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File: | include/eiquadprog/eiquadprog-rt.hpp |
Date: | 2024-08-26 22:54:11 |
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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_hpp__ | ||
20 | #define __eiquadprog_rt_hpp__ | ||
21 | |||
22 | #include <Eigen/Dense> | ||
23 | |||
24 | #include "eiquadprog/eiquadprog-utils.hxx" | ||
25 | |||
26 | #define OPTIMIZE_STEP_1_2 // compute s(x) = ci^T * x + ci0 | ||
27 | #define OPTIMIZE_COMPUTE_D // use noalias | ||
28 | #define OPTIMIZE_UPDATE_Z // use noalias | ||
29 | #define OPTIMIZE_HESSIAN_INVERSE // use solveInPlace | ||
30 | #define OPTIMIZE_UNCONSTR_MINIM | ||
31 | |||
32 | // #define USE_WARM_START | ||
33 | // #define PROFILE_EIQUADPROG | ||
34 | // #define DEBUG_STREAM(msg) std::cout<<msg; | ||
35 | #define DEBUG_STREAM(msg) | ||
36 | |||
37 | #ifdef PROFILE_EIQUADPROG | ||
38 | #define START_PROFILER_EIQUADPROG_RT(x) START_PROFILER(x) | ||
39 | #define STOP_PROFILER_EIQUADPROG_RT(x) STOP_PROFILER(x) | ||
40 | #else | ||
41 | #define START_PROFILER_EIQUADPROG_RT(x) | ||
42 | #define STOP_PROFILER_EIQUADPROG_RT(x) | ||
43 | #endif | ||
44 | |||
45 | #define PROFILE_EIQUADPROG_CHOWLESKY_DECOMPOSITION "EIQUADPROG_RT Chowlesky dec" | ||
46 | #define PROFILE_EIQUADPROG_CHOWLESKY_INVERSE "EIQUADPROG_RT Chowlesky inv" | ||
47 | #define PROFILE_EIQUADPROG_ADD_EQ_CONSTR "EIQUADPROG_RT ADD_EQ_CONSTR" | ||
48 | #define PROFILE_EIQUADPROG_ADD_EQ_CONSTR_1 "EIQUADPROG_RT ADD_EQ_CONSTR_1" | ||
49 | #define PROFILE_EIQUADPROG_ADD_EQ_CONSTR_2 "EIQUADPROG_RT ADD_EQ_CONSTR_2" | ||
50 | #define PROFILE_EIQUADPROG_STEP_1 "EIQUADPROG_RT STEP_1" | ||
51 | #define PROFILE_EIQUADPROG_STEP_1_1 "EIQUADPROG_RT STEP_1_1" | ||
52 | #define PROFILE_EIQUADPROG_STEP_1_2 "EIQUADPROG_RT STEP_1_2" | ||
53 | #define PROFILE_EIQUADPROG_STEP_1_UNCONSTR_MINIM \ | ||
54 | "EIQUADPROG_RT STEP_1_UNCONSTR_MINIM" | ||
55 | #define PROFILE_EIQUADPROG_STEP_2 "EIQUADPROG_RT STEP_2" | ||
56 | #define PROFILE_EIQUADPROG_STEP_2A "EIQUADPROG_RT STEP_2A" | ||
57 | #define PROFILE_EIQUADPROG_STEP_2B "EIQUADPROG_RT STEP_2B" | ||
58 | #define PROFILE_EIQUADPROG_STEP_2C "EIQUADPROG_RT STEP_2C" | ||
59 | |||
60 | #define DEFAULT_MAX_ITER 1000 | ||
61 | |||
62 | template <int Rows, int Cols> | ||
63 | struct RtMatrixX { | ||
64 | typedef Eigen::Matrix<double, Rows, Cols> d; | ||
65 | }; | ||
66 | |||
67 | template <int Rows> | ||
68 | struct RtVectorX { | ||
69 | typedef Eigen::Matrix<double, Rows, 1> d; | ||
70 | typedef Eigen::Matrix<int, Rows, 1> i; | ||
71 | }; | ||
72 | |||
73 | namespace eiquadprog { | ||
74 | |||
75 | namespace solvers { | ||
76 | |||
77 | /** | ||
78 | * Possible states of the solver. | ||
79 | */ | ||
80 | enum RtEiquadprog_status { | ||
81 | RT_EIQUADPROG_OPTIMAL = 0, | ||
82 | RT_EIQUADPROG_INFEASIBLE = 1, | ||
83 | RT_EIQUADPROG_UNBOUNDED = 2, | ||
84 | RT_EIQUADPROG_MAX_ITER_REACHED = 3, | ||
85 | RT_EIQUADPROG_REDUNDANT_EQUALITIES = 4 | ||
86 | }; | ||
87 | |||
88 | template <int nVars, int nEqCon, int nIneqCon> | ||
89 | class RtEiquadprog { | ||
90 | public: | ||
91 | EIGEN_MAKE_ALIGNED_OPERATOR_NEW | ||
92 | |||
93 | RtEiquadprog(); | ||
94 | virtual ~RtEiquadprog(); | ||
95 | |||
96 | int getMaxIter() const { return m_maxIter; } | ||
97 | |||
98 | bool setMaxIter(int maxIter) { | ||
99 | if (maxIter < 0) return false; | ||
100 | m_maxIter = maxIter; | ||
101 | return true; | ||
102 | } | ||
103 | |||
104 | /** | ||
105 | * @return The size of the active set, namely the number of | ||
106 | * active constraints (including the equalities). | ||
107 | */ | ||
108 | int getActiveSetSize() const { return q; } | ||
109 | |||
110 | /** | ||
111 | * @return The number of active-set iteratios. | ||
112 | */ | ||
113 | int getIteratios() const { return iter; } | ||
114 | |||
115 | /** | ||
116 | * @return The value of the objective function. | ||
117 | */ | ||
118 | 16 | double getObjValue() const { return f_value; } | |
119 | |||
120 | /** | ||
121 | * @return The Lagrange multipliers | ||
122 | */ | ||
123 | const typename RtVectorX<nIneqCon + nEqCon>::d& getLagrangeMultipliers() | ||
124 | const { | ||
125 | return u; | ||
126 | } | ||
127 | |||
128 | /** | ||
129 | * Return the active set, namely the indeces of active constraints. | ||
130 | * The first nEqCon indexes are for the equalities and are negative. | ||
131 | * The last nIneqCon indexes are for the inequalities and start from 0. | ||
132 | * Only the first q elements of the return vector are valid, where q | ||
133 | * is the size of the active set. | ||
134 | * @return The set of indexes of the active constraints. | ||
135 | */ | ||
136 | const typename RtVectorX<nIneqCon + nEqCon>::i& getActiveSet() const { | ||
137 | return A; | ||
138 | } | ||
139 | |||
140 | /** | ||
141 | * solves the problem | ||
142 | * min. x' Hess x + 2 g0' x | ||
143 | * s.t. CE x + ce0 = 0 | ||
144 | * CI x + ci0 >= 0 | ||
145 | */ | ||
146 | RtEiquadprog_status solve_quadprog( | ||
147 | const typename RtMatrixX<nVars, nVars>::d& Hess, | ||
148 | const typename RtVectorX<nVars>::d& g0, | ||
149 | const typename RtMatrixX<nEqCon, nVars>::d& CE, | ||
150 | const typename RtVectorX<nEqCon>::d& ce0, | ||
151 | const typename RtMatrixX<nIneqCon, nVars>::d& CI, | ||
152 | const typename RtVectorX<nIneqCon>::d& ci0, | ||
153 | typename RtVectorX<nVars>::d& x); | ||
154 | |||
155 | typename RtMatrixX<nVars, nVars>::d m_J; // J * J' = Hessian | ||
156 | bool is_inverse_provided_; | ||
157 | |||
158 | private: | ||
159 | int m_maxIter; /// max number of active-set iterations | ||
160 | double f_value; /// current value of cost function | ||
161 | |||
162 | Eigen::LLT<typename RtMatrixX<nVars, nVars>::d, Eigen::Lower> chol_; | ||
163 | double solver_return_; | ||
164 | |||
165 | /// from QR of L' N, where L is Cholewsky factor of Hessian, and N is the | ||
166 | /// matrix of active constraints | ||
167 | typename RtMatrixX<nVars, nVars>::d R; | ||
168 | |||
169 | /// CI*x+ci0 | ||
170 | typename RtVectorX<nIneqCon>::d s; | ||
171 | |||
172 | /// infeasibility multipliers, i.e. negative step direction in dual space | ||
173 | typename RtVectorX<nIneqCon + nEqCon>::d r; | ||
174 | |||
175 | /// Lagrange multipliers | ||
176 | typename RtVectorX<nIneqCon + nEqCon>::d u; | ||
177 | |||
178 | /// step direction in primal space | ||
179 | typename RtVectorX<nVars>::d z; | ||
180 | |||
181 | /// J' np | ||
182 | typename RtVectorX<nVars>::d d; | ||
183 | |||
184 | /// current constraint normal | ||
185 | typename RtVectorX<nVars>::d np; | ||
186 | |||
187 | /// active set (indeces of active constraints) | ||
188 | /// the first nEqCon indeces are for the equalities and are negative | ||
189 | /// the last nIneqCon indeces are for the inequalities are start from 0 | ||
190 | typename RtVectorX<nIneqCon + nEqCon>::i A; | ||
191 | |||
192 | /// initialized as K \ A | ||
193 | /// iai(i)=-1 iff inequality constraint i is in the active set | ||
194 | /// iai(i)=i otherwise | ||
195 | typename RtVectorX<nIneqCon>::i iai; | ||
196 | |||
197 | /// initialized as [1, ..., 1, .] | ||
198 | /// if iaexcl(i)!=1 inequality constraint i cannot be added to the active set | ||
199 | /// if adding ineq constraint i fails => iaexcl(i)=0 | ||
200 | /// iaexcl(i)=0 iff ineq constraint i is linearly dependent to other active | ||
201 | /// constraints iaexcl(i)=1 otherwise | ||
202 | typename RtVectorX<nIneqCon>::i iaexcl; | ||
203 | |||
204 | typename RtVectorX<nVars>::d x_old; // old value of x | ||
205 | typename RtVectorX<nIneqCon + nEqCon>::d u_old; // old value of u | ||
206 | typename RtVectorX<nIneqCon + nEqCon>::i A_old; // old value of A | ||
207 | |||
208 | #ifdef OPTIMIZE_ADD_CONSTRAINT | ||
209 | typename RtVectorX<nVars>::d T1; // tmp vector | ||
210 | #endif | ||
211 | |||
212 | /// size of the active set A (containing the indices of the active | ||
213 | /// constraints) | ||
214 | int q; | ||
215 | |||
216 | /// number of active-set iterations | ||
217 | int iter; | ||
218 | |||
219 | template <typename Scalar> | ||
220 | inline Scalar distance(Scalar a, Scalar b) { | ||
221 | Scalar a1, b1, t; | ||
222 | a1 = std::abs(a); | ||
223 | b1 = std::abs(b); | ||
224 | if (a1 > b1) { | ||
225 | t = (b1 / a1); | ||
226 | return a1 * std::sqrt(1.0 + t * t); | ||
227 | } else if (b1 > a1) { | ||
228 | t = (a1 / b1); | ||
229 | return b1 * std::sqrt(1.0 + t * t); | ||
230 | } | ||
231 | return a1 * std::sqrt(2.0); | ||
232 | } | ||
233 | |||
234 | 26 | inline void compute_d(typename RtVectorX<nVars>::d& d, | |
235 | const typename RtMatrixX<nVars, nVars>::d& J, | ||
236 | const typename RtVectorX<nVars>::d& np) { | ||
237 | #ifdef OPTIMIZE_COMPUTE_D | ||
238 |
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26 | d.noalias() = J.adjoint() * np; |
239 | #else | ||
240 | d = J.adjoint() * np; | ||
241 | #endif | ||
242 | } | ||
243 | |||
244 | 24 | inline void update_z(typename RtVectorX<nVars>::d& z, | |
245 | const typename RtMatrixX<nVars, nVars>::d& J, | ||
246 | const typename RtVectorX<nVars>::d& d, int iq) { | ||
247 | #ifdef OPTIMIZE_UPDATE_Z | ||
248 |
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24 | z.noalias() = J.rightCols(nVars - iq) * d.tail(nVars - iq); |
249 | #else | ||
250 | z = J.rightCols(J.cols() - iq) * d.tail(J.cols() - iq); | ||
251 | #endif | ||
252 | } | ||
253 | |||
254 | 26 | inline void update_r(const typename RtMatrixX<nVars, nVars>::d& R, | |
255 | typename RtVectorX<nIneqCon + nEqCon>::d& r, | ||
256 | const typename RtVectorX<nVars>::d& d, int iq) { | ||
257 |
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26 | r.head(iq) = d.head(iq); |
258 | 26 | R.topLeftCorner(iq, iq) | |
259 |
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26 | .template triangularView<Eigen::Upper>() |
260 |
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26 | .solveInPlace(r.head(iq)); |
261 | } | ||
262 | |||
263 | bool add_constraint(typename RtMatrixX<nVars, nVars>::d& R, | ||
264 | typename RtMatrixX<nVars, nVars>::d& J, | ||
265 | typename RtVectorX<nVars>::d& d, int& iq, double& R_norm); | ||
266 | |||
267 | void delete_constraint(typename RtMatrixX<nVars, nVars>::d& R, | ||
268 | typename RtMatrixX<nVars, nVars>::d& J, | ||
269 | typename RtVectorX<nIneqCon + nEqCon>::i& A, | ||
270 | typename RtVectorX<nIneqCon + nEqCon>::d& u, int& iq, | ||
271 | int l); | ||
272 | }; | ||
273 | |||
274 | } /* namespace solvers */ | ||
275 | } /* namespace eiquadprog */ | ||
276 | |||
277 | #include "eiquadprog/eiquadprog-rt.hxx" | ||
278 | /* --- Details | ||
279 | * -------------------------------------------------------------------- */ | ||
280 | |||
281 | #endif /* __eiquadprog_rt_hpp__ */ | ||
282 |