matthiasm@8: function pot = linear_gaussian_to_cpot(mu, Sigma, W, domain, ns, cnodes, evidence)
matthiasm@8: % LINEAR_GAUSSIAN_TO_CPOT Convert a linear Gaussian CPD  to a canonical potential.
matthiasm@8: % pot = linear_gaussian_to_cpot(mu, Sigma, W, domain, ns, cnodes, evidence)
matthiasm@8: %
matthiasm@8: % We include any cts evidence, but ignore any discrete evidence.
matthiasm@8: % (Use gaussian_CPD_params_given_dps to use discrete evidence to select mu, Sigma, W.)
matthiasm@8: 
matthiasm@8: odom = domain(~isemptycell(evidence(domain)));
matthiasm@8: hdom = domain(isemptycell(evidence(domain)));
matthiasm@8: cobs = myintersect(cnodes, odom);
matthiasm@8: chid = myintersect(cnodes, hdom);
matthiasm@8: cvals = cat(1, evidence{cobs});
matthiasm@8: 
matthiasm@8: %[g,h,K] = gaussian_to_canonical(mu, Sigma, W);
matthiasm@8: Sinv = inv(Sigma);
matthiasm@8: g = -0.5*mu'*Sinv*mu + log(normal_coef(Sigma));
matthiasm@8: if isempty(W) | (size(W,2)==0)  % no cts parents
matthiasm@8:   h = Sinv*mu;
matthiasm@8:   K = Sinv;
matthiasm@8: else
matthiasm@8:   h = [-W'*Sinv*mu; Sinv*mu];
matthiasm@8:   K = [W'*Sinv*W  -W'*Sinv';
matthiasm@8:        -Sinv*W     Sinv]; 
matthiasm@8: end
matthiasm@8: 
matthiasm@8: if ~isempty(cvals)
matthiasm@8:   %[g, h, K] = enter_evidence_canonical(g, h, K, chid, cobs, cvals(:), ns);  
matthiasm@8:   [hx, hy, KXX, KXY, KYX, KYY] = partition_matrix_vec(h, K, chid, cobs, ns);
matthiasm@8:   y = cvals(:);
matthiasm@8:   g = g + hy'*y - 0.5*y'*KYY*y;
matthiasm@8:   if length(hx)==0 % isempty(X) % i.e., we have instantiated everything away
matthiasm@8:     h = [];
matthiasm@8:     K = [];
matthiasm@8:   else
matthiasm@8:     h = hx - KXY*y;
matthiasm@8:     K = KXX;
matthiasm@8:   end
matthiasm@8: end
matthiasm@8: 
matthiasm@8: ns(odom) = 0;
matthiasm@8: pot = cpot(domain, ns(domain), g, h, K);
matthiasm@8: 
matthiasm@8: