wolffd@0: function fullm = add_evidence_to_gmarginal(fmarginal, evidence, ns, cnodes)
wolffd@0: % ADD_EVIDENCE_TO_GMARGINAL 'pump up' observed nodes back to their original size.
wolffd@0: % function fullm = add_evidence_to_gmarginal(fmarginal, evidence, ns, cnodes)
wolffd@0: %
wolffd@0: % We introduce 0s into the array in positions which are incompatible with the evidence.
wolffd@0: % for both discrete and continuous nodes.
wolffd@0: %
wolffd@0: % See also add_ev_to_dmarginal
wolffd@0: 
wolffd@0: dom = fmarginal.domain;
wolffd@0: fullm.domain = fmarginal.domain;
wolffd@0: 
wolffd@0: % Find out which values of the discrete parents (if any) are compatible with 
wolffd@0: % the discrete evidence (if any).
wolffd@0: dnodes = mysetdiff(1:length(ns), cnodes);
wolffd@0: ddom = myintersect(dom, dnodes);
wolffd@0: cdom = myintersect(dom, cnodes);
wolffd@0: odom = dom(~isemptycell(evidence(dom)));
wolffd@0: hdom = dom(isemptycell(evidence(dom)));
wolffd@0: 
wolffd@0: % Find the entries in the big table that are compatible with the discrete evidence.
wolffd@0: % (We will put the probabilities from the small inferred table into these positions.)
wolffd@0: % We could use add_ev_to_dmarginal to do this.
wolffd@0: dobs = myintersect(ddom, odom);
wolffd@0: dvals = cat(1, evidence{dobs});
wolffd@0: ens = ns; % effective node sizes
wolffd@0: ens(dobs) = 1;
wolffd@0: S = prod(ens(ddom));
wolffd@0: subs = ind2subv(ens(ddom), 1:S);
wolffd@0: mask = find_equiv_posns(dobs, ddom);
wolffd@0: %subs(mask) = dvals; % bug fix by P. Brutti
wolffd@0: for i=1:length(mask),
wolffd@0:   subs(:,mask(i)) = dvals(i);
wolffd@0: end       
wolffd@0: supportedQs = subv2ind(ns(ddom), subs);
wolffd@0: 
wolffd@0: if isempty(ddom)
wolffd@0:   Qarity = 1;
wolffd@0: else
wolffd@0:   Qarity = prod(ns(ddom));
wolffd@0: end
wolffd@0: fullm.T = zeros(Qarity, 1);
wolffd@0: fullm.T(supportedQs) = fmarginal.T(:);
wolffd@0: fullm.T = myreshape(fullm.T, ns(ddom));
wolffd@0: 
wolffd@0: 
wolffd@0: if isempty(cdom)
wolffd@0:   fullm.mu = [];
wolffd@0:   fullm.sigma = [];
wolffd@0:   return;
wolffd@0: end
wolffd@0: 
wolffd@0: % Now put the hidden cts parts into their right blocks,
wolffd@0: % leaving the observed cts parts as 0.
wolffd@0: cobs = myintersect(cdom, odom);
wolffd@0: chid = myintersect(cdom, hdom);
wolffd@0: cvals = cat(1, evidence{cobs});
wolffd@0: n = sum(ns(cdom));
wolffd@0: fullm.mu = zeros(n,Qarity);
wolffd@0: fullm.Sigma = zeros(n,n,Qarity);
wolffd@0: 
wolffd@0: if ~isempty(chid)
wolffd@0:   chid_blocks = block(find_equiv_posns(chid, cdom), ns(cdom));
wolffd@0: end
wolffd@0: if ~isempty(cobs)
wolffd@0:   cobs_blocks = block(find_equiv_posns(cobs, cdom), ns(cdom));
wolffd@0: end
wolffd@0: 
wolffd@0: for i=1:length(supportedQs)
wolffd@0:   Q = supportedQs(i);
wolffd@0:   if ~isempty(chid)
wolffd@0:     fullm.mu(chid_blocks, Q) = fmarginal.mu(:, i);
wolffd@0:     fullm.Sigma(chid_blocks, chid_blocks, Q) = fmarginal.Sigma(:,:,i);
wolffd@0:   end
wolffd@0:   if ~isempty(cobs)
wolffd@0:     fullm.mu(cobs_blocks, Q) = cvals(:);
wolffd@0:   end
wolffd@0: end