function gdl = mk_gdl_graph(G, domains, node_sizes, kernels, varargin)% MK_GDL_GRAPH Make a GDL (generalized distributed law) graph% gdl = mk_gdl_graph(G, domains, node_sizes, kernels, ...)%% A GDL graph is like a moralized, but untriangulated, Bayes net:% each "node" represents a domain with a corresponding kernel function.% For details, see "The Generalized Distributive Law", Aji and McEliece,% IEEE Trans. Info. Theory, 46(2): 325--343, 2000% % G(i,j) = 1 if there is an (undirected) edge between domains i,j%% domains{i} is the domain of node i%% 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.% node_sizes(i) = 1 if i is a utility node.%% kernels is the list of 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]% chance   - the list of nodes which are random variables [1:N]% decision - the list of nodes which are decision nodes [ [] ]% utility  - the list of nodes which are utility nodes [ [] ]ns = node_sizes;N = length(domains);vars = [];for i=1:N  vars = myunion(vars, domains{i});endNvars  = length(vars);gdl.equiv_class = 1:length(kernels);gdl.chance_nodes = 1:Nvars;gdl.utility_nodes = [];gdl.decision_nodes = [];gdl.dnodes = 1:Nvars;if nargin >= 5  args = varargin;  nargs = length(args);  for i=1:2:nargs    switch args{i},     case 'equiv_class', bnet.equiv_class = args{i+1};      case 'chance',      bnet.chance_nodes = args{i+1};      case 'utility',     bnet.utility_nodes = args{i+1};      case 'decision',    bnet.decision_nodes = args{i+1};      case 'discrete',    bnet.dnodes = args{i+1};      otherwise,        error(['invalid argument name ' args{i}]);           end  endendgdl.G = G;gdl.vars = vars;gdl.doms = domains;gdl.node_sizes = node_sizes;gdl.cnodes = mysetdiff(vars, gdl.dnodes);gdl.kernels = kernels;gdl.type = 'gdl';% Compute a bit vector representation of the set of domains% dom_bitv(i,j) = 1 iff variable j occurs in domain igdl.dom_bitv = zeros(N, length(vars));for i=1:N  gdl.dom_bitv(i, domains{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(G, i);  gdl.nbrs{i} = nbrs;  for j = nbrs(:)'    gdl.sepset{i,j} = myintersect(domains{i}, domains{j});  endend