AIMA.Probability.Bayes.Approx.LikelihoodWeighting.weightedSample C# (CSharp) Method

        public Pair<Map<RandomVariable, Object>, Double> weightedSample(
            BayesianNetwork bn, AssignmentProposition[] e)
        {
            // w <- 1;
            double w = 1.0;
            // <b>x</b> <- an event with n elements initialized from e
            Map<RandomVariable, Object> x = new LinkedHashMap<RandomVariable, Object>();
            foreach (AssignmentProposition ap in
            e)
            {
                x.Add(ap.getTermVariable(), ap.getValue());
            }

            // foreach variable X<sub>i</sub> in X<sub>1</sub>,...,X<sub>n</sub> do
            foreach (RandomVariable Xi in
            bn.getVariablesInTopologicalOrder())
            {
                // if X<sub>i</sub> is an evidence variable with value x<sub>i</sub>
                // in e
                if (x.ContainsKey(Xi))
                {
                    // then w <- w * P(X<sub>i</sub> = x<sub>i</sub> |
                    // parents(X<sub>i</sub>))
                    w *= bn.getNode(Xi)
                        .getCPD()
                        .getValue(
                            ProbUtil.getEventValuesForXiGivenParents(
                                bn.getNode(Xi), x));
                }
                else
                {
                    // else <b>x</b>[i] <- a random sample from
                    // <b>P</b>(X<sub>i</sub> | parents(X<sub>i</sub>))
                    x.Add(Xi, ProbUtil.randomSample(bn.getNode(Xi), x, randomizer));
                }
            }
            // return <b>x</b>, w
            return new Pair<Map<RandomVariable, Object>, Double>(x, w);
        }