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1 function pot = linear_gaussian_to_cpot(mu, Sigma, W, domain, ns, cnodes, evidence)
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2 % LINEAR_GAUSSIAN_TO_CPOT Convert a linear Gaussian CPD to a canonical potential.
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3 % pot = linear_gaussian_to_cpot(mu, Sigma, W, domain, ns, cnodes, evidence)
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4 %
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5 % We include any cts evidence, but ignore any discrete evidence.
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6 % (Use gaussian_CPD_params_given_dps to use discrete evidence to select mu, Sigma, W.)
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7
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8 odom = domain(~isemptycell(evidence(domain)));
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9 hdom = domain(isemptycell(evidence(domain)));
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10 cobs = myintersect(cnodes, odom);
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11 chid = myintersect(cnodes, hdom);
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12 cvals = cat(1, evidence{cobs});
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13
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14 %[g,h,K] = gaussian_to_canonical(mu, Sigma, W);
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15 Sinv = inv(Sigma);
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16 g = -0.5*mu'*Sinv*mu + log(normal_coef(Sigma));
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17 if isempty(W) | (size(W,2)==0) % no cts parents
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18 h = Sinv*mu;
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19 K = Sinv;
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20 else
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21 h = [-W'*Sinv*mu; Sinv*mu];
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22 K = [W'*Sinv*W -W'*Sinv';
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23 -Sinv*W Sinv];
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24 end
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25
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26 if ~isempty(cvals)
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27 %[g, h, K] = enter_evidence_canonical(g, h, K, chid, cobs, cvals(:), ns);
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28 [hx, hy, KXX, KXY, KYX, KYY] = partition_matrix_vec(h, K, chid, cobs, ns);
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29 y = cvals(:);
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30 g = g + hy'*y - 0.5*y'*KYY*y;
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31 if length(hx)==0 % isempty(X) % i.e., we have instantiated everything away
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32 h = [];
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33 K = [];
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34 else
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35 h = hx - KXY*y;
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36 K = KXX;
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37 end
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38 end
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39
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40 ns(odom) = 0;
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41 pot = cpot(domain, ns(domain), g, h, K);
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42
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43
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