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SquaredExponentialKernel Class Reference

Stationary kernel with C^ smooth realizations. More...

Inheritance diagram for SquaredExponentialKernel:
Kernel

Public Member Functions

void compute_gram (const std::vector< MatrixXd > &dists2, const VectorXd &theta_values, MatrixXd &gram) override
 Compute a Gram matrix given a vector of squared distances and kernel hyperparameters. More...
 
void compute_gram_derivs (const MatrixXd &gram, const std::vector< MatrixXd > &dists2, const VectorXd &theta_values, std::vector< MatrixXd > &gram_derivs) override
 Compute the derivatives of the Gram matrix with respect to the kernel hyperparameters. More...
 
MatrixXd compute_first_deriv_pred_gram (const MatrixXd &pred_gram, const std::vector< MatrixXd > &mixed_dists, const VectorXd &theta_values, const int index) override
 Compute the first derivatve of the prediction matrix for a given component. More...
 
MatrixXd compute_second_deriv_pred_gram (const MatrixXd &pred_gram, const std::vector< MatrixXd > &mixed_dists, const VectorXd &theta_values, const int index_i, const int index_j) override
 Compute the second derivatve of the prediction matrix for a pair of components. More...
 

Additional Inherited Members

- Protected Member Functions inherited from Kernel
void compute_Dbar (const std::vector< MatrixXd > &cw_dists2, const VectorXd &theta_values, bool take_sqrt=true)
 Compute the ``Dbar'' matrices of scaled distances. More...
 
- Protected Attributes inherited from Kernel
MatrixXd Dbar
 
MatrixXd Dbar2
 

Detailed Description

Stationary kernel with C^ smooth realizations.

Member Function Documentation

void compute_gram ( const std::vector< MatrixXd > &  dists2,
const VectorXd theta_values,
MatrixXd gram 
)
overridevirtual

Compute a Gram matrix given a vector of squared distances and kernel hyperparameters.

Parameters
[in]dists2Vector of squared distance matrices.
[in]theta_valuesVector of hyperparameters.
[in,out]gramGram matrix.
Returns
Gram matrix.

Implements Kernel.

References Kernel::compute_Dbar().

void compute_gram_derivs ( const MatrixXd gram,
const std::vector< MatrixXd > &  dists2,
const VectorXd theta_values,
std::vector< MatrixXd > &  gram_derivs 
)
overridevirtual

Compute the derivatives of the Gram matrix with respect to the kernel hyperparameters.

Parameters
[in]gramGram Matrix
[in]dists2Vector of squared distance matrices.
[in]theta_valuesVector of hyperparameters.
[in,out]gram_derivsVector of Gram matrix derivatives.
Returns
Derivatives of the Gram matrix w.r.t. the hyperparameters.

Implements Kernel.

MatrixXd compute_first_deriv_pred_gram ( const MatrixXd pred_gram,
const std::vector< MatrixXd > &  mixed_dists,
const VectorXd theta_values,
const int  index 
)
overridevirtual

Compute the first derivatve of the prediction matrix for a given component.

Parameters
[in]pred_gramPrediction Gram matrix - Rectangular matrix of kernel evaluations between the surrogate and prediction points.
[in]mixed_distsComponent-wise signed distances between the prediction and build points.
[in]theta_valuesVector of hyperparameters.
[in]indexSpecifies the component of the derivative.
Returns
first_deriv_pred_gram First derivative of the prediction Gram matrix for a given component.

Implements Kernel.

MatrixXd compute_second_deriv_pred_gram ( const MatrixXd pred_gram,
const std::vector< MatrixXd > &  mixed_dists,
const VectorXd theta_values,
const int  index_i,
const int  index_j 
)
overridevirtual

Compute the second derivatve of the prediction matrix for a pair of components.

Parameters
[in]pred_gramPrediction Gram matrix - Rectangular matrix of kernel evaluations between the surrogate and prediction points.
[in]mixed_distsComponent-wise signed distances between the prediction and build points.
[in]theta_valuesVector of hyperparameters.
[in]index_iSpecifies the first component of the second derivative.
[in]index_jSpecifies the second component of the second derivative.
Returns
second_deriv_pred_gram Second derivative of the prediction matrix for a pair of components.

Implements Kernel.


The documentation for this class was generated from the following files: