ExponentialCovariance.h

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//* This file is part of the MOOSE framework
//* https://mooseframework.inl.gov
//*
//* All rights reserved, see COPYRIGHT for full restrictions
//* https://github.com/idaholab/moose/blob/master/COPYRIGHT
//*
//* Licensed under LGPL 2.1, please see LICENSE for details
//* https://www.gnu.org/licenses/lgpl-2.1.html

#pragma once

#include "CovarianceFunctionBase.h"

class ExponentialCovariance : public CovarianceFunctionBase
{
public:
  static InputParameters validParams();
  ExponentialCovariance(const InputParameters & parameters);

  void computeCovarianceMatrix(RealEigenMatrix & K,
                               const RealEigenMatrix & x,
                               const RealEigenMatrix & xp,
                               const bool is_self_covariance) const override;

  static void ExponentialFunction(RealEigenMatrix & K,
                                  const RealEigenMatrix & x,
                                  const RealEigenMatrix & xp,
                                  const std::vector<Real> & length_factor,
                                  const Real sigma_f_squared,
                                  const Real sigma_n_squared,
                                  const Real gamma,
                                  const bool is_self_covariance);

  bool computedKdhyper(RealEigenMatrix & dKdhp,
                       const RealEigenMatrix & x,
                       const std::string & hyper_param_name,
                       unsigned int ind) const override;

  static void computedKdlf(RealEigenMatrix & K,
                           const RealEigenMatrix & x,
                           const std::vector<Real> & length_factor,
                           const Real sigma_f_squared,
                           const Real gamma,
                           const int ind);

private:
  const std::vector<Real> & _length_factor;

  const Real & _sigma_f_squared;

  const Real & _sigma_n_squared;

  const Real & _gamma;
};