function [cov, covf] = gpcovar(net, x)%GPCOVAR Calculate the covariance for a Gaussian Process.%%	Description%%	COV = GPCOVAR(NET, X) takes  a Gaussian Process data structure NET%	together with a matrix X of input vectors, and computes the%	covariance matrix COV.  The inverse of this matrix is used when%	calculating the mean and variance of the predictions made by NET.%%	[COV, COVF] = GPCOVAR(NET, X) also generates the covariance matrix%	due to the covariance function specified by NET.COVARFN as calculated%	by GPCOVARF.%%	See also%	GP, GPPAK, GPUNPAK, GPCOVARP, GPCOVARF, GPFWD, GPERR, GPGRAD%%	Copyright (c) Ian T Nabney (1996-2001)% Check arguments for consistencyerrstring = consist(net, 'gp', x);if ~isempty(errstring);  error(errstring);endndata = size(x, 1);% Compute prior covarianceif nargout >= 2  [covp, covf] = gpcovarp(net, x, x);else  covp = gpcovarp(net, x, x);end% Add output noise variancecov = covp + (net.min_noise + exp(net.noise))*eye(ndata);