comparison toolboxes/FullBNT-1.0.7/bnt/inference/static/@pearl_inf_engine/enter_evidence.m @ 0:e9a9cd732c1e tip

first hg version after svn
author wolffd
date Tue, 10 Feb 2015 15:05:51 +0000
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comparison
equal deleted inserted replaced
-1:000000000000 0:e9a9cd732c1e
1 function [engine, loglik, niter] = enter_evidence(engine, evidence, varargin)
2 % ENTER_EVIDENCE Add the specified evidence to the network (pearl)
3 % [engine, loglik, num_iter] = enter_evidence(engine, evidence, ...)
4 % evidence{i} = [] if if X(i) is hidden, and otherwise contains its observed value (scalar or column vector)
5 %
6 % The following optional arguments can be specified in the form of name/value pa irs:
7 % [default value in brackets]
8 %
9 % maximize - if 1, does max-product instead of sum-product [0]
10 % 'filename' - msgs will be printed to this file, so you can assess convergence while it runs [engine.filename]
11 %
12 % e.g., engine = enter_evidence(engine, ev, 'maximize', 1)
13 %
14 % For discrete nodes, loglik is the negative Bethe free energy evaluated at the final beliefs.
15 % For Gaussian nodes, loglik is currently always 0.
16 %
17 % 'num_iter' returns the number of iterations used.
18
19 maximize = 0;
20 filename = engine.filename;
21
22 % parse optional params
23 args = varargin;
24 nargs = length(args);
25 if nargs > 0
26 for i=1:2:nargs
27 switch args{i},
28 case 'maximize', maximize = args{i+1};
29 case 'filename', filename = args{i+1};
30 otherwise,
31 error(['invalid argument name ' args{i}]);
32 end
33 end
34 end
35
36
37 if maximize
38 error('can''t handle max-prop yet')
39 end
40
41 engine.maximize = maximize;
42 engine.filename = filename;
43 engine.bel = []; % reset if necessary
44
45 bnet = bnet_from_engine(engine);
46 N = length(bnet.dag);
47 ns = bnet.node_sizes(:);
48
49 observed_bitv = ~isemptycell(evidence);
50 disconnected = find(engine.disconnected_nodes_bitv);
51 if ~all(observed_bitv(disconnected))
52 error(['The following discrete nodes must be observed: ' num2str(disconnected)])
53 end
54 msg = init_pearl_msgs(engine.msg_type, engine.msg_dag, ns, evidence);
55
56 niter = 1;
57 switch engine.protocol
58 case 'parallel', [msg, niter] = parallel_protocol(engine, evidence, msg);
59 case 'tree', msg = tree_protocol(engine, evidence, msg);
60 otherwise,
61 error(['unrecognized protocol ' engine.protocol])
62 end
63 engine.niter = niter;
64
65 engine.marginal = cell(1,N);
66 nodes = find(~engine.disconnected_nodes_bitv);
67 for n=nodes(:)'
68 engine.marginal{n} = compute_bel(engine.msg_type, msg{n}.pi, msg{n}.lambda);
69 end
70
71 engine.evidence = evidence; % needed by marginal_nodes and marginal_family
72 engine.msg = msg; % needed by marginal_family
73
74 if (nargout >= 2)
75 if (engine.msg_type == 'd')
76 loglik = bethe_free_energy(engine, evidence);
77 else
78 loglik = 0;
79 end
80 end
81
82
83
84 %%%%%%%%%%%
85
86 function msg = init_pearl_msgs(msg_type, dag, ns, evidence)
87 % INIT_MSGS Initialize the lambda/pi message and state vectors
88 % msg = init_msgs(dag, ns, evidence)
89 %
90
91 N = length(dag);
92 msg = cell(1,N);
93 observed = ~isemptycell(evidence);
94 lam_msg = 1;
95
96 for n=1:N
97 ps = parents(dag, n);
98 msg{n}.pi_from_parent = cell(1, length(ps));
99 for i=1:length(ps)
100 p = ps(i);
101 msg{n}.pi_from_parent{i} = mk_msg(msg_type, ns(p));
102 end
103
104 cs = children(dag, n);
105 msg{n}.lambda_from_child = cell(1, length(cs));
106 for i=1:length(cs)
107 c = cs(i);
108 msg{n}.lambda_from_child{i} = mk_msg(msg_type, ns(n), lam_msg);
109 end
110
111 msg{n}.lambda = mk_msg(msg_type, ns(n), lam_msg);
112 msg{n}.pi = mk_msg(msg_type, ns(n));
113
114 if observed(n)
115 msg{n}.lambda_from_self = mk_msg_with_evidence(msg_type, ns(n), evidence{n});
116 else
117 msg{n}.lambda_from_self = mk_msg(msg_type, ns(n), lam_msg);
118 end
119 end
120
121
122
123 %%%%%%%%%
124
125 function msg = mk_msg(msg_type, sz, is_lambda_msg)
126
127 if nargin < 3, is_lambda_msg = 0; end
128
129 switch msg_type
130 case 'd', msg = ones(sz, 1);
131 case 'g',
132 if is_lambda_msg
133 msg.precision = zeros(sz, sz);
134 msg.info_state = zeros(sz, 1);
135 else
136 msg.Sigma = zeros(sz, sz);
137 msg.mu = zeros(sz,1);
138 end
139 end
140
141 %%%%%%%%%%%%
142
143 function msg = mk_msg_with_evidence(msg_type, sz, val)
144
145 switch msg_type
146 case 'd',
147 msg = zeros(sz, 1);
148 msg(val) = 1;
149 case 'g',
150 %msg.observed_val = val(:);
151 msg.precision = inf;
152 msg.mu = val(:);
153 end