wolffd@0: function engine = jtree_sparse_2TBN_inf_engine(bnet, varargin)
wolffd@0: % JTREE_ONLINE_INF_ENGINE Online Junction tree inference algorithm for DBNs.
wolffd@0: % engine = jtree_online_inf_engine(bnet, ...)
wolffd@0: %
wolffd@0: % The following optional arguments can be specified in the form of name/value pairs:
wolffd@0: % [default value in brackets]
wolffd@0: %
wolffd@0: % clusters - specifies variables that must be grouped in the 1.5 slice DBN
wolffd@0: % maximize - 1 means do max-product, 0 means sum-product [0]
wolffd@0: %
wolffd@0: % The same nodes must be observed in every slice.
wolffd@0: 
wolffd@0: ss = length(bnet.intra);
wolffd@0: clusters = {};
wolffd@0: engine.maximize = 0;
wolffd@0: 
wolffd@0: args = varargin;
wolffd@0: nargs = length(args);
wolffd@0: for i=1:2:length(args)
wolffd@0:   switch args{i},
wolffd@0:    case 'clusters', clusters = args{i+1};
wolffd@0:    case 'maximize', engine.maximize = args{i+1};
wolffd@0:    otherwise, error(['unrecognized argument ' args{i}])
wolffd@0:   end
wolffd@0: end
wolffd@0: 
wolffd@0: engine.evidence = [];
wolffd@0: engine.node_sizes = [];
wolffd@0: 
wolffd@0: int = [];
wolffd@0: % include nodes with any outgoing arcs
wolffd@0: for u=1:ss
wolffd@0:   if any(bnet.inter(u,:))
wolffd@0:     int = [int u];
wolffd@0:   end
wolffd@0: end
wolffd@0: 
wolffd@0: engine.interface = int;
wolffd@0: engine.nonint = mysetdiff(1:ss, int);
wolffd@0: 
wolffd@0: onodes = bnet.observed;
wolffd@0: 
wolffd@0: % Create a "1.5 slice" jtree, containing the interface nodes of slice 1
wolffd@0: % and all the nodes of slice 2
wolffd@0: % To keep the node numbering the same, we simply disconnect the non-interface nodes
wolffd@0: % from slice 1, and set their size to 1.
wolffd@0: % We do this to speed things up, and so that the likelihood is computed correctly - we do not need to do
wolffd@0: % this if we just want to compute marginals (i.e., we can include nodes whose potentials will
wolffd@0: % be left as all 1s).
wolffd@0: intra15 = bnet.intra;
wolffd@0: for i=engine.nonint(:)'
wolffd@0:   intra15(:,i) = 0;
wolffd@0:   intra15(i,:) = 0;
wolffd@0:   assert(~any(bnet.inter(i,:)))
wolffd@0: end
wolffd@0: dag15 = [intra15      bnet.inter;
wolffd@0: 	 zeros(ss)    bnet.intra];
wolffd@0: ns = bnet.node_sizes(:);
wolffd@0: ns(engine.nonint) = 1; % disconnected nodes get size 1
wolffd@0: obs_nodes = [onodes(:) onodes(:)+ss];
wolffd@0: bnet15 = mk_bnet(dag15, ns, 'discrete', bnet.dnodes, 'equiv_class', bnet.equiv_class(:), ...
wolffd@0: 		 'observed', obs_nodes(:));
wolffd@0: 
wolffd@0: % use unconstrained elimination,
wolffd@0: % but force there to be a clique containing both interfaces
wolffd@0: clusters(end+1:end+2) = {int, int+ss};
wolffd@0: %engine.jtree_engine = jtree_inf_engine(bnet15, 'clusters', clusters, 'root', int+ss);
wolffd@0: engine.jtree_engine = jtree_sparse_inf_engine(bnet15, 'clusters', clusters, 'root', int+ss);
wolffd@0: jtree_engine = struct(engine.jtree_engine); % violate object privacy
wolffd@0: 
wolffd@0: engine.in_clq = clq_containing_nodes(engine.jtree_engine, int);
wolffd@0: engine.out_clq = clq_containing_nodes(engine.jtree_engine, int+ss);
wolffd@0: engine.clq_ass_to_node = jtree_engine.clq_ass_to_node;
wolffd@0: engine.root = jtree_engine.root_clq;
wolffd@0: 
wolffd@0: % Also create an engine just for slice 1
wolffd@0: bnet1 = mk_bnet(bnet.intra1, bnet.node_sizes_slice, 'discrete', myintersect(bnet.dnodes,1:ss), ...
wolffd@0: 		'equiv_class', bnet.equiv_class(:,1), 'observed', onodes);
wolffd@0: for i=1:max(bnet1.equiv_class)
wolffd@0:   bnet1.CPD{i} = bnet.CPD{i};
wolffd@0: end
wolffd@0: %engine.jtree_engine1 = jtree_inf_engine(bnet1, 'clusters', {int}, 'root', int);
wolffd@0: engine.jtree_engine1 = jtree_sparse_inf_engine(bnet1, 'clusters', {int}, 'root', int);
wolffd@0: jtree_engine1 = struct(engine.jtree_engine1); % violate object privacy
wolffd@0: engine.int_clq1 = clq_containing_nodes(engine.jtree_engine1, int);
wolffd@0: engine.clq_ass_to_node1 = jtree_engine1.clq_ass_to_node;
wolffd@0: engine.root1 = jtree_engine1.root_clq;
wolffd@0: 
wolffd@0: engine.observed = [onodes onodes+ss];
wolffd@0: engine.observed1 = onodes;
wolffd@0: engine.pot_type = determine_pot_type(bnet, onodes);
wolffd@0: engine.slice_size = bnet.nnodes_per_slice;
wolffd@0: 
wolffd@0: engine = class(engine, 'jtree_sparse_2TBN_inf_engine', inf_engine(bnet));
wolffd@0: