AIMA.Probability.Bayes.Impl.DynamicBayesNet.DynamicBayesNet C# (CSharp) 메소드

        public DynamicBayesNet(BayesianNetwork priorNetwork,
                               Map<RandomVariable, RandomVariable> X_0_to_X_1,
                               Set<RandomVariable> E_1, params Node[] rootNodes)
            : base(rootNodes)
        {


            foreach (RandomVariable rv in X_0_to_X_1.keySet()
                )
            {
                RandomVariable x0 = rv;
                RandomVariable x1 = X_0_to_X_1[rv];
                this.X_0.add(x0);
                this.X_1.add(x1);
                this.X_0_to_X_1.put(x0, x1);
                this.X_1_to_X_0.put(x1, x0);
            }
            this.E_1.addAll(new List<RandomVariable>(E_1));

            // Assert the X_0, X_1, and E_1 sets are of expected sizes
            Set<RandomVariable> combined = new Set<RandomVariable>();
            combined.addAll(new List<RandomVariable>(X_0));
            combined.addAll(new List<RandomVariable>(X_1));
            combined.addAll(new List<RandomVariable>(E_1));
            if (
                SetOps.difference(new List<RandomVariable>(varToNodeMap.keySet()), new List<RandomVariable>(combined)).
                    Count != 0)
            {
                throw new IllegalArgumentException(
                    "X_0, X_1, and E_1 do not map correctly to the Nodes describing this Dynamic Bayesian Network.");
            }
            this.priorNetwork = priorNetwork;

            X_1_VariablesInTopologicalOrder
                .AddRange(getVariablesInTopologicalOrder());
            X_1_VariablesInTopologicalOrder.RemoveAll(X_0);
            X_1_VariablesInTopologicalOrder.RemoveAll(E_1);
        }