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annotate toolboxes/FullBNT-1.0.7/bnt/examples/dynamic/HHMM/Old/mk_hhmm3_args.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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wolffd@0 1 function bnet = mk_hhmm3(varargin)
wolffd@0 2 % MK_HHMM3 Make a 3 level Hierarchical HMM
wolffd@0 3 % bnet = mk_hhmm3(...)
wolffd@0 4 %
wolffd@0 5 % 3-layer hierarchical HMM where level 1 only connects to level 2, not 3 or obs.
wolffd@0 6 % This enforces sub-models (which differ only in their Q1 index) to be shared.
wolffd@0 7 % Also, we enforce the fact that each model always starts in its initial state
wolffd@0 8 % and only finishes in its final state. However, the prob. of finishing (as opposed to
wolffd@0 9 % self-transitioning to the final state) can be learned.
wolffd@0 10 % The fact that we always finish from the same state means we do not need to condition
wolffd@0 11 % F(i) on Q(i-1), since finishing prob is indep of calling context.
wolffd@0 12 %
wolffd@0 13 % The DBN is the same as Fig 10 in my tech report.
wolffd@0 14 %
wolffd@0 15 % Q1 ----------> Q1
wolffd@0 16 % | / |
wolffd@0 17 % | / |
wolffd@0 18 % | F2 ------- |
wolffd@0 19 % | ^ \ |
wolffd@0 20 % | /| \ |
wolffd@0 21 % v | v v
wolffd@0 22 % Q2-| --------> Q2
wolffd@0 23 % /| | ^
wolffd@0 24 % / | | /|
wolffd@0 25 % | | F3 ---------/ |
wolffd@0 26 % | | ^ \ |
wolffd@0 27 % | v / v
wolffd@0 28 % | Q3 -----------> Q3
wolffd@0 29 % | |
wolffd@0 30 % \ |
wolffd@0 31 % v v
wolffd@0 32 % O
wolffd@0 33 %
wolffd@0 34 % Q1 (slice 1) is clamped to be uniform.
wolffd@0 35 % Q2 (slice 1) is clamped to always start in state 1.
wolffd@0 36 % Q3 (slice 1) is clamped to always start in state 1.
wolffd@0 37 % F3 by default will only finish if Q3 is in its last state (F3 is a tabular_CPD)
wolffd@0 38 % F2 by default gets the default hhmmF_CPD params.
wolffd@0 39 % Q1:Q3 (slice 2) by default gets the default hhmmQ_CPD params.
wolffd@0 40 % O by default gets the default tabular/Gaussian params.
wolffd@0 41 %
wolffd@0 42 % Optional arguments in name/value format [default]
wolffd@0 43 %
wolffd@0 44 % Qsizes - sizes at each level [ none ]
wolffd@0 45 % Osize - size of O node [ none ]
wolffd@0 46 % discrete_obs - 1 means O is tabular_CPD, 0 means O is gaussian_CPD [0]
wolffd@0 47 % Oargs - cell array of args to pass to the O CPD [ {} ]
wolffd@0 48 % Q1args - args to be passed to constructor for Q1 (slice 2) [ {} ]
wolffd@0 49 % Q2args - args to be passed to constructor for Q2 (slice 2) [ {} ]
wolffd@0 50 % Q3args - args to be passed to constructor for Q3 (slice 2) [ {} ]
wolffd@0 51 % F2args - args to be passed to constructor for F2 [ {} ]
wolffd@0 52 % F3args - args to be passed to constructor for F3 [ {'CPT', finish in last Q3 state} ]
wolffd@0 53 %
wolffd@0 54
wolffd@0 55 ss = 6; D = 3;
wolffd@0 56 Q1 = 1; Q2 = 2; Q3 = 3; F3 = 4; F2 = 5; obs = 6;
wolffd@0 57 Qnodes = [Q1 Q2 Q3]; Fnodes = [F2 F3];
wolffd@0 58 names = {'Q1', 'Q2', 'Q3', 'F3', 'F2', 'obs'};
wolffd@0 59
wolffd@0 60 intra = zeros(ss);
wolffd@0 61 intra(Q1, Q2) = 1;
wolffd@0 62 intra(Q2, [F2 Q3 obs]) = 1;
wolffd@0 63 intra(Q3, [F3 obs]) = 1;
wolffd@0 64 intra(F3, F2) = 1;
wolffd@0 65
wolffd@0 66 inter = zeros(ss);
wolffd@0 67 inter(Q1,Q1) = 1;
wolffd@0 68 inter(Q2,Q2) = 1;
wolffd@0 69 inter(Q3,Q3) = 1;
wolffd@0 70 inter(F2,[Q1 Q2]) = 1;
wolffd@0 71 inter(F3,[Q2 Q3]) = 1;
wolffd@0 72
wolffd@0 73
wolffd@0 74 % get sizes of nodes
wolffd@0 75 args = varargin;
wolffd@0 76 nargs = length(args);
wolffd@0 77 Qsizes = [];
wolffd@0 78 Osize = 0;
wolffd@0 79 for i=1:2:nargs
wolffd@0 80 switch args{i},
wolffd@0 81 case 'Qsizes', Qsizes = args{i+1};
wolffd@0 82 case 'Osize', Osize = args{i+1};
wolffd@0 83 end
wolffd@0 84 end
wolffd@0 85 if isempty(Qsizes), error('must specify Qsizes'); end
wolffd@0 86 if Osize==0, error('must specify Osize'); end
wolffd@0 87
wolffd@0 88 % set default params
wolffd@0 89 discrete_obs = 0;
wolffd@0 90 Oargs = {};
wolffd@0 91 Q1args = {};
wolffd@0 92 Q2args = {};
wolffd@0 93 Q3args = {};
wolffd@0 94 F2args = {};
wolffd@0 95
wolffd@0 96 % P(Q3, F3)
wolffd@0 97 CPT = zeros(Qsizes(3), 2);
wolffd@0 98 % Each model can only terminate in its final state.
wolffd@0 99 % 0 params will remain 0 during EM, thus enforcing this constraint.
wolffd@0 100 CPT(:, 1) = 1.0; % all states turn F off ...
wolffd@0 101 p = 0.5;
wolffd@0 102 CPT(Qsizes(3), 2) = p; % except the last one
wolffd@0 103 CPT(Qsizes(3), 1) = 1-p;
wolffd@0 104 F3args = {'CPT', CPT};
wolffd@0 105
wolffd@0 106 for i=1:2:nargs
wolffd@0 107 switch args{i},
wolffd@0 108 case 'discrete_obs', discrete_obs = args{i+1};
wolffd@0 109 case 'Oargs', Oargs = args{i+1};
wolffd@0 110 case 'Q1args', Q1args = args{i+1};
wolffd@0 111 case 'Q2args', Q2args = args{i+1};
wolffd@0 112 case 'Q3args', Q3args = args{i+1};
wolffd@0 113 case 'F2args', F2args = args{i+1};
wolffd@0 114 case 'F3args', F3args = args{i+1};
wolffd@0 115 end
wolffd@0 116 end
wolffd@0 117
wolffd@0 118 ns = zeros(1,ss);
wolffd@0 119 ns(Qnodes) = Qsizes;
wolffd@0 120 ns(obs) = Osize;
wolffd@0 121 ns(Fnodes) = 2;
wolffd@0 122
wolffd@0 123 dnodes = [Qnodes Fnodes];
wolffd@0 124 if discrete_obs
wolffd@0 125 dnodes = [dnodes obs];
wolffd@0 126 end
wolffd@0 127 onodes = [obs];
wolffd@0 128
wolffd@0 129 bnet = mk_dbn(intra, inter, ns, 'observed', onodes, 'discrete', dnodes, 'names', names);
wolffd@0 130 eclass = bnet.equiv_class;
wolffd@0 131
wolffd@0 132 % SLICE 1
wolffd@0 133
wolffd@0 134 % We clamp untied nodes in the first slice, since their params can't be estimated
wolffd@0 135 % from just one sequence
wolffd@0 136
wolffd@0 137 % uniform prior on initial model
wolffd@0 138 CPT = normalise(ones(1,ns(Q1)));
wolffd@0 139 bnet.CPD{eclass(Q1,1)} = tabular_CPD(bnet, Q1, 'CPT', CPT, 'adjustable', 0);
wolffd@0 140
wolffd@0 141 % each model always starts in state 1
wolffd@0 142 CPT = zeros(ns(Q1), ns(Q2));
wolffd@0 143 CPT(:, 1) = 1.0;
wolffd@0 144 bnet.CPD{eclass(Q2,1)} = tabular_CPD(bnet, Q2, 'CPT', CPT, 'adjustable', 0);
wolffd@0 145
wolffd@0 146 % each model always starts in state 1
wolffd@0 147 CPT = zeros(ns(Q2), ns(Q3));
wolffd@0 148 CPT(:, 1) = 1.0;
wolffd@0 149 bnet.CPD{eclass(Q3,1)} = tabular_CPD(bnet, Q3, 'CPT', CPT, 'adjustable', 0);
wolffd@0 150
wolffd@0 151 bnet.CPD{eclass(F2,1)} = hhmmF_CPD(bnet, F2, Qnodes, 2, D, F2args{:});
wolffd@0 152
wolffd@0 153 bnet.CPD{eclass(F3,1)} = tabular_CPD(bnet, F3, F3args{:});
wolffd@0 154
wolffd@0 155 if discrete_obs
wolffd@0 156 bnet.CPD{eclass(obs,1)} = tabular_CPD(bnet, obs, Oargs{:});
wolffd@0 157 else
wolffd@0 158 bnet.CPD{eclass(obs,1)} = gaussian_CPD(bnet, obs, Oargs{:});
wolffd@0 159 end
wolffd@0 160
wolffd@0 161 % SLICE 2
wolffd@0 162
wolffd@0 163 bnet.CPD{eclass(Q1,2)} = hhmmQ_CPD(bnet, Q1+ss, Qnodes, 1, D, Q1args{:});
wolffd@0 164 bnet.CPD{eclass(Q2,2)} = hhmmQ_CPD(bnet, Q2+ss, Qnodes, 2, D, Q2args{:});
wolffd@0 165 bnet.CPD{eclass(Q3,2)} = hhmmQ_CPD(bnet, Q3+ss, Qnodes, 3, D, Q3args{:});