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