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); }