function [err, time, engine] = cmp_inference(bnet, engine, exact, T, filter, singletons, maximize)% CMP_INFERENCE Compare several inference engines on a DBN% [err, time, engine] = cmp_inference(bnet, engine, exact, T, filter, singletons, maximize)%% engine{i} is the i'th inference engine.% 'exact' specifies which engines do exact inference - %   we check that these all give the same results.% 'T' is the length of the random sequence we generate.% If filter=1, we do filtering, else smoothing (default: smoothing)% If singletons=1, we compare marginal_nodes, else marginal_family (default: family)%% err(e,n,t) = sum_i | Pr_exact(X(n,t)=i) - Pr_e(X(n,t)=i) |%   where Pr_e = prob. according to engine e% time(e) = elapsed time for doing inference with engine eerr = [];if nargin < 5, filter = 0; endif nargin < 6, singletons = 0; endif nargin < 7, maximize = 0; endcheck_ll = 1;assert(~maximize);E = length(engine);ref = exact(1); % referencess = length(bnet.intra);ev = sample_dbn(bnet, 'length', T);evidence = cell(ss,T);onodes = bnet.observed;evidence(onodes,:) = ev(onodes, :);assert(~filter);for i=1:E  tic;  %[engine{i}, ll(i)] = enter_evidence(engine{i}, evidence, 'maximize', maximize);  [engine{i}, ll(i)] = enter_evidence(engine{i}, evidence);  time(i)=toc;  fprintf('engine %d took %6.4f seconds\n', i, time(i));endcmp = mysetdiff(exact, ref);if check_llfor i=cmp(:)'  if ~approxeq(ll(ref), ll(i))    error(['engine ' num2str(i) ' has wrong ll'])  endendendllhnodes = mysetdiff(1:ss, onodes);m = cell(1,E);for t=1:T  for n=hnodes(:)'    for e=1:E      if singletons	m{e} = marginal_nodes(engine{e}, n, t);      else	m{e} = marginal_family(engine{e}, n, t);      end    end    for e=1:E      assert(isequal(m{e}.domain, m{ref}.domain));    end    for e=cmp(:)'      if ~approxeq(m{ref}.T(:), m{e}.T(:))	str= sprintf('engine %d is wrong; n=%d, t=%d', e, n, t);	error(str)      end    end  endend