package agents.anac.y2015.Phoenix.GP;/* This file is part of the jgpml Project.
* http://github.com/renzodenardi/jgpml
*
* Copyright (c) 2011 Renzo De Nardi and Hugo Gravato-Marques
*
* Permission is hereby granted, free of charge, to any person
* obtaining a copy of this software and associated documentation
* files (the "Software"), to deal in the Software without
* restriction, including without limitation the rights to use,
* copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the
* Software is furnished to do so, subject to the following
* conditions:
*
* The above copyright notice and this permission notice shall be
* included in all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
* EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
* OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
* NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
* HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
* WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
* FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
* OTHER DEALINGS IN THE SOFTWARE.
*/
import agents.Jama.Matrix;
public interface CovarianceFunction {
/**
* Returns the number of hyperparameters of thisPhoenixAlpha.CovarianceFunction
* @return number of hyperparameters
*/
public int numParameters();
/**
* Compute covariance matrix of a dataset X
* @param loghyper column Matrix
of hyperparameters
* @param X input dataset
* @return K covariance Matrix
*/
public Matrix compute(Matrix loghyper, Matrix X);
/**
* Compute compute test set covariances
* @param loghyper column Matrix
of hyperparameters
* @param X input dataset
* @param Xstar test set
* @return [K(Xstar,Xstar) K(X,Xstar)]
*/
public Matrix[] compute(Matrix loghyper, Matrix X, Matrix Xstar);
/**
* Coompute the derivatives of this PhoenixAlpha.CovarianceFunction
with respect
* to the hyperparameter with index idx
*
* @param loghyper hyperparameters
* @param X input dataset
* @param index hyperparameter index
* @return Matrix
of derivatives
*/
public Matrix computeDerivatives(Matrix loghyper, Matrix X, int index);
}