? alpha_*x + half*lb_*oma_
179 : ((deriv == 1) ? alpha_ : zero));
180 }
181 else if ( x >= ub_ ) {
182 reg = ((deriv == 0) ? beta_*x - half*ub_*bmo_
183 : ((deriv == 1) ? beta_ : zero));
184 }
185 else {
186 reg = ((deriv == 0) ? half/eps_*x*x + x
187 : ((deriv == 1) ? x/eps_ + one : one/eps_));
188 }
189 return reg;
190 }
191
192 void check(void) {
193 ExpectationQuad<Real>::check();
194 Real zero(0), one(1), two(2), p1(0.1);
195 // Check v'(ub)
196 Real x = ub_;
197 Real vx = zero, vy = zero;
198 Real dv = regret(x,1);
199 Real t = one;
200 Real diff = zero;
201 Real err = zero;
202 std::cout << std::right << std::setw(20) << "CHECK REGRET: v'(ub) is correct? \n";
203 std::cout << std::right << std::setw(20) << "t"
204 << std::setw(20) << "v'(x)"
205 << std::setw(20) << "(v(x+t)-v(x-t))/2t"
206 << std::setw(20) << "Error"
207 << "\n";
208 for (int i = 0; i < 13; i++) {
209 vy = regret(x+t,0);
210 vx = regret(x-t,0);
211 diff = (vy-vx)/(two*t);
212 err = std::abs(diff-dv);
213 std::cout << std::scientific << std::setprecision(11) << std::right
214 << std::setw(20) << t
215 << std::setw(20) << dv
216 << std::setw(20) << diff
217 << std::setw(20) << err
218 << "\n";
219 t *= p1;
220 }
221 std::cout << "\n";
222 // check v''(ub)
223 vx = zero;
224 vy = zero;
225 dv = regret(x,2);
226 t = one;
227 diff = zero;
228 err = zero;
229 std::cout << std::right << std::setw(20) << "CHECK REGRET: v''(ub) is correct? \n";
230 std::cout << std::right << std::setw(20) << "t"
231 << std::setw(20) << "v''(x)"
232 << std::setw(20) << "(v'(x+t)-v'(x-t))/2t"
233 << std::setw(20) << "Error"
234 << "\n";
235 for (int i = 0; i < 13; i++) {
236 vy = regret(x+t,1);
237 vx = regret(x-t,1);
238 diff = (vy-vx)/(two*t);
239 err = std::abs(diff-dv);
240 std::cout << std::scientific << std::setprecision(11) << std::right
241 << std::setw(20) << t
242 << std::setw(20) << dv
243 << std::setw(20) << diff
244 << std::setw(20) << err
245 << "\n";
246 t *= p1;
247 }
248 std::cout << "\n";
249 // Check v'(0)
250 x = zero;
251 vx = zero;
252 vy = zero;
253 dv = regret(x,1);
254 t = one;
255 diff = zero;
256 err = zero;
257 std::cout << std::right << std::setw(20) << "CHECK REGRET: v'(0) is correct? \n";
258 std::cout << std::right << std::setw(20) << "t"
259 << std::setw(20) << "v'(x)"
260 << std::setw(20) << "(v(x+t)-v(x-t))/2t"
261 << std::setw(20) << "Error"
262 << "\n";
263 for (int i = 0; i < 13; i++) {
264 vy = regret(x+t,0);
265 vx = regret(x-t,0);
266 diff = (vy-vx)/(two*t);
267 err = std::abs(diff-dv);
268 std::cout << std::scientific << std::setprecision(11) << std::right
269 << std::setw(20) << t
270 << std::setw(20) << dv
271 << std::setw(20) << diff
272 << std::setw(20) << err
273 << "\n";
274 t *= p1;
275 }
276 std::cout << "\n";
277 // check v''(0)
278 vx = zero;
279 vy = zero;
280 dv = regret(x,2);
281 t = one;
282 diff = zero;
283 err = zero;
284 std::cout << std::right << std::setw(20) << "CHECK REGRET: v''(0) is correct? \n";
285 std::cout << std::right << std::setw(20) << "t"
286 << std::setw(20) << "v''(x)"
287 << std::setw(20) << "(v'(x+t)-v'(x-t))/2t"
288 << std::setw(20) << "Error"
289 << "\n";
290 for (int i = 0; i < 13; i++) {
291 vy = regret(x+t,1);
292 vx = regret(x-t,1);
293 diff = (vy-vx)/(two*t);
294 err = std::abs(diff-dv);
295 std::cout << std::scientific << std::setprecision(11) << std::right
296 << std::setw(20) << t
297 << std::setw(20) << dv
298 << std::setw(20) << diff
299 << std::setw(20) << err
300 << "\n";
301 t *= p1;
302 }
303 std::cout << "\n";
304 // Check v'(lb)
305 x = lb_;
306 vx = zero;
307 vy = zero;
308 dv = regret(x,1);
309 t = one;
310 diff = zero;
311 err = zero;
312 std::cout << std::right << std::setw(20) << "CHECK REGRET: v'(lb) is correct? \n";
313 std::cout << std::right << std::setw(20) << "t"
314 << std::setw(20) << "v'(x)"
315 << std::setw(20) << "(v(x+t)-v(x-t))/2t"
316 << std::setw(20) << "Error"
317 << "\n";
318 for (int i = 0; i < 13; i++) {
319 vy = regret(x+t,0);
320 vx = regret(x-t,0);
321 diff = (vy-vx)/(two*t);
322 err = std::abs(diff-dv);
323 std::cout << std::scientific << std::setprecision(11) << std::right
324 << std::setw(20) << t
325 << std::setw(20) << dv
326 << std::setw(20) << diff
327 << std::setw(20) << err
328 << "\n";
329 t *= p1;
330 }
331 std::cout << "\n";
332 // check v''(lb)
333 vx = zero;
334 vy = zero;
335 dv = regret(x,2);
336 t = one;
337 diff = zero;
338 err = zero;
339 std::cout << std::right << std::setw(20) << "CHECK REGRET: v''(lb) is correct? \n";
340 std::cout << std::right << std::setw(20) << "t"
341 << std::setw(20) << "v''(x)"
342 << std::setw(20) << "(v'(x+t)-v'(x-t))/2t"
343 << std::setw(20) << "Error"
344 << "\n";
345 for (int i = 0; i < 13; i++) {
346 vy = regret(x+t,1);
347 vx = regret(x-t,1);
348 diff = (vy-vx)/(two*t);
349 err = std::abs(diff-dv);
350 std::cout << std::scientific << std::setprecision(11) << std::right
351 << std::setw(20) << t
352 << std::setw(20) << dv
353 << std::setw(20) << diff
354 << std::setw(20) << err
355 << "\n";
356 t *= p1;
357 }
358 std::cout << "\n";
359 }
360
361};
362
363}
364#endif
ROL_ExpectationQuad.hpp
zero
Objective_SerialSimOpt(const Ptr< Obj > &obj, const V &ui) z0_ zero()
Definition ROL_Objective_SerialSimOpt.hpp:77
ROL::ExpectationQuad
Provides a general interface for risk and error measures generated through the expectation risk quadr...
Definition ROL_ExpectationQuad.hpp:53
ROL::ExpectationQuad::check
virtual void check(void)
Run default derivative tests for the scalar regret function.
Definition ROL_ExpectationQuad.hpp:82
ROL::GenMoreauYosidaCVaR::GenMoreauYosidaCVaR
GenMoreauYosidaCVaR(Real prob, Real lam, Real eps)
Constructor.
Definition ROL_GenMoreauYosidaCVaR.hpp:146
ROL::GenMoreauYosidaCVaR::GenMoreauYosidaCVaR
GenMoreauYosidaCVaR(Real prob, Real eps)
Constructor.
Definition ROL_GenMoreauYosidaCVaR.hpp:134
ROL::GenMoreauYosidaCVaR::check
void check(void)
Run default derivative tests for the scalar regret function.
Definition ROL_GenMoreauYosidaCVaR.hpp:192
ROL::GenMoreauYosidaCVaR::regret
Real regret(Real x, int deriv=0)
Evaluate the scalar regret function at x.
Definition ROL_GenMoreauYosidaCVaR.hpp:175
ROL::GenMoreauYosidaCVaR::error
Real error(Real x, int deriv=0)
Evaluate the scalar error function at x.
Definition ROL_GenMoreauYosidaCVaR.hpp:169
ROL::GenMoreauYosidaCVaR::parseParameterList
void parseParameterList(ROL::ParameterList &parlist)
Definition ROL_GenMoreauYosidaCVaR.hpp:87
ROL::GenMoreauYosidaCVaR::GenMoreauYosidaCVaR
GenMoreauYosidaCVaR(ROL::ParameterList &parlist)
Constructor.
Definition ROL_GenMoreauYosidaCVaR.hpp:162
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