wolffd@0: % Check that online inference gives same results as filtering for various algorithms
wolffd@0: 
wolffd@0: N = 3;
wolffd@0: Q = 2;
wolffd@0: ss = N*2;
wolffd@0: 
wolffd@0: rand('state', 0);
wolffd@0: randn('state', 0);
wolffd@0: 
wolffd@0: 
wolffd@0: obs_size = 1;
wolffd@0: discrete_obs = 0;
wolffd@0: bnet = mk_chmm(N, Q, obs_size, discrete_obs);
wolffd@0: ns = bnet.node_sizes_slice;
wolffd@0: 
wolffd@0: engine = {};
wolffd@0: engine{end+1} = hmm_inf_engine(bnet);
wolffd@0: E = length(engine);
wolffd@0: 
wolffd@0: onodes = (1:N)+N;
wolffd@0: 
wolffd@0: T = 4;
wolffd@0: ev = cell(ss,T);
wolffd@0: ev(onodes,:) = num2cell(randn(N, T));
wolffd@0: 
wolffd@0: 
wolffd@0: filter = 1;
wolffd@0: loglik2 = zeros(1,E);
wolffd@0: for e=1:E
wolffd@0:   [engine2{e}, loglik2(e)] = enter_evidence(engine{e}, ev, 'filter', filter);
wolffd@0: end
wolffd@0: 
wolffd@0: loglik = zeros(1,E);
wolffd@0: marg1 = cell(E,N,T);
wolffd@0: for e=1:E
wolffd@0:   ll = zeros(1,T);
wolffd@0:   engine{e} = dbn_init_bel(engine{e});
wolffd@0:   for t=1:T
wolffd@0:     [engine{e}, ll(t)] = dbn_update_bel(engine{e}, ev(:,t), t);
wolffd@0:     for i=1:N
wolffd@0:       marg1{e,i,t} = dbn_marginal_from_bel(engine{e}, i);
wolffd@0:     end
wolffd@0:   end
wolffd@0:   loglik1(e) = sum(ll);
wolffd@0: end
wolffd@0: 
wolffd@0: assert(approxeq(loglik1, loglik2))
wolffd@0: 
wolffd@0: a = zeros(E,N,T);
wolffd@0: for e=1:E
wolffd@0:   for t=1:T
wolffd@0:     for i=1:N
wolffd@0:       marg2{e,i,t} = marginal_nodes(engine2{e}, i, t);
wolffd@0:       a(e,i,t) = (approxeq(marg2{e,i,t}.T(:), marg1{e,i,t}.T(:)));
wolffd@0:     end
wolffd@0:   end
wolffd@0: end
wolffd@0: 
wolffd@0: assert(all(a(:)==1))