construct_predmat.m

The BNL toolbox is a set of Matlab functions for defining and estimating the parameters of a Bayesi

function pred_mat=construct_predmat(equiv_class,evidence_nodes,partial_evidence_nodes,terminal_merged_nodes,hid_nodes,gausskwadnodes)
pred_mat=cell(max(equiv_class),1);
for i=1:length(pred_mat)
    node_nr=find(equiv_class==i,1);
    if mysubset(node_nr, evidence_nodes.nodenrs) 
        error('evidence nodes not yet incorporated, treat them as partial evidence nodes');
        %termnr=find(evidence_nodes.nodenrs==node_nr);
        %des = eye(evidence_nodes.respcat(termnr)-1);
    elseif mysubset(node_nr, partial_evidence_nodes.nodenrs) 
        termnr=find(partial_evidence_nodes.nodenrs==node_nr);
        des = eye(partial_evidence_nodes.nodesizes(termnr)-1);
    elseif mysubset(node_nr, hid_nodes.nodenrs) 
        termnr=find(hid_nodes.nodenrs==node_nr);
        des = eye(hid_nodes.nodesizes(termnr)-1);
    elseif mysubset(node_nr, gausskwadnodes.nodenrs) 
        termnr=find(gausskwadnodes.nodenrs==node_nr);
        des = eye(gausskwadnodes.nodesizes(termnr)-1);
        
        
    else
        termnr=find(terminal_merged_nodes.nodenrs==node_nr);
        des=eye(sum(terminal_merged_nodes.respcat{termnr}-1));
        
    end
    pred_mat{i}=des;
end