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SquaredExponentialCovariance.h
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9 
10 #pragma once
11 
12 #include "CovarianceFunctionBase.h"
13 
15 {
16 public:
19 
22  const RealEigenMatrix & x,
23  const RealEigenMatrix & xp,
24  const bool is_self_covariance) const override;
25 
27  const RealEigenMatrix & x,
28  const RealEigenMatrix & xp,
29  const std::vector<Real> & length_factor,
30  const Real sigma_f_squared,
31  const Real sigma_n_squared,
32  const bool is_self_covariance);
33 
35  bool computedKdhyper(RealEigenMatrix & dKdhp,
36  const RealEigenMatrix & x,
37  const std::string & hyper_param_name,
38  unsigned int ind) const override;
39 
41  static void computedKdlf(RealEigenMatrix & K,
42  const RealEigenMatrix & x,
43  const std::vector<Real> & length_factor,
44  const Real sigma_f_squared,
45  const int ind);
46 
47 protected:
49  const std::vector<Real> & _length_factor;
50 
53 
56 };
const std::vector< Real > & _length_factor
lengh factor () for the kernel, in vector form for multiple parameters
SquaredExponentialCovariance(const InputParameters &parameters)
static const std::string K
Definition: NS.h:170
static void computedKdlf(RealEigenMatrix &K, const RealEigenMatrix &x, const std::vector< Real > &length_factor, const Real sigma_f_squared, const int ind)
Computes dK/dlf for individual length factors.
Base class for covariance functions that are used in Gaussian Processes.
void computeCovarianceMatrix(RealEigenMatrix &K, const RealEigenMatrix &x, const RealEigenMatrix &xp, const bool is_self_covariance) const override
Generates the Covariance Matrix given two points in the parameter space.
const Real & _sigma_f_squared
signal variance (^2)
const std::vector< double > x
const Real & _sigma_n_squared
noise variance (^2)
Eigen::Matrix< Real, Eigen::Dynamic, Eigen::Dynamic > RealEigenMatrix
bool computedKdhyper(RealEigenMatrix &dKdhp, const RealEigenMatrix &x, const std::string &hyper_param_name, unsigned int ind) const override
Redirect dK/dhp for hyperparameter "hp".
DIE A HORRIBLE DEATH HERE typedef LIBMESH_DEFAULT_SCALAR_TYPE Real
const InputParameters & parameters() const
static void SquaredExponentialFunction(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 bool is_self_covariance)