comparison toolboxes/FullBNT-1.0.7/bnt/CPDs/@gmux_CPD/gmux_CPD.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 CPD = gmux_CPD(bnet, self, varargin)
2 % GMUX_CPD Make a Gaussian multiplexer node
3 %
4 % CPD = gmux_CPD(bnet, node, ...) is used similarly to gaussian_CPD,
5 % except we assume there is exactly one discrete parent (call it M)
6 % which is used to select which cts parent to pass through to the output.
7 % i.e., we define P(Y=y|M=m, X1, ..., XK) = N(y | W(m)*x(m) + mu(m), Sigma(m))
8 % where Y represents this node, and the Xi's are the cts parents.
9 % All the Xi must have the same size, and the num values for M must be K.
10 %
11 % Currently the params for this kind of CPD cannot be learned.
12 %
13 % Optional arguments [ default in brackets ]
14 %
15 % mean - mu(:,i) is the mean given M=i [ zeros(Y,K) ]
16 % cov - Sigma(:,:,i) is the covariance given M=i [ repmat(1*eye(Y,Y), [1 1 K]) ]
17 % weights - W(:,:,i) is the regression matrix given M=i [ randn(Y,X,K) ]
18
19 if nargin==0
20 % This occurs if we are trying to load an object from a file.
21 CPD = init_fields;
22 clamp = 0;
23 CPD = class(CPD, 'gmux_CPD', generic_CPD(clamp));
24 return;
25 elseif isa(bnet, 'gmux_CPD')
26 % This might occur if we are copying an object.
27 CPD = bnet;
28 return;
29 end
30 CPD = init_fields;
31
32 CPD = class(CPD, 'gmux_CPD', generic_CPD(1));
33
34 ns = bnet.node_sizes;
35 ps = parents(bnet.dag, self);
36 dps = myintersect(ps, bnet.dnodes);
37 cps = myintersect(ps, bnet.cnodes);
38 fam_sz = ns([ps self]);
39
40 CPD.self = self;
41 CPD.sizes = fam_sz;
42
43 % Figure out which (if any) of the parents are discrete, and which cts, and how big they are
44 % dps = discrete parents, cps = cts parents
45 CPD.cps = find_equiv_posns(cps, ps); % cts parent index
46 CPD.dps = find_equiv_posns(dps, ps);
47 if length(CPD.dps) ~= 1
48 error('gmux must have exactly 1 discrete parent')
49 end
50 ss = fam_sz(end);
51 cpsz = fam_sz(CPD.cps(1)); % in gaussian_CPD, cpsz = sum(fam_sz(CPD.cps))
52 if ~all(fam_sz(CPD.cps) == cpsz)
53 error('all cts parents must have same size')
54 end
55 dpsz = fam_sz(CPD.dps);
56 if dpsz ~= length(cps)
57 error(['the arity of the mux node is ' num2str(dpsz) ...
58 ' but there are ' num2str(length(cps)) ' cts parents']);
59 end
60
61 % set default params
62 %CPD.mean = zeros(ss, 1);
63 %CPD.cov = eye(ss);
64 %CPD.weights = randn(ss, cpsz);
65 CPD.mean = zeros(ss, dpsz);
66 CPD.cov = 1*repmat(eye(ss), [1 1 dpsz]);
67 CPD.weights = randn(ss, cpsz, dpsz);
68
69 args = varargin;
70 nargs = length(args);
71 for i=1:2:nargs
72 switch args{i},
73 case 'mean', CPD.mean = args{i+1};
74 case 'cov', CPD.cov = args{i+1};
75 case 'weights', CPD.weights = args{i+1};
76 otherwise,
77 error(['invalid argument name ' args{i}]);
78 end
79 end
80
81 %%%%%%%%%%%
82
83 function CPD = init_fields()
84 % This ensures we define the fields in the same order
85 % no matter whether we load an object from a file,
86 % or create it from scratch. (Matlab requires this.)
87
88 CPD.self = [];
89 CPD.sizes = [];
90 CPD.cps = [];
91 CPD.dps = [];
92 CPD.mean = [];
93 CPD.cov = [];
94 CPD.weights = [];
95