wolffd@0: function CPD = deterministic_CPD(bnet, self, fname, pfail)
wolffd@0: % DETERMINISTIC_CPD Make a tabular CPD representing a (noisy) deterministic function
wolffd@0: %
wolffd@0: % CPD = deterministic_CPD(bnet, self, fname)
wolffd@0: % This calls feval(fname, pvals) for each possible vector of parent values.
wolffd@0: % e.g., suppose there are 2 ternary parents, then pvals = 
wolffd@0: %  [1 1], [2 1], [3 1],   [1 2], [2 2], [3 2],   [1 3], [2 3], [3 3]
wolffd@0: % If v = feval(fname, pvals(i)), then
wolffd@0: %  CPD(x | parents=pvals(i)) = 1 if x==v, and = 0 if x<>v
wolffd@0: % e.g., suppose X4 = X2 AND (NOT X3). Then
wolffd@0: %    bnet.CPD{4} = deterministic_CPD(bnet, 4, inline('((x(1)-1) & ~(x(2)-1)) + 1'));  
wolffd@0: % Note that x(1) refers pvals(1) = X2, and x(2) refers to pvals(2)=X3
wolffd@0: % See also boolean_CPD.
wolffd@0: %
wolffd@0: % CPD = deterministic_CPD(bnet, self, fname, pfail)
wolffd@0: % will put probability mass 1-pfail on f(parents), and distribute pfail over the other values.
wolffd@0: % This is useful for simulating noisy deterministic functions.
wolffd@0: % If pfail is omitted, it is set to 0.
wolffd@0: %
wolffd@0: 
wolffd@0: 
wolffd@0: if nargin==0
wolffd@0:   % This occurs if we are trying to load an object from a file.
wolffd@0:   CPD = tabular_CPD(bnet, self);
wolffd@0:   return;
wolffd@0: elseif isa(bnet, 'deterministic_CPD')
wolffd@0:   % This might occur if we are copying an object.
wolffd@0:   CPD = bnet;
wolffd@0:   return;
wolffd@0: end
wolffd@0: 
wolffd@0: if nargin < 4, pfail = 0; end
wolffd@0: 
wolffd@0: ps = parents(bnet.dag, self);
wolffd@0: ns = bnet.node_sizes;
wolffd@0: psizes = ns(ps);
wolffd@0: self_size = ns(self);
wolffd@0: 
wolffd@0: psucc = 1-pfail;
wolffd@0: 
wolffd@0: CPT = zeros(prod(psizes), self_size);
wolffd@0: pvals = zeros(1, length(ps));
wolffd@0: for i=1:prod(psizes)
wolffd@0:   pvals = ind2subv(psizes, i);
wolffd@0:   x = feval(fname, pvals);
wolffd@0:   %fprintf('%d ', [pvals x]); fprintf('\n');
wolffd@0:   if psucc == 1
wolffd@0:     CPT(i, x) = 1;
wolffd@0:   else
wolffd@0:     CPT(i, x) = psucc;
wolffd@0:     rest = mysetdiff(1:self_size, x);
wolffd@0:     CPT(i, rest) = pfail/length(rest);
wolffd@0:   end
wolffd@0: end
wolffd@0: CPT = reshape(CPT, [psizes self_size]);  
wolffd@0: 
wolffd@0: CPD = tabular_CPD(bnet, self, 'CPT',CPT, 'clamped',1);
wolffd@0: 
wolffd@0: