matthiasm@8: function T = convert_to_table(CPD, domain, evidence)
matthiasm@8: % CONVERT_TO_TABLE Convert a softmax CPD to a table, incorporating any evidence 
matthiasm@8: % T = convert_to_table(CPD, domain, evidence)
matthiasm@8: 
matthiasm@8: self       = domain(end);             
matthiasm@8: ps         = domain(1:end-1);                            
matthiasm@8: cnodes     = domain(CPD.cpndx);
matthiasm@8: cps        = myintersect(ps, cnodes);
matthiasm@8: dps        = domain(CPD.dpndx); 
matthiasm@8: dps_as_cps = domain(CPD.dps_as_cps.ndx);
matthiasm@8: all_dps    = union(dps,dps_as_cps);
matthiasm@8: odom       = domain(~isemptycell(evidence(domain))); 
matthiasm@8: if ~isempty(cps), assert(myismember(cps, odom)); end % all cts parents must be observed
matthiasm@8: 
matthiasm@8: ns         = zeros(1, max(domain));
matthiasm@8: ns(domain) = CPD.sizes;
matthiasm@8: ens        = ns; % effective node sizes
matthiasm@8: ens(odom)  = 1;
matthiasm@8: 
matthiasm@8: % dpsize >= glimsz because the glm parameters are tied across the dps_as_cps parents
matthiasm@8: dpsize       = prod(ens(all_dps)); % size of ALL self'discrete parents
matthiasm@8: dpvals       = cat(1, evidence{myintersect(all_dps, odom)});
matthiasm@8: cpvals       = cat(1, evidence{cps});
matthiasm@8: if ~isempty(dps_as_cps),
matthiasm@8:   separator          = CPD.dps_as_cps.separator;
matthiasm@8:   dp_as_cpmap        = find_equiv_posns(dps_as_cps, all_dps);
matthiasm@8:   dops_map           = find_equiv_posns(myintersect(all_dps, odom), all_dps);
matthiasm@8:   puredp_map         = find_equiv_posns(dps, all_dps);
matthiasm@8:   subs               = ind2subv(ens(all_dps), 1:prod(ens(all_dps)));
matthiasm@8:   if ~isempty(dops_map), subs(:,dops_map) = subs(:,dops_map)+repmat(dpvals(:)',[size(subs,1) 1])-1; end
matthiasm@8: end
matthiasm@8: 
matthiasm@8: [w,b] = extract_params(CPD);
matthiasm@8: T = zeros(dpsize, ns(self));                                       
matthiasm@8: for i=1:dpsize,    
matthiasm@8:   active_glm  = i;
matthiasm@8:   dp_as_cpvals=zeros(1,sum(ns(dps_as_cps)));                                                                  
matthiasm@8:   if ~isempty(dps_as_cps),                          
matthiasm@8:     active_glm = max([1,subv2ind(ns(dps), subs(i,puredp_map))]);
matthiasm@8:     % Extract the params compatible with the observations (if any) on the 'pure' discrete parents (if any)
matthiasm@8:     where_one = separator + subs(i,dp_as_cpmap);
matthiasm@8:     % and get in the dp_as_cp parents...
matthiasm@8:     dp_as_cpvals(where_one)=1;                    
matthiasm@8:   end                                               
matthiasm@8:   T(i,:) = normalise(exp([dp_as_cpvals(:); cpvals(:)]'*w(:,:,active_glm) + b(:,active_glm)'));
matthiasm@8: end
matthiasm@8: if myismember(self, odom)
matthiasm@8:   r = evidence{self};
matthiasm@8:   T = T(:,r);
matthiasm@8: end
matthiasm@8: 
matthiasm@8: T = myreshape(T, ens(domain));