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1 function CPD = update_ess(CPD, fmarginal, evidence, ns, cnodes, hidden_bitv)
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2 % UPDATE_ESS Update the Expected Sufficient Statistics of a hhmmF node.
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3 % function CPD = update_ess(CPD, fmarginal, evidence, ns, cnodes, hidden_bitv)
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4 %
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5 % We assume the F nodes are always hidden
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6
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7 % Figure out the node numbers associated with each parent
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8 dom = fmarginal.domain;
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9 %Fself = dom(end);
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10 %Fbelow = dom(CPD.Fbelow_ndx);
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11 Qself = dom(CPD.Qself_ndx);
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12 Qps = dom(CPD.Qps_ndx);
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13
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14 Qsz = CPD.Qsz;
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15 Qpsz = CPD.Qpsz;
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16
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17 if all(hidden_bitv(Qps)) % we assume all are hidden or all are observed
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18 k_ndx = 1:Qpsz;
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19 eff_Qpsz = Qpsz;
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20 else
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21 k_ndx = subv2ind(Qpsz, cat(1, evidence{Qps}));
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22 eff_Qpsz = 1;
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23 end
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24
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25 if hidden_bitv(Qself)
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26 j_ndx = 1:Qsz;
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27 eff_Qsz = Qsz;
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28 else
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29 j_ndx = evidence{Qself};
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30 eff_Qsz = 1;
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31 end
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32
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33 % Fmarginal(Qps, Q, Fbelow, F)
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34 fmarg = myreshape(fmarginal.T, [eff_Qpsz eff_Qsz 2 2]);
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35
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36 counts = zeros(Qpsz, Qsz, 2);
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37 %counts(k_ndx, j_ndx, :) = sum(fmarginal.T(:, :, :, :), 3); % sum over Fbelow
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38 counts(k_ndx, j_ndx, :) = fmarg(:, :, 2, :); % Fbelow = 2
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39
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40 CPD.sub_CPD_term = update_ess_simple(CPD.sub_CPD_term, counts);
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