FIX: performance measures take algorithm representing the input tree

src/mhtree/benchmarking/PerformanceMeasures.java

 package mhtree.benchmarking;
 
+import messif.algorithms.Algorithm;
+import messif.algorithms.AlgorithmMethodException;
 import messif.objects.util.DistanceRankedObject;
 import messif.objects.util.RankedAbstractObject;
 import messif.operations.query.ApproxKNNQueryOperation;
 import messif.operations.query.KNNQueryOperation;
-import messif.utility.reflection.NoSuchInstantiatorException;
 
-import java.lang.reflect.InvocationTargetException;
 import java.util.ArrayList;
 import java.util.HashMap;
 import java.util.List;
@@ -16,13 +16,9 @@ import java.util.stream.Collectors;
 
 public class PerformanceMeasures {
 
-    public static double measureErrorOnThePosition(ApproxKNNQueryOperation approxKNNQueryOperation, Tree tree) {
+    public static double measureErrorOnThePosition(ApproxKNNQueryOperation approxKNNQueryOperation, Algorithm tree) throws NoSuchMethodException, AlgorithmMethodException {
         KNNQueryOperation rankedObjects = new KNNQueryOperation(approxKNNQueryOperation.getQueryObject(), tree.getObjectCount());
-        try {
-            tree.kNN(rankedObjects);
-        } catch (ClassNotFoundException | NoSuchInstantiatorException | InvocationTargetException e) {
-            e.printStackTrace();
-        }
+        tree.executeOperation(rankedObjects);
 
         Map<String, Integer> IDtoPosition = new HashMap<>(rankedObjects.getAnswerCount());
 
@@ -44,15 +40,11 @@ public class PerformanceMeasures {
     }
 
     // comparing done based on distances, counts how many of the same distances of KNNQueryOperation were presents in the answer of ApproxKNNQueryOperation
-    public static double measureRecall(ApproxKNNQueryOperation approxKNNQueryOperation, Tree tree) {
+    public static double measureRecall(ApproxKNNQueryOperation approxKNNQueryOperation, Algorithm tree) throws NoSuchMethodException, AlgorithmMethodException {
         if (approxKNNQueryOperation.getAnswerCount() == 0) return 0d;
 
         KNNQueryOperation knnQueryOperation = new KNNQueryOperation(approxKNNQueryOperation.getQueryObject(), approxKNNQueryOperation.getK());
-        try {
-            tree.kNN(knnQueryOperation);
-        } catch (ClassNotFoundException | NoSuchInstantiatorException | InvocationTargetException e) {
-            e.printStackTrace();
-        }
+        tree.executeOperation(knnQueryOperation);
 
         List<RankedAbstractObject> objects = new ArrayList<>(knnQueryOperation.getAnswerCount());
         for (RankedAbstractObject object : knnQueryOperation)