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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 consistency
errstring = consist(net, 'gp', x);
if ~isempty(errstring);
error(errstring);
end
ndata = size(x, 1);
% Compute prior covariance
if nargout >= 2
[covp, covf] = gpcovarp(net, x, x);
else
covp = gpcovarp(net, x, x);
end
% Add output noise variance
cov = covp + (net.min_noise + exp(net.noise))*eye(ndata);
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