1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
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))
|
