AIMA.Probability.FullJointDistributionModel.jointDistribution C# (CSharp) Метод

        public CategoricalDistribution jointDistribution(
            params IProposition[] propositions)
        {
            ProbabilityTable d = null;
            IProposition conjProp = ProbUtil
                .constructConjunction(propositions);
            LinkedHashSet<RandomVariable> vars = new LinkedHashSet<RandomVariable>(
                conjProp.getUnboundScope());

            if (vars.Count > 0)
            {
                RandomVariable[] distVars = new RandomVariable[vars.Count];
                vars.CopyTo(distVars);

                ProbabilityTable ud = new ProbabilityTable(distVars);
                Object[] values = new Object[vars.Count];

                //ProbabilityTable.Iterator di = new ProbabilityTable.Iterator() {

                //    public void iterate(Map<RandomVariable, Object> possibleWorld,
                //            double probability) {
                //        if (conjProp.holds(possibleWorld)) {
                //            int i = 0;
                //            for (RandomVariable rv : vars) {
                //                values[i] = possibleWorld.get(rv);
                //                i++;
                //            }
                //            int dIdx = ud.getIndex(values);
                //            ud.setValue(dIdx, ud.getValues()[dIdx] + probability);
                //        }
                //    }
                //};

                //distribution.iterateOverTable(di);
                // TODO:
                d = ud;
            }
            else
            {
                // No Unbound Variables, therefore just return
                // the singular probability related to the proposition.
                d = new ProbabilityTable();
                d.setValue(0, prior(propositions));
            }
            return d;
        }