Directory: | ./ |
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File: | bindings/python/algorithm/admm-solver.cpp |
Date: | 2025-02-12 21:03:38 |
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Lines: | 97 | 116 | 83.6% |
Branches: | 160 | 336 | 47.6% |
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1 | // | ||
2 | // Copyright (c) 2024 INRIA | ||
3 | // | ||
4 | |||
5 | #include <eigenpy/memory.hpp> | ||
6 | #include <eigenpy/eigen-from-python.hpp> | ||
7 | #include <eigenpy/eigen-to-python.hpp> | ||
8 | |||
9 | #include "pinocchio/bindings/python/fwd.hpp" | ||
10 | |||
11 | #include "pinocchio/algorithm/admm-solver.hpp" | ||
12 | #include "pinocchio/algorithm/contact-cholesky.hpp" | ||
13 | #include "pinocchio/algorithm/delassus-operator-dense.hpp" | ||
14 | #include "pinocchio/algorithm/delassus-operator-sparse.hpp" | ||
15 | |||
16 | #include "pinocchio/bindings/python/algorithm/contact-solver-base.hpp" | ||
17 | #include "pinocchio/bindings/python/utils/std-vector.hpp" | ||
18 | #include "pinocchio/bindings/python/utils/macros.hpp" | ||
19 | |||
20 | namespace pinocchio | ||
21 | { | ||
22 | namespace python | ||
23 | { | ||
24 | namespace bp = boost::python; | ||
25 | |||
26 | typedef ADMMContactSolverTpl<context::Scalar> Solver; | ||
27 | typedef Solver::PowerIterationAlgo PowerIterationAlgo; | ||
28 | typedef Solver::SolverStats SolverStats; | ||
29 | typedef context::Scalar Scalar; | ||
30 | typedef context::VectorXs VectorXs; | ||
31 | typedef const Eigen::Ref<const VectorXs> ConstRefVectorXs; | ||
32 | typedef ContactCholeskyDecompositionTpl<context::Scalar, context::Options> | ||
33 | ContactCholeskyDecomposition; | ||
34 | |||
35 | #ifdef PINOCCHIO_PYTHON_PLAIN_SCALAR_TYPE | ||
36 | |||
37 | template<typename DelassusDerived> | ||
38 | ✗ | static bool solve_wrapper( | |
39 | Solver & solver, | ||
40 | DelassusDerived & delassus, | ||
41 | const context::VectorXs & g, | ||
42 | const context::CoulombFrictionConeVector & cones, | ||
43 | const context::VectorXs & R, | ||
44 | const boost::optional<ConstRefVectorXs> primal_solution = boost::none, | ||
45 | const boost::optional<ConstRefVectorXs> dual_solution = boost::none, | ||
46 | bool compute_largest_eigen_values = true, | ||
47 | bool stat_record = false) | ||
48 | { | ||
49 | ✗ | return solver.solve( | |
50 | delassus, g, cones, R, primal_solution, dual_solution, compute_largest_eigen_values, | ||
51 | ✗ | stat_record); | |
52 | } | ||
53 | |||
54 | template<typename DelassusDerived> | ||
55 | static bool solve_wrapper2( | ||
56 | Solver & solver, | ||
57 | DelassusDerived & delassus, | ||
58 | const context::VectorXs & g, | ||
59 | const context::CoulombFrictionConeVector & cones, | ||
60 | Eigen::Ref<context::VectorXs> x) | ||
61 | { | ||
62 | return solver.solve(delassus, g, cones, x); | ||
63 | } | ||
64 | #endif | ||
65 | |||
66 | #ifndef PINOCCHIO_PYTHON_SKIP_CASADI_UNSUPPORTED | ||
67 | |||
68 | ✗ | static context::VectorXs computeConeProjection_wrapper( | |
69 | const context::CoulombFrictionConeVector & cones, const context::VectorXs & forces) | ||
70 | { | ||
71 | ✗ | context::VectorXs res(forces.size()); | |
72 | ✗ | ::pinocchio::internal::computeConeProjection(cones, forces, res); | |
73 | ✗ | return res; | |
74 | } | ||
75 | |||
76 | ✗ | static context::VectorXs computeDualConeProjection_wrapper( | |
77 | const context::CoulombFrictionConeVector & cones, const context::VectorXs & velocities) | ||
78 | { | ||
79 | ✗ | context::VectorXs res(velocities.size()); | |
80 | ✗ | ::pinocchio::internal::computeDualConeProjection(cones, velocities, res); | |
81 | ✗ | return res; | |
82 | } | ||
83 | |||
84 | ✗ | static context::Scalar computePrimalFeasibility_wrapper( | |
85 | const context::CoulombFrictionConeVector & cones, const context::VectorXs & forces) | ||
86 | { | ||
87 | ✗ | return ::pinocchio::internal::computePrimalFeasibility(cones, forces); | |
88 | } | ||
89 | |||
90 | ✗ | static context::Scalar computeReprojectionError_wrapper( | |
91 | const context::CoulombFrictionConeVector & cones, | ||
92 | const context::VectorXs & forces, | ||
93 | const context::VectorXs & velocities) | ||
94 | { | ||
95 | ✗ | return ::pinocchio::internal::computeReprojectionError(cones, forces, velocities); | |
96 | } | ||
97 | |||
98 | ✗ | static context::VectorXs computeComplementarityShift_wrapper( | |
99 | const context::CoulombFrictionConeVector & cones, const context::VectorXs & velocities) | ||
100 | { | ||
101 | ✗ | context::VectorXs res(velocities.size()); | |
102 | ✗ | ::pinocchio::internal::computeComplementarityShift(cones, velocities, res); | |
103 | ✗ | return res; | |
104 | } | ||
105 | #endif // PINOCCHIO_PYTHON_SKIP_CASADI_UNSUPPORTED | ||
106 | |||
107 | 69 | void exposeADMMContactSolver() | |
108 | { | ||
109 | #ifdef PINOCCHIO_PYTHON_PLAIN_SCALAR_TYPE | ||
110 | bp::class_<Solver> cl( | ||
111 | "ADMMContactSolver", | ||
112 | "Alternating Direction Method of Multi-pliers solver for contact dynamics.", | ||
113 |
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130 | bp::init<int, Scalar, Scalar, Scalar, Scalar, Scalar, int>( |
114 |
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195 | (bp::arg("self"), bp::arg("problem_dim"), bp::arg("mu_prox") = Scalar(1e-6), |
115 |
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260 | bp::arg("tau") = Scalar(0.5), bp::arg("rho_power") = Scalar(0.2), |
116 |
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260 | bp::arg("rho_power_factor") = Scalar(0.05), bp::arg("ratio_primal_dual") = Scalar(10), |
117 |
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130 | bp::arg("max_it_largest_eigen_value_solver") = 20), |
118 |
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65 | "Default constructor.")); |
119 |
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65 | cl.def(ContactSolverBasePythonVisitor<Solver>()) |
120 | |||
121 |
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65 | .def( |
122 | "solve", solve_wrapper<ContactCholeskyDecomposition::DelassusCholeskyExpression>, | ||
123 |
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65 | (bp::args("self", "delassus", "g", "cones", "R"), |
124 |
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130 | bp::arg("primal_solution") = boost::none, bp::arg("dual_solution") = boost::none, |
125 |
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130 | bp::arg("compute_largest_eigen_values") = true, bp::arg("stat_record") = false), |
126 | "Solve the constrained conic problem, starting from the optional initial guess.") | ||
127 |
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65 | .def( |
128 | "solve", solve_wrapper<context::DelassusOperatorDense>, | ||
129 |
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130 | (bp::args("self", "delassus", "g", "cones", "R"), |
130 |
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130 | bp::arg("primal_solution") = boost::none, bp::arg("dual_solution") = boost::none, |
131 |
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130 | bp::arg("compute_largest_eigen_values") = true, bp::arg("stat_record") = false), |
132 | "Solve the constrained conic problem, starting from the optional initial guess.") | ||
133 |
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65 | .def( |
134 | "solve", solve_wrapper<context::DelassusOperatorSparse>, | ||
135 |
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130 | (bp::args("self", "delassus", "g", "cones", "R"), |
136 |
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130 | bp::arg("primal_solution") = boost::none, bp::arg("dual_solution") = boost::none, |
137 |
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130 | bp::arg("compute_largest_eigen_values") = true, bp::arg("stat_record") = false), |
138 | "Solve the constrained conic problem, starting from the optional initial guess.") | ||
139 | |||
140 |
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130 | .def("setRho", &Solver::setRho, bp::args("self", "rho"), "Set the ADMM penalty value.") |
141 |
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130 | .def("getRho", &Solver::getRho, bp::arg("self"), "Get the ADMM penalty value.") |
142 | |||
143 |
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65 | .def( |
144 |
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130 | "setRhoPower", &Solver::setRhoPower, bp::args("self", "rho_power"), |
145 | "Set the power associated to the problem conditionning.") | ||
146 |
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65 | .def( |
147 |
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130 | "getRhoPower", &Solver::getRhoPower, bp::arg("self"), |
148 | "Get the power associated to the problem conditionning.") | ||
149 | |||
150 |
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65 | .def( |
151 |
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130 | "setRhoPowerFactor", &Solver::setRhoPowerFactor, bp::args("self", "rho_power_factor"), |
152 | "Set the power factor associated to the problem conditionning.") | ||
153 |
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65 | .def( |
154 |
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130 | "getRhoPowerFactor", &Solver::getRhoPowerFactor, bp::arg("self"), |
155 | "Get the power factor associated to the problem conditionning.") | ||
156 | |||
157 |
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65 | .def( |
158 |
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130 | "setTau", &Solver::setTau, bp::args("self", "tau"), "Set the tau linear scaling factor.") |
159 |
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130 | .def("getTau", &Solver::getTau, bp::arg("self"), "Get the tau linear scaling factor.") |
160 | |||
161 |
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65 | .def( |
162 |
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130 | "setProximalValue", &Solver::setProximalValue, bp::args("self", "mu"), |
163 | "Set the proximal value.") | ||
164 |
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65 | .def( |
165 |
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130 | "getProximalValue", &Solver::getProximalValue, bp::arg("self"), "Get the proximal value.") |
166 | |||
167 |
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65 | .def( |
168 |
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130 | "setRatioPrimalDual", &Solver::setRatioPrimalDual, bp::args("self", "ratio_primal_dual"), |
169 | "Set the primal/dual ratio.") | ||
170 |
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65 | .def( |
171 |
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130 | "getRatioPrimalDual", &Solver::getRatioPrimalDual, bp::arg("self"), |
172 | "Get the primal/dual ratio.") | ||
173 | |||
174 |
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65 | .def( |
175 |
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65 | "getPrimalSolution", &Solver::getPrimalSolution, bp::arg("self"), |
176 | 65 | "Returns the primal solution of the problem.", bp::return_internal_reference<>()) | |
177 | |||
178 |
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65 | .def( |
179 |
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65 | "getDualSolution", &Solver::getDualSolution, bp::arg("self"), |
180 | 65 | "Returns the dual solution of the problem.", bp::return_internal_reference<>()) | |
181 | |||
182 |
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65 | .def( |
183 |
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130 | "getCholeskyUpdateCount", &Solver::getCholeskyUpdateCount, bp::arg("self"), |
184 | "Returns the number of updates of the Cholesky factorization due to rho updates.") | ||
185 | |||
186 |
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65 | .def( |
187 |
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130 | "computeRho", &Solver::computeRho, bp::args("L", "m", "rho_power"), |
188 | "Compute the penalty ADMM value from the current largest and lowest eigenvalues and " | ||
189 | "the scaling spectral factor.") | ||
190 |
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65 | .staticmethod("computeRho") |
191 |
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65 | .def( |
192 |
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130 | "computeRhoPower", &Solver::computeRhoPower, bp::args("L", "m", "rho"), |
193 | "Compute the scaling spectral factor of the ADMM penalty term from the current " | ||
194 | "largest and lowest eigenvalues and the ADMM penalty term.") | ||
195 |
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65 | .staticmethod("computeRhoPower") |
196 | |||
197 |
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65 | .def( |
198 |
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65 | "getPowerIterationAlgo", &Solver::getPowerIterationAlgo, bp::arg("self"), |
199 | 65 | bp::return_internal_reference<>()) | |
200 | |||
201 |
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65 | .def("getStats", &Solver::getStats, bp::arg("self"), bp::return_internal_reference<>()); |
202 | |||
203 | #ifdef PINOCCHIO_WITH_ACCELERATE_SUPPORT | ||
204 | { | ||
205 | typedef Eigen::AccelerateLLT<context::SparseMatrix> AccelerateLLT; | ||
206 | typedef DelassusOperatorSparseTpl<context::Scalar, context::Options, AccelerateLLT> | ||
207 | DelassusOperatorSparseAccelerate; | ||
208 | cl.def( | ||
209 | "solve", solve_wrapper<DelassusOperatorSparseAccelerate>, | ||
210 | (bp::args("self", "delassus", "g", "cones", "R"), | ||
211 | bp::arg("primal_solution") = boost::none, bp::arg("dual_solution") = boost::none, | ||
212 | bp::arg("compute_largest_eigen_values") = true, bp::arg("stat_record") = false), | ||
213 | "Solve the constrained conic problem, starting from the optional initial guess."); | ||
214 | } | ||
215 | #endif | ||
216 | |||
217 |
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65 | bp::def( |
218 |
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130 | "computeConeProjection", computeConeProjection_wrapper, bp::args("cones", "forces"), |
219 | "Project a vector on the cartesian product of cones."); | ||
220 | |||
221 |
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65 | bp::def( |
222 | "computeDualConeProjection", computeDualConeProjection_wrapper, | ||
223 |
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130 | bp::args("cones", "velocities"), |
224 | "Project a vector on the cartesian product of dual cones."); | ||
225 | |||
226 |
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65 | bp::def( |
227 |
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130 | "computePrimalFeasibility", computePrimalFeasibility_wrapper, bp::args("cones", "forces"), |
228 | "Compute the primal feasibility."); | ||
229 | |||
230 |
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65 | bp::def( |
231 | "computeReprojectionError", computeReprojectionError_wrapper, | ||
232 |
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130 | bp::args("cones", "forces", "velocities"), "Compute the reprojection error."); |
233 | |||
234 |
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65 | bp::def( |
235 | "computeComplementarityShift", computeComplementarityShift_wrapper, | ||
236 |
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130 | bp::args("cones", "velocities"), |
237 | "Compute the complementarity shift associated to the De Saxé function."); | ||
238 | |||
239 | { | ||
240 |
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65 | bp::class_<SolverStats>( |
241 | "SolverStats", "", | ||
242 |
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130 | bp::init<int>((bp::arg("self"), bp::arg("max_it")), "Default constructor")) |
243 |
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130 | .def("reset", &SolverStats::reset, bp::arg("self"), "Reset the stasts.") |
244 |
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65 | .def( |
245 |
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130 | "size", &SolverStats::size, bp::arg("self"), |
246 | "Size of the vectors stored in the structure.") | ||
247 | |||
248 |
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65 | .PINOCCHIO_ADD_PROPERTY_READONLY(SolverStats, primal_feasibility, "") |
249 |
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65 | .PINOCCHIO_ADD_PROPERTY_READONLY(SolverStats, dual_feasibility, "") |
250 |
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65 | .PINOCCHIO_ADD_PROPERTY_READONLY(SolverStats, dual_feasibility_ncp, "") |
251 |
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65 | .PINOCCHIO_ADD_PROPERTY_READONLY(SolverStats, complementarity, "") |
252 |
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65 | .PINOCCHIO_ADD_PROPERTY_READONLY(SolverStats, rho, "") |
253 |
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65 | .PINOCCHIO_ADD_PROPERTY_READONLY( |
254 | SolverStats, it, "Number of iterations performed by the algorithm.") | ||
255 |
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65 | .PINOCCHIO_ADD_PROPERTY_READONLY( |
256 | SolverStats, cholesky_update_count, | ||
257 | "Number of Cholesky updates performed by the algorithm."); | ||
258 | } | ||
259 | |||
260 | { | ||
261 | typedef PowerIterationAlgoTpl<context::VectorXs> PowerIterationAlgo; | ||
262 |
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65 | bp::class_<PowerIterationAlgo>( |
263 | "PowerIterationAlgo", "", | ||
264 |
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65 | bp::init<Eigen::DenseIndex, int, Scalar>( |
265 |
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130 | (bp::arg("self"), bp::arg("size"), bp::arg("max_it") = 10, bp::arg("rel_tol") = 1e-8), |
266 | "Default constructor")) | ||
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130 | .def("run", &PowerIterationAlgo::run<context::MatrixXs>, bp::arg("self"), "") |
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65 | .def( |
269 | "lowest", &PowerIterationAlgo::lowest<context::MatrixXs>, | ||
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130 | (bp::arg("self"), bp::arg("compute_largest") = true), "") |
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130 | .def("reset", &PowerIterationAlgo::reset, bp::arg("self")) |
272 | |||
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65 | .PINOCCHIO_ADD_PROPERTY(PowerIterationAlgo, principal_eigen_vector, "") |
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65 | .PINOCCHIO_ADD_PROPERTY(PowerIterationAlgo, lowest_eigen_vector, "") |
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65 | .PINOCCHIO_ADD_PROPERTY(PowerIterationAlgo, max_it, "") |
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65 | .PINOCCHIO_ADD_PROPERTY(PowerIterationAlgo, rel_tol, "") |
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65 | .PINOCCHIO_ADD_PROPERTY_READONLY(PowerIterationAlgo, largest_eigen_value, "") |
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65 | .PINOCCHIO_ADD_PROPERTY_READONLY(PowerIterationAlgo, lowest_eigen_value, "") |
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65 | .PINOCCHIO_ADD_PROPERTY_READONLY(PowerIterationAlgo, it, "") |
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65 | .PINOCCHIO_ADD_PROPERTY_READONLY(PowerIterationAlgo, convergence_criteria, ""); |
281 | } | ||
282 | #endif | ||
283 | 69 | } | |
284 | |||
285 | } // namespace python | ||
286 | } // namespace pinocchio | ||
287 |