wolffd@0: function [engine, loglik] = enter_evidence(engine, evidence, varargin)
wolffd@0: % ENTER_EVIDENCE Add the specified evidence to the network (hmm)
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, does filtering, else smoothing [0]
wolffd@0: % oneslice - 1 means only compute marginals on nodes within a single slice [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: oneslice = 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:      case 'oneslice', oneslice = 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: [ss T] = size(evidence);
wolffd@0: engine.maximize = maximize;
wolffd@0: engine.evidence = evidence;
wolffd@0: bnet = bnet_from_engine(engine);
wolffd@0: engine.node_sizes = repmat(bnet.node_sizes_slice(:), [1 T]);
wolffd@0: 
wolffd@0: obs_bitv = ~isemptycell(evidence(:));
wolffd@0: bitv = reshape(obs_bitv, ss, T);
wolffd@0: for t=1:T
wolffd@0:   onodes = find(bitv(:,t));
wolffd@0:   if ~isequal(onodes, bnet.observed(:))
wolffd@0:     error(['dbn was created assuming observed nodes per slice were '...
wolffd@0: 	   num2str(bnet.observed(:)')  ' but the evidence in slice ' num2str(t) ...
wolffd@0: 	   ' has observed nodes ' num2str(onodes(:)')]);
wolffd@0:   end
wolffd@0: end
wolffd@0: 
wolffd@0: obslik = mk_hmm_obs_lik_matrix(engine, evidence);
wolffd@0: 
wolffd@0: %[alpha, beta, gamma, loglik, xi] = fwdback(engine.startprob, engine.transprob, obslik, ...
wolffd@0: [alpha, beta, gamma, loglik, xi] = fwdback_twoslice(engine, engine.startprob,...
wolffd@0:                                                     engine.transprob, obslik, ...
wolffd@0:                                                     'maximize', maximize, 'fwd_only', filter, ...
wolffd@0:                                                     'compute_xi', ~oneslice);
wolffd@0: 
wolffd@0: engine.one_slice_marginal = gamma; % gamma(:,t) for t=1:T
wolffd@0: if ~oneslice
wolffd@0:   Q = size(gamma,1);
wolffd@0:   engine.two_slice_marginal = reshape(xi, [Q*Q T-1]); % xi(:,t) for t=1:T-1
wolffd@0: end