diff toolboxes/FullBNT-1.0.7/bnt/examples/dynamic/Old/online1.m @ 0:e9a9cd732c1e tip

first hg version after svn

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/toolboxes/FullBNT-1.0.7/bnt/examples/dynamic/Old/online1.m	Tue Feb 10 15:05:51 2015 +0000
@@ -0,0 +1,59 @@
+% Check that online inference gives same results as filtering for various algorithms
+
+N = 3;
+Q = 2;
+ss = N*2;
+
+rand('state', 0);
+randn('state', 0);
+
+
+obs_size = 1;
+discrete_obs = 0;
+bnet = mk_chmm(N, Q, obs_size, discrete_obs);
+ns = bnet.node_sizes_slice;
+
+engine = {};
+engine{end+1} = hmm_inf_engine(bnet);
+E = length(engine);
+
+onodes = (1:N)+N;
+
+T = 4;
+ev = cell(ss,T);
+ev(onodes,:) = num2cell(randn(N, T));
+
+
+filter = 1;
+loglik2 = zeros(1,E);
+for e=1:E
+  [engine2{e}, loglik2(e)] = enter_evidence(engine{e}, ev, 'filter', filter);
+end
+
+loglik = zeros(1,E);
+marg1 = cell(E,N,T);
+for e=1:E
+  ll = zeros(1,T);
+  engine{e} = dbn_init_bel(engine{e});
+  for t=1:T
+    [engine{e}, ll(t)] = dbn_update_bel(engine{e}, ev(:,t), t);
+    for i=1:N
+      marg1{e,i,t} = dbn_marginal_from_bel(engine{e}, i);
+    end
+  end
+  loglik1(e) = sum(ll);
+end
+
+assert(approxeq(loglik1, loglik2))
+
+a = zeros(E,N,T);
+for e=1:E
+  for t=1:T
+    for i=1:N
+      marg2{e,i,t} = marginal_nodes(engine2{e}, i, t);
+      a(e,i,t) = (approxeq(marg2{e,i,t}.T(:), marg1{e,i,t}.T(:)));
+    end
+  end
+end
+
+assert(all(a(:)==1))