wolffd@0: function gdl = bnet_to_gdl_graph(bnet)
wolffd@0: % BNET_TO_GDL_GRAPH Convert a Bayesian network to a GDL graph
wolffd@0: % gdl = bnet_to_gdl_graph(bnet)
wolffd@0: %
wolffd@0: % Each node in the BN gets converted to a single node in the GDL graph,
wolffd@0: % representing its family; its kernel function is the corresponding CPD.
wolffd@0: 
wolffd@0: N = length(bnet.dag);
wolffd@0: doms = cell(1,N);
wolffd@0: for i=1:N
wolffd@0:   doms{i} = family(bnet.dag, i);
wolffd@0: end
wolffd@0: 
wolffd@0: U = mk_undirected(bnet.dag);
wolffd@0: gdl = mk_gdl_graph(U, doms, bnet.node_sizes, bnet.CPD, 'equiv_class', bnet.equiv_class, ...
wolffd@0: 		   'discrete', bnet.dnodes, 'chance', bnet.chance_nodes, ...
wolffd@0: 		   'decision', bnet.decision_nodes, 'utility', bnet.utility_nodes);
wolffd@0: