GCC Code Coverage Report

Line	Branch	Exec	Source
1			///////////////////////////////////////////////////////////////////////////////
2			// BSD 3-Clause License
3			//
4			// Copyright (C) 2019-2023, LAAS-CNRS, University of Edinburgh, New York
5			// University,
6			// Max Planck Gesellschaft,
7			// Heriot-Watt University
8			// Copyright note valid unless otherwise stated in individual files.
9			// All rights reserved.
10			///////////////////////////////////////////////////////////////////////////////
11
12			#ifndef CROCODDYL_CORE_NUMDIFF_COST_HPP_
13			#define CROCODDYL_CORE_NUMDIFF_COST_HPP_
14
15			#include <boost/function.hpp>
16
17			#include "crocoddyl/core/cost-base.hpp"
18			#include "crocoddyl/multibody/fwd.hpp"
19
20			namespace crocoddyl {
21
22			/**
23			* @brief This class computes the numerical differentiation of a cost model.
24			*
25			* It computes the Jacobian and Hessian of the cost model via numerical
26			* differentiation, i.e., \f$\mathbf{\ell_x}\f$, \f$\mathbf{\ell_u}\f$,
27			* \f$\mathbf{\ell_{xx}}\f$, \f$\mathbf{\ell_{uu}}\f$, and
28			* \f$\mathbf{\ell_{xu}}\f$ which denote the Jacobians and Hessians of the cost
29			* function, respectively.
30			*
31			* \sa `CostModelAbstractTpl()`, `calcDiff()`
32			*/
33			template <typename _Scalar>
34			class CostModelNumDiffTpl : public CostModelAbstractTpl<_Scalar> {
35			public:
36			EIGEN_MAKE_ALIGNED_OPERATOR_NEW
37
38			typedef _Scalar Scalar;
39			typedef CostDataAbstractTpl<Scalar> CostDataAbstract;
40			typedef CostModelAbstractTpl<Scalar> Base;
41			typedef CostDataNumDiffTpl<Scalar> Data;
42			typedef DataCollectorAbstractTpl<Scalar> DataCollectorAbstract;
43			typedef MathBaseTpl<Scalar> MathBase;
44			typedef typename MathBaseTpl<Scalar>::VectorXs VectorXs;
45			typedef typename MathBaseTpl<Scalar>::MatrixXs MatrixXs;
46			typedef boost::function<void(const VectorXs&, const VectorXs&)>
47			ReevaluationFunction;
48
49			/**
50			* @brief Initialize the numdiff cost model
51			*
52			* @param model Cost model that we want to apply the numerical
53			* differentiation
54			*/
55			explicit CostModelNumDiffTpl(const std::shared_ptr<Base>& model);
56
57			/**
58			* @brief Initialize the numdiff cost model
59			*/
60			virtual ~CostModelNumDiffTpl();
61
62			/**
63			* @brief @copydoc Base::calc()
64			*/
65			virtual void calc(const std::shared_ptr<CostDataAbstract>& data,
66			const Eigen::Ref<const VectorXs>& x,
67			const Eigen::Ref<const VectorXs>& u);
68
69			/**
70			* @brief @copydoc Base::calc(const std::shared_ptr<CostDataAbstract>& data,
71			* const Eigen::Ref<const VectorXs>& x)
72			*/
73			virtual void calc(const std::shared_ptr<CostDataAbstract>& data,
74			const Eigen::Ref<const VectorXs>& x);
75
76			/**
77			* @brief @copydoc Base::calcDiff()
78			*/
79			virtual void calcDiff(const std::shared_ptr<CostDataAbstract>& data,
80			const Eigen::Ref<const VectorXs>& x,
81			const Eigen::Ref<const VectorXs>& u);
82
83			/**
84			* @brief @copydoc Base::calcDiff(const std::shared_ptr<CostDataAbstract>&
85			* data, const Eigen::Ref<const VectorXs>& x)
86			*/
87			virtual void calcDiff(const std::shared_ptr<CostDataAbstract>& data,
88			const Eigen::Ref<const VectorXs>& x);
89
90			/**
91			* @brief Create a numdiff cost data
92			*
93			* @param data Data collector used by the original model
94			* @return the numdiff cost data
95			*/
96			virtual std::shared_ptr<CostDataAbstract> createData(
97			DataCollectorAbstract* const data);
98
99			/**
100			* @brief Return the original cost model
101			*/
102			const std::shared_ptr<Base>& get_model() const;
103
104			/**
105			* @brief Return the disturbance constant used by the numerical
106			* differentiation routine
107			*/
108			const Scalar get_disturbance() const;
109
110			/**
111			* @brief Modify the disturbance constant used by the numerical
112			* differentiation routine
113			*/
114			void set_disturbance(const Scalar disturbance);
115
116			/**
117			* @brief Identify if the Gauss approximation is going to be used or not.
118			*
119			* @return true
120			* @return false
121			*/
122			bool get_with_gauss_approx();
123
124			/**
125			* @brief Register functions that updates the shared data computed for a
126			* system rollout The updated data is used to evaluate of the gradient and
127			* Hessian.
128			*
129			* @param reevals are the registered functions.
130			*/
131			void set_reevals(const std::vector<ReevaluationFunction>& reevals);
132
133			protected:
134			using Base::activation_;
135			using Base::nu_;
136			using Base::state_;
137			using Base::unone_;
138
139			private:
140			/**
141			* @brief Make sure that when we finite difference the Cost Model, the user
142			* does not face unknown behaviour because of the finite differencing of a
143			* quaternion around pi. This behaviour might occur if state cost in and
144			* floating systems.
145			*
146			* For full discussions see issue
147			* https://gepgitlab.laas.fr/loco-3d/crocoddyl/issues/139
148			*
149			* @param x is the state at which the check is performed.
150			*/
151			void assertStableStateFD(const Eigen::Ref<const VectorXs>& /x/);
152
153			std::shared_ptr<Base> model_; //!< Cost model hat we want to apply the
154			//!< numerical differentiation
155			Scalar e_jac_; //!< Constant used for computing disturbances in Jacobian
156			//!< calculation
157			std::vector<ReevaluationFunction>
158			reevals_; //!< Functions that needs execution before calc or calcDiff
159			};
160
161			template <typename _Scalar>
162			struct CostDataNumDiffTpl : public CostDataAbstractTpl<_Scalar> {
163			EIGEN_MAKE_ALIGNED_OPERATOR_NEW
164
165			typedef _Scalar Scalar;
166			typedef MathBaseTpl<Scalar> MathBase;
167			typedef CostDataAbstractTpl<Scalar> Base;
168			typedef DataCollectorAbstractTpl<Scalar> DataCollectorAbstract;
169			typedef ActivationDataAbstractTpl<Scalar> ActivationDataAbstract;
170			typedef typename MathBaseTpl<Scalar>::VectorXs VectorXs;
171
172			/**
173			* @brief Initialize the numdiff cost data
174			*
175			* @tparam Model is the type of the `CostModelAbstractTpl`.
176			* @param model is the object to compute the numerical differentiation from.
177			*/
178			template <template <typename Scalar> class Model>
179		652	explicit CostDataNumDiffTpl(Model<Scalar>* const model,
180			DataCollectorAbstract* const shared_data)
181			: Base(model, shared_data),
182	1/2 ✓ Branch 3 taken 652 times. ✗ Branch 4 not taken.	652	dx(model->get_state()->get_ndx()),
183	1/2 ✓ Branch 4 taken 652 times. ✗ Branch 5 not taken.	652	xp(model->get_state()->get_nx()),
184	1/2 ✓ Branch 2 taken 652 times. ✗ Branch 3 not taken.	652	du(model->get_nu()),
185	1/2 ✓ Branch 4 taken 652 times. ✗ Branch 5 not taken.	1304	up(model->get_nu()) {
186	1/2 ✓ Branch 1 taken 652 times. ✗ Branch 2 not taken.	652	dx.setZero();
187	1/2 ✓ Branch 1 taken 652 times. ✗ Branch 2 not taken.	652	xp.setZero();
188	1/2 ✓ Branch 1 taken 652 times. ✗ Branch 2 not taken.	652	du.setZero();
189	1/2 ✓ Branch 1 taken 652 times. ✗ Branch 2 not taken.	652	up.setZero();
190
191		652	const std::size_t ndx = model->get_model()->get_state()->get_ndx();
192		652	const std::size_t nu = model->get_model()->get_nu();
193	1/2 ✓ Branch 3 taken 652 times. ✗ Branch 4 not taken.	652	data_0 = model->get_model()->createData(shared_data);
194	2/2 ✓ Branch 0 taken 26156 times. ✓ Branch 1 taken 652 times.	26808	for (std::size_t i = 0; i < ndx; ++i) {
195	2/4 ✓ Branch 3 taken 26156 times. ✗ Branch 4 not taken. ✓ Branch 6 taken 26156 times. ✗ Branch 7 not taken.	26156	data_x.push_back(model->get_model()->createData(shared_data));
196			}
197	2/2 ✓ Branch 0 taken 13078 times. ✓ Branch 1 taken 652 times.	13730	for (std::size_t i = 0; i < nu; ++i) {
198	2/4 ✓ Branch 3 taken 13078 times. ✗ Branch 4 not taken. ✓ Branch 6 taken 13078 times. ✗ Branch 7 not taken.	13078	data_u.push_back(model->get_model()->createData(shared_data));
199			}
200		652	}
201
202		1304	virtual ~CostDataNumDiffTpl() {}
203
204			using Base::activation;
205			using Base::cost;
206			using Base::Lu;
207			using Base::Luu;
208			using Base::Lx;
209			using Base::Lxu;
210			using Base::Lxx;
211			using Base::residual;
212			using Base::shared;
213
214			Scalar x_norm; //!< Norm of the state vector
215			Scalar
216			xh_jac; //!< Disturbance value used for computing \f$ \ell_\mathbf{x} \f$
217			Scalar
218			uh_jac; //!< Disturbance value used for computing \f$ \ell_\mathbf{u} \f$
219			VectorXs dx; //!< State disturbance.
220			VectorXs xp; //!< The integrated state from the disturbance on one DoF "\f$
221			//!< \int x dx_i \f$".
222			VectorXs du; //!< Control disturbance.
223			VectorXs up; //!< The integrated control from the disturbance on one DoF "\f$
224			//!< \int u du_i = u + du \f$".
225			std::shared_ptr<Base> data_0; //!< The data at the approximation point.
226			std::vector<std::shared_ptr<Base> >
227			data_x; //!< The temporary data associated with the state variation.
228			std::vector<std::shared_ptr<Base> >
229			data_u; //!< The temporary data associated with the control variation.
230			};
231
232			} // namespace crocoddyl
233
234			/* --- Details -------------------------------------------------------------- */
235			/* --- Details -------------------------------------------------------------- */
236			/* --- Details -------------------------------------------------------------- */
237			#include "crocoddyl/core/numdiff/cost.hxx"
238
239			#endif // CROCODDYL_CORE_NUMDIFF_COST_HPP_
240