wolffd@0: function [engine, loglik] = enter_evidence(engine, evidence, varargin)
wolffd@0: % ENTER_EVIDENCE Add the specified evidence to the network (frontier)
wolffd@0: % [engine, loglik] = enter_evidence(engine, evidence, ...)
wolffd@0: %
wolffd@0: % evidence{i,t} = [] if if X(i,t) is hidden, and otherwise contains its observed value (scalar or column vector)
wolffd@0: %
wolffd@0: % The following optional arguments can be specified in the form of name/value pairs:
wolffd@0: % [default value in brackets]
wolffd@0: %
wolffd@0: % maximize - if 1, does max-product (not yet supported), else sum-product [0]
wolffd@0: % filter -   if 1, do filtering, else smoothing [0]
wolffd@0: %
wolffd@0: % e.g., engine = enter_evidence(engine, ev, 'maximize', 1)
wolffd@0: 
wolffd@0: maximize = 0;
wolffd@0: filter = 0;
wolffd@0: 
wolffd@0: % parse optional params
wolffd@0: args = varargin;
wolffd@0: nargs = length(args);
wolffd@0: if nargs > 0
wolffd@0:   for i=1:2:nargs
wolffd@0:     switch args{i},
wolffd@0:      case 'maximize', maximize = args{i+1}; 
wolffd@0:      case 'filter', filter = args{i+1}; 
wolffd@0:      otherwise,  
wolffd@0:       error(['invalid argument name ' args{i}]);       
wolffd@0:     end
wolffd@0:   end
wolffd@0: end
wolffd@0: 
wolffd@0: assert(~maximize);
wolffd@0: 
wolffd@0: [ss T] = size(evidence);
wolffd@0: bnet = bnet_from_engine(engine);
wolffd@0: onodes = find(~isemptycell(evidence));
wolffd@0: cnodes = unroll_set(bnet.cnodes(:), ss, T);
wolffd@0: pot_type = determine_pot_type(bnet, onodes);
wolffd@0: 
wolffd@0: CPDpot = convert_dbn_CPDs_to_pots(bnet, evidence, pot_type);
wolffd@0: 
wolffd@0: [engine.fwdback, loglik, engine.fwd_frontier, engine.back_frontier] = ...
wolffd@0:     enter_soft_evidence(engine, CPDpot, onodes, pot_type, filter);
wolffd@0: