| Directory: | ./ |
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| File: | include/eiquadprog/eiquadprog-rt.hxx |
| Date: | 2024-12-04 10:05:36 |
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| Lines: | 120 | 190 | 63.2% |
| Branches: | 24 | 66 | 36.4% |
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| 1 | // | ||
| 2 | // Copyright (c) 2017 CNRS | ||
| 3 | // | ||
| 4 | // This file is part of eiquadprog. | ||
| 5 | // | ||
| 6 | // eiquadprog is free software: you can redistribute it and/or modify | ||
| 7 | // it under the terms of the GNU Lesser General Public License as published by | ||
| 8 | // the Free Software Foundation, either version 3 of the License, or | ||
| 9 | //(at your option) any later version. | ||
| 10 | |||
| 11 | // eiquadprog is distributed in the hope that it will be useful, | ||
| 12 | // but WITHOUT ANY WARRANTY; without even the implied warranty of | ||
| 13 | // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the | ||
| 14 | // GNU Lesser General Public License for more details. | ||
| 15 | |||
| 16 | // You should have received a copy of the GNU Lesser General Public License | ||
| 17 | // along with eiquadprog. If not, see <https://www.gnu.org/licenses/>. | ||
| 18 | |||
| 19 | #ifndef __eiquadprog_rt_hxx__ | ||
| 20 | #define __eiquadprog_rt_hxx__ | ||
| 21 | |||
| 22 | #include "eiquadprog/eiquadprog-utils.hxx" | ||
| 23 | |||
| 24 | namespace eiquadprog { | ||
| 25 | |||
| 26 | namespace solvers { | ||
| 27 | |||
| 28 | template <int nVars, int nEqCon, int nIneqCon> | ||
| 29 | 24 | RtEiquadprog<nVars, nEqCon, nIneqCon>::RtEiquadprog() | |
| 30 |
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24 | : solver_return_(std::numeric_limits<double>::infinity()) { |
| 31 | 24 | m_maxIter = DEFAULT_MAX_ITER; | |
| 32 | 24 | q = 0; // size of the active set A | |
| 33 | // (containing the indices of the active constraints) | ||
| 34 | 24 | is_inverse_provided_ = false; | |
| 35 | 24 | } | |
| 36 | |||
| 37 | template <int nVars, int nEqCon, int nIneqCon> | ||
| 38 | 24 | RtEiquadprog<nVars, nEqCon, nIneqCon>::~RtEiquadprog() {} | |
| 39 | |||
| 40 | template <int nVars, int nEqCon, int nIneqCon> | ||
| 41 | 22 | bool RtEiquadprog<nVars, nEqCon, nIneqCon>::add_constraint( | |
| 42 | typename RtMatrixX<nVars, nVars>::d &R, | ||
| 43 | typename RtMatrixX<nVars, nVars>::d &J, typename RtVectorX<nVars>::d &d, | ||
| 44 | int &iq, double &R_norm) { | ||
| 45 | // int n=J.rows(); | ||
| 46 | #ifdef EIQGUADPROG_TRACE_SOLVER | ||
| 47 | std::cerr << "Add constraint " << iq << '/'; | ||
| 48 | #endif | ||
| 49 | int j, k; | ||
| 50 | double cc, ss, h, t1, t2, xny; | ||
| 51 | |||
| 52 | #ifdef OPTIMIZE_ADD_CONSTRAINT | ||
| 53 | Eigen::Vector2d cc_ss; | ||
| 54 | #endif | ||
| 55 | |||
| 56 | /* we have to find the Givens rotation which will reduce the element | ||
| 57 | d(j) to zero. | ||
| 58 | if it is already zero we don't have to do anything, except of | ||
| 59 | decreasing j */ | ||
| 60 |
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36 | for (j = nVars - 1; j >= iq + 1; j--) { |
| 61 | /* The Givens rotation is done with the matrix (cc cs, cs -cc). | ||
| 62 | If cc is one, then element (j) of d is zero compared with | ||
| 63 | element (j - 1). Hence we don't have to do anything. If cc is zero, then | ||
| 64 | we just have to switch column (j) and column (j - 1) of J. Since we only | ||
| 65 | switch columns in J, we have to be careful how we update d depending on | ||
| 66 | the sign of gs. Otherwise we have to apply the Givens rotation to these | ||
| 67 | columns. The i - 1 element of d has to be updated to h. */ | ||
| 68 | 14 | cc = d(j - 1); | |
| 69 | 14 | ss = d(j); | |
| 70 | 14 | h = utils::distance(cc, ss); | |
| 71 |
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14 | if (h == 0.0) continue; |
| 72 | 14 | d(j) = 0.0; | |
| 73 | 14 | ss = ss / h; | |
| 74 | 14 | cc = cc / h; | |
| 75 |
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14 | if (cc < 0.0) { |
| 76 | ✗ | cc = -cc; | |
| 77 | ✗ | ss = -ss; | |
| 78 | ✗ | d(j - 1) = -h; | |
| 79 | } else | ||
| 80 | 14 | d(j - 1) = h; | |
| 81 | 14 | xny = ss / (1.0 + cc); | |
| 82 | |||
| 83 | // #define OPTIMIZE_ADD_CONSTRAINT | ||
| 84 | #ifdef OPTIMIZE_ADD_CONSTRAINT // the optimized code is actually slower than | ||
| 85 | // the original | ||
| 86 | T1 = J.col(j - 1); | ||
| 87 | cc_ss(0) = cc; | ||
| 88 | cc_ss(1) = ss; | ||
| 89 | J.col(j - 1).noalias() = J.template middleCols<2>(j - 1) * cc_ss; | ||
| 90 | J.col(j) = xny * (T1 + J.col(j - 1)) - J.col(j); | ||
| 91 | #else | ||
| 92 | // J.col(j-1) = J[:,j-1:j] * [cc; ss] | ||
| 93 |
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42 | for (k = 0; k < nVars; k++) { |
| 94 | 28 | t1 = J(k, j - 1); | |
| 95 | 28 | t2 = J(k, j); | |
| 96 | 28 | J(k, j - 1) = t1 * cc + t2 * ss; | |
| 97 | 28 | J(k, j) = xny * (t1 + J(k, j - 1)) - t2; | |
| 98 | } | ||
| 99 | #endif | ||
| 100 | } | ||
| 101 | /* update the number of constraints added*/ | ||
| 102 | 22 | iq++; | |
| 103 | /* To update R we have to put the iq components of the d vector | ||
| 104 | into column iq - 1 of R | ||
| 105 | */ | ||
| 106 |
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22 | R.col(iq - 1).head(iq) = d.head(iq); |
| 107 | #ifdef EIQGUADPROG_TRACE_SOLVER | ||
| 108 | std::cerr << iq << std::endl; | ||
| 109 | #endif | ||
| 110 | |||
| 111 |
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22 | if (std::abs(d(iq - 1)) <= std::numeric_limits<double>::epsilon() * R_norm) |
| 112 | // problem degenerate | ||
| 113 | 2 | return false; | |
| 114 | 20 | R_norm = std::max<double>(R_norm, std::abs(d(iq - 1))); | |
| 115 | 20 | return true; | |
| 116 | } | ||
| 117 | |||
| 118 | template <int nVars, int nEqCon, int nIneqCon> | ||
| 119 | ✗ | void RtEiquadprog<nVars, nEqCon, nIneqCon>::delete_constraint( | |
| 120 | typename RtMatrixX<nVars, nVars>::d &R, | ||
| 121 | typename RtMatrixX<nVars, nVars>::d &J, | ||
| 122 | typename RtVectorX<nIneqCon + nEqCon>::i &A, | ||
| 123 | typename RtVectorX<nIneqCon + nEqCon>::d &u, int &iq, int l) { | ||
| 124 | // int n = J.rows(); | ||
| 125 | #ifdef EIQGUADPROG_TRACE_SOLVER | ||
| 126 | std::cerr << "Delete constraint " << l << ' ' << iq; | ||
| 127 | #endif | ||
| 128 | int i, j, k; | ||
| 129 | ✗ | int qq = 0; | |
| 130 | double cc, ss, h, xny, t1, t2; | ||
| 131 | |||
| 132 | /* Find the index qq for active constraint l to be removed */ | ||
| 133 | ✗ | for (i = nEqCon; i < iq; i++) | |
| 134 | ✗ | if (A(i) == l) { | |
| 135 | ✗ | qq = i; | |
| 136 | ✗ | break; | |
| 137 | } | ||
| 138 | |||
| 139 | /* remove the constraint from the active set and the duals */ | ||
| 140 | ✗ | for (i = qq; i < iq - 1; i++) { | |
| 141 | ✗ | A(i) = A(i + 1); | |
| 142 | ✗ | u(i) = u(i + 1); | |
| 143 | ✗ | R.col(i) = R.col(i + 1); | |
| 144 | } | ||
| 145 | |||
| 146 | ✗ | A(iq - 1) = A(iq); | |
| 147 | ✗ | u(iq - 1) = u(iq); | |
| 148 | ✗ | A(iq) = 0; | |
| 149 | ✗ | u(iq) = 0.0; | |
| 150 | ✗ | for (j = 0; j < iq; j++) R(j, iq - 1) = 0.0; | |
| 151 | /* constraint has been fully removed */ | ||
| 152 | ✗ | iq--; | |
| 153 | #ifdef EIQGUADPROG_TRACE_SOLVER | ||
| 154 | std::cerr << '/' << iq << std::endl; | ||
| 155 | #endif | ||
| 156 | |||
| 157 | ✗ | if (iq == 0) return; | |
| 158 | |||
| 159 | ✗ | for (j = qq; j < iq; j++) { | |
| 160 | ✗ | cc = R(j, j); | |
| 161 | ✗ | ss = R(j + 1, j); | |
| 162 | ✗ | h = utils::distance(cc, ss); | |
| 163 | ✗ | if (h == 0.0) continue; | |
| 164 | ✗ | cc = cc / h; | |
| 165 | ✗ | ss = ss / h; | |
| 166 | ✗ | R(j + 1, j) = 0.0; | |
| 167 | ✗ | if (cc < 0.0) { | |
| 168 | ✗ | R(j, j) = -h; | |
| 169 | ✗ | cc = -cc; | |
| 170 | ✗ | ss = -ss; | |
| 171 | } else | ||
| 172 | ✗ | R(j, j) = h; | |
| 173 | |||
| 174 | ✗ | xny = ss / (1.0 + cc); | |
| 175 | ✗ | for (k = j + 1; k < iq; k++) { | |
| 176 | ✗ | t1 = R(j, k); | |
| 177 | ✗ | t2 = R(j + 1, k); | |
| 178 | ✗ | R(j, k) = t1 * cc + t2 * ss; | |
| 179 | ✗ | R(j + 1, k) = xny * (t1 + R(j, k)) - t2; | |
| 180 | } | ||
| 181 | ✗ | for (k = 0; k < nVars; k++) { | |
| 182 | ✗ | t1 = J(k, j); | |
| 183 | ✗ | t2 = J(k, j + 1); | |
| 184 | ✗ | J(k, j) = t1 * cc + t2 * ss; | |
| 185 | ✗ | J(k, j + 1) = xny * (J(k, j) + t1) - t2; | |
| 186 | } | ||
| 187 | } | ||
| 188 | } | ||
| 189 | |||
| 190 | template <int nVars, int nEqCon, int nIneqCon> | ||
| 191 | 12 | RtEiquadprog_status RtEiquadprog<nVars, nEqCon, nIneqCon>::solve_quadprog( | |
| 192 | const typename RtMatrixX<nVars, nVars>::d &Hess, | ||
| 193 | const typename RtVectorX<nVars>::d &g0, | ||
| 194 | const typename RtMatrixX<nEqCon, nVars>::d &CE, | ||
| 195 | const typename RtVectorX<nEqCon>::d &ce0, | ||
| 196 | const typename RtMatrixX<nIneqCon, nVars>::d &CI, | ||
| 197 | const typename RtVectorX<nIneqCon>::d &ci0, | ||
| 198 | typename RtVectorX<nVars>::d &x) { | ||
| 199 | int i, k, l; // indices | ||
| 200 | int ip; // index of the chosen violated constraint | ||
| 201 | int iq; // current number of active constraints | ||
| 202 | double psi; // current sum of constraint violations | ||
| 203 | double c1; // Hessian trace | ||
| 204 | double c2; // Hessian Chowlesky factor trace | ||
| 205 | double ss; // largest constraint violation (negative for violation) | ||
| 206 | double R_norm; // norm of matrix R | ||
| 207 | 12 | const double inf = std::numeric_limits<double>::infinity(); | |
| 208 | double t, t1, t2; | ||
| 209 | /* t is the step length, which is the minimum of the partial step length t1 | ||
| 210 | * and the full step length t2 */ | ||
| 211 | |||
| 212 | 12 | iter = 0; // active-set iteration number | |
| 213 | |||
| 214 | /* | ||
| 215 | * Preprocessing phase | ||
| 216 | */ | ||
| 217 | /* compute the trace of the original matrix Hess */ | ||
| 218 | 12 | c1 = Hess.trace(); | |
| 219 | |||
| 220 | /* decompose the matrix Hess in the form LL^T */ | ||
| 221 | 12 | if (!is_inverse_provided_) { | |
| 222 | START_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_CHOWLESKY_DECOMPOSITION); | ||
| 223 | 12 | chol_.compute(Hess); | |
| 224 | STOP_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_CHOWLESKY_DECOMPOSITION); | ||
| 225 | } | ||
| 226 | |||
| 227 | /* initialize the matrix R */ | ||
| 228 | 12 | d.setZero(nVars); | |
| 229 | 12 | R.setZero(nVars, nVars); | |
| 230 | 12 | R_norm = 1.0; | |
| 231 | |||
| 232 | /* compute the inverse of the factorized matrix Hess^-1, this is the initial | ||
| 233 | * value for H */ | ||
| 234 | // m_J = L^-T | ||
| 235 | 12 | if (!is_inverse_provided_) { | |
| 236 | START_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_CHOWLESKY_INVERSE); | ||
| 237 | 12 | m_J.setIdentity(nVars, nVars); | |
| 238 | #ifdef OPTIMIZE_HESSIAN_INVERSE | ||
| 239 | 12 | chol_.matrixU().solveInPlace(m_J); | |
| 240 | #else | ||
| 241 | m_J = chol_.matrixU().solve(m_J); | ||
| 242 | #endif | ||
| 243 | STOP_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_CHOWLESKY_INVERSE); | ||
| 244 | } | ||
| 245 | |||
| 246 | 12 | c2 = m_J.trace(); | |
| 247 | #ifdef EIQGUADPROG_TRACE_SOLVER | ||
| 248 | utils::print_matrix("m_J", m_J); | ||
| 249 | #endif | ||
| 250 | |||
| 251 | /* c1 * c2 is an estimate for cond(Hess) */ | ||
| 252 | |||
| 253 | /* | ||
| 254 | * Find the unconstrained minimizer of the quadratic form 0.5 * x Hess x + g0 | ||
| 255 | * x this is a feasible point in the dual space x = Hess^-1 * g0 | ||
| 256 | */ | ||
| 257 | START_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_STEP_1_UNCONSTR_MINIM); | ||
| 258 | 12 | if (is_inverse_provided_) { | |
| 259 | ✗ | x = m_J * (m_J.transpose() * g0); | |
| 260 | } else { | ||
| 261 | #ifdef OPTIMIZE_UNCONSTR_MINIM | ||
| 262 | 12 | x = -g0; | |
| 263 | 12 | chol_.solveInPlace(x); | |
| 264 | } | ||
| 265 | #else | ||
| 266 | x = chol_.solve(g0); | ||
| 267 | } | ||
| 268 | x = -x; | ||
| 269 | #endif | ||
| 270 | /* and compute the current solution value */ | ||
| 271 | 12 | f_value = 0.5 * g0.dot(x); | |
| 272 | #ifdef EIQGUADPROG_TRACE_SOLVER | ||
| 273 | std::cerr << "Unconstrained solution: " << f_value << std::endl; | ||
| 274 | utils::print_vector("x", x); | ||
| 275 | #endif | ||
| 276 | STOP_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_STEP_1_UNCONSTR_MINIM); | ||
| 277 | |||
| 278 | /* Add equality constraints to the working set A */ | ||
| 279 | |||
| 280 | START_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_ADD_EQ_CONSTR); | ||
| 281 | 12 | iq = 0; | |
| 282 | 17 | for (i = 0; i < nEqCon; i++) { | |
| 283 | START_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_ADD_EQ_CONSTR_1); | ||
| 284 | // np = CE.row(i); // does not compile if nEqCon=0 | ||
| 285 | 18 | for (int tmp = 0; tmp < nVars; tmp++) np[tmp] = CE(i, tmp); | |
| 286 | 6 | compute_d(d, m_J, np); | |
| 287 | 6 | update_z(z, m_J, d, iq); | |
| 288 | 6 | update_r(R, r, d, iq); | |
| 289 | |||
| 290 | #ifdef EIQGUADPROG_TRACE_SOLVER | ||
| 291 | utils::print_matrix("R", R); | ||
| 292 | utils::print_vector("z", z); | ||
| 293 | utils::print_vector("r", r); | ||
| 294 | utils::print_vector("d", d); | ||
| 295 | #endif | ||
| 296 | |||
| 297 | /* compute full step length t2: i.e., the minimum step in primal space s.t. | ||
| 298 | the contraint becomes feasible */ | ||
| 299 | 6 | t2 = 0.0; | |
| 300 | 12 | if (std::abs(z.dot(z)) > | |
| 301 | 6 | std::numeric_limits<double>::epsilon()) // i.e. z != 0 | |
| 302 | 5 | t2 = (-np.dot(x) - ce0(i)) / z.dot(np); | |
| 303 | |||
| 304 | 6 | x += t2 * z; | |
| 305 | |||
| 306 | /* set u = u+ */ | ||
| 307 | 6 | u(iq) = t2; | |
| 308 | 6 | u.head(iq) -= t2 * r.head(iq); | |
| 309 | |||
| 310 | /* compute the new solution value */ | ||
| 311 | 6 | f_value += 0.5 * (t2 * t2) * z.dot(np); | |
| 312 | 6 | A(i) = -i - 1; | |
| 313 | STOP_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_ADD_EQ_CONSTR_1); | ||
| 314 | |||
| 315 | START_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_ADD_EQ_CONSTR_2); | ||
| 316 | 6 | if (!add_constraint(R, m_J, d, iq, R_norm)) { | |
| 317 | // Equality constraints are linearly dependent | ||
| 318 | 1 | return RT_EIQUADPROG_REDUNDANT_EQUALITIES; | |
| 319 | } | ||
| 320 | STOP_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_ADD_EQ_CONSTR_2); | ||
| 321 | } | ||
| 322 | STOP_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_ADD_EQ_CONSTR); | ||
| 323 | |||
| 324 | /* set iai = K \ A */ | ||
| 325 | 22 | for (i = 0; i < nIneqCon; i++) iai(i) = i; | |
| 326 | |||
| 327 | #ifdef USE_WARM_START | ||
| 328 | // DEBUG_STREAM("Gonna warm start using previous active | ||
| 329 | // set:\n"<<A.transpose()<<"\n") | ||
| 330 | for (i = nEqCon; i < q; i++) { | ||
| 331 | iai(i - nEqCon) = -1; | ||
| 332 | ip = A(i); | ||
| 333 | np = CI.row(ip); | ||
| 334 | compute_d(d, m_J, np); | ||
| 335 | update_z(z, m_J, d, iq); | ||
| 336 | update_r(R, r, d, iq); | ||
| 337 | |||
| 338 | /* compute full step length t2: i.e., the minimum step in primal space s.t. | ||
| 339 | the contraint becomes feasible */ | ||
| 340 | t2 = 0.0; | ||
| 341 | if (std::abs(z.dot(z)) > | ||
| 342 | std::numeric_limits<double>::epsilon()) // i.e. z != 0 | ||
| 343 | t2 = (-np.dot(x) - ci0(ip)) / z.dot(np); | ||
| 344 | else | ||
| 345 | DEBUG_STREAM("[WARM START] z=0\n") | ||
| 346 | |||
| 347 | x += t2 * z; | ||
| 348 | |||
| 349 | /* set u = u+ */ | ||
| 350 | u(iq) = t2; | ||
| 351 | u.head(iq) -= t2 * r.head(iq); | ||
| 352 | |||
| 353 | /* compute the new solution value */ | ||
| 354 | f_value += 0.5 * (t2 * t2) * z.dot(np); | ||
| 355 | |||
| 356 | if (!add_constraint(R, m_J, d, iq, R_norm)) { | ||
| 357 | // constraints are linearly dependent | ||
| 358 | std::cerr << "[WARM START] Constraints are linearly dependent\n"; | ||
| 359 | return RT_EIQUADPROG_REDUNDANT_EQUALITIES; | ||
| 360 | } | ||
| 361 | } | ||
| 362 | #else | ||
| 363 | |||
| 364 | #endif | ||
| 365 | |||
| 366 | 11 | l1: | |
| 367 | START_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_STEP_1); | ||
| 368 | 16 | iter++; | |
| 369 | 16 | if (iter >= m_maxIter) { | |
| 370 | ✗ | q = iq; | |
| 371 | ✗ | return RT_EIQUADPROG_MAX_ITER_REACHED; | |
| 372 | } | ||
| 373 | |||
| 374 | #ifdef EIQGUADPROG_TRACE_SOLVER | ||
| 375 | utils::print_vector("x", x); | ||
| 376 | #endif | ||
| 377 | /* step 1: choose a violated constraint */ | ||
| 378 | 22 | for (i = nEqCon; i < iq; i++) { | |
| 379 | 6 | ip = A(i); | |
| 380 | 6 | iai(ip) = -1; | |
| 381 | } | ||
| 382 | |||
| 383 | /* compute s(x) = ci^T * x + ci0 for all elements of K \ A */ | ||
| 384 | START_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_STEP_1_2); | ||
| 385 | 16 | ss = 0.0; | |
| 386 | 16 | ip = 0; /* ip will be the index of the chosen violated constraint */ | |
| 387 | |||
| 388 | #ifdef OPTIMIZE_STEP_1_2 | ||
| 389 | 16 | s = ci0; | |
| 390 | 16 | s.noalias() += CI * x; | |
| 391 | 16 | iaexcl.setOnes(); | |
| 392 | 16 | psi = (s.cwiseMin(RtVectorX<nIneqCon>::d::Zero())).sum(); | |
| 393 | #else | ||
| 394 | psi = 0.0; /* this value will contain the sum of all infeasibilities */ | ||
| 395 | for (i = 0; i < nIneqCon; i++) { | ||
| 396 | iaexcl(i) = 1; | ||
| 397 | s(i) = CI.row(i).dot(x) + ci0(i); | ||
| 398 | psi += std::min(0.0, s(i)); | ||
| 399 | } | ||
| 400 | #endif | ||
| 401 | STOP_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_STEP_1_2); | ||
| 402 | #ifdef EIQGUADPROG_TRACE_SOLVER | ||
| 403 | utils::print_vector("s", s); | ||
| 404 | #endif | ||
| 405 | |||
| 406 | STOP_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_STEP_1); | ||
| 407 | |||
| 408 | 16 | if (std::abs(psi) <= | |
| 409 | 16 | nIneqCon * std::numeric_limits<double>::epsilon() * c1 * c2 * 100.0) { | |
| 410 | /* numerically there are not infeasibilities anymore */ | ||
| 411 | 9 | q = iq; | |
| 412 | // DEBUG_STREAM("Optimal active | ||
| 413 | // set:\n"<<A.head(iq).transpose()<<"\n\n") | ||
| 414 | 9 | return RT_EIQUADPROG_OPTIMAL; | |
| 415 | } | ||
| 416 | |||
| 417 | /* save old values for u, x and A */ | ||
| 418 | 7 | u_old.head(iq) = u.head(iq); | |
| 419 | 7 | A_old.head(iq) = A.head(iq); | |
| 420 | 7 | x_old = x; | |
| 421 | |||
| 422 | 7 | l2: /* Step 2: check for feasibility and determine a new S-pair */ | |
| 423 | START_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_STEP_2); | ||
| 424 | // find constraint with highest violation (what about normalizing | ||
| 425 | // constraints?) | ||
| 426 | 20 | for (i = 0; i < nIneqCon; i++) { | |
| 427 | 13 | if (s(i) < ss && iai(i) != -1 && iaexcl(i)) { | |
| 428 | 7 | ss = s(i); | |
| 429 | 7 | ip = i; | |
| 430 | } | ||
| 431 | } | ||
| 432 | 7 | if (ss >= 0.0) { | |
| 433 | ✗ | q = iq; | |
| 434 | // DEBUG_STREAM("Optimal active set:\n"<<A.transpose()<<"\n\n") | ||
| 435 | ✗ | return RT_EIQUADPROG_OPTIMAL; | |
| 436 | } | ||
| 437 | |||
| 438 | /* set np = n(ip) */ | ||
| 439 | // np = CI.row(ip); // does not compile if nIneqCon=0 | ||
| 440 | 21 | for (int tmp = 0; tmp < nVars; tmp++) np[tmp] = CI(ip, tmp); | |
| 441 | /* set u = (u 0)^T */ | ||
| 442 | 7 | u(iq) = 0.0; | |
| 443 | /* add ip to the active set A */ | ||
| 444 | 7 | A(iq) = ip; | |
| 445 | |||
| 446 | // DEBUG_STREAM("Add constraint "<<ip<<" to active set\n") | ||
| 447 | |||
| 448 | #ifdef EIQGUADPROG_TRACE_SOLVER | ||
| 449 | std::cerr << "Trying with constraint " << ip << std::endl; | ||
| 450 | utils::print_vector("np", np); | ||
| 451 | #endif | ||
| 452 | STOP_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_STEP_2); | ||
| 453 | |||
| 454 | 7 | l2a: /* Step 2a: determine step direction */ | |
| 455 | START_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_STEP_2A); | ||
| 456 | /* compute z = H np: the step direction in the primal space (through m_J, see | ||
| 457 | * the paper) */ | ||
| 458 | 7 | compute_d(d, m_J, np); | |
| 459 | // update_z(z, m_J, d, iq); | ||
| 460 | 7 | if (iq >= nVars) { | |
| 461 | // throw std::runtime_error("iq >= m_J.cols()"); | ||
| 462 | 1 | z.setZero(); | |
| 463 | } else { | ||
| 464 | 6 | update_z(z, m_J, d, iq); | |
| 465 | } | ||
| 466 | /* compute N* np (if q > 0): the negative of the step direction in the dual | ||
| 467 | * space */ | ||
| 468 | 7 | update_r(R, r, d, iq); | |
| 469 | #ifdef EIQGUADPROG_TRACE_SOLVER | ||
| 470 | std::cerr << "Step direction z" << std::endl; | ||
| 471 | utils::print_vector("z", z); | ||
| 472 | utils::print_vector("r", r); | ||
| 473 | utils::print_vector("u", u); | ||
| 474 | utils::print_vector("d", d); | ||
| 475 | utils::print_vector("A", A); | ||
| 476 | #endif | ||
| 477 | STOP_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_STEP_2A); | ||
| 478 | |||
| 479 | /* Step 2b: compute step length */ | ||
| 480 | START_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_STEP_2B); | ||
| 481 | 7 | l = 0; | |
| 482 | /* Compute t1: partial step length (maximum step in dual space without | ||
| 483 | * violating dual feasibility */ | ||
| 484 | 7 | t1 = inf; /* +inf */ | |
| 485 | /* find the index l s.t. it reaches the minimum of u+(x) / r */ | ||
| 486 | // l: index of constraint to drop (maybe) | ||
| 487 | 10 | for (k = nEqCon; k < iq; k++) { | |
| 488 | double tmp; | ||
| 489 | 3 | if (r(k) > 0.0 && ((tmp = u(k) / r(k)) < t1)) { | |
| 490 | ✗ | t1 = tmp; | |
| 491 | ✗ | l = A(k); | |
| 492 | } | ||
| 493 | } | ||
| 494 | /* Compute t2: full step length (minimum step in primal space such that the | ||
| 495 | * constraint ip becomes feasible */ | ||
| 496 | 14 | if (std::abs(z.dot(z)) > | |
| 497 | 7 | std::numeric_limits<double>::epsilon()) // i.e. z != 0 | |
| 498 | 5 | t2 = -s(ip) / z.dot(np); | |
| 499 | else | ||
| 500 | 2 | t2 = inf; /* +inf */ | |
| 501 | |||
| 502 | /* the step is chosen as the minimum of t1 and t2 */ | ||
| 503 | 7 | t = std::min(t1, t2); | |
| 504 | #ifdef EIQGUADPROG_TRACE_SOLVER | ||
| 505 | std::cerr << "Step sizes: " << t << " (t1 = " << t1 << ", t2 = " << t2 | ||
| 506 | << ") "; | ||
| 507 | #endif | ||
| 508 | STOP_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_STEP_2B); | ||
| 509 | |||
| 510 | /* Step 2c: determine new S-pair and take step: */ | ||
| 511 | START_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_STEP_2C); | ||
| 512 | /* case (i): no step in primal or dual space */ | ||
| 513 | 7 | if (t >= inf) { | |
| 514 | /* QPP is infeasible */ | ||
| 515 | 2 | q = iq; | |
| 516 | STOP_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_STEP_2C); | ||
| 517 | 2 | return RT_EIQUADPROG_UNBOUNDED; | |
| 518 | } | ||
| 519 | /* case (ii): step in dual space */ | ||
| 520 | 5 | if (t2 >= inf) { | |
| 521 | /* set u = u + t * [-r 1) and drop constraint l from the active set A */ | ||
| 522 | ✗ | u.head(iq) -= t * r.head(iq); | |
| 523 | ✗ | u(iq) += t; | |
| 524 | ✗ | iai(l) = l; | |
| 525 | ✗ | delete_constraint(R, m_J, A, u, iq, l); | |
| 526 | #ifdef EIQGUADPROG_TRACE_SOLVER | ||
| 527 | std::cerr << " in dual space: " << f_value << std::endl; | ||
| 528 | utils::print_vector("x", x); | ||
| 529 | utils::print_vector("z", z); | ||
| 530 | utils::print_vector("A", A); | ||
| 531 | #endif | ||
| 532 | STOP_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_STEP_2C); | ||
| 533 | ✗ | goto l2a; | |
| 534 | } | ||
| 535 | |||
| 536 | /* case (iii): step in primal and dual space */ | ||
| 537 | 5 | x += t * z; | |
| 538 | /* update the solution value */ | ||
| 539 | 5 | f_value += t * z.dot(np) * (0.5 * t + u(iq)); | |
| 540 | |||
| 541 | 5 | u.head(iq) -= t * r.head(iq); | |
| 542 | 5 | u(iq) += t; | |
| 543 | |||
| 544 | #ifdef EIQGUADPROG_TRACE_SOLVER | ||
| 545 | std::cerr << " in both spaces: " << f_value << std::endl; | ||
| 546 | utils::print_vector("x", x); | ||
| 547 | utils::print_vector("u", u); | ||
| 548 | utils::print_vector("r", r); | ||
| 549 | utils::print_vector("A", A); | ||
| 550 | #endif | ||
| 551 | |||
| 552 | 5 | if (t == t2) { | |
| 553 | #ifdef EIQGUADPROG_TRACE_SOLVER | ||
| 554 | std::cerr << "Full step has taken " << t << std::endl; | ||
| 555 | utils::print_vector("x", x); | ||
| 556 | #endif | ||
| 557 | /* full step has taken */ | ||
| 558 | /* add constraint ip to the active set*/ | ||
| 559 | 5 | if (!add_constraint(R, m_J, d, iq, R_norm)) { | |
| 560 | ✗ | iaexcl(ip) = 0; | |
| 561 | ✗ | delete_constraint(R, m_J, A, u, iq, ip); | |
| 562 | #ifdef EIQGUADPROG_TRACE_SOLVER | ||
| 563 | utils::print_matrix("R", R); | ||
| 564 | utils::print_vector("A", A); | ||
| 565 | #endif | ||
| 566 | ✗ | for (i = 0; i < nIneqCon; i++) iai(i) = i; | |
| 567 | ✗ | for (i = 0; i < iq; i++) { | |
| 568 | ✗ | A(i) = A_old(i); | |
| 569 | ✗ | iai(A(i)) = -1; | |
| 570 | ✗ | u(i) = u_old(i); | |
| 571 | } | ||
| 572 | ✗ | x = x_old; | |
| 573 | STOP_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_STEP_2C); | ||
| 574 | ✗ | goto l2; /* go to step 2 */ | |
| 575 | } else | ||
| 576 | 5 | iai(ip) = -1; | |
| 577 | #ifdef EIQGUADPROG_TRACE_SOLVER | ||
| 578 | utils::print_matrix("R", R); | ||
| 579 | utils::print_vector("A", A); | ||
| 580 | #endif | ||
| 581 | STOP_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_STEP_2C); | ||
| 582 | 5 | goto l1; | |
| 583 | } | ||
| 584 | |||
| 585 | /* a partial step has been taken => drop constraint l */ | ||
| 586 | ✗ | iai(l) = l; | |
| 587 | ✗ | delete_constraint(R, m_J, A, u, iq, l); | |
| 588 | // s(ip) = CI.row(ip).dot(x) + ci0(ip); // does not compile if nIneqCon=0 | ||
| 589 | ✗ | s(ip) = ci0(ip); | |
| 590 | ✗ | for (int tmp = 0; tmp < nVars; tmp++) s(ip) += CI(ip, tmp) * x[tmp]; | |
| 591 | |||
| 592 | #ifdef EIQGUADPROG_TRACE_SOLVER | ||
| 593 | std::cerr << "Partial step has taken " << t << std::endl; | ||
| 594 | utils::print_vector("x", x); | ||
| 595 | utils::print_matrix("R", R); | ||
| 596 | utils::print_vector("A", A); | ||
| 597 | utils::print_vector("s", s); | ||
| 598 | #endif | ||
| 599 | STOP_PROFILER_EIQUADPROG_RT(PROFILE_EIQUADPROG_STEP_2C); | ||
| 600 | |||
| 601 | ✗ | goto l2a; | |
| 602 | } | ||
| 603 | } /* namespace solvers */ | ||
| 604 | } /* namespace eiquadprog */ | ||
| 605 | #endif /* __eiquadprog_rt_hxx__ */ | ||
| 606 |