function [G,Z] = repcov(M,N,g)

% REPCOV        Calculates the intermediate matrix computations for a
% covariance function.
%
% [G,Z] = REPCOV(M,N,g)
%
% This computes the nominal terms in a covariance function for,
%
%                   G = (zi-zj)'*D*(zi-zj)
%                   Z = (zdi-zdj).*(zdi-zdj)
%
% where D=diag{g1,g2,...,gd} is a diagonal matrix. Z = (zi-zj).^2 in 'd'
% sets for different lengthscales and G  computers the vector 
% multiplication of Z'DZ giving a matrix size of N0xN0xD0.
%
% Inputs:
%       M   = Input explanatory variable of dimension {n1 x d}
%       N   = Input explanatory variable of dimension {n2 x d}
%       p   = Hyperparameters, [a g1 g2 ... gd], D=diag{g1,g2,...,gd}
%
% Output:
%       G   = Resulting [Z.*Z]
%       Z   = Resulting [Z'*D*Z]
%
%
% (C) Gaussian Process Toolbox 1.0
% (C) Copyright 2005-2007, Keith Neo <keith.neo@nuim.ie>
%                          http://www.hamilton.ie

N0=size(M,1);
Nt=size(N,1);
Z=(repmat(permute(M,[1,3,2]),[1,Nt,1])-repmat(permute(N',[3,2 1]),[N0,1,1])).^2;
G=Z.*repmat(permute(g',[3,2,1]),[N0,Nt,1]);