quadratic-flat-log.hpp

// BSD 3-Clause License
//
// Copyright (C) 2020-2025, LAAS-CNRS, University of Edinburgh,
// Heriot-Watt University
// Copyright note valid unless otherwise stated in individual files.
// All rights reserved.

#ifndef CROCODDYL_CORE_ACTIVATIONS_QUADRATIC_FLAT_LOG_HPP_
#define CROCODDYL_CORE_ACTIVATIONS_QUADRATIC_FLAT_LOG_HPP_

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

namespace crocoddyl {

template <typename _Scalar>
class ActivationModelQuadFlatLogTpl
 : public ActivationModelAbstractTpl<_Scalar> {
 public:
 EIGEN_MAKE_ALIGNED_OPERATOR_NEW
 CROCODDYL_DERIVED_CAST(ActivationModelBase, ActivationModelQuadFlatLogTpl)

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

 /*
 * @brief Initialize the quadratic-flat-log activation model
 *
 * The default `alpha` value is defined as 1.
 *
 * @param[in] nr Dimension of the residual vector
 * @param[in] alpha Width of quadratic basin (default: 1.)
 */

 explicit ActivationModelQuadFlatLogTpl(const std::size_t nr,
 const Scalar alpha = Scalar(1.))
 : Base(nr), alpha_(alpha) {
 if (alpha < Scalar(0.)) {
 throw_pretty("Invalid argument: " << "alpha should be a positive value");
 }
 };
 virtual ~ActivationModelQuadFlatLogTpl() = default;

 /*
 * @brief Compute the quadratic-flat-log function
 *
 * @param[in] data Quadratic-log activation data
 * @param[in] r Residual vector \f$\mathbf{r}\in\mathbb{R}^{nr}\f$
 */
 virtual void calc(const std::shared_ptr<ActivationDataAbstract>& data,
 const Eigen::Ref<const VectorXs>& r) override {
 if (static_cast<std::size_t>(r.size()) != nr_) {
 throw_pretty(
 "Invalid argument: " << "r has wrong dimension (it should be " +
 std::to_string(nr_) + ")");
 }
 std::shared_ptr<Data> d = std::static_pointer_cast<Data>(data);
 d->a0 = r.squaredNorm() / alpha_;
 data->a_value = log(Scalar(1.0) + d->a0);
 };

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

 d->a1 = Scalar(2.0) / (alpha_ + alpha_ * d->a0);
 data->Ar = d->a1 * r;
 data->Arr.diagonal() = -d->a1 * d->a1 * r.array().square();
 data->Arr.diagonal().array() += d->a1;
 };

 /*
 * @brief Create the quadratic-flat-log activation data
 *
 * @return the activation data
 */
 virtual std::shared_ptr<ActivationDataAbstract> createData() override {
 std::shared_ptr<Data> data =
 std::allocate_shared<Data>(Eigen::aligned_allocator<Data>(), this);
 return data;
 };

 template <typename NewScalar>
 ActivationModelQuadFlatLogTpl<NewScalar> cast() const {
 typedef ActivationModelQuadFlatLogTpl<NewScalar> ReturnType;
 ReturnType res(nr_, scalar_cast<NewScalar>(alpha_));
 return res;
 }

 Scalar get_alpha() const { return alpha_; };
 void set_alpha(const Scalar alpha) { alpha_ = alpha; };

 virtual void print(std::ostream& os) const override {
 os << "ActivationModelQuadFlatLog {nr=" << nr_ << ", a=" << alpha_ << "}";
 }

 protected:
 using Base::nr_;

 private:
 Scalar alpha_;
};

/*
 * @brief Data structure of the quadratic-flat-log activation
 *
 * @param[in] a0 computed in calc to avoid recomputation
 * @param[in] a1 computed in calcDiff to avoid recomputation
 */
template <typename _Scalar>
struct ActivationDataQuadFlatLogTpl
 : public ActivationDataAbstractTpl<_Scalar> {
 EIGEN_MAKE_ALIGNED_OPERATOR_NEW

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

 template <typename Activation>
 explicit ActivationDataQuadFlatLogTpl(Activation* const activation)
 : Base(activation), a0(Scalar(0)), a1(Scalar(0)) {}
 virtual ~ActivationDataQuadFlatLogTpl() = default;

 Scalar a0;
 Scalar a1;

 using Base::a_value;
 using Base::Ar;
 using Base::Arr;
};

} // namespace crocoddyl

CROCODDYL_DECLARE_EXTERN_TEMPLATE_CLASS(
 crocoddyl::ActivationModelQuadFlatLogTpl)
CROCODDYL_DECLARE_EXTERN_TEMPLATE_STRUCT(
 crocoddyl::ActivationDataQuadFlatLogTpl)

#endif // CROCODDYL_CORE_ACTIVATIONS_QUADRATIC_FLAT_LOG_HPP_