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GCC Code Coverage Report

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File:	include/crocoddyl/core/activations/smooth-1norm.hpp	Lines:	26	33	78.8 %
Date:	2024-02-13 11:12:33	Branches:	22	90	24.4 %


///////////////////////////////////////////////////////////////////////////////
// BSD 3-Clause License
//
// Copyright (C) 2019-2020, LAAS-CNRS, University of Edinburgh
// Copyright note valid unless otherwise stated in individual files.
// All rights reserved.
///////////////////////////////////////////////////////////////////////////////

#ifndef CROCODDYL_CORE_ACTIVATIONS_SMOOTH_1NORM_HPP_
#define CROCODDYL_CORE_ACTIVATIONS_SMOOTH_1NORM_HPP_

#include <iostream>
#include <stdexcept>

#include "crocoddyl/core/activation-base.hpp"
#include "crocoddyl/core/fwd.hpp"
#include "crocoddyl/core/utils/exception.hpp"

namespace crocoddyl {

/**
 * @brief Smooth-abs activation
 *
 * This activation function describes a smooth representation of an absolute
 * activation (1-norm) for each element of a residual vector, i.e. \f[
 * \begin{equation} sum^nr_{i=0} \sqrt{\epsilon + \|r_i\|^2} \end{equation} \f]
 * where \f$\epsilon\f$ defines the smoothing factor, \f$r_i\f$ is the scalar
 * residual for the \f$i\f$ constraints, \f$nr\f$ is the dimension of the
 * residual vector.
 *
 * The computation of the function and it derivatives are carried out in
 * `calc()` and `caldDiff()`, respectively.
 *
 * \sa `calc()`, `calcDiff()`, `createData()`
 */
template <typename _Scalar>
class ActivationModelSmooth1NormTpl
    : public ActivationModelAbstractTpl<_Scalar> {
 public:
  EIGEN_MAKE_ALIGNED_OPERATOR_NEW

  typedef _Scalar Scalar;
  typedef MathBaseTpl<Scalar> MathBase;
  typedef ActivationModelAbstractTpl<Scalar> Base;
  typedef ActivationDataAbstractTpl<Scalar> ActivationDataAbstract;
  typedef ActivationDataSmooth1NormTpl<Scalar> Data;
  typedef typename MathBase::VectorXs VectorXs;
  typedef typename MathBase::MatrixXs MatrixXs;

  /**
   * @brief Initialize the smooth-abs activation model
   *
   * The default `eps` value is defined as 1.
   *
   * @param[in] nr   Dimension of the residual vector
   * @param[in] eps  Smoothing factor (default: 1.)
   */
  explicit ActivationModelSmooth1NormTpl(const std::size_t nr,
                                         const Scalar eps = Scalar(1.))
      : Base(nr), eps_(eps) {
    if (eps < Scalar(0.)) {
      throw_pretty("Invalid argument: "
                   << "eps should be a positive value");
    }
    if (eps == Scalar(0.)) {
      std::cerr << "Warning: eps=0 leads to derivatives discontinuities in the "
                   "origin, it becomes the absolute function"
                << std::endl;
    }
  };
  virtual ~ActivationModelSmooth1NormTpl(){};

  /**
   * @brief Compute the smooth-abs function
   *
   * @param[in] data  Smooth-abs activation data
   * @param[in] r     Residual vector \f$\mathbf{r}\in\mathbb{R}^{nr}\f$
   */
  virtual void calc(const boost::shared_ptr<ActivationDataAbstract>& data,
                    const Eigen::Ref<const VectorXs>& r) {
    if (static_cast<std::size_t>(r.size()) != nr_) {
      throw_pretty("Invalid argument: "
                   << "r has wrong dimension (it should be " +
                          std::to_string(nr_) + ")");
    }
    boost::shared_ptr<Data> d = boost::static_pointer_cast<Data>(data);

    d->a = (r.array().cwiseAbs2().array() + eps_).array().cwiseSqrt();
    data->a_value = d->a.sum();
  };

  /**
   * @brief Compute the derivatives of the smooth-abs function
   *
   * @param[in] data  Smooth-abs activation data
   * @param[in] r     Residual vector \f$\mathbf{r}\in\mathbb{R}^{nr}\f$
   */
  virtual void calcDiff(const boost::shared_ptr<ActivationDataAbstract>& data,
                        const Eigen::Ref<const VectorXs>& r) {
    if (static_cast<std::size_t>(r.size()) != nr_) {
      throw_pretty("Invalid argument: "
                   << "r has wrong dimension (it should be " +
                          std::to_string(nr_) + ")");
    }

    boost::shared_ptr<Data> d = boost::static_pointer_cast<Data>(data);
    data->Ar = r.cwiseProduct(d->a.cwiseInverse());
    data->Arr.diagonal() =
        d->a.cwiseProduct(d->a).cwiseProduct(d->a).cwiseInverse();
  };

  /**
   * @brief Create the smooth-abs activation data
   *
   * @return the activation data
   */
  virtual boost::shared_ptr<ActivationDataAbstract> createData() {
    return boost::allocate_shared<Data>(Eigen::aligned_allocator<Data>(), this);
  };

  /**
   * @brief Print relevant information of the smooth-1norm model
   *
   * @param[out] os  Output stream object
   */
  virtual void print(std::ostream& os) const {
    os << "ActivationModelSmooth1Norm {nr=" << nr_ << ", eps=" << eps_ << "}";
  }

 protected:
  using Base::nr_;  //!< Dimension of the residual vector
  Scalar eps_;      //!< Smoothing factor
};

template <typename _Scalar>
struct ActivationDataSmooth1NormTpl
    : public ActivationDataAbstractTpl<_Scalar> {
  EIGEN_MAKE_ALIGNED_OPERATOR_NEW

  typedef _Scalar Scalar;
  typedef ActivationDataAbstractTpl<Scalar> Base;
  typedef MathBaseTpl<Scalar> MathBase;
  typedef typename MathBase::VectorXs VectorXs;
  typedef typename MathBase::MatrixXs MatrixXs;

  template <typename Activation>
  explicit ActivationDataSmooth1NormTpl(Activation* const activation)
      : Base(activation), a(VectorXs::Zero(activation->get_nr())) {}

  VectorXs a;
  using Base::Arr;
};

}  // namespace crocoddyl

#endif  // CROCODDYL_CORE_ACTIVATIONS_SMOOTH_1NORM_HPP_


Generated by: GCOVR (Version 4.2)

Line	Branch	Exec	Source
1			///////////////////////////////////////////////////////////////////////////////
2			// BSD 3-Clause License
3			//
4			// Copyright (C) 2019-2020, LAAS-CNRS, University of Edinburgh
5			// Copyright note valid unless otherwise stated in individual files.
6			// All rights reserved.
7			///////////////////////////////////////////////////////////////////////////////
8
9			#ifndef CROCODDYL_CORE_ACTIVATIONS_SMOOTH_1NORM_HPP_
10			#define CROCODDYL_CORE_ACTIVATIONS_SMOOTH_1NORM_HPP_
11
12			#include <iostream>
13			#include <stdexcept>
14
15			#include "crocoddyl/core/activation-base.hpp"
16			#include "crocoddyl/core/fwd.hpp"
17			#include "crocoddyl/core/utils/exception.hpp"
18
19			namespace crocoddyl {
20
21			/**
22			* @brief Smooth-abs activation
23			*
24			* This activation function describes a smooth representation of an absolute
25			* activation (1-norm) for each element of a residual vector, i.e. \f[
26			* \begin{equation} sum^nr_{i=0} \sqrt{\epsilon + \\|r_i\\|^2} \end{equation} \f]
27			* where \f$\epsilon\f$ defines the smoothing factor, \f$r_i\f$ is the scalar
28			* residual for the \f$i\f$ constraints, \f$nr\f$ is the dimension of the
29			* residual vector.
30			*
31			* The computation of the function and it derivatives are carried out in
32			* `calc()` and `caldDiff()`, respectively.
33			*
34			* \sa `calc()`, `calcDiff()`, `createData()`
35			*/
36			template <typename _Scalar>
37			class ActivationModelSmooth1NormTpl
38			: public ActivationModelAbstractTpl<_Scalar> {
39			public:
40			EIGEN_MAKE_ALIGNED_OPERATOR_NEW
41
42			typedef _Scalar Scalar;
43			typedef MathBaseTpl<Scalar> MathBase;
44			typedef ActivationModelAbstractTpl<Scalar> Base;
45			typedef ActivationDataAbstractTpl<Scalar> ActivationDataAbstract;
46			typedef ActivationDataSmooth1NormTpl<Scalar> Data;
47			typedef typename MathBase::VectorXs VectorXs;
48			typedef typename MathBase::MatrixXs MatrixXs;
49
50			/**
51			* @brief Initialize the smooth-abs activation model
52			*
53			* The default `eps` value is defined as 1.
54			*
55			* @param[in] nr Dimension of the residual vector
56			* @param[in] eps Smoothing factor (default: 1.)
57			*/
58		223	explicit ActivationModelSmooth1NormTpl(const std::size_t nr,
59			const Scalar eps = Scalar(1.))
60		223	: Base(nr), eps_(eps) {
61	✗✓	223	if (eps < Scalar(0.)) {
62			throw_pretty("Invalid argument: "
63			<< "eps should be a positive value");
64			}
65	✗✓	223	if (eps == Scalar(0.)) {
66			std::cerr << "Warning: eps=0 leads to derivatives discontinuities in the "
67			"origin, it becomes the absolute function"
68			<< std::endl;
69			}
70		223	};
71		450	virtual ~ActivationModelSmooth1NormTpl(){};
72
73			/**
74			* @brief Compute the smooth-abs function
75			*
76			* @param[in] data Smooth-abs activation data
77			* @param[in] r Residual vector \f$\mathbf{r}\in\mathbb{R}^{nr}\f$
78			*/
79		9675	virtual void calc(const boost::shared_ptr<ActivationDataAbstract>& data,
80			const Eigen::Ref<const VectorXs>& r) {
81	✓✗✗✓	9675	if (static_cast<std::size_t>(r.size()) != nr_) {
82			throw_pretty("Invalid argument: "
83			<< "r has wrong dimension (it should be " +
84			std::to_string(nr_) + ")");
85			}
86		9675	boost::shared_ptr<Data> d = boost::static_pointer_cast<Data>(data);
87
88	✓✗✓✗ ✓✗✓✗ ✓✗	9675	d->a = (r.array().cwiseAbs2().array() + eps_).array().cwiseSqrt();
89	✓✗	9675	data->a_value = d->a.sum();
90		9675	};
91
92			/**
93			* @brief Compute the derivatives of the smooth-abs function
94			*
95			* @param[in] data Smooth-abs activation data
96			* @param[in] r Residual vector \f$\mathbf{r}\in\mathbb{R}^{nr}\f$
97			*/
98		304	virtual void calcDiff(const boost::shared_ptr<ActivationDataAbstract>& data,
99			const Eigen::Ref<const VectorXs>& r) {
100	✓✗✗✓	304	if (static_cast<std::size_t>(r.size()) != nr_) {
101			throw_pretty("Invalid argument: "
102			<< "r has wrong dimension (it should be " +
103			std::to_string(nr_) + ")");
104			}
105
106		304	boost::shared_ptr<Data> d = boost::static_pointer_cast<Data>(data);
107	✓✗✓✗ ✓✗	304	data->Ar = r.cwiseProduct(d->a.cwiseInverse());
108	✓✗✓✗	304	data->Arr.diagonal() =
109	✓✗✓✗	304	d->a.cwiseProduct(d->a).cwiseProduct(d->a).cwiseInverse();
110		304	};
111
112			/**
113			* @brief Create the smooth-abs activation data
114			*
115			* @return the activation data
116			*/
117		7837	virtual boost::shared_ptr<ActivationDataAbstract> createData() {
118	✓✗	7837	return boost::allocate_shared<Data>(Eigen::aligned_allocator<Data>(), this);
119			};
120
121			/**
122			* @brief Print relevant information of the smooth-1norm model
123			*
124			* @param[out] os Output stream object
125			*/
126		37	virtual void print(std::ostream& os) const {
127		37	os << "ActivationModelSmooth1Norm {nr=" << nr_ << ", eps=" << eps_ << "}";
128		37	}
129
130			protected:
131			using Base::nr_; //!< Dimension of the residual vector
132			Scalar eps_; //!< Smoothing factor
133			};
134
135			template <typename _Scalar>
136			struct ActivationDataSmooth1NormTpl
137			: public ActivationDataAbstractTpl<_Scalar> {
138			EIGEN_MAKE_ALIGNED_OPERATOR_NEW
139
140			typedef _Scalar Scalar;
141			typedef ActivationDataAbstractTpl<Scalar> Base;
142			typedef MathBaseTpl<Scalar> MathBase;
143			typedef typename MathBase::VectorXs VectorXs;
144			typedef typename MathBase::MatrixXs MatrixXs;
145
146			template <typename Activation>
147		7837	explicit ActivationDataSmooth1NormTpl(Activation* const activation)
148	✓✗✓✗	7837	: Base(activation), a(VectorXs::Zero(activation->get_nr())) {}
149
150			VectorXs a;
151			using Base::Arr;
152			};
153
154			} // namespace crocoddyl
155
156			#endif // CROCODDYL_CORE_ACTIVATIONS_SMOOTH_1NORM_HPP_