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

first hg version after svn

+function engine = belprop_gdl_inf_engine(gdl, varargin) 
+% BELPROP_GDL_INF_ENGINE Make a belief propagation inference engine for a GDL graph
+% engine = belprop_gdl_inf_engine(gdl_graph, ...)
+%
+% If the GDL graph is a tree, this will give exact results.
+%
+% The following optional arguments can be specified in the form of name/value pairs:
+% [default in brackets]
+% e.g., engine = belprop_inf_engine(gdl, 'tol', 1e-2, 'max_iter', 10)
+%
+% 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]
+
+
+engine = init_fields;
+engine = class(engine, 'belprop_gdl_inf_engine');
+
+% set default params
+N = length(gdl.G);
+engine.protocol = 'parallel';
+engine.max_iter = 2*N;
+engine.momentum = 0;
+engine.tol = 1e-3;
+engine.maximize = 0;
+
+engine = set_params(engine, varargin);
+
+engine.gdl = gdl;
+
+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(gdl.G, root);
+  assert(~cyclic);
+end
+
+% store results computed by enter_evidence here
+ndoms = length(gdl.doms);
+nvars = length(gdl.vars);
+engine.marginal_domains = cell(1, ndoms);
+
+% to compute the marginal on each variable, we need to know which domain to marginalize
+% and we want to choose the lightest. We compute the weight once we have seen the evidence.
+engine.dom_weight = [];
+engine.evidence = [];
+
+
+%%%%%%%%%
+
+function engine = init_fields()
+
+engine.protocol = [];
+engine.gdl = [];
+engine.max_iter = [];
+engine.momentum = [];
+engine.tol = [];
+engine.maximize = [];
+engine.marginal_domains = [];
+engine.evidence = [];
+engine.tree = [];
+engine.preorder = [];
+engine.postorder = [];
+engine.dom_weight = [];