Daniel@0: function CPD = update_ess(CPD, fmarginal, evidence, ns, cnodes, hidden_bitv)
Daniel@0: % UPDATE_ESS Update the Expected Sufficient Statistics of a hhmmF node.
Daniel@0: % function CPD = update_ess(CPD, fmarginal, evidence, ns, cnodes, hidden_bitv)
Daniel@0: %
Daniel@0: % We assume the F nodes are always hidden
Daniel@0: 
Daniel@0: % Figure out the node numbers associated with each parent
Daniel@0: dom = fmarginal.domain;
Daniel@0: %Fself = dom(end); 
Daniel@0: %Fbelow = dom(CPD.Fbelow_ndx);
Daniel@0: Qself = dom(CPD.Qself_ndx);
Daniel@0: Qps = dom(CPD.Qps_ndx);
Daniel@0: 
Daniel@0: Qsz = CPD.Qsz;
Daniel@0: Qpsz = CPD.Qpsz;
Daniel@0: 
Daniel@0: if all(hidden_bitv(Qps)) % we assume all are hidden or all are observed
Daniel@0:   k_ndx = 1:Qpsz;
Daniel@0:   eff_Qpsz = Qpsz;
Daniel@0: else
Daniel@0:   k_ndx = subv2ind(Qpsz, cat(1, evidence{Qps}));
Daniel@0:   eff_Qpsz = 1;
Daniel@0: end
Daniel@0: 
Daniel@0: if hidden_bitv(Qself)
Daniel@0:   j_ndx = 1:Qsz;
Daniel@0:   eff_Qsz = Qsz;
Daniel@0: else
Daniel@0:   j_ndx = evidence{Qself};
Daniel@0:   eff_Qsz = 1;
Daniel@0: end
Daniel@0: 
Daniel@0: % Fmarginal(Qps, Q, Fbelow, F)
Daniel@0: fmarg = myreshape(fmarginal.T, [eff_Qpsz eff_Qsz  2 2]);
Daniel@0: 
Daniel@0: counts = zeros(Qpsz, Qsz, 2);
Daniel@0: %counts(k_ndx, j_ndx, :) = sum(fmarginal.T(:, :, :, :), 3); % sum over Fbelow
Daniel@0: counts(k_ndx, j_ndx, :) = fmarg(:, :, 2, :); % Fbelow = 2
Daniel@0: 
Daniel@0: CPD.sub_CPD_term = update_ess_simple(CPD.sub_CPD_term, counts);