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