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comparison toolboxes/FullBNT-1.0.7/bnt/examples/static/Models/mk_alarm_bnet.m @ 0:e9a9cd732c1e tip

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first hg version after svn
author wolffd
date Tue, 10 Feb 2015 15:05:51 +0000
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-1:000000000000 0:e9a9cd732c1e
1 function bnet = mk_alarm_bnet()
2
3 % Written by Qian Diao <qian.diao@intel.com> on 11 Dec 01
4
5 N = 37;
6 dag = zeros(N,N);
7 dag(21,23) = 1 ;
8 dag(21,24) = 1 ;
9 dag(1,24) = 1 ;
10 dag(1,23) = 1 ;
11 dag(2,26) = 1 ;
12 dag(2,25) = 1 ;
13 dag(2,24) = 1 ;
14 dag(2,13) = 1 ;
15 dag(2,23) = 1 ;
16 dag(13,30) = 1 ;
17 dag(30,31) = 1 ;
18 dag(3,14) = 1 ;
19 dag(3,19) = 1 ;
20 dag(4,36) = 1 ;
21 dag(14,35) = 1 ;
22 dag(32,33) = 1 ;
23 dag(32,35) = 1 ;
24 dag(32,34) = 1 ;
25 dag(32,36) = 1 ;
26 dag(15,21) = 1 ;
27 dag(5,31) = 1 ;
28 dag(27,30) = 1 ;
29 dag(28,31) = 1 ;
30 dag(28,29) = 1 ;
31 dag(26,28) = 1 ;
32 dag(26,27) = 1 ;
33 dag(16,31) = 1 ;
34 dag(16,37) = 1 ;
35 dag(23,26) = 1 ;
36 dag(23,29) = 1 ;
37 dag(23,25) = 1 ;
38 dag(6,15) = 1 ;
39 dag(7,27) = 1 ;
40 dag(8,21) = 1 ;
41 dag(19,20) = 1 ;
42 dag(19,22) = 1 ;
43 dag(31,32) = 1 ;
44 dag(9,14) = 1 ;
45 dag(9,17) = 1 ;
46 dag(9,19) = 1 ;
47 dag(10,33) = 1 ;
48 dag(10,34) = 1 ;
49 dag(11,16) = 1 ;
50 dag(12,13) = 1 ;
51 dag(12,18) = 1 ;
52 dag(35,37) = 1 ;
53
54 node_sizes = 2*ones(1,N);
55 node_sizes(2) = 3;
56 node_sizes(6) = 3;
57 node_sizes(14) = 3;
58 node_sizes(15) = 4;
59 node_sizes(16) = 3;
60 node_sizes(18) = 3;
61 node_sizes(19) = 3;
62 node_sizes(20) = 3;
63 node_sizes(21) = 4;
64 node_sizes(22) = 3;
65 node_sizes(23) = 4;
66 node_sizes(24) = 4;
67 node_sizes(25) = 4;
68 node_sizes(26) = 4;
69 node_sizes(27) = 3;
70 node_sizes(28) = 3;
71 node_sizes(29) = 4;
72 node_sizes(30) = 3;
73 node_sizes(32) = 3;
74 node_sizes(33) = 3;
75 node_sizes(34) = 3;
76 node_sizes(35) = 3;
77 node_sizes(36) = 3;
78 node_sizes(37) = 3;
79
80 bnet = mk_bnet(dag, node_sizes);
81
82 bnet.CPD{1} = tabular_CPD(bnet, 1,[0.96 0.04 ]);
83 bnet.CPD{2} = tabular_CPD(bnet, 2,[0.92 0.03 0.05 ]);
84 bnet.CPD{3} = tabular_CPD(bnet, 3,[0.8 0.2 ]);
85 bnet.CPD{4} = tabular_CPD(bnet, 4,[0.95 0.05 ]);
86 bnet.CPD{5} = tabular_CPD(bnet, 5,[0.8 0.2 ]);
87 bnet.CPD{6} = tabular_CPD(bnet, 6,[0.01 0.98 0.01 ]);
88 bnet.CPD{7} = tabular_CPD(bnet, 7,[0.01 0.99 ]);
89 bnet.CPD{8} = tabular_CPD(bnet, 8,[0.95 0.05 ]);
90 bnet.CPD{9} = tabular_CPD(bnet, 9,[0.95 0.05 ]);
91 bnet.CPD{10} = tabular_CPD(bnet, 10,[0.9 0.1 ]);
92 bnet.CPD{11} = tabular_CPD(bnet, 11,[0.99 0.01 ]);
93 bnet.CPD{12} = tabular_CPD(bnet, 12,[0.99 0.01 ]);
94 bnet.CPD{13} = tabular_CPD(bnet, 13,[0.95 0.95 0.05 0.1 0.1 0.01 0.05 0.05 0.95 0.9 0.9 0.99 ]);
95 bnet.CPD{14} = tabular_CPD(bnet, 14,[0.05 0.95 0.5 0.98 0.9 0.04 0.49 0.01 0.05 0.01 0.01 0.01 ]);
96 bnet.CPD{15} = tabular_CPD(bnet, 15,[0.01 0.01 0.01 0.97 0.01 0.01 0.01 0.97 0.01 0.01 0.01 0.97 ]);
97 bnet.CPD{16} = tabular_CPD(bnet, 16,[0.3 0.98 0.4 0.01 0.3 0.01 ]);
98 bnet.CPD{17} = tabular_CPD(bnet, 17,[0.99 0.1 0.01 0.9 ]);
99 bnet.CPD{18} = tabular_CPD(bnet, 18,[0.05 0.01 0.9 0.19 0.05 0.8 ]);
100 bnet.CPD{19} = tabular_CPD(bnet, 19,[0.05 0.98 0.01 0.95 0.9 0.01 0.09 0.04 0.05 0.01 0.9 0.01 ]);
101 bnet.CPD{20} = tabular_CPD(bnet, 20,[0.95 0.04 0.01 0.04 0.95 0.29 0.01 0.01 0.7 ]);
102 bnet.CPD{21} = tabular_CPD(bnet, 21,[0.97 0.97 0.01 0.97 0.01 0.97 0.01 0.97 0.01 0.01 0.97 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.97 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.97 0.01 ]);
103 bnet.CPD{22} = tabular_CPD(bnet, 22,[0.95 0.04 0.01 0.04 0.95 0.04 0.01 0.01 0.95 ]);
104 bnet.CPD{23} = tabular_CPD(bnet, 23,[0.97 0.97 0.97 0.97 0.97 0.97 0.01 0.95 0.97 0.97 0.01 0.95 0.01 0.4 0.97 0.97 0.01 0.5 0.01 0.3 0.97 0.97 0.01 0.3 0.01 0.01 0.01 0.01 0.01 0.01 0.97 0.03 0.01 0.01 0.97 0.03 0.01 0.58 0.01 0.01 0.01 0.48 0.01 0.68 0.01 0.01 0.01 0.68 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.97 0.01 0.01 0.01 0.97 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.97 0.01 0.01 0.01 0.97 0.01 ]);
105 bnet.CPD{24} = tabular_CPD(bnet, 24,[0.97 0.97 0.97 0.97 0.97 0.97 0.01 0.01 0.4 0.1 0.01 0.01 0.01 0.01 0.2 0.05 0.01 0.01 0.01 0.01 0.2 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.97 0.49 0.58 0.84 0.9 0.29 0.01 0.01 0.75 0.25 0.01 0.01 0.01 0.01 0.7 0.15 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.3 0.01 0.05 0.08 0.3 0.97 0.08 0.04 0.25 0.38 0.08 0.01 0.01 0.09 0.25 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.2 0.01 0.01 0.01 0.4 0.01 0.9 0.01 0.45 0.6 0.9 0.97 0.97 0.01 0.59 0.97 0.97 ]);
106 bnet.CPD{25} = tabular_CPD(bnet, 25,[0.97 0.97 0.97 0.01 0.6 0.01 0.01 0.5 0.01 0.01 0.5 0.01 0.01 0.01 0.01 0.97 0.38 0.97 0.01 0.48 0.01 0.01 0.48 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.97 0.01 0.97 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.97 0.01 0.97 ]);
107 bnet.CPD{26} = tabular_CPD(bnet, 26,[0.97 0.97 0.97 0.01 0.01 0.03 0.01 0.01 0.01 0.97 0.01 0.01 0.01 0.01 0.01 0.97 0.97 0.95 0.01 0.01 0.94 0.01 0.01 0.88 0.01 0.01 0.01 0.01 0.01 0.01 0.97 0.97 0.04 0.01 0.01 0.1 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.97 0.97 0.01 ]);
108 bnet.CPD{27} = tabular_CPD(bnet, 27,[0.98 0.98 0.98 0.98 0.95 0.01 0.95 0.01 0.01 0.01 0.01 0.01 0.04 0.95 0.04 0.01 0.01 0.01 0.01 0.01 0.01 0.04 0.01 0.98 ]);
109 bnet.CPD{28} = tabular_CPD(bnet, 28,[0.01 0.01 0.04 0.9 0.01 0.01 0.92 0.09 0.98 0.98 0.04 0.01 ]);
110 bnet.CPD{29} = tabular_CPD(bnet, 29,[0.97 0.01 0.01 0.01 0.97 0.01 0.01 0.01 0.97 0.01 0.01 0.01 0.01 0.97 0.97 0.97 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.97 0.97 0.97 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.97 0.97 0.43 ]);
111 bnet.CPD{30} = tabular_CPD(bnet, 30,[0.98 0.98 0.01 0.98 0.01 0.69 0.01 0.01 0.98 0.01 0.01 0.3 0.01 0.01 0.01 0.01 0.98 0.01 ]);
112 bnet.CPD{31} = tabular_CPD(bnet, 31,[0.05 0.01 0.05 0.01 0.05 0.01 0.05 0.01 0.05 0.01 0.05 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.1 0.01 0.95 0.01 0.95 0.05 0.1 0.01 0.95 0.01 0.95 0.05 0.1 0.01 0.3 0.01 0.3 0.01 0.95 0.01 0.99 0.05 0.95 0.05 0.95 0.01 0.99 0.05 0.99 0.05 0.3 0.01 0.99 0.01 0.3 0.01 0.95 0.99 0.95 0.99 0.95 0.99 0.95 0.99 0.95 0.99 0.95 0.99 0.99 0.99 0.99 0.99 0.99 0.99 0.9 0.99 0.05 0.99 0.05 0.95 0.9 0.99 0.05 0.99 0.05 0.95 0.9 0.99 0.7 0.99 0.7 0.99 0.05 0.99 0.00999999 0.95 0.05 0.95 0.05 0.99 0.01 0.95 0.01 0.95 0.7 0.99 0.01 0.99 0.7 0.99 ]);
113 bnet.CPD{32} = tabular_CPD(bnet, 32,[0.1 0.01 0.89 0.09 0.01 0.9 ]);
114 bnet.CPD{33} = tabular_CPD(bnet, 33,[0.98 0.33333334 0.01 0.33333334 0.01 0.33333334 0.01 0.33333334 0.98 0.33333334 0.01 0.33333334 0.01 0.33333334 0.01 0.33333334 0.98 0.33333334 ]);
115 bnet.CPD{34} = tabular_CPD(bnet, 34,[0.98 0.33333334 0.01 0.33333334 0.01 0.33333334 0.01 0.33333334 0.98 0.33333334 0.01 0.33333334 0.01 0.33333334 0.01 0.33333334 0.98 0.33333334 ]);
116 bnet.CPD{35} = tabular_CPD(bnet, 35,[0.98 0.95 0.3 0.95 0.04 0.01 0.8 0.01 0.01 0.01 0.04 0.69 0.04 0.95 0.3 0.19 0.04 0.01 0.01 0.01 0.01 0.01 0.01 0.69 0.01 0.95 0.98 ]);
117 bnet.CPD{36} = tabular_CPD(bnet, 36,[0.98 0.98 0.01 0.4 0.01 0.3 0.01 0.01 0.98 0.59 0.01 0.4 0.01 0.01 0.01 0.01 0.98 0.3 ]);
118 bnet.CPD{37} = tabular_CPD(bnet, 37,[0.98 0.98 0.3 0.98 0.1 0.05 0.9 0.05 0.01 0.01 0.01 0.6 0.01 0.85 0.4 0.09 0.2 0.09 0.01 0.01 0.1 0.01 0.05 0.55 0.01 0.75 0.9 ]);