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/////////////////////////////////////////////////////////////////////////////// |
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// BSD 3-Clause License |
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// |
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// Copyright (C) 2019-2025, LAAS-CNRS, University of Edinburgh, |
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// University of Oxford, 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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// Auto-generated file for double |
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#include "python/crocoddyl/core/diff-action-base.hpp" |
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#include "python/crocoddyl/core/core.hpp" |
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#include "python/crocoddyl/utils/vector-converter.hpp" |
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namespace crocoddyl { |
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namespace python { |
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template <typename Model> |
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struct DifferentialActionModelAbstractVisitor |
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: public bp::def_visitor<DifferentialActionModelAbstractVisitor<Model>> { |
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typedef typename Model::DifferentialActionModel ActionModel; |
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typedef typename Model::DifferentialActionData ActionData; |
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typedef typename Model::VectorXs VectorXs; |
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BOOST_PYTHON_MEMBER_FUNCTION_OVERLOADS( |
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DifferentialActionModel_quasiStatic_wraps, ActionModel::quasiStatic_x, 2, |
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4) |
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template <class PyClass> |
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void visit(PyClass& cl) const { |
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cl.def("calc", pure_virtual(&Model::calc), |
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bp::args("self", "data", "x", "u"), |
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"Compute the system acceleration and cost value.\n\n" |
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":param data: differential action data\n" |
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":param x: state point (dim. state.nx)\n" |
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":param u: control input (dim. nu)") |
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.def("calc", |
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static_cast<void (ActionModel::*)( |
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const std::shared_ptr<ActionData>&, |
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const Eigen::Ref<const VectorXs>&)>(&ActionModel::calc), |
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bp::args("self", "data", "x"), |
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"Compute the total cost value for nodes that depends only on the " |
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"state.\n\n" |
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"It updates the total cost and the system acceleration is not " |
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"updated as the control input is undefined. This function is used " |
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"in the terminal nodes of an optimal control problem.\n" |
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":param data: differential action data\n" |
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":param x: state point (dim. state.nx)") |
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.def("calcDiff", pure_virtual(&Model::calcDiff), |
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bp::args("self", "data", "x", "u"), |
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"Compute the derivatives of the dynamics and cost functions.\n\n" |
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"It computes the partial derivatives of the dynamical system and " |
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"the cost function. It assumes that calc has been run first. This " |
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"function builds a quadratic approximation of the time-continuous " |
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"action model (i.e. dynamical system and cost function).\n" |
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":param data: differential action data\n" |
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":param x: state point (dim. state.nx)\n" |
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":param u: control input (dim. nu)") |
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.def("calcDiff", |
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static_cast<void (ActionModel::*)( |
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const std::shared_ptr<ActionData>&, |
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const Eigen::Ref<const VectorXs>&)>(&ActionModel::calcDiff), |
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bp::args("self", "data", "x"), |
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"Compute the derivatives of the cost functions with respect to " |
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"the state only.\n\n" |
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"It updates the derivatives of the cost function with respect to " |
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"the state only. This function is used in the terminal nodes of " |
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"an optimal control problem.\n" |
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":param data: action data\n" |
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":param x: state point (dim. state.nx)") |
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.def("createData", &Model::createData, &Model::default_createData, |
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bp::args("self"), |
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"Create the differential action data.\n\n" |
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"Each differential action model has its own data that needs to be " |
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"allocated. This function returns the allocated data for a " |
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"predefined DAM.\n" |
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":return DAM data.") |
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.def("quasiStatic", &Model::quasiStatic_x, |
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DifferentialActionModel_quasiStatic_wraps( |
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bp::args("self", "data", "x", "maxiter", "tol"), |
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"Compute the quasic-static control given a state.\n\n" |
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"It runs an iterative Newton step in order to compute the " |
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"quasic-static regime given a state configuration.\n" |
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":param data: action data\n" |
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":param x: discrete-time state vector\n" |
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":param maxiter: maximum allowed number of iterations\n" |
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":param tol: stopping tolerance criteria (default 1e-9)\n" |
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":return u: quasic-static control")) |
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.def("quasiStatic", &Model::quasiStatic, &Model::default_quasiStatic, |
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bp::args("self", "data", "u", "x", "maxiter", "tol")) |
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.add_property("nu", bp::make_function(&Model::get_nu), |
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"dimension of control vector") |
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.add_property("nr", bp::make_function(&Model::get_nr), |
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"dimension of cost-residual vector") |
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.add_property("ng", bp::make_function(&Model::get_ng), |
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"number of inequality constraints") |
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.add_property("nh", bp::make_function(&Model::get_nh), |
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"number of equality constraints") |
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.add_property("ng_T", bp::make_function(&Model::get_ng_T), |
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"number of inequality terminal constraints") |
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.add_property("nh_T", bp::make_function(&Model::get_nh_T), |
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"number of equality terminal constraints") |
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.add_property( |
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"state", |
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bp::make_function(&Model::get_state, |
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bp::return_value_policy<bp::return_by_value>()), |
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"state") |
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.add_property("g_lb", |
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bp::make_function(&Model::get_g_lb, |
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bp::return_internal_reference<>()), |
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&Model::set_g_lb, |
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"lower bound of the inequality constraints") |
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.add_property("g_ub", |
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bp::make_function(&Model::get_g_ub, |
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bp::return_internal_reference<>()), |
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&Model::set_g_ub, |
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"upper bound of the inequality constraints") |
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.add_property("u_lb", |
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bp::make_function(&Model::get_u_lb, |
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bp::return_internal_reference<>()), |
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&Model::set_u_lb, "lower control limits") |
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.add_property("u_ub", |
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bp::make_function(&Model::get_u_ub, |
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bp::return_internal_reference<>()), |
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&Model::set_u_ub, "upper control limits") |
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.add_property("has_control_limits", |
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bp::make_function(&Model::get_has_control_limits), |
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"indicates whether problem has finite control limits"); |
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} |
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}; |
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template <typename Data> |
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struct DifferentialActionDataAbstractVisitor |
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: public bp::def_visitor<DifferentialActionDataAbstractVisitor<Data>> { |
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template <class PyClass> |
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void visit(PyClass& cl) const { |
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cl.add_property( |
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"cost", |
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bp::make_getter(&Data::cost, |
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bp::return_value_policy<bp::return_by_value>()), |
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bp::make_setter(&Data::cost), "cost value") |
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.add_property( |
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"xout", |
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bp::make_getter(&Data::xout, bp::return_internal_reference<>()), |
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bp::make_setter(&Data::xout), "evolution state") |
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.add_property( |
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"r", bp::make_getter(&Data::r, bp::return_internal_reference<>()), |
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bp::make_setter(&Data::r), "cost residual") |
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.add_property( |
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"Fx", bp::make_getter(&Data::Fx, bp::return_internal_reference<>()), |
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bp::make_setter(&Data::Fx), |
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"Jacobian of the dynamics w.r.t. the state") |
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.add_property( |
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"Fu", bp::make_getter(&Data::Fu, bp::return_internal_reference<>()), |
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bp::make_setter(&Data::Fu), |
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"Jacobian of the dynamics w.r.t. the control") |
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.add_property( |
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"Lx", bp::make_getter(&Data::Lx, bp::return_internal_reference<>()), |
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bp::make_setter(&Data::Lx), "Jacobian of the cost w.r.t. the state") |
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.add_property( |
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"Lu", bp::make_getter(&Data::Lu, bp::return_internal_reference<>()), |
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bp::make_setter(&Data::Lu), |
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"Jacobian of the cost w.r.t. the control") |
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.add_property( |
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"Lxx", |
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bp::make_getter(&Data::Lxx, bp::return_internal_reference<>()), |
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bp::make_setter(&Data::Lxx), "Hessian of the cost w.r.t. the state") |
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.add_property( |
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"Lxu", |
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bp::make_getter(&Data::Lxu, bp::return_internal_reference<>()), |
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bp::make_setter(&Data::Lxu), |
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"Hessian of the cost w.r.t. the state and control") |
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.add_property( |
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"Luu", |
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bp::make_getter(&Data::Luu, bp::return_internal_reference<>()), |
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bp::make_setter(&Data::Luu), |
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"Hessian of the cost w.r.t. the control") |
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.add_property( |
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"g", bp::make_getter(&Data::g, bp::return_internal_reference<>()), |
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bp::make_setter(&Data::g), "Inequality constraint values") |
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.add_property( |
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"Gx", bp::make_getter(&Data::Gx, bp::return_internal_reference<>()), |
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bp::make_setter(&Data::Gx), |
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"Jacobian of the inequality constraint w.r.t. the state") |
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.add_property( |
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"Gu", bp::make_getter(&Data::Gu, bp::return_internal_reference<>()), |
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bp::make_setter(&Data::Gu), |
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"Jacobian of the inequality constraint w.r.t. the control") |
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.add_property( |
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"h", bp::make_getter(&Data::h, bp::return_internal_reference<>()), |
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bp::make_setter(&Data::h), "Equality constraint values") |
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.add_property( |
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"Hx", bp::make_getter(&Data::Hx, bp::return_internal_reference<>()), |
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bp::make_setter(&Data::Hx), |
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"Jacobian of the equality constraint w.r.t. the state") |
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.add_property( |
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"Hu", bp::make_getter(&Data::Hu, bp::return_internal_reference<>()), |
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bp::make_setter(&Data::Hu), |
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"Jacobian of the equality constraint w.r.t. the control"); |
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} |
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}; |
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#define CROCODDYL_DIFFACTION_MODEL_ABSTRACT_PYTHON_BINDINGS(Scalar) \ |
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typedef DifferentialActionModelAbstractTpl<Scalar> Model; \ |
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typedef DifferentialActionModelAbstractTpl_wrap<Scalar> Model_wrap; \ |
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typedef StateAbstractTpl<Scalar> State; \ |
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typedef std::shared_ptr<Model> DifferentialActionModelPtr; \ |
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StdVectorPythonVisitor<std::vector<DifferentialActionModelPtr>, \ |
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true>::expose("StdVec_DiffActionModel"); \ |
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bp::register_ptr_to_python<std::shared_ptr<Model>>(); \ |
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bp::class_<Model_wrap, boost::noncopyable>( \ |
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"DifferentialActionModelAbstract", \ |
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"Abstract class for the differential action model.\n\n" \ |
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"A differential action model is the time-continuous version of an " \ |
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"action model. Each node, in our optimal control problem, is described " \ |
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"through an action model. Every time that we want describe a problem, " \ |
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"we need to provide ways of computing the dynamics, cost functions, " \ |
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"constraints and their derivatives. These computations are mainly " \ |
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"carried out inside calc() and calcDiff(), respectively.", \ |
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bp::init<std::shared_ptr<State>, std::size_t, \ |
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bp::optional<std::size_t, std::size_t, std::size_t, \ |
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std::size_t, std::size_t>>( \ |
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bp::args("self", "state", "nu", "nr", "ng", "nh", "ng_T", "nh_T"), \ |
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"Initialize the differential action model.\n\n" \ |
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"We can also describe autonomous systems by setting nu = 0.\n" \ |
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":param state: state\n" \ |
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":param nu: dimension of control vector\n" \ |
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":param nr: dimension of cost-residual vector (default 1)\n" \ |
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":param ng: number of inequality constraints (default 0)\n" \ |
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":param nh: number of equality constraints (default 0)\n" \ |
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":param ng_T: number of inequality terminal constraints (default " \ |
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"0)\n" \ |
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":param nh_T: number of equality terminal constraints (default 0)")) \ |
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.def(DifferentialActionModelAbstractVisitor<Model_wrap>()) \ |
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.def(PrintableVisitor<Model_wrap>()) \ |
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.def(CopyableVisitor<Model_wrap>()); |
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#define CROCODDYL_DIFFACTION_DATA_ABSTRACT_PYTHON_BINDINGS(Scalar) \ |
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typedef DifferentialActionDataAbstractTpl<Scalar> Data; \ |
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typedef DifferentialActionModelAbstractTpl<Scalar> Model; \ |
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typedef std::shared_ptr<Data> DifferentialActionDataPtr; \ |
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StdVectorPythonVisitor<std::vector<DifferentialActionDataPtr>, \ |
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true>::expose("StdVec_DiffActionData"); \ |
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bp::register_ptr_to_python<std::shared_ptr<Data>>(); \ |
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bp::class_<Data, boost::noncopyable>( \ |
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"DifferentialActionDataAbstract", \ |
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"Abstract class for differential action data.\n\n" \ |
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"In crocoddyl, an action data contains all the required information " \ |
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"for processing an user-defined action model. The action data " \ |
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"typically is allocated onces by running model.createData() and " \ |
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"contains the first- and second-order derivatives of the dynamics and " \ |
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"cost function, respectively.", \ |
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bp::init<Model*>(bp::args("self", "model"), \ |
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"Create common data shared between DAMs.\n\n" \ |
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"The differential action data uses the model in order " \ |
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"to first process it.\n" \ |
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":param model: differential action model")) \ |
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.def(DifferentialActionDataAbstractVisitor<Data>()) \ |
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.def(CopyableVisitor<Data>()); |
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void exposeDifferentialActionAbstract() { |
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CROCODDYL_DIFFACTION_MODEL_ABSTRACT_PYTHON_BINDINGS(double) |
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CROCODDYL_DIFFACTION_DATA_ABSTRACT_PYTHON_BINDINGS(double) |
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} |
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} // namespace python |
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} // namespace crocoddyl |
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