comparison toolboxes/FullBNT-1.0.7/bnt/CPDs/@hhmmQ_CPD/Old/hhmmQ_CPD.m @ 0:e9a9cd732c1e tip

first hg version after svn
author wolffd
date Tue, 10 Feb 2015 15:05:51 +0000
parents
children
comparison
equal deleted inserted replaced
-1:000000000000 0:e9a9cd732c1e
1 function CPD = hhmmQ_CPD(bnet, self, Qnodes, d, D, varargin)
2 % HHMMQ_CPD Make the CPD for a Q node at depth D of a D-level hierarchical HMM
3 % CPD = hhmmQ_CPD(bnet, self, Qnodes, d, D, ...)
4 %
5 % Fd(t-1) \ Q1:d-1(t)
6 % \ |
7 % \ v
8 % Qd(t-1) -> Qd(t)
9 % /
10 % /
11 % Fd+1(t-1)
12 %
13 % We assume parents are ordered (numbered) as follows:
14 % Qd(t-1), Fd+1(t-1), Fd(t-1), Q1(t), ..., Qd(t)
15 %
16 % The parents of Qd(t) can either be just Qd-1(t) or the whole stack Q1:d-1(t) (allQ)
17 % In either case, we will call them Qps.
18 % If d=1, Qps does not exist. Also, the F1(t-1) -> Q1(t) arc is optional.
19 % If the arc is missing, startprob does not need to be specified,
20 % since the toplevel is assumed to never reset (F1 does not exist).
21 % If d=D, Fd+1(t-1) does not exist (there is no signal from below).
22 %
23 % optional args [defaults]
24 %
25 % transprob - transprob(i,k,j) = prob transition from i to j given Qps = k ['leftright']
26 % selfprob - prob of a transition from i to i given Qps=k [0.1]
27 % startprob - startprob(k,j) = prob start in j given Qps = k ['leftstart']
28 % startargs - other args to be passed to the sub tabular_CPD for learning startprob
29 % transargs - other args will be passed to the sub tabular_CPD for learning transprob
30 % allQ - 1 means use all Q nodes above d as parents, 0 means just level d-1 [0]
31 % F1toQ1 - 1 means add F1(t-1) -> Q1(t) arc, 0 means level 1 never resets [0]
32 %
33 % For d=1, startprob(1,j) is only needed if F1toQ1=1
34 % Also, transprob(i,j) can be used instead of transprob(i,1,j).
35 %
36 % hhmmQ_CPD is a subclass of tabular_CPD so we inherit inference methods like CPD_to_pot, etc.
37 %
38 % We create isolated tabular_CPDs with no F parents to learn transprob/startprob
39 % so we can avail of e.g., entropic or Dirichlet priors.
40 % In the future, we will be able to represent the transprob using a tree_CPD.
41 %
42 % For details, see "Linear-time inference in hierarchical HMMs", Murphy and Paskin, NIPS'01.
43
44
45 ss = bnet.nnodes_per_slice;
46 %assert(self == Qnodes(d)+ss);
47 ns = bnet.node_sizes(:);
48 CPD.Qsizes = ns(Qnodes);
49 CPD.d = d;
50 CPD.D = D;
51 allQ = 0;
52
53 % find out which parents to use, to get right size
54 for i=1:2:length(varargin)
55 switch varargin{i},
56 case 'allQ', allQ = varargin{i+1};
57 end
58 end
59
60 if d==1
61 CPD.Qps = [];
62 else
63 if allQ
64 CPD.Qps = Qnodes(1:d-1);
65 else
66 CPD.Qps = Qnodes(d-1);
67 end
68 end
69
70 Qsz = ns(self);
71 Qpsz = prod(ns(CPD.Qps));
72
73 % set default arguments
74 startprob = 'leftstart';
75 transprob = 'leftright';
76 startargs = {};
77 transargs = {};
78 CPD.F1toQ1 = 0;
79 selfprob = 0.1;
80
81 for i=1:2:length(varargin)
82 switch varargin{i},
83 case 'transprob', transprob = varargin{i+1};
84 case 'selfprob', selfprob = varargin{i+1};
85 case 'startprob', startprob = varargin{i+1};
86 case 'startargs', startargs = varargin{i+1};
87 case 'transargs', transargs = varargin{i+1};
88 case 'F1toQ1', CPD.F1toQ1 = varargin{i+1};
89 end
90 end
91
92 Qps = CPD.Qps + ss;
93 old_self = self-ss;
94
95 if strcmp(transprob, 'leftright')
96 LR = mk_leftright_transmat(Qsz, selfprob);
97 transprob = repmat(reshape(LR, [1 Qsz Qsz]), [Qpsz 1 1]); % transprob(k,i,j)
98 transprob = permute(transprob, [2 1 3]); % now transprob(i,k,j)
99 end
100 transargs{end+1} = 'CPT';
101 transargs{end+1} = transprob;
102 CPD.sub_CPD_trans = mk_isolated_tabular_CPD([old_self Qps], ns([old_self Qps self]), transargs);
103 S = struct(CPD.sub_CPD_trans);
104 CPD.transprob = myreshape(S.CPT, [Qsz Qpsz Qsz]);
105
106
107 if strcmp(startprob, 'leftstart')
108 startprob = zeros(Qpsz, Qsz);
109 startprob(:,1) = 1;
110 end
111
112 if (d==1) & ~CPD.F1toQ1
113 CPD.sub_CPD_start = [];
114 CPD.startprob = [];
115 else
116 startargs{end+1} = 'CPT';
117 startargs{end+1} = startprob;
118 CPD.sub_CPD_start = mk_isolated_tabular_CPD(Qps, ns([Qps self]), startargs);
119 S = struct(CPD.sub_CPD_start);
120 CPD.startprob = myreshape(S.CPT, [Qpsz Qsz]);
121 end
122
123 CPD = class(CPD, 'hhmmQ_CPD', tabular_CPD(bnet, self));
124
125 CPD = update_CPT(CPD);
126