function [engine, loglik] = enter_evidence(engine, evidence, varargin)% ENTER_EVIDENCE Add the specified evidence to the network (ff)% [engine, loglik] = enter_evidence(engine, evidence, ...)%% evidence{i,t} = [] if if X(i,t) is hidden, and otherwise contains its observed value (scalar or% column vector)%% The following optional arguments can be specified in the form of name/value pairs:% [default value in brackets]%% maximize - if 1, does max-product (not yet supported), else sum-product [0]% filter -   if 1, do filtering, else smoothing [0]%% e.g., engine = enter_evidence(engine, ev, 'maximize', 1)maximize = 0;filter = 0;% parse optional paramsargs = varargin;nargs = length(args);if nargs > 0  for i=1:2:nargs    switch args{i},     case 'maximize', maximize = args{i+1};      case 'filter', filter = args{i+1};      otherwise,        error(['invalid argument name ' args{i}]);           end  endendassert(~maximize);[ss T] = size(evidence);observed = ~isemptycell(evidence);bnet = bnet_from_engine(engine);%pot_type = determine_pot_type(find(observed(:,1)), bnet.cnodes_slice, bnet.intra);pot_type = determine_pot_type(bnet, observed);% we assume we can use the same pot_type in all slicesCPDpot = convert_dbn_CPDs_to_pots(bnet, evidence, pot_type);% Now convert CPDs on observed nodes to be potentials just on their parentsassert(pot_type == 'd');onodes = bnet.observed(:);ns = bnet.node_sizes_slice;ns(onodes) = 1;for t=1:T  for i=onodes    p = parents(bnet.dag, i);    %CPDpot{i,t} = set_domain_pot(CPDpot{i,t}, p); % leaves size too long    temp = pot_to_marginal(CPDpot{i,t});    CPDpot{i,t} = dpot(p, ns(p), temp.T); % assumes pot_type = d  endend[engine.marginals, engine.fwd, engine.back, loglik] = enter_soft_evidence(engine, CPDpot, observed, pot_type, filter);engine.CPDpot = CPDpot;engine.filter = filter;