wolffd@0: function CPD = tabular_decision_node(bnet, self, CPT)
wolffd@0: % TABULAR_DECISION_NODE Represent a stochastic policy over a discrete decision/action node as a table
wolffd@0: % CPD = tabular_decision_node(bnet, self, CPT)
wolffd@0: %
wolffd@0: % node is the number of a node in this equivalence class.
wolffd@0: % CPT is an optional argument (see tabular_CPD for details); by default, it is the uniform policy.
wolffd@0: 
wolffd@0: if nargin==0
wolffd@0:   % This occurs if we are trying to load an object from a file.
wolffd@0:   CPD = init_fields;
wolffd@0:   CPD = class(CPD, 'tabular_decision_node', discrete_CPD(1, []));
wolffd@0:   return;
wolffd@0: elseif isa(bnet, 'tabular_decision_node')
wolffd@0:   % This might occur if we are copying an object.
wolffd@0:   CPD = bnet;
wolffd@0:   return;
wolffd@0: end
wolffd@0: CPD = init_fields;
wolffd@0: 
wolffd@0: ns = bnet.node_sizes;
wolffd@0: fam = family(bnet.dag, self);
wolffd@0: ps = parents(bnet.dag, self);
wolffd@0: sz = ns(fam);
wolffd@0: 
wolffd@0: if nargin < 3
wolffd@0:   CPT = mk_stochastic(myones(sz)); 
wolffd@0: else
wolffd@0:   CPT = myreshape(CPT, sz);
wolffd@0: end
wolffd@0: 
wolffd@0: CPD.CPT = CPT;
wolffd@0: CPD.sizes = sz; 
wolffd@0: 
wolffd@0: clamped = 1; % don't update using EM
wolffd@0: CPD = class(CPD, 'tabular_decision_node', discrete_CPD(clamped, ns([ps self])));
wolffd@0: 
wolffd@0: %%%%%%%%%%%
wolffd@0: 
wolffd@0: function CPD = init_fields()
wolffd@0: % This ensures we define the fields in the same order 
wolffd@0: % no matter whether we load an object from a file,
wolffd@0: % or create it from scratch. (Matlab requires this.)
wolffd@0: 
wolffd@0: CPD.CPT = [];
wolffd@0: CPD.sizes = [];