testfunctions.hpp 6.91 KB
 Antoine Cully committed Apr 11, 2016 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 ``````#define _USE_MATH_DEFINES #include // support functions inline double sign(double x) { if (x < 0) return -1; if (x > 0) return 1; return 0; } inline double sqr(double x) { return x * x; }; inline double hat(double x) { if (x != 0) return log(fabs(x)); return 0; } inline double c1(double x) { if (x > 0) return 10; return 5.5; } inline double c2(double x) { if (x > 0) return 7.9; return 3.1; } inline Eigen::VectorXd t_osz(const Eigen::VectorXd& x) { Eigen::VectorXd r = x; for (int i = 0; i < x.size(); i++) r(i) = sign(x(i)) * exp(hat(x(i)) + 0.049 * sin(c1(x(i)) * hat(x(i))) + sin(c2(x(i)) * hat(x(i)))); return r; } struct Sphere { static constexpr size_t dim_in = 2; static constexpr size_t dim_out = 1; double operator()(const Eigen::VectorXd& x) const { Eigen::VectorXd opt(2); opt << 0.5, 0.5; return (x - opt).squaredNorm(); } Eigen::MatrixXd solutions() const { Eigen::MatrixXd sols(1, 2); sols << 0.5, 0.5; return sols; } }; struct Ellipsoid { static constexpr size_t dim_in = 2; static constexpr size_t dim_out = 1; double operator()(const Eigen::VectorXd& x) const { Eigen::VectorXd opt(2); opt << 0.5, 0.5; Eigen::VectorXd z = t_osz(x - opt); double r = 0; for (size_t i = 0; i < dim_in; ++i) r += std::pow(10, ((double)i) / (dim_in - 1.0)) * z(i) * z(i) + 1; return r; } Eigen::MatrixXd solutions() const { Eigen::MatrixXd sols(1, 2); sols << 0.5, 0.5; return sols; } }; struct Rastrigin { static constexpr size_t dim_in = 4; static constexpr size_t dim_out = 1; double operator()(const Eigen::VectorXd& x) const { `````` Konstantinos Chatzilygeroudis committed May 19, 2016 97 98 99 100 `````` double f = 10 * dim_in; for (size_t i = 0; i < dim_in; ++i) f += x(i) * x(i) - 10 * cos(2 * M_PI * x(i)); return f; `````` Antoine Cully committed Apr 11, 2016 101 102 103 104 `````` } Eigen::MatrixXd solutions() const { `````` Konstantinos Chatzilygeroudis committed May 19, 2016 105 106 107 108 `````` Eigen::MatrixXd sols(1, 4); for (size_t i = 0; i < 4; ++i) sols(0, i) = 0; return sols; `````` Antoine Cully committed Apr 11, 2016 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 `````` } }; // see : http://www.sfu.ca/~ssurjano/hart3.html struct Hartman3 { static constexpr size_t dim_in = 3; static constexpr size_t dim_out = 1; double operator()(const Eigen::VectorXd& x) const { Eigen::MatrixXd a(4, 3); Eigen::MatrixXd p(4, 3); a << 3.0, 10, 30, 0.1, 10, 35, 3.0, 10, 30, 0.1, 10, 36; p << 0.3689, 0.1170, 0.2673, 0.4699, 0.4387, 0.7470, 0.1091, 0.8732, 0.5547, 0.0382, 0.5743, 0.8828; Eigen::VectorXd alpha(4); alpha << 1.0, 1.2, 3.0, 3.2; double res = 0; for (int i = 0; i < 4; i++) { double s = 0.0f; for (size_t j = 0; j < 3; j++) { s += a(i, j) * (x(j) - p(i, j)) * (x(j) - p(i, j)); } res += alpha(i) * exp(-s); } return -res; } Eigen::MatrixXd solutions() const { Eigen::MatrixXd sols(1, 3); sols << 0.114614, 0.555649, 0.852547; return sols; } }; // see : http://www.sfu.ca/~ssurjano/hart6.html struct Hartman6 { static constexpr size_t dim_in = 6; static constexpr size_t dim_out = 1; double operator()(const Eigen::VectorXd& x) const { Eigen::MatrixXd a(4, 6); Eigen::MatrixXd p(4, 6); a << 10, 3, 17, 3.5, 1.7, 8, 0.05, 10, 17, 0.1, 8, 14, 3, 3.5, 1.7, 10, 17, 8, 17, 8, 0.05, 10, 0.1, 14; p << 0.1312, 0.1696, 0.5569, 0.0124, 0.8283, 0.5886, 0.2329, 0.4135, 0.8307, 0.3736, 0.1004, 0.9991, 0.2348, 0.1451, 0.3522, 0.2883, 0.3047, 0.665, 0.4047, 0.8828, 0.8732, 0.5743, 0.1091, 0.0381; Eigen::VectorXd alpha(4); alpha << 1.0, 1.2, 3.0, 3.2; double res = 0; for (int i = 0; i < 4; i++) { double s = 0.0f; for (size_t j = 0; j < 6; j++) { s += a(i, j) * sqr(x(j) - p(i, j)); } res += alpha(i) * exp(-s); } return -res; } Eigen::MatrixXd solutions() const { Eigen::MatrixXd sols(1, 6); sols << 0.20169, 0.150011, 0.476874, 0.275332, 0.311652, 0.6573; return sols; } }; // see : http://www.sfu.ca/~ssurjano/goldpr.html // (with ln, as suggested in Jones et al.) struct GoldenPrice { static constexpr size_t dim_in = 2; static constexpr size_t dim_out = 1; double operator()(const Eigen::VectorXd& xx) const { Eigen::VectorXd x = (4.0 * xx); x(0) -= 2.0; x(1) -= 2.0; double r = (1 + (x(0) + x(1) + 1) * (x(0) + x(1) + 1) * (19 - 14 * x(0) + 3 * x(0) * x(0) - 14 * x(1) + 6 * x(0) * x(1) + 3 * x(1) * x(1))) * (30 + (2 * x(0) - 3 * x(1)) * (2 * x(0) - 3 * x(1)) * (18 - 32 * x(0) + 12 * x(0) * x(0) + 48 * x(1) - 36 * x(0) * x(1) + 27 * x(1) * x(1))); return log(r) - 5; } Eigen::MatrixXd solutions() const { Eigen::MatrixXd sols(1, 2); sols << 0.5, 0.25; return sols; } }; struct BraninNormalized { static constexpr size_t dim_in = 2; static constexpr size_t dim_out = 1; double operator()(const Eigen::VectorXd& x) const { double a = x(0) * 15 - 5; double b = x(1) * 15; return sqr(b - (5.1 / (4 * sqr(M_PI))) * sqr(a) + 5 * a / M_PI - 6) + 10 * (1 - 1 / (8 * M_PI)) * cos(a) + 10; } Eigen::MatrixXd solutions() const { Eigen::MatrixXd sols(3, 2); sols << 0.1238938, 0.818333, 0.5427728, 0.151667, 0.961652, 0.1650; return sols; } }; struct SixHumpCamel { static constexpr size_t dim_in = 2; static constexpr size_t dim_out = 1; double operator()(const Eigen::VectorXd& x) const { double x1_2 = x(0) * x(0); double x2_2 = x(1) * x(1); double tmp1 = (4 - 2.1 * x1_2 + (x1_2 * x1_2) / 3) * x1_2; double tmp2 = x(0) * x(1); double tmp3 = (-4 + 4 * x2_2) * x2_2; return tmp1 + tmp2 + tmp3; } Eigen::MatrixXd solutions() const { Eigen::MatrixXd sols(2, 2); sols << 0.0898, -0.7126, -0.0898, 0.7126; return sols; } }; template class Benchmark { public: static constexpr size_t dim_in = Function::dim_in; static constexpr size_t dim_out = Function::dim_out; Eigen::VectorXd operator()(const Eigen::VectorXd& x) const { Eigen::VectorXd res(1); res(0) = -f(x); return res; } `````` Konstantinos Chatzilygeroudis committed May 19, 2016 264 `````` double accuracy(Eigen::VectorXd obs) `````` Antoine Cully committed Apr 11, 2016 265 `````` { `````` Konstantinos Chatzilygeroudis committed May 19, 2016 266 `````` double x = obs[0]; `````` Antoine Cully committed Apr 11, 2016 267 268 269 270 `````` Eigen::MatrixXd sols = f.solutions(); double diff = std::abs(x + f(sols.row(0))); double min_diff = diff; `````` Konstantinos Chatzilygeroudis committed May 27, 2016 271 `````` for (int i = 1; i < sols.rows(); i++) { `````` Antoine Cully committed Apr 11, 2016 272 273 274 275 276 277 278 279 280 281 `````` diff = std::abs(x + f(sols.row(i))); if (diff < min_diff) min_diff = diff; } return min_diff; } Function f; };``````