smooth-1norm.hpp

 
// 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 {
 
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;
 
  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() {};
 
  virtual void calc(const std::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_) + ")");
    }
    std::shared_ptr<Data> d = std::static_pointer_cast<Data>(data);
 
    d->a = (r.array().cwiseAbs2().array() + eps_).array().cwiseSqrt();
    data->a_value = d->a.sum();
  };
 
  virtual void calcDiff(const std::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_) + ")");
    }
 
    std::shared_ptr<Data> d = std::static_pointer_cast<Data>(data);
    data->Ar = r.cwiseProduct(d->a.cwiseInverse());
    data->Arr.diagonal() =
        d->a.cwiseProduct(d->a).cwiseProduct(d->a).cwiseInverse();
  };
 
  virtual std::shared_ptr<ActivationDataAbstract> createData() {
    return std::allocate_shared<Data>(Eigen::aligned_allocator<Data>(), this);
  };
 
  virtual void print(std::ostream& os) const {
    os << "ActivationModelSmooth1Norm {nr=" << nr_ << ", eps=" << eps_ << "}";
  }
 
 protected:
  using Base::nr_;  
  Scalar eps_;      
};
 
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_