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/////////////////////////////////////////////////////////////////////////////// |
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// BSD 3-Clause License |
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// |
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// Copyright (C) 2021-2023, University of Edinburgh, University of Pisa, |
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// 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 float |
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#include "crocoddyl/core/numdiff/state.hpp" |
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#include "python/crocoddyl/core/core.hpp" |
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#include "python/crocoddyl/core/state-base.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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template <typename State> |
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struct StateNumDiffVisitor |
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: public bp::def_visitor<StateNumDiffVisitor<State>> { |
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typedef typename State::Scalar Scalar; |
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BOOST_PYTHON_MEMBER_FUNCTION_OVERLOADS(Jdiffs, |
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StateAbstractTpl<Scalar>::Jdiff_Js, 2, |
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3) |
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BOOST_PYTHON_MEMBER_FUNCTION_OVERLOADS( |
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Jintegrates, StateAbstractTpl<Scalar>::Jintegrate_Js, 2, 3) |
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template <class PyClass> |
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void visit(PyClass& cl) const { |
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cl.def("zero", &State::zero, bp::args("self"), |
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"Return a zero reference state.\n\n" |
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":return zero reference state") |
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.def("rand", &State::rand, bp::args("self"), |
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"Return a random reference state.\n\n" |
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":return random reference state") |
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.def("diff", &State::diff_dx, bp::args("self", "x0", "x1"), |
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"Operator that differentiates the two state points.\n\n" |
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"It returns the value of x1 [-] x0 operation. Due to a state " |
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"vector lies in the Euclidean space, this operator is defined " |
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"with arithmetic subtraction.\n" |
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":param x0: current state (dim state.nx).\n" |
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":param x1: next state (dim state.nx).\n" |
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":return x1 - x0 value (dim state.nx).") |
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.def("integrate", &State::integrate_x, bp::args("self", "x", "dx"), |
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"Operator that integrates the current state.\n\n" |
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"It returns the value of x [+] dx operation. Due to a state " |
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"vector lies in the Euclidean space, this operator is defined " |
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"with arithmetic addition. Futhermore there is no timestep here " |
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"(i.e. dx = v*dt), note this if you're integrating a velocity v " |
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"during an interval dt.\n" |
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":param x: current state (dim state.nx).\n" |
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":param dx: displacement of the state (dim state.nx).\n" |
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":return x + dx value (dim state.nx).") |
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.def("Jdiff", &State::Jdiff_Js, |
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Jdiffs(bp::args("self", "x0", "x1", "firstsecond"), |
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"Compute the partial derivatives of arithmetic " |
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"substraction.\n\n" |
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"Both Jacobian matrices are represented throught an " |
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"identity matrix, with the exception that the first " |
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"partial derivatives (w.r.t. x0) has negative signed. By " |
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"default, this function returns the derivatives of the " |
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"first and second argument (i.e., firstsecond='both'). " |
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"However we ask for a specific partial derivative by " |
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"setting firstsecond='first' or firstsecond='second'.\n" |
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":param x0: current state (dim state.nx).\n" |
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":param x1: next state (dim state.nx).\n" |
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":param firstsecond: derivative w.r.t x0 or x1 or both\n" |
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":return the partial derivative(s) of the diff(x0, x1) " |
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"function")) |
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.def("Jintegrate", &State::Jintegrate_Js, |
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Jintegrates( |
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bp::args("self", "x", "dx", "firstsecond"), |
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"Compute the partial derivatives of arithmetic addition.\n\n" |
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"Both Jacobian matrices are represented throught an identity " |
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"matrix. By default, this function returns the derivatives of " |
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"the first and second argument (i.e., firstsecond='both'). " |
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"However we ask for a specific partial derivative by setting " |
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"firstsecond='first' or firstsecond='second'.\n" |
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":param x: current state (dim state.nx).\n" |
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":param dx: displacement of the state (dim state.nx).\n" |
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":param firstsecond: derivative w.r.t x or dx or both\n" |
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":return the partial derivative(s) of the integrate(x, dx) " |
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"function")) |
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.def("JintegrateTransport", &State::JintegrateTransport, |
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bp::args("self", "x", "dx", "Jin", "firstsecond"), |
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"Parallel transport from integrate(x, dx) to x.\n\n" |
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"This function performs the parallel transportation of an input " |
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"matrix whose columns are expressed in the tangent space at " |
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"integrate(x, dx) to the tangent space at x point.\n" |
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":param x: state point (dim. state.nx).\n" |
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":param dx: velocity vector (dim state.ndx).\n" |
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":param Jin: input matrix (number of rows = state.nv).\n" |
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":param firstsecond: derivative w.r.t x or dx") |
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.add_property( |
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"disturbance", bp::make_function(&State::get_disturbance), |
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&State::set_disturbance, |
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"disturbance constant used in the numerical differentiation"); |
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} |
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}; |
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#define CROCODDYL_STATE_NUMDIFF_PYTHON_BINDINGS(Scalar) \ |
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typedef StateNumDiffTpl<Scalar> State; \ |
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typedef StateAbstractTpl<Scalar> StateBase; \ |
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bp::register_ptr_to_python<std::shared_ptr<State>>(); \ |
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bp::class_<State, bp::bases<StateBase>>( \ |
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"StateNumDiff", \ |
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"Abstract class for computing Jdiff and Jintegrate by using numerical " \ |
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"differentiation.\n\n", \ |
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bp::init<std::shared_ptr<StateBase>>( \ |
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bp::args("self", "state"), \ |
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"Initialize the state numdiff.\n\n" \ |
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":param model: state where we compute the derivatives through " \ |
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"numerial differentiation")) \ |
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.def(StateNumDiffVisitor<State>()) \ |
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.def(CastVisitor<State>()) \ |
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.def(PrintableVisitor<State>()) \ |
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.def(CopyableVisitor<State>()); |
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void exposeStateNumDiff() { |
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CROCODDYL_STATE_NUMDIFF_PYTHON_BINDINGS(float) |
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} |
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} // namespace python |
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} // namespace crocoddyl |
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