ROL
ROL_ExpectationQuad.hpp
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43
44#ifndef ROL_EXPECTATIONQUAD_HPP
45#define ROL_EXPECTATIONQUAD_HPP
46
47#include "ROL_Types.hpp"
48
82
83
84namespace ROL {
85
86template<class Real>
88public:
89 virtual ~ExpectationQuad(void) {}
91
99 virtual Real regret(Real x, int deriv = 0) = 0;
100
108 virtual Real error(Real x, int deriv = 0) {
109 const Real one(1), zero(0);
110 Real X = (deriv==0 ? x : (deriv==1 ? one : zero));
111 return regret(x,deriv) - X;
112 }
113
116 virtual void check(void) {
117 Real zero(0), half(0.5), two(2), one(1), oem3(1.e-3), fem4(5.e-4), p1(0.1);
118 // Check v(0) = 0
119 Real x = zero;
120 Real vx = regret(x,0);
121 std::cout << std::right << std::setw(20) << "CHECK REGRET: v(0) = 0? \n";
122 std::cout << std::right << std::setw(20) << "v(0)" << "\n";
123 std::cout << std::scientific << std::setprecision(11) << std::right
124 << std::setw(20) << std::abs(vx)
125 << "\n";
126 std::cout << "\n";
127 // Check v(x) > x
128 Real scale = two;
129 std::cout << std::right << std::setw(20) << "CHECK REGRET: x < v(x) for |x| > 0? \n";
130 std::cout << std::right << std::setw(20) << "x"
131 << std::right << std::setw(20) << "v(x)"
132 << "\n";
133 for (int i = 0; i < 10; i++) {
134 x = scale*(Real)rand()/(Real)RAND_MAX - scale*half;
135 vx = regret(x,0);
136 std::cout << std::scientific << std::setprecision(11) << std::right
137 << std::setw(20) << x
138 << std::setw(20) << vx
139 << "\n";
140 scale *= two;
141 }
142 std::cout << "\n";
143 // Check v(x) is convex
144 Real y = zero;
145 Real vy = zero;
146 Real z = zero;
147 Real vz = zero;
148 Real l = zero;
149 scale = two;
150 std::cout << std::right << std::setw(20) << "CHECK REGRET: v(x) is convex? \n";
151 std::cout << std::right << std::setw(20) << "v(l*x+(1-l)*y)"
152 << std::setw(20) << "l*v(x)+(1-l)*v(y)"
153 << "\n";
154 for (int i = 0; i < 10; i++) {
155 x = scale*(Real)rand()/(Real)RAND_MAX - scale*half;
156 vx = regret(x,0);
157 y = scale*(Real)rand()/(Real)RAND_MAX - scale*half;
158 vy = regret(y,0);
159 l = (Real)rand()/(Real)RAND_MAX;
160 z = l*x + (one-l)*y;
161 vz = regret(z,0);
162 std::cout << std::scientific << std::setprecision(11) << std::right
163 << std::setw(20) << vz
164 << std::setw(20) << l*vx + (one-l)*vy
165 << "\n";
166 scale *= two;
167 }
168 std::cout << "\n";
169 // Check v'(x)
170 x = oem3*(Real)rand()/(Real)RAND_MAX - fem4;
171 vx = regret(x,0);
172 Real dv = regret(x,1);
173 Real t = one;
174 Real diff = zero;
175 Real err = zero;
176 std::cout << std::right << std::setw(20) << "CHECK REGRET: v'(x) is correct? \n";
177 std::cout << std::right << std::setw(20) << "t"
178 << std::setw(20) << "v'(x)"
179 << std::setw(20) << "(v(x+t)-v(x))/t"
180 << std::setw(20) << "Error"
181 << "\n";
182 for (int i = 0; i < 13; i++) {
183 y = x + t;
184 vy = regret(y,0);
185 diff = (vy-vx)/t;
186 err = std::abs(diff-dv);
187 std::cout << std::scientific << std::setprecision(11) << std::right
188 << std::setw(20) << t
189 << std::setw(20) << dv
190 << std::setw(20) << diff
191 << std::setw(20) << err
192 << "\n";
193 t *= p1;
194 }
195 std::cout << "\n";
196 // Check v''(x)
197 x = oem3*(Real)rand()/(Real)RAND_MAX - fem4;
198 vx = regret(x,1);
199 dv = regret(x,2);
200 t = one;
201 diff = zero;
202 err = zero;
203 std::cout << std::right << std::setw(20) << "CHECK REGRET: v''(x) is correct? \n";
204 std::cout << std::right << std::setw(20) << "t"
205 << std::setw(20) << "v''(x)"
206 << std::setw(20) << "(v'(x+t)-v'(x))/t"
207 << std::setw(20) << "Error"
208 << "\n";
209 for (int i = 0; i < 13; i++) {
210 y = x + t;
211 vy = regret(y,1);
212 diff = (vy-vx)/t;
213 err = std::abs(diff-dv);
214 std::cout << std::scientific << std::setprecision(11) << std::right
215 << std::setw(20) << t
216 << std::setw(20) << dv
217 << std::setw(20) << diff
218 << std::setw(20) << err
219 << "\n";
220 t *= p1;
221 }
222 std::cout << "\n";
223 }
224};
225
226}
227
228#endif
Objective_SerialSimOpt(const Ptr< Obj > &obj, const V &ui) z0 zero)()
Contains definitions of custom data types in ROL.
virtual void check(void)
Run default derivative tests for the scalar regret function.
virtual Real error(Real x, int deriv=0)
Evaluate the scalar error function at x.
virtual Real regret(Real x, int deriv=0)=0
Evaluate the scalar regret function at x.