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/////////////////////////////////////////////////////////////////////////////// |
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// BSD 3-Clause License |
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// |
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// Copyright (C) 2020-2023, LAAS-CNRS, Heriot-Watt University |
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// Copyright note valid unless otherwise stated in individual files. |
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// All rights reserved. |
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/////////////////////////////////////////////////////////////////////////////// |
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#include "crocoddyl/core/solvers/kkt.hpp" |
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#include "python/crocoddyl/core/core.hpp" |
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#include "python/crocoddyl/utils/copyable.hpp" |
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namespace crocoddyl { |
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namespace python { |
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BOOST_PYTHON_MEMBER_FUNCTION_OVERLOADS(SolverKKT_solves, SolverKKT::solve, 0, 5) |
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BOOST_PYTHON_MEMBER_FUNCTION_OVERLOADS(SolverKKT_computeDirections, |
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SolverKKT::computeDirection, 0, 1) |
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BOOST_PYTHON_MEMBER_FUNCTION_OVERLOADS(SolverKKT_trySteps, SolverKKT::tryStep, |
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0, 1) |
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void exposeSolverKKT() { |
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bp::register_ptr_to_python<boost::shared_ptr<SolverKKT> >(); |
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✓✗ |
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bp::class_<SolverKKT, bp::bases<SolverAbstract> >( |
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"SolverKKT", |
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"KKT solver.\n\n" |
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"The KKT solver computes a primal and dual optimal by inverting\n" |
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"the kkt matrix \n" |
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":param shootingProblem: shooting problem (list of action models along " |
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"trajectory.)", |
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bp::init<boost::shared_ptr<ShootingProblem> >( |
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bp::args("self", "problem"), |
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"Initialize the vector dimension.\n\n" |
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":param problem: shooting problem.")) |
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.def("solve", &SolverKKT::solve, |
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✓✗ |
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SolverKKT_solves( |
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bp::args("self", "init_xs", "init_us", "maxiter", "isFeasible", |
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"regInit"), |
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"Compute the optimal primal(xopt, uopt) and dual(Vx) terms.\n\n" |
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":param init_xs: initial guess for state trajectory with T+1 " |
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"elements (default []).\n" |
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":param init_us: initial guess for control trajectory with T " |
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"elements (default []) (default []).\n" |
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":param maxiter: maximun allowed number of iterations (default " |
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"100).\n" |
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":param isFeasible: true if the init_xs are obtained from " |
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"integrating the init_us (rollout) (default " |
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"False).\n" |
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":param regInit: initial guess for the regularization value. " |
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"Very low values are typical\n" |
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" used with very good guess points (init_xs, " |
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"init_us) (default None).\n" |
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":returns the optimal trajectory xopt, uopt and a boolean that " |
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✓✗ |
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"describes if convergence was reached.")) |
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.def("computeDirection", &SolverKKT::computeDirection, |
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✓✗ |
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SolverKKT_computeDirections( |
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bp::args("self", "recalc"), |
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"Compute the search direction (dx, du), lambdas for the current " |
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"guess (xs, us).\n\n" |
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"You must call setCandidate first in order to define the " |
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"current\n" |
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"guess. A current guess defines a state and control trajectory\n" |
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"(xs, us) of T+1 and T elements, respectively.\n" |
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":params recalc: true for recalculating the derivatives at " |
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"current state and control.\n" |
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":returns the search direction dx, du and the dual lambdas as " |
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"lists of T+1, T and T+1 lengths.")) |
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.def("tryStep", &SolverKKT::tryStep, |
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SolverKKT_trySteps( |
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bp::args("self", " stepLength=1"), |
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"Rollout the system with a predefined step length.\n\n" |
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":param stepLength: step length\n" |
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":returns the cost improvement.")) |
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.def("stoppingCriteria", &SolverKKT::stoppingCriteria, bp::args("self"), |
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"Return a sum of positive parameters whose sum quantifies the DDP " |
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"termination.") |
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.def("expectedImprovement", &SolverKKT::expectedImprovement, |
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bp::return_value_policy<bp::copy_const_reference>(), |
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bp::args("self"), |
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"Return two scalars denoting the quadratic improvement model\n\n" |
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"For computing the expected improvement, you need to compute first\n" |
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"the search direction by running computeDirection. The quadratic\n" |
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"improvement model is described as dV = f_0 - f_+ = d1*a + " |
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"d2*a**2/2.") |
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.add_property( |
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"kkt", |
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make_function(&SolverKKT::get_kkt, |
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bp::return_value_policy<bp::copy_const_reference>()), |
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"kkt") |
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.add_property( |
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"kktref", |
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make_function(&SolverKKT::get_kktref, |
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bp::return_value_policy<bp::copy_const_reference>()), |
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"kktref") |
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.add_property( |
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"primaldual", |
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make_function(&SolverKKT::get_primaldual, |
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bp::return_value_policy<bp::copy_const_reference>()), |
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"primaldual") |
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.add_property( |
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"lambdas", |
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make_function(&SolverKKT::get_lambdas, |
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bp::return_value_policy<bp::copy_const_reference>()), |
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"lambdas") |
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.add_property( |
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"dxs", |
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make_function(&SolverKKT::get_dxs, |
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bp::return_value_policy<bp::copy_const_reference>()), |
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"dxs") |
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.add_property( |
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"dus", |
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make_function(&SolverKKT::get_dus, |
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bp::return_value_policy<bp::copy_const_reference>()), |
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"dus") |
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.def(CopyableVisitor<SolverKKT>()); |
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} |
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} // namespace python |
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} // namespace crocoddyl |