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root / _FullBNT / BNT / CPDs / @gaussian_CPD / private / CPD_to_linear_gaussian.m @ 8:b5b38998ef3b
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function [mu, Sigma, W] = CPD_to_linear_gaussian(CPD, domain, ns, cnodes, evidence) |
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ps = domain(1:end-1); |
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dnodes = mysetdiff(1:length(ns), cnodes); |
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dps = myintersect(ps, dnodes); % discrete parents |
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if isempty(dps) |
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Q = 1; |
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else |
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assert(~any(isemptycell(evidence(dps)))); |
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dpvals = cat(1, evidence{dps});
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Q = subv2ind(ns(dps), dpvals(:)'); |
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end |
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mu = CPD.mean(:,Q); |
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Sigma = CPD.cov(:,:,Q); |
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W = CPD.weights(:,:,Q); |
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