LikelihoodWeighting.java

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package edu.tum.cs.bayesnets.inference;

import edu.ksu.cis.bnj.ver3.core.BeliefNode;
import edu.tum.cs.bayesnets.core.BeliefNetworkEx;
import edu.tum.cs.util.Stopwatch;

public class LikelihoodWeighting extends Sampler {
        int[] nodeOrder;
        
        public LikelihoodWeighting(BeliefNetworkEx bn) throws Exception {
                super(bn);
                nodeOrder = bn.getTopologicalOrder();
        }
        
        @Override
        public SampledDistribution _infer() throws Exception {
                // sample
                Stopwatch sw = new Stopwatch();
                createDistribution();
                out.println("sampling...");
                sw.start();
                WeightedSample s = new WeightedSample(bn);
                for(int i = 1; i <= numSamples; i++) {
                        if(i % infoInterval == 0)
                                out.println("  step " + i);                     
                        WeightedSample ret = getWeightedSample(s, nodeOrder, evidenceDomainIndices); 
                        if(ret != null) {
                                addSample(ret);
                                
                                if(false) { // debugging of weighting
                                        out.print("w=" + ret.weight);
                                        for(int j = 0; j < evidenceDomainIndices.length; j++)
                                                if(evidenceDomainIndices[j] == -1) {
                                                        BeliefNode node = nodes[j];                                                     
                                                        out.print(" " + node.getName() + "=" + node.getDomain().getName(s.nodeDomainIndices[j]));
                                                }
                                        out.println();
                                }
                        }
                        if(converged())
                                break;
                }
                sw.stop();
                out.println(String.format("time taken: %.2fs (%.4fs per sample, %.1f trials/sample, %d samples)\n", sw.getElapsedTimeSecs(), sw.getElapsedTimeSecs()/numSamples, dist.getTrialsPerStep(), dist.steps));
                return dist;
        }
        
        public WeightedSample getWeightedSample(WeightedSample s, int[] nodeOrder, int[] evidenceDomainIndices) throws Exception {
                s.trials = 0;
                boolean successful = false;
loop:   while(!successful) {
                        s.weight = 1.0;
                        s.trials++;
                        if(maxTrials > 0 && s.trials > this.maxTrials) {
                                if(!this.skipFailedSteps)
                                        throw new Exception("Could not obtain a countable sample in the maximum allowed number of trials (" + maxTrials + ")");
                                else
                                        return null;
                        }
                        // assign values to the nodes in order
                        for(int i=0; i < nodeOrder.length; i++) {
                                int nodeIdx = nodeOrder[i];
                                int domainIdx = evidenceDomainIndices[nodeIdx];
                                // for evidence nodes, adjust the weight
                                if(domainIdx >= 0) { 
                                        s.nodeDomainIndices[nodeIdx] = domainIdx;
                                        double prob = getCPTProbability(nodes[nodeIdx], s.nodeDomainIndices);
                                        if(prob == 0.0) {
                                                if(debug)
                                                        out.println("!!! evidence probability was 0 at node " + nodes[nodeIdx] + " in step " + (dist.steps+1));
                                                continue loop;
                                        }
                                        s.weight *= prob;
                                } 
                                // for non-evidence nodes, do forward sampling
                                else {
                                        domainIdx = sampleForward(nodes[nodeIdx], s.nodeDomainIndices);
                                        if(domainIdx < 0) {
                                                if(debug)
                                                        out.println("!!! could not sample forward because of column with only 0s in CPT of " + nodes[nodeIdx].getName() + " in step " + (dist.steps+1));
                                                bn.removeAllEvidences();
                                                continue loop;
                                        }
                                        s.nodeDomainIndices[nodeIdx] = domainIdx;
                                }
                        }
                        successful = true;
                }
                return s;               
        }
}

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srldb
Author(s): Dominik Jain, Stefan Waldherr, Moritz Tenorth
autogenerated on Fri Jan 11 09:58:29 2013