ROL
ROL_GenMoreauYosidaCVaR.hpp
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43 
44 #ifndef ROL_GENMOREAUYOSIDACVAR_HPP
45 #define ROL_GENMOREAUYOSIDACVAR_HPP
46 
47 #include "ROL_ExpectationQuad.hpp"
48 
102 namespace ROL {
103 
104 template<class Real>
105 class GenMoreauYosidaCVaR : public ExpectationQuad<Real> {
106 private:
107 
108  Real prob_;
109  Real lam_;
110  Real eps_;
111 
112  Real alpha_;
113  Real beta_;
114 
115  Real omp_;
116  Real oma_;
117  Real bmo_;
118  Real lb_;
119  Real ub_;
120 
121  void parseParameterList(ROL::ParameterList &parlist) {
122  std::string type = parlist.sublist("SOL").get("Stochastic Component Type","Risk Averse");
123  ROL::ParameterList list;
124  if (type == "Risk Averse") {
125  list = parlist.sublist("SOL").sublist("Risk Measure").sublist("Generalized Moreau-Yosida CVaR");
126  }
127  else if (type == "Error") {
128  list = parlist.sublist("SOL").sublist("Error Measure").sublist("Generalized Moreau-Yosida-Koenker-Bassett");
129  }
130  else if (type == "Deviation") {
131  list = parlist.sublist("SOL").sublist("Deviation Measure").sublist("Generalized Moreau-Yosida CVaR");
132  }
133  else if (type == "Regret") {
134  list = parlist.sublist("SOL").sublist("Regret Measure").sublist("Generalized Moreau-Yosida Mean Absolute Loss");
135  }
136  prob_ = list.get<Real>("Confidence Level");
137  lam_ = list.get<Real>("Convex Combination Parameter");
138  eps_ = list.get<Real>("Smoothing Parameter");
139  }
140 
141  void checkInputs(void) const {
142  Real zero(0), one(1);
143  ROL_TEST_FOR_EXCEPTION((prob_ <= zero) || (prob_ >= one), std::invalid_argument,
144  ">>> ERROR (ROL::GenMoreauYosidaCVaR): Confidence level must be between 0 and 1!");
145  ROL_TEST_FOR_EXCEPTION((lam_ < zero) || (lam_ > one), std::invalid_argument,
146  ">>> ERROR (ROL::GenMoreauYosidaCVaR): Convex combination parameter must be positive!");
147  ROL_TEST_FOR_EXCEPTION((eps_ <= zero), std::invalid_argument,
148  ">>> ERROR (ROL::GenMoreauYosidaCVaR): Smoothing parameter must be positive!");
149  }
150 
151  void setParameters(void) {
152  const Real one(1);
153  omp_ = one-prob_;
154  alpha_ = lam_;
155  beta_ = (one-alpha_*prob_)/omp_;
156  oma_ = one-alpha_;
157  bmo_ = beta_-one;
158  lb_ = -eps_*oma_;
159  ub_ = eps_*bmo_;
160  }
161 
162 public:
168  GenMoreauYosidaCVaR(Real prob, Real eps )
169  : ExpectationQuad<Real>(), prob_(prob), lam_(0), eps_(eps) {
170  checkInputs();
171  setParameters();
172  }
173 
180  GenMoreauYosidaCVaR(Real prob, Real lam, Real eps )
181  : ExpectationQuad<Real>(), prob_(prob), lam_(lam), eps_(eps) {
182  checkInputs();
183  setParameters();
184  }
185 
196  GenMoreauYosidaCVaR(ROL::ParameterList &parlist)
197  : ExpectationQuad<Real>() {
198  parseParameterList(parlist);
199  checkInputs();
200  setParameters();
201  }
202 
203  Real error(Real x, int deriv = 0) {
204  Real zero(0), one(1);
205  Real X = ((deriv==0) ? x : ((deriv==1) ? one : zero));
206  return regret(x,deriv) - X;
207  }
208 
209  Real regret(Real x, int deriv = 0) {
210  Real zero(0), half(0.5), one(1), reg(0);
211  if ( x <= lb_ ) {
212  reg = ((deriv == 0) ? alpha_*x + half*lb_*oma_
213  : ((deriv == 1) ? alpha_ : zero));
214  }
215  else if ( x >= ub_ ) {
216  reg = ((deriv == 0) ? beta_*x - half*ub_*bmo_
217  : ((deriv == 1) ? beta_ : zero));
218  }
219  else {
220  reg = ((deriv == 0) ? half/eps_*x*x + x
221  : ((deriv == 1) ? x/eps_ + one : one/eps_));
222  }
223  return reg;
224  }
225 
226  void check(void) {
227  ExpectationQuad<Real>::check();
228  Real zero(0), one(1), two(2), p1(0.1);
229  // Check v'(ub)
230  Real x = ub_;
231  Real vx = zero, vy = zero;
232  Real dv = regret(x,1);
233  Real t = one;
234  Real diff = zero;
235  Real err = zero;
236  std::cout << std::right << std::setw(20) << "CHECK REGRET: v'(ub) is correct? \n";
237  std::cout << std::right << std::setw(20) << "t"
238  << std::setw(20) << "v'(x)"
239  << std::setw(20) << "(v(x+t)-v(x-t))/2t"
240  << std::setw(20) << "Error"
241  << "\n";
242  for (int i = 0; i < 13; i++) {
243  vy = regret(x+t,0);
244  vx = regret(x-t,0);
245  diff = (vy-vx)/(two*t);
246  err = std::abs(diff-dv);
247  std::cout << std::scientific << std::setprecision(11) << std::right
248  << std::setw(20) << t
249  << std::setw(20) << dv
250  << std::setw(20) << diff
251  << std::setw(20) << err
252  << "\n";
253  t *= p1;
254  }
255  std::cout << "\n";
256  // check v''(ub)
257  vx = zero;
258  vy = zero;
259  dv = regret(x,2);
260  t = one;
261  diff = zero;
262  err = zero;
263  std::cout << std::right << std::setw(20) << "CHECK REGRET: v''(ub) is correct? \n";
264  std::cout << std::right << std::setw(20) << "t"
265  << std::setw(20) << "v''(x)"
266  << std::setw(20) << "(v'(x+t)-v'(x-t))/2t"
267  << std::setw(20) << "Error"
268  << "\n";
269  for (int i = 0; i < 13; i++) {
270  vy = regret(x+t,1);
271  vx = regret(x-t,1);
272  diff = (vy-vx)/(two*t);
273  err = std::abs(diff-dv);
274  std::cout << std::scientific << std::setprecision(11) << std::right
275  << std::setw(20) << t
276  << std::setw(20) << dv
277  << std::setw(20) << diff
278  << std::setw(20) << err
279  << "\n";
280  t *= p1;
281  }
282  std::cout << "\n";
283  // Check v'(0)
284  x = zero;
285  vx = zero;
286  vy = zero;
287  dv = regret(x,1);
288  t = one;
289  diff = zero;
290  err = zero;
291  std::cout << std::right << std::setw(20) << "CHECK REGRET: v'(0) is correct? \n";
292  std::cout << std::right << std::setw(20) << "t"
293  << std::setw(20) << "v'(x)"
294  << std::setw(20) << "(v(x+t)-v(x-t))/2t"
295  << std::setw(20) << "Error"
296  << "\n";
297  for (int i = 0; i < 13; i++) {
298  vy = regret(x+t,0);
299  vx = regret(x-t,0);
300  diff = (vy-vx)/(two*t);
301  err = std::abs(diff-dv);
302  std::cout << std::scientific << std::setprecision(11) << std::right
303  << std::setw(20) << t
304  << std::setw(20) << dv
305  << std::setw(20) << diff
306  << std::setw(20) << err
307  << "\n";
308  t *= p1;
309  }
310  std::cout << "\n";
311  // check v''(0)
312  vx = zero;
313  vy = zero;
314  dv = regret(x,2);
315  t = one;
316  diff = zero;
317  err = zero;
318  std::cout << std::right << std::setw(20) << "CHECK REGRET: v''(0) is correct? \n";
319  std::cout << std::right << std::setw(20) << "t"
320  << std::setw(20) << "v''(x)"
321  << std::setw(20) << "(v'(x+t)-v'(x-t))/2t"
322  << std::setw(20) << "Error"
323  << "\n";
324  for (int i = 0; i < 13; i++) {
325  vy = regret(x+t,1);
326  vx = regret(x-t,1);
327  diff = (vy-vx)/(two*t);
328  err = std::abs(diff-dv);
329  std::cout << std::scientific << std::setprecision(11) << std::right
330  << std::setw(20) << t
331  << std::setw(20) << dv
332  << std::setw(20) << diff
333  << std::setw(20) << err
334  << "\n";
335  t *= p1;
336  }
337  std::cout << "\n";
338  // Check v'(lb)
339  x = lb_;
340  vx = zero;
341  vy = zero;
342  dv = regret(x,1);
343  t = one;
344  diff = zero;
345  err = zero;
346  std::cout << std::right << std::setw(20) << "CHECK REGRET: v'(lb) is correct? \n";
347  std::cout << std::right << std::setw(20) << "t"
348  << std::setw(20) << "v'(x)"
349  << std::setw(20) << "(v(x+t)-v(x-t))/2t"
350  << std::setw(20) << "Error"
351  << "\n";
352  for (int i = 0; i < 13; i++) {
353  vy = regret(x+t,0);
354  vx = regret(x-t,0);
355  diff = (vy-vx)/(two*t);
356  err = std::abs(diff-dv);
357  std::cout << std::scientific << std::setprecision(11) << std::right
358  << std::setw(20) << t
359  << std::setw(20) << dv
360  << std::setw(20) << diff
361  << std::setw(20) << err
362  << "\n";
363  t *= p1;
364  }
365  std::cout << "\n";
366  // check v''(lb)
367  vx = zero;
368  vy = zero;
369  dv = regret(x,2);
370  t = one;
371  diff = zero;
372  err = zero;
373  std::cout << std::right << std::setw(20) << "CHECK REGRET: v''(lb) is correct? \n";
374  std::cout << std::right << std::setw(20) << "t"
375  << std::setw(20) << "v''(x)"
376  << std::setw(20) << "(v'(x+t)-v'(x-t))/2t"
377  << std::setw(20) << "Error"
378  << "\n";
379  for (int i = 0; i < 13; i++) {
380  vy = regret(x+t,1);
381  vx = regret(x-t,1);
382  diff = (vy-vx)/(two*t);
383  err = std::abs(diff-dv);
384  std::cout << std::scientific << std::setprecision(11) << std::right
385  << std::setw(20) << t
386  << std::setw(20) << dv
387  << std::setw(20) << diff
388  << std::setw(20) << err
389  << "\n";
390  t *= p1;
391  }
392  std::cout << "\n";
393  }
394 
395 };
396 
397 }
398 #endif
ROL::ExpectationQuad
Provides a general interface for risk and error measures generated through the expectation risk quadr...
Definition: ROL_ExpectationQuad.hpp:87
ROL::GenMoreauYosidaCVaR::regret
Real regret(Real x, int deriv=0)
Evaluate the scalar regret function at x.
Definition: ROL_GenMoreauYosidaCVaR.hpp:209
ROL::GenMoreauYosidaCVaR::error
Real error(Real x, int deriv=0)
Evaluate the scalar error function at x.
Definition: ROL_GenMoreauYosidaCVaR.hpp:203
ROL::ExpectationQuad::check
virtual void check(void)
Run default derivative tests for the scalar regret function.
Definition: ROL_ExpectationQuad.hpp:116
ROL::GenMoreauYosidaCVaR::GenMoreauYosidaCVaR
GenMoreauYosidaCVaR(Real prob, Real eps)
Constructor.
Definition: ROL_GenMoreauYosidaCVaR.hpp:168
ROL_ExpectationQuad.hpp
ROL::GenMoreauYosidaCVaR::GenMoreauYosidaCVaR
GenMoreauYosidaCVaR(Real prob, Real lam, Real eps)
Constructor.
Definition: ROL_GenMoreauYosidaCVaR.hpp:180
zero
Objective_SerialSimOpt(const Ptr< Obj > &obj, const V &ui) z0_ zero()
Definition: ROL_Objective_SerialSimOpt.hpp:163
ROL::GenMoreauYosidaCVaR::check
void check(void)
Run default derivative tests for the scalar regret function.
Definition: ROL_GenMoreauYosidaCVaR.hpp:226
ROL::GenMoreauYosidaCVaR::GenMoreauYosidaCVaR
GenMoreauYosidaCVaR(ROL::ParameterList &parlist)
Constructor.
Definition: ROL_GenMoreauYosidaCVaR.hpp:196
ROL::GenMoreauYosidaCVaR::parseParameterList
void parseParameterList(ROL::ParameterList &parlist)
Definition: ROL_GenMoreauYosidaCVaR.hpp:121
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