comparison toolboxes/FullBNT-1.0.7/bnt/inference/static/@belprop_inf_engine/belprop_inf_engine.m @ 0:e9a9cd732c1e tip

first hg version after svn

+function engine = belprop_inf_engine(bnet, varargin) 
+% BELPROP_INF_ENGINE Make a loopy belief propagation inference engine
+% engine = belprop_inf_engine(bnet, ...)
+%
+% This is like pearl_inf_engine, except it uses potential objects,
+% instead of lambda/pi structs. Hence it is slower.
+%
+% The following optional arguments can be specified in the form of name/value pairs:
+% [default in brackets]
+%
+% protocol - 'tree' means send messages up then down the tree,
+%            'parallel' means use synchronous updates ['parallel']
+% max_iter - max. num. iterations [ 2*num_nodes ]
+% momentum - weight assigned to old message in convex combination (useful for damping oscillations) [0]
+% tol      - tolerance used to assess convergence [1e-3]
+% maximize - 1 means use max-product, 0 means use sum-product [0]
+% filename - name of file to write beliefs to after each iteration within enter_evidence [ [] ]
+%
+% e.g., engine = belprop_inf_engine(bnet, 'maximize', 1, 'max_iter', 10)
+
+% gdl = general distributive law
+engine.gdl = bnet_to_gdl(bnet);
+
+% set default params
+N = length(engine.gdl.G);
+engine.protocol = 'parallel';
+engine.max_iter = 2*N;
+engine.momentum = 0;
+engine.tol = 1e-3;
+engine.maximize = 0;
+engine.filename = [];
+engine.fid = [];
+
+args = varargin;
+nargs = length(args);
+for i=1:2:nargs
+  switch args{i},
+   case 'max_iter', engine.max_iter = args{i+1};
+   case 'momentum', engine.momentum = args{i+1};
+   case 'tol',      engine.tol = args{i+1};
+   case 'protocol', engine.protocol = args{i+1};
+   case 'filename', engine.filename = args{i+1};
+   otherwise,
+    error(['invalid argument name ' args{i}]);
+  end
+end
+
+
+if strcmp(engine.protocol, 'tree')
+  % Make a rooted tree, so there is a fixed message passing order.
+  root = N;
+  [engine.tree, engine.preorder, engine.postorder, height, cyclic] = mk_rooted_tree(engine.gdl.G, root);
+  assert(~cyclic);
+end
+
+% store results computed by enter_evidence here
+engine.marginal_domains = cell(1, N);
+
+engine.niter = [];
+
+engine = class(engine, 'belprop_inf_engine', inf_engine(bnet));
+
+%%%%%%%%%
+
+function gdl = bnet_to_gdl(bnet)
+
+gdl.G = mk_undirected(bnet.dag);
+N = length(bnet.dag);
+gdl.doms = cell(1,N);
+for i=1:N
+  gdl.doms{i} = family(bnet.dag, i);
+end 
+
+% Compute a bit vector representation of the set of domains
+% dom_bitv(i,j) = 1 iff variable j occurs in domain i
+gdl.dom_bitv = zeros(N, N);
+for i=1:N
+  gdl.dom_bitv(i, gdl.doms{i}) = 1;
+end
+   
+% compute the interesection of the domains on either side of each edge (separating set)
+gdl.sepset = cell(N, N);
+gdl.nbrs = cell(1,N);
+for i=1:N
+  nbrs = neighbors(gdl.G, i);
+  gdl.nbrs{i} = nbrs;
+  for j = nbrs(:)'
+    gdl.sepset{i,j} = myintersect(gdl.doms{i}, gdl.doms{j});
+  end
+end