Mauch MIREX 2010

function pot = linear_gaussian_to_cpot(mu, Sigma, W, domain, ns, cnodes, evidence)

% LINEAR_GAUSSIAN_TO_CPOT Convert a linear Gaussian CPD  to a canonical potential.

% pot = linear_gaussian_to_cpot(mu, Sigma, W, domain, ns, cnodes, evidence)

%

% We include any cts evidence, but ignore any discrete evidence.

% (Use gaussian_CPD_params_given_dps to use discrete evidence to select mu, Sigma, W.)

odom = domain(~isemptycell(evidence(domain)));

hdom = domain(isemptycell(evidence(domain)));

cobs = myintersect(cnodes, odom);

chid = myintersect(cnodes, hdom);

cvals = cat(1, evidence{cobs});

%[g,h,K] = gaussian_to_canonical(mu, Sigma, W);

Sinv = inv(Sigma);

g = -0.5*mu'*Sinv*mu + log(normal_coef(Sigma));

if isempty(W) | (size(W,2)==0)  % no cts parents

  h = Sinv*mu;

  K = Sinv;

else

  h = [-W'*Sinv*mu; Sinv*mu];

  K = [W'*Sinv*W  -W'*Sinv';

       -Sinv*W     Sinv]; 

end

if ~isempty(cvals)

  %[g, h, K] = enter_evidence_canonical(g, h, K, chid, cobs, cvals(:), ns);  

  [hx, hy, KXX, KXY, KYX, KYY] = partition_matrix_vec(h, K, chid, cobs, ns);

  y = cvals(:);

  g = g + hy'*y - 0.5*y'*KYY*y;

  if length(hx)==0 % isempty(X) % i.e., we have instantiated everything away

    h = [];

    K = [];

  else

    h = hx - KXY*y;

    K = KXX;

  end

end

ns(odom) = 0;

pot = cpot(domain, ns(domain), g, h, K);