wolffd@0: function CPT = CPD_to_CPT(CPD)
wolffd@0: % CPD_TO_CPT Convert the discrete CPD to tabular form (noisyor)
wolffd@0: % CPT = CPD_to_CPT(CPD)
wolffd@0: %
wolffd@0: % CPT(U1,...,Un, X) = Pr(X|U1,...,Un) where the Us are the parents (excluding leak).
wolffd@0: 
wolffd@0: if ~isempty(CPD.CPT)
wolffd@0:   CPT = CPD.CPT; % remember to flush cache if params change (e.g., during learning)
wolffd@0:   return;
wolffd@0: end
wolffd@0: 
wolffd@0: q = [CPD.leak_inhibit CPD.inhibit(:)'];
wolffd@0: % q(i) is the prob. that the i'th parent will be inhibited (flipped from 1 to 0).
wolffd@0: % q(1) is the leak inhibition probability, and length(q) = n + 1.
wolffd@0: 
wolffd@0: if length(q)==1
wolffd@0:   CPT = [q  1-q];
wolffd@0:   return;
wolffd@0: end
wolffd@0: 
wolffd@0: n = length(q);
wolffd@0: Bn = ind2subv(2*ones(1,n), 1:(2^n))-1;  % all n bit vectors, with the left most column toggling fastest (LSB)
wolffd@0: CPT = zeros(2^n, 2);
wolffd@0: % Pr(X=0 | U_1 .. U_n) = prod_{i: U_i = on} q_i =  prod_i q_i ^ U_i = exp(u' * log(q_i))
wolffd@0: % This method is problematic when q contains zeros
wolffd@0: 
wolffd@0: Q = repmat(q(:)', 2^n, 1);
wolffd@0: Q(logical(~Bn)) = 1;
wolffd@0: CPT(:,1) = prod(Q,2);
wolffd@0: CPT(:,2) = 1-CPT(:,1);
wolffd@0: 
wolffd@0: CPT = reshape(CPT(2:2:end), 2*ones(1,n)); % skip cases in which the leak is off       
wolffd@0: 
wolffd@0: CPD.CPT = CPT;