- reengineered matrixbased distances

src/fr/inrialpes/exmo/align/impl/MatrixMeasure.java

@@ -21,12 +21,13 @@
 package fr.inrialpes.exmo.align.impl; 
 
 import java.util.Iterator;
-import java.util.Vector;
+import java.util.HashMap;
 import java.net.URI;
 
 import org.semanticweb.owl.model.OWLOntology;
 import org.semanticweb.owl.model.OWLClass;
 import org.semanticweb.owl.model.OWLProperty;
+import org.semanticweb.owl.model.OWLIndividual;
 import org.semanticweb.owl.model.OWLException;
 
 import org.semanticweb.owl.align.Alignment;
@@ -58,10 +59,11 @@ public abstract class MatrixMeasure implements Similarity {
     public int nbprop2 = 0; // number of classes in onto2
     public int i, j = 0;     // index for onto1 and onto2 classes
     public int l1, l2 = 0;   // length of strings (for normalizing)
-    public Vector classlist2 = null; // onto2 classes
-    public Vector classlist1 = null; // onto1 classes
-    public Vector proplist2 = null; // onto2 classes
-    public Vector proplist1 = null; // onto1 classes
+    public HashMap classlist2 = null; // onto2 classes
+    public HashMap classlist1 = null; // onto1 classes
+    public HashMap proplist2 = null; // onto2 properties
+    public HashMap proplist1 = null; // onto1 properties
+
     public double clmatrix[][];   // distance matrix
     public double prmatrix[][];   // distance matrix
 	
@@ -73,40 +75,47 @@ public abstract class MatrixMeasure implements Similarity {
     public void initialize( OWLOntology o1, OWLOntology o2 ){
 	onto1 = o1;
 	onto2 = o2;
-	classlist2 = new Vector(10); // onto2 classes
-	classlist1 = new Vector(10); // onto1 classes
-	proplist2 = new Vector(10); // onto2 classes
-	proplist1 = new Vector(10); // onto1 classes
+	classlist2 = new HashMap(); // onto2 classes
+	classlist1 = new HashMap(); // onto1 classes
+	proplist2 = new HashMap(); // onto2 properties
+	proplist1 = new HashMap(); // onto1 properties
 
 	try {
 	    // Create class lists
 	    for ( Iterator it = onto2.getClasses().iterator(); it.hasNext(); nbclass2++ ){
-		classlist2.add( it.next() );
+		classlist2.put( it.next(), new Integer(nbclass2) );
 	    }
 	    for ( Iterator it = onto1.getClasses().iterator(); it.hasNext(); nbclass1++ ){
-		classlist1.add( it.next() );
+		classlist1.put( it.next(), new Integer(nbclass1)  );
 	    }
 	    clmatrix = new double[nbclass1+1][nbclass2+1];
 
 	    // Create property lists
 	    for ( Iterator it = onto2.getObjectProperties().iterator(); it.hasNext(); nbprop2++ ){
-		proplist2.add( it.next() );
+		proplist2.put( it.next(), new Integer(nbprop2) );
 	    }
 	    for ( Iterator it = onto2.getDataProperties().iterator(); it.hasNext(); nbprop2++ ){
-		proplist2.add( it.next() );
+		proplist2.put( it.next(), new Integer(nbprop2)  );
 	    }
 	    for ( Iterator it = onto1.getObjectProperties().iterator(); it.hasNext(); nbprop1++ ){
-		proplist1.add( it.next() );
+		proplist1.put( it.next(), new Integer(nbprop1) );
 	    }
 	    for ( Iterator it = onto1.getDataProperties().iterator(); it.hasNext(); nbprop1++ ){
-		proplist1.add( it.next() );
+		proplist1.put( it.next(), new Integer(nbprop1) );
 	    }
 	    prmatrix = new double[nbprop1+1][nbprop2+1];
 	} catch (OWLException e) { e.printStackTrace(); };
     }
 
-    public double getSimilarity( URI uri1, URI uri2 ){
+    public double getIndividualSimilarity( OWLIndividual i1, OWLIndividual i2 ){
 	// JE: non finished...
+        int i,j = 0;
 	return 0.;
     }
+    public double getClassSimilarity( OWLClass c1, OWLClass c2 ){
+	return clmatrix[((Integer)classlist1.get(c1)).intValue()][((Integer)classlist2.get(c2)).intValue()];
+    }
+    public double getPropertySimilarity( OWLProperty p1, OWLProperty p2 ){
+	return prmatrix[((Integer)proplist1.get(p1)).intValue()][((Integer)proplist2.get(p2)).intValue()];
+    }
 }