comparison toolboxes/FullBNT-1.0.7/bnt/general/mk_fgraph.m @ 0:e9a9cd732c1e tip

first hg version after svn

+function fg = mk_fgraph(G, node_sizes, factors, varargin)
+% MK_FGRAPH Make a factor graph
+% fg = mk_fgraph(G, node_sizes, factors, ...)
+%
+% A factor graph is a bipartite graph, with one side containing variables,
+% and the other containing functions of (subsets of) these variables.
+% For details, see "Factor Graphs and the Sum-Product Algorithm",
+%  F. Kschischang and B. Frey and H-A. Loeliger,
+%  IEEE Trans. Info. Theory, 2001
+%
+% G(i,j) = 1 if there is an arc from variable i to factor j
+%
+% node_sizes(i) is the number of values node i can take on,
+%   or the length of node i if i is a continuous-valued vector.
+%
+% 'factors' is the list of factors (kernel functions)
+%
+% The list below gives optional arguments [default value in brackets].
+% 
+% equiv_class - equiv_class(i)=j  means factor node i gets its params from factors{j} [1:F]
+% discrete - the list of nodes which are discrete random variables [1:N]
+%
+% e.g., fg = mk_fgraph(G, [2 2], {bnet.CPD{1},bnet.CPD{2}}, 'discrete', [1 2])
+
+fg.G = G;
+fg.node_sizes = node_sizes;
+fg.factors = factors;
+[fg.nvars fg.nfactors] = size(G);
+
+% default values for parameters
+fg.equiv_class = 1:fg.nfactors;
+fg.dnodes = 1:fg.nvars;
+
+if nargin >= 4
+  args = varargin;
+  nargs = length(args);
+  for i=1:2:nargs
+    switch args{i},
+     case 'equiv_class', fg.equiv_class = args{i+1}; 
+     case 'discrete',    fg.dnodes = args{i+1}; 
+     otherwise,  
+      error(['invalid argument name ' args{i}]);       
+    end
+  end
+end
+
+% so that determine_pot_type will work...
+fg.utility_nodes = [];
+%fg.decision_nodes = [];
+%fg.chance_nodes = fg.nvars;
+
+fg.dom = cell(1, fg.nfactors);
+for f=1:fg.nfactors
+  fg.dom{f} = find(G(:,f));
+end
+fg.dep = cell(1, fg.nvars);
+for x=1:fg.nvars
+  fg.dep{x} = find(G(x,:));
+end
+fg.cnodes = mysetdiff(1:fg.nvars, fg.dnodes);