GCC Code Coverage Report

Directory: ./
File: bindings/python/crocoddyl/core/numdiff/action.cpp
Date: 2025-01-30 11:01:55
Exec Total Coverage
Lines: 50 50 100.0%
Branches: 36 72 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 "crocoddyl/core/numdiff/action.hpp"
11
12 #include "python/crocoddyl/core/action-base.hpp"
13 #include "python/crocoddyl/core/core.hpp"
14 #include "python/crocoddyl/utils/copyable.hpp"
15
16 namespace crocoddyl {
17 namespace python {
18
19 10 void exposeActionNumDiff() {
20 10 bp::register_ptr_to_python<std::shared_ptr<ActionModelNumDiff> >();
21
22
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 10 bp::class_<ActionModelNumDiff, bp::bases<ActionModelAbstract> >(
23 "ActionModelNumDiff",
24 "Abstract class for computing calcDiff by using numerical "
25 "differentiation.\n\n",
26
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 10 bp::init<std::shared_ptr<ActionModelAbstract>, bp::optional<bool> >(
27 20 bp::args("self", "model", "gaussApprox"),
28 "Initialize the action model NumDiff.\n\n"
29 ":param model: action model where we compute the derivatives through "
30 "NumDiff\n"
31 ":param gaussApprox: compute the Hessian using Gauss approximation "
32 "(default False)"))
33 .def<void (ActionModelNumDiff::*)(
34 const std::shared_ptr<ActionDataAbstract>&,
35 const Eigen::Ref<const Eigen::VectorXd>&,
36 20 const Eigen::Ref<const Eigen::VectorXd>&)>(
37
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 20 "calc", &ActionModelNumDiff::calc, bp::args("self", "data", "x", "u"),
38 "Compute the next state and cost value.\n\n"
39 "The system evolution is described in model.\n"
40 ":param data: NumDiff action data\n"
41 ":param x: state point (dim. state.nx)\n"
42 ":param u: control input (dim. nu)")
43 .def<void (ActionModelNumDiff::*)(
44 const std::shared_ptr<ActionDataAbstract>&,
45
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 10 const Eigen::Ref<const Eigen::VectorXd>&)>(
46
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 20 "calc", &ActionModelAbstract::calc, bp::args("self", "data", "x"))
47 .def<void (ActionModelNumDiff::*)(
48 const std::shared_ptr<ActionDataAbstract>&,
49 const Eigen::Ref<const Eigen::VectorXd>&,
50
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 10 const Eigen::Ref<const Eigen::VectorXd>&)>(
51 "calcDiff", &ActionModelNumDiff::calcDiff,
52
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 20 bp::args("self", "data", "x", "u"),
53 "Compute the derivatives of the dynamics and cost functions.\n\n"
54 "It computes the Jacobian and Hessian using numerical "
55 "differentiation.\n"
56 "It assumes that calc has been run first.\n"
57 ":param data: NumDiff action data\n"
58 ":param x: state point (dim. state.nx)\n"
59 ":param u: control input (dim. nu)")
60 .def<void (ActionModelNumDiff::*)(
61 const std::shared_ptr<ActionDataAbstract>&,
62
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 10 const Eigen::Ref<const Eigen::VectorXd>&)>(
63 "calcDiff", &ActionModelAbstract::calcDiff,
64
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 20 bp::args("self", "data", "x"))
65
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 20 .def("createData", &ActionModelNumDiff::createData, bp::args("self"),
66 "Create the action data.\n\n"
67 "Each action model (AM) has its own data that needs to be "
68 "allocated.\n"
69 "This function returns the allocated data for a predefined AM.\n"
70 ":return AM data.")
71
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 10 .add_property(
72 "model",
73
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 10 bp::make_function(&ActionModelNumDiff::get_model,
74 10 bp::return_value_policy<bp::return_by_value>()),
75 "action model")
76
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 10 .add_property(
77 "disturbance",
78
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 20 bp::make_function(&ActionModelNumDiff::get_disturbance),
79 &ActionModelNumDiff::set_disturbance,
80 "disturbance constant used in the numerical differentiation")
81
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 10 .add_property(
82 "withGaussApprox",
83
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 10 bp::make_function(&ActionModelNumDiff::get_with_gauss_approx,
84 10 bp::return_value_policy<bp::return_by_value>()),
85 "Gauss approximation for computing the Hessians")
86
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 10 .def(CopyableVisitor<ActionModelNumDiff>());
87
88 10 bp::register_ptr_to_python<std::shared_ptr<ActionDataNumDiff> >();
89
90
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 10 bp::class_<ActionDataNumDiff, bp::bases<ActionDataAbstract> >(
91 "ActionDataNumDiff", "Numerical differentiation action data.",
92
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 10 bp::init<ActionModelNumDiff*>(
93 20 bp::args("self", "model"),
94 "Create numerical differentiation action data.\n\n"
95 ":param model: numdiff action model"))
96
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 10 .add_property("Rx",
97
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 10 bp::make_getter(&ActionDataNumDiff::Rx,
98 10 bp::return_internal_reference<>()),
99 "Jacobian of the cost residual.")
100
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 10 .add_property("Ru",
101
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 10 bp::make_getter(&ActionDataNumDiff::Ru,
102 10 bp::return_internal_reference<>()),
103 "Jacobian of the cost residual.")
104
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 10 .add_property("dx",
105
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 10 bp::make_getter(&ActionDataNumDiff::dx,
106 10 bp::return_internal_reference<>()),
107 "state disturbance.")
108
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 10 .add_property("du",
109
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 10 bp::make_getter(&ActionDataNumDiff::du,
110 10 bp::return_internal_reference<>()),
111 "control disturbance.")
112
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 10 .add_property(
113 "data_0",
114
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 10 bp::make_getter(&ActionDataNumDiff::data_0,
115 10 bp::return_value_policy<bp::return_by_value>()),
116 "data that contains the final results")
117
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 10 .add_property(
118 "data_x",
119
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 10 bp::make_getter(&ActionDataNumDiff::data_x,
120 10 bp::return_value_policy<bp::return_by_value>()),
121 "temporary data associated with the state variation")
122
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 10 .add_property(
123 "data_u",
124
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 10 bp::make_getter(&ActionDataNumDiff::data_u,
125 10 bp::return_value_policy<bp::return_by_value>()),
126 "temporary data associated with the control variation")
127
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 10 .def(CopyableVisitor<ActionDataNumDiff>());
128 10 }
129
130 } // namespace python
131 } // namespace crocoddyl
132