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function pot = convert_to_pot(CPD, pot_type, domain, evidence)
% CONVERT_TO_POT Convert a tabular CPD to one or more potentials
% pot = convert_to_pot(CPD, pot_type, domain, evidence)
% This is the same as discrete_CPD/convert_to_pot,
% except we didn't want to the kernel to inherit methods like sample_node etc.
sz = CPD.sz;
ns = zeros(1, max(domain));
ns(domain) = sz;
odom = domain(~isemptycell(evidence(domain)));
T = convert_to_table(CPD, domain, evidence);
switch pot_type
case 'u',
pot = upot(domain, sz, T, 0*myones(sz));
case 'd',
ns(odom) = 1;
pot = dpot(domain, ns(domain), T);
case 'c',
% Since we want the output to be a Gaussian, the whole family must be observed.
% In other words, the potential is really just a constant.
p = T.p;
%p = prob_node(CPD, evidence(domain(end)), evidence(domain(1:end-1)));
ns(domain) = 0;
pot = cpot(domain, ns(domain), log(p));
case 'cg',
T = T(:);
ns(odom) = 1;
can = cell(1, length(T));
for i=1:length(T)
can{i} = cpot([], [], log(T(i)));
end
pot = cgpot(domain, [], ns, can);
end
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