Mauch MIREX 2010

function bnet = fgraph_to_bnet(fg)

% FGRAPH_TO_BNET Convert a factor graph to a Bayes net

% bnet = fgraph_to_bnet(fg)

%

% We assume all factors are tabular_CPD.

% We create 1 dummy observed node for every factor.

N = fg.nvars + fg.nfactors;

vnodes = 1:fg.nvars;

fnodes = fg.nvars+1:N;

dag = zeros(N);

for x=1:fg.nvars

  dag(x, fnodes(fg.dep{x})) = 1;

end

ns = [fg.node_sizes ones(1, fg.nfactors)];

discrete = [fg.dnodes fnodes];

bnet = mk_bnet(dag, ns, 'discrete', discrete);

for x=1:fg.nvars

  bnet.CPD{x} = tabular_CPD(bnet, x, 'CPT', 'unif');

end

ev = cell(1, fg.nvars); % no evidence

for i=1:fg.nfactors

  f = fnodes(i);

  e = fg.equiv_class(i);

  pot = convert_to_pot(fg.factors{e}, 'd', fg.dom{i}, ev);

  m = pot_to_marginal(pot);

  bnet.CPD{f} = tabular_CPD(bnet, f, 'CPT', m.T);

end