diff -u -r1.2 -r1.3
--- ExamplePFA.java	1 Oct 2005 01:35:41 -0000	1.2
+++ ExamplePFA.java	14 Oct 2005 17:53:34 -0000	1.3
@@ -11,10 +11,6 @@

 
 public class ExamplePFA extends Driver
 {

-    public ExamplePFA() {
-	this(false);
-    }
-

     public ExamplePFA(boolean writeLikelihood) 
     {
 	// Begin with a big-scale cluster set, made with the MST:

@@ -55,29 +51,37 @@

 	add(remapTracks);
 
 	// Find clumps within clusters

+	ClumpFinder findClumps = new ClumpFinder("MSTCluster linked", "Track segments linked", "Clumps");
+	add(findClumps);

 
 	// Run likelihood structural analysis

-	if (false) {
-	    ClusterAssociator assoc = null;

+	if (true) {
+	    ClusterAssociator assoc = new ClusterEnergyAssociator();

 	    if (writeLikelihood) {
 		// Obtain and write likelihood histograms

+		System.out.println("ExamplePFA: I will obtain and write out likelihood histograms.");

 		LikelihoodEvaluator eval = new LikelihoodEvaluator();

-		LikelihoodFindingStructuralDriver likelihoodWriter = new LikelihoodFindingStructuralDriver(eval, assoc);

+		eval.addLikelihoodQuantityTrackToTrack(new TrackToTrackDOCA(), 10, 0.0, 50.0, false, true);
+		////eval.addLikelihoodQuantityTrackToTrack(new ClusterToClusterMinDistance(), 5, 0.0, 250.0, false, true);
+		//eval.addLikelihoodQuantityTrackToTrack(new TrackToTrackPOCAInCalorimeter(), 2, -0.5, 1.5, false, false);
+		eval.addLikelihoodQuantityTrackToTrack(new TrackToTrackSmallestDistanceToPOCA(), 5, 0.0, 50.0, false, true);
+		//eval.addLikelihoodQuantityTrackToTrack(new TrackToTrackIntermediateHitsCount(), 10, -0.5, 9.5, false, true);
+		//eval.addLikelihoodQuantityTrackToTrack(new TrackToTrackIntermediateHitsFraction(), 11, -0.05, 1.05, false, false);
+		eval.addLikelihoodQuantityTrackToClump(new TrackToClumpDOCA(), 5, 0.0, 250.0, false, true);
+		eval.addLikelihoodQuantityTrackToClump(new ClusterToClusterMinDistance(), 5, 0.0, 250.0, false, true);
+		eval.addLikelihoodQuantityClumpToClump(new ClumpToClumpDOCA(), 5, 0.0, 500.0, false, true);
+		eval.addLikelihoodQuantityClumpToClump(new ClusterToClusterMinDistance(), 5, 0.0, 500.0, false, true);
+		LikelihoodFindingStructuralDriver likelihoodWriter = new LikelihoodFindingStructuralDriver(eval, assoc, "MSTCluster linked", "Track segments linked", "Clumps");
+		likelihoodWriter.setIgnoreClusterDecision(new ClusterSizeDecision(10));

 		add(likelihoodWriter);

+                Driver checkpoint = new LikelihoodEvaluatorCheckpointDriver(eval, 10);
+		add(checkpoint);

 	    } else {
 		// Use pre-existing likelihood histograms to check clusters

+		System.out.println("ExamplePFA: I will read in likelihood histograms and use them to make clusters.");

 		LikelihoodEvaluator eval = LikelihoodEvaluator.readFromFile("likelihood.bin");

-		eval.addLikelihoodQuantityTrackToTrack(new TrackToTrackDOCA(), 10, 0.0, 5.0, false, true);
-		eval.addLikelihoodQuantityTrackToTrack(new TrackToTrackPOCAInCalorimeter(), 2, -0.5, 1.5, false, false);
-		eval.addLikelihoodQuantityTrackToTrack(new TrackToTrackSmallestDistanceToPOCA(), 5, 0.0, 5.0, false, true);
-		eval.addLikelihoodQuantityTrackToTrack(new TrackToTrackIntermediateHitsCount(), 10, -0.5, 9.5, false, true);
-		eval.addLikelihoodQuantityTrackToTrack(new TrackToTrackIntermediateHitsFraction(), 11, -0.05, 1.05, false, false);
-		eval.addLikelihoodQuantityTrackToClump(new TrackToClumpDOCA(), 5, 0.0, 25.0, false, true);
-		eval.addLikelihoodQuantityTrackToClump(new ClusterToClusterMinDistance(), 5, 0.0, 25.0, false, true);
-		eval.addLikelihoodQuantityClumpToClump(new ClumpToClumpDOCA(), 5, 0.0, 50.0, false, true);
-		eval.addLikelihoodQuantityClumpToClump(new ClusterToClusterMinDistance(), 5, 0.0, 50.0, false, true);
-		
-		LikelihoodLinkPlotterDriver likelihoodPlotter = new LikelihoodLinkPlotterDriver(eval, 0.5, 0.5, 0.5, assoc);

+		LikelihoodLinkPlotterDriver likelihoodPlotter = new LikelihoodLinkPlotterDriver(eval, 0.5, 0.5, 0.5, assoc, "MSTCluster linked", "Track segments linked", "Clumps", "MapClustersToSkeletons");
+		likelihoodPlotter.setIgnoreClusterDecision(new ClusterSizeDecision(10));

 		likelihoodPlotter.initPlots("likelihoodPerformance.aida");
 		add(likelihoodPlotter);
 	    }