| Directory: | ./ |
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| File: | bindings/python/crocoddyl/core/solver-base.cpp |
| Date: | 2025-01-16 08:47:40 |
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| Lines: | 94 | 95 | 98.9% |
| Branches: | 97 | 194 | 50.0% |
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| 1 | /////////////////////////////////////////////////////////////////////////////// | ||
| 2 | // BSD 3-Clause License | ||
| 3 | // | ||
| 4 | // Copyright (C) 2019-2023, LAAS-CNRS, University of Edinburgh, | ||
| 5 | // Heriot-Watt University | ||
| 6 | // Copyright note valid unless otherwise stated in individual files. | ||
| 7 | // All rights reserved. | ||
| 8 | /////////////////////////////////////////////////////////////////////////////// | ||
| 9 | |||
| 10 | #include "python/crocoddyl/core/solver-base.hpp" | ||
| 11 | |||
| 12 | #include "python/crocoddyl/utils/copyable.hpp" | ||
| 13 | #include "python/crocoddyl/utils/deprecate.hpp" | ||
| 14 | #include "python/crocoddyl/utils/vector-converter.hpp" | ||
| 15 | |||
| 16 | namespace crocoddyl { | ||
| 17 | namespace python { | ||
| 18 | |||
| 19 | 10 | void exposeSolverAbstract() { | |
| 20 | // Register custom converters between std::vector and Python list | ||
| 21 | typedef boost::shared_ptr<CallbackAbstract> CallbackAbstractPtr; | ||
| 22 |
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10 | StdVectorPythonVisitor<std::vector<CallbackAbstractPtr>, true>::expose( |
| 23 | "StdVec_Callback"); | ||
| 24 | |||
| 25 | 20 | bp::enum_<FeasibilityNorm>("FeasibilityNorm") | |
| 26 |
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10 | .value("LInf", LInf) |
| 27 |
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10 | .value("L1", L1) |
| 28 |
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10 | .export_values(); |
| 29 | |||
| 30 |
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10 | bp::class_<SolverAbstract_wrap, boost::noncopyable>( |
| 31 | "SolverAbstract", | ||
| 32 | "Abstract class for optimal control solvers.\n\n" | ||
| 33 | "A solver resolves an optimal control solver which is formulated in a " | ||
| 34 | "shooting problem\n" | ||
| 35 | "abstraction. The main routines are computeDirection and tryStep. The " | ||
| 36 | "former finds\n" | ||
| 37 | "a search direction and typically computes the derivatives of each " | ||
| 38 | "action model. The latter\n" | ||
| 39 | "rollout the dynamics and cost (i.e. the action) to try the search " | ||
| 40 | "direction found by\n" | ||
| 41 | "computeDirection. Both functions used the current guess defined by " | ||
| 42 | "setCandidate. Finally\n" | ||
| 43 | "solve function is used to define when the search direction and length " | ||
| 44 | "are computed in each\n" | ||
| 45 | "iterate. It also describes the globalization strategy (i.e. " | ||
| 46 | "regularization) of the\n" | ||
| 47 | "numerical optimization.", | ||
| 48 |
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10 | bp::init<boost::shared_ptr<ShootingProblem> >( |
| 49 | 20 | bp::args("self", "problem"), | |
| 50 | "Initialize the solver model.\n\n" | ||
| 51 | ":param problem: shooting problem")) | ||
| 52 |
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10 | .def("solve", pure_virtual(&SolverAbstract_wrap::solve), |
| 53 |
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20 | bp::args("self", "init_xs", "init_us", "maxiter", "isFeasible", |
| 54 | "regInit"), | ||
| 55 | "Compute the optimal trajectory xopt,uopt as lists of T+1 and T " | ||
| 56 | "terms.\n\n" | ||
| 57 | "From an initial guess init_xs,init_us (feasible or not), iterate\n" | ||
| 58 | "over computeDirection and tryStep until stoppingCriteria is below\n" | ||
| 59 | "threshold. It also describes the globalization strategy used\n" | ||
| 60 | "during the numerical optimization.\n" | ||
| 61 | ":param init_xs: initial guess for state trajectory with T+1 " | ||
| 62 | "elements (default [])\n" | ||
| 63 | ":param init_us: initial guess for control trajectory with T " | ||
| 64 | "elements (default []).\n" | ||
| 65 | ":param maxiter: maximum allowed number of iterations (default " | ||
| 66 | "100).\n" | ||
| 67 | ":param isFeasible: true if the init_xs are obtained from " | ||
| 68 | "integrating the init_us (rollout) (default " | ||
| 69 | "False).\n" | ||
| 70 | ":param regInit: initial guess for the regularization value. Very " | ||
| 71 | "low\n" | ||
| 72 | " values are typical used with very good guess " | ||
| 73 | "points (init_xs, init_us).\n" | ||
| 74 | ":returns A boolean that describes if convergence was reached.") | ||
| 75 |
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10 | .def("computeDirection", |
| 76 | pure_virtual(&SolverAbstract_wrap::computeDirection), | ||
| 77 |
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20 | bp::args("self", "recalc"), |
| 78 | "Compute the search direction (dx, du) for the current guess (xs, " | ||
| 79 | "us).\n\n" | ||
| 80 | "You must call setCandidate first in order to define the current\n" | ||
| 81 | "guess. A current guess defines a state and control trajectory\n" | ||
| 82 | "(xs, us) of T+1 and T elements, respectively.\n" | ||
| 83 | ":params recalc: true for recalculating the derivatives at current " | ||
| 84 | "state and control.\n" | ||
| 85 | ":returns the search direction dx, du and the dual lambdas as lists " | ||
| 86 | "of T+1, T and T+1 lengths.") | ||
| 87 |
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10 | .def( |
| 88 | "tryStep", pure_virtual(&SolverAbstract_wrap::tryStep), | ||
| 89 |
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20 | bp::args("self", "stepLength"), |
| 90 | "Try a predefined step length and compute its cost improvement.\n\n" | ||
| 91 | "It uses the search direction found by computeDirection to try a\n" | ||
| 92 | "determined step length; so you need to first run computeDirection.\n" | ||
| 93 | "Additionally it returns the cost improvement along the predefined\n" | ||
| 94 | "step length.\n" | ||
| 95 | ":param stepLength: step length\n" | ||
| 96 | ":returns the cost improvement.") | ||
| 97 |
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10 | .def( |
| 98 | "stoppingCriteria", | ||
| 99 | pure_virtual(&SolverAbstract_wrap::stoppingCriteria), | ||
| 100 |
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20 | bp::args("self"), |
| 101 | "Return a positive value that quantifies the algorithm " | ||
| 102 | "termination.\n\n" | ||
| 103 | "These values typically represents the gradient norm which tell us\n" | ||
| 104 | "that it's been reached the local minima. This function is used to\n" | ||
| 105 | "evaluate the algorithm convergence. The stopping criteria strictly\n" | ||
| 106 | "speaking depends on the search direction (calculated by\n" | ||
| 107 | "computeDirection) but it could also depend on the chosen step\n" | ||
| 108 | "length, tested by tryStep.") | ||
| 109 |
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10 | .def("expectedImprovement", |
| 110 | pure_virtual(&SolverAbstract_wrap::expectedImprovement_wrap), | ||
| 111 |
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20 | bp::args("self"), |
| 112 | "Return the expected improvement from a given current search " | ||
| 113 | "direction.\n\n" | ||
| 114 | "For computing the expected improvement, you need to compute first\n" | ||
| 115 | "the search direction by running computeDirection.") | ||
| 116 |
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10 | .def("setCandidate", &SolverAbstract_wrap::setCandidate, |
| 117 |
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10 | setCandidate_overloads( |
| 118 |
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20 | bp::args("self", "xs", "us", "isFeasible"), |
| 119 | "Set the solver candidate warm-point values (xs, us).\n\n" | ||
| 120 | "The solver candidates are defined as a state and control " | ||
| 121 | "trajectory\n" | ||
| 122 | "(xs, us) of T+1 and T elements, respectively. Additionally, we " | ||
| 123 | "need\n" | ||
| 124 | "to define is (xs,us) pair is feasible, this means that the " | ||
| 125 | "dynamics\n" | ||
| 126 | "rollout give us produces xs.\n" | ||
| 127 | ":param xs: state trajectory of T+1 elements (default []).\n" | ||
| 128 | ":param us: control trajectory of T elements (default []).\n" | ||
| 129 | ":param isFeasible: true if the xs are obtained from " | ||
| 130 | "integrating the\n" | ||
| 131 | "us (rollout).")) | ||
| 132 |
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10 | .def("computeDynamicFeasibility", |
| 133 |
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20 | &SolverAbstract_wrap::computeDynamicFeasibility, bp::args("self"), |
| 134 | "Compute the dynamic feasibility for the current guess.\n\n" | ||
| 135 | "The feasibility can be computed using the computed using the l-1 " | ||
| 136 | "and l-inf norms.\n" | ||
| 137 | "By default we use the l-inf norm, however, we can use the l-1 norm " | ||
| 138 | "by defining inffeas as False.") | ||
| 139 |
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10 | .def("computeInequalityFeasibility", |
| 140 |
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20 | &SolverAbstract_wrap::computeInequalityFeasibility, bp::args("self"), |
| 141 | "Compute the feasibility of the inequality constraint for the " | ||
| 142 | "current guess.\n\n" | ||
| 143 | "The feasibility can be computed using the computed using the l-1 " | ||
| 144 | "and l-inf norms.\n" | ||
| 145 | "By default we use the l-inf norm, however, we can use the l-1 norm " | ||
| 146 | "by defining inffeas as False.") | ||
| 147 |
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10 | .def("computeEqualityFeasibility", |
| 148 |
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20 | &SolverAbstract_wrap::computeEqualityFeasibility, bp::args("self"), |
| 149 | "Compute the feasibility of the equality constraint for the current " | ||
| 150 | "guess.\n\n" | ||
| 151 | "The feasibility can be computed using the computed using the l-1 " | ||
| 152 | "and l-inf norms.\n" | ||
| 153 | "By default we use the l-inf norm, however, we can use the l-1 norm " | ||
| 154 | "by defining inffeas as False.") | ||
| 155 |
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10 | .def("setCallbacks", &SolverAbstract_wrap::setCallbacks, |
| 156 |
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20 | bp::args("self", "callbacks"), |
| 157 | "Set a list of callback functions using for diagnostic.\n\n" | ||
| 158 | "Each iteration, the solver calls these set of functions in order " | ||
| 159 | "to\n" | ||
| 160 | "allowed user the diagnostic of the its performance.\n" | ||
| 161 | ":param callbacks: set of callback functions.") | ||
| 162 |
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10 | .def("getCallbacks", &SolverAbstract_wrap::getCallbacks, |
| 163 | ✗ | bp::return_value_policy<bp::copy_const_reference>(), | |
| 164 |
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20 | bp::args("self"), |
| 165 | "Return the list of callback functions using for diagnostic.\n\n" | ||
| 166 | ":return set of callback functions.") | ||
| 167 |
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10 | .add_property("problem", |
| 168 |
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10 | bp::make_function( |
| 169 | &SolverAbstract_wrap::get_problem, | ||
| 170 | 10 | bp::return_value_policy<bp::copy_const_reference>()), | |
| 171 | "shooting problem") | ||
| 172 |
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10 | .def_readwrite("xs", &SolverAbstract_wrap::xs_, "state trajectory") |
| 173 |
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10 | .def_readwrite("us", &SolverAbstract_wrap::us_, "control sequence") |
| 174 |
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10 | .def_readwrite("fs", &SolverAbstract_wrap::fs_, "dynamics gaps") |
| 175 |
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10 | .def_readwrite("isFeasible", &SolverAbstract_wrap::is_feasible_, |
| 176 | "feasible (xs,us)") | ||
| 177 |
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10 | .def_readwrite("cost", &SolverAbstract_wrap::cost_, |
| 178 | "cost for the current guess") | ||
| 179 |
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10 | .def_readwrite("merit", &SolverAbstract_wrap::merit_, |
| 180 | "merit for the current guess") | ||
| 181 |
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10 | .def_readwrite("stop", &SolverAbstract_wrap::stop_, |
| 182 | "stopping criteria value") | ||
| 183 |
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10 | .def_readwrite("d", &SolverAbstract_wrap::d_, |
| 184 | "linear and quadratic terms of the expected improvement") | ||
| 185 |
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10 | .def_readwrite("dV", &SolverAbstract_wrap::dV_, |
| 186 | "reduction in the cost function computed by `tryStep()`") | ||
| 187 |
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10 | .def_readwrite("dPhi", &SolverAbstract_wrap::dPhi_, |
| 188 | "reduction in the merit function computed by `tryStep()`") | ||
| 189 |
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10 | .def_readwrite("dVexp", &SolverAbstract_wrap::dVexp_, |
| 190 | "expected reduction in the cost function") | ||
| 191 |
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10 | .def_readwrite("dPhiexp", &SolverAbstract_wrap::dPhiexp_, |
| 192 | "expected reduction in the merit function") | ||
| 193 |
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10 | .def_readwrite("dfeas", &SolverAbstract_wrap::dfeas_, |
| 194 | "reduction in the feasibility") | ||
| 195 |
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10 | .def_readwrite("feas", &SolverAbstract_wrap::feas_, |
| 196 | "total feasibility for the current guess") | ||
| 197 | 20 | .def_readwrite( | |
| 198 |
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10 | "ffeas", &SolverAbstract_wrap::ffeas_, |
| 199 | "feasibility of the dynamic constraint for the current guess") | ||
| 200 | 20 | .def_readwrite( | |
| 201 |
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10 | "gfeas", &SolverAbstract_wrap::gfeas_, |
| 202 | "feasibility of the inequality constraint for the current guess") | ||
| 203 | 20 | .def_readwrite( | |
| 204 |
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10 | "hfeas", &SolverAbstract_wrap::hfeas_, |
| 205 | "feasibility of the equality constraint for the current guess") | ||
| 206 | 20 | .def_readwrite( | |
| 207 |
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10 | "ffeas_try", &SolverAbstract_wrap::ffeas_try_, |
| 208 | "feasibility of the dynamic constraint for the current step length") | ||
| 209 |
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10 | .def_readwrite("gfeas_try", &SolverAbstract_wrap::gfeas_try_, |
| 210 | "feasibility of the inequality constraint for the current " | ||
| 211 | "step length") | ||
| 212 | 20 | .def_readwrite( | |
| 213 |
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10 | "hfeas_try", &SolverAbstract_wrap::hfeas_try_, |
| 214 | "feasibility of the equality constraint for the current step length") | ||
| 215 |
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10 | .add_property("preg", bp::make_function(&SolverAbstract_wrap::get_preg), |
| 216 |
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20 | bp::make_function(&SolverAbstract_wrap::set_preg), |
| 217 | "primal-variable regularization") | ||
| 218 |
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10 | .add_property("dreg", bp::make_function(&SolverAbstract_wrap::get_dreg), |
| 219 |
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20 | bp::make_function(&SolverAbstract_wrap::set_dreg), |
| 220 | "dual-variable regularization") | ||
| 221 |
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10 | .add_property( |
| 222 | "x_reg", | ||
| 223 |
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10 | bp::make_function( |
| 224 | &SolverAbstract_wrap::get_xreg, | ||
| 225 |
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20 | deprecated<bp::return_value_policy<bp::return_by_value> >( |
| 226 | "Deprecated. Use preg")), | ||
| 227 |
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20 | bp::make_function(&SolverAbstract_wrap::set_xreg, |
| 228 |
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20 | deprecated<>("Deprecated. Use preg.")), |
| 229 | "state regularization") | ||
| 230 |
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10 | .add_property( |
| 231 | "u_reg", | ||
| 232 |
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10 | bp::make_function( |
| 233 | &SolverAbstract_wrap::get_ureg, | ||
| 234 |
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20 | deprecated<bp::return_value_policy<bp::return_by_value> >( |
| 235 | "Deprecated. Use preg")), | ||
| 236 |
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20 | bp::make_function(&SolverAbstract_wrap::set_ureg, |
| 237 |
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20 | deprecated<>("Deprecated. Use preg.")), |
| 238 | "control regularization") | ||
| 239 |
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10 | .def_readwrite("stepLength", &SolverAbstract_wrap::steplength_, |
| 240 | "applied step length") | ||
| 241 |
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10 | .add_property("th_acceptStep", |
| 242 |
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10 | bp::make_function(&SolverAbstract_wrap::get_th_acceptstep), |
| 243 |
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20 | bp::make_function(&SolverAbstract_wrap::set_th_acceptstep), |
| 244 | "threshold for step acceptance") | ||
| 245 |
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10 | .add_property("th_stop", |
| 246 |
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10 | bp::make_function(&SolverAbstract_wrap::get_th_stop), |
| 247 |
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20 | bp::make_function(&SolverAbstract_wrap::set_th_stop), |
| 248 | "threshold for stopping criteria") | ||
| 249 |
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10 | .add_property("th_gapTol", |
| 250 |
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10 | bp::make_function(&SolverAbstract_wrap::get_th_gaptol), |
| 251 |
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20 | bp::make_function(&SolverAbstract_wrap::set_th_gaptol), |
| 252 | "threshold for accepting a gap as non-zero") | ||
| 253 |
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10 | .add_property( |
| 254 |
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10 | "feasNorm", bp::make_function(&SolverAbstract_wrap::get_feasnorm), |
| 255 |
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20 | bp::make_function(&SolverAbstract_wrap::set_feasnorm), |
| 256 | "norm used to compute the dynamic and constraints feasibility") | ||
| 257 |
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10 | .def_readwrite("iter", &SolverAbstract_wrap::iter_, |
| 258 | "number of iterations runned in solve()") | ||
| 259 |
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10 | .def(CopyableVisitor<SolverAbstract_wrap>()); |
| 260 | |||
| 261 | 10 | bp::class_<CallbackAbstract_wrap, boost::noncopyable>( | |
| 262 | "CallbackAbstract", | ||
| 263 | "Abstract class for solver callbacks.\n\n" | ||
| 264 | "A callback is used to diagnostic the behaviour of our solver in each " | ||
| 265 | "iteration of it.\n" | ||
| 266 | "For instance, it can be used to print values, record data or display " | ||
| 267 | "motions") | ||
| 268 |
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10 | .def("__call__", pure_virtual(&CallbackAbstract_wrap::operator()), |
| 269 |
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20 | bp::args("self", "solver"), |
| 270 | "Run the callback function given a solver.\n\n" | ||
| 271 | ":param solver: solver to be diagnostic") | ||
| 272 |
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10 | .def(CopyableVisitor<CallbackAbstract_wrap>()); |
| 273 | 10 | } | |
| 274 | |||
| 275 | } // namespace python | ||
| 276 | } // namespace crocoddyl | ||
| 277 |