wolffd@0: function pot_type = determine_pot_type(model, onodes, nodes)
wolffd@0: % DETERMINE_POT_TYPE Determine the type of potential based on the evidence pattern.
wolffd@0: % pot_type = determine_pot_type(model, onodes, nodes)
wolffd@0: %
wolffd@0: % If there are any utility nodes, pot_type = 'u'
wolffd@0: % else
wolffd@0: % If all hidden nodes are discrete, pot_type = 'd'.
wolffd@0: % If all hidden nodes are continuous, pot_type = 'g' (Gaussian).
wolffd@0: % If some hidden nodes are discrete, and some cts, pot_type = 'cg' (conditional Gaussian).
wolffd@0: %
wolffd@0: % nodes defaults to all nodes in graph
wolffd@0: 
wolffd@0: nnodes = length(model.node_sizes);
wolffd@0: if nargin < 3, nodes = 1:nnodes; end
wolffd@0: 
wolffd@0: hnodes = mysetdiff(nodes, onodes);
wolffd@0: if isfield(model, 'limid') %~isempty(model.utility_nodes)
wolffd@0:   pot_type = 'u';
wolffd@0: elseif isempty(myintersect(model.cnodes, hnodes))
wolffd@0:   pot_type = 'd';
wolffd@0: elseif mysubset(hnodes, model.cnodes)
wolffd@0:   pot_type = 'g';
wolffd@0: else
wolffd@0:   pot_type = 'cg';
wolffd@0: end