1 files changed, 10 insertions, 10 deletions

diff --git a/src/de/lmu/ifi/dbs/elki/algorithm/clustering/DBSCAN.java b/src/de/lmu/ifi/dbs/elki/algorithm/clustering/DBSCAN.java
index fcf81faa..57dcb435 100644
--- a/src/de/lmu/ifi/dbs/elki/algorithm/clustering/DBSCAN.java
+++ b/src/de/lmu/ifi/dbs/elki/algorithm/clustering/DBSCAN.java
@@ -4,7 +4,7 @@ package de.lmu.ifi.dbs.elki.algorithm.clustering;
  This file is part of ELKI:
  Environment for Developing KDD-Applications Supported by Index-Structures
 
- Copyright (C) 2012
+ Copyright (C) 2013
  Ludwig-Maximilians-Universität München
  Lehr- und Forschungseinheit für Datenbanksysteme
  ELKI Development Team
@@ -40,10 +40,10 @@ import de.lmu.ifi.dbs.elki.database.ids.DBIDRef;
 import de.lmu.ifi.dbs.elki.database.ids.DBIDUtil;
 import de.lmu.ifi.dbs.elki.database.ids.HashSetModifiableDBIDs;
 import de.lmu.ifi.dbs.elki.database.ids.ModifiableDBIDs;
+import de.lmu.ifi.dbs.elki.database.ids.distance.DistanceDBIDList;
 import de.lmu.ifi.dbs.elki.database.query.range.RangeQuery;
 import de.lmu.ifi.dbs.elki.database.relation.Relation;
 import de.lmu.ifi.dbs.elki.distance.distancefunction.DistanceFunction;
-import de.lmu.ifi.dbs.elki.distance.distanceresultlist.DistanceDBIDResult;
 import de.lmu.ifi.dbs.elki.distance.distancevalue.Distance;
 import de.lmu.ifi.dbs.elki.logging.Logging;
 import de.lmu.ifi.dbs.elki.logging.progress.FiniteProgress;
@@ -140,7 +140,7 @@ public class DBSCAN<O, D extends Distance<D>> extends AbstractDistanceBasedAlgor
 
     FiniteProgress objprog = LOG.isVerbose() ? new FiniteProgress("Processing objects", size, LOG) : null;
     IndefiniteProgress clusprog = LOG.isVerbose() ? new IndefiniteProgress("Number of clusters", LOG) : null;
-    resultList = new ArrayList<ModifiableDBIDs>();
+    resultList = new ArrayList<>();
     noise = DBIDUtil.newHashSet();
     processedIDs = DBIDUtil.newHashSet(size);
     if(size < minpts) {
@@ -170,14 +170,14 @@ public class DBSCAN<O, D extends Distance<D>> extends AbstractDistanceBasedAlgor
       clusprog.setCompleted(LOG);
     }
 
-    Clustering<Model> result = new Clustering<Model>("DBSCAN Clustering", "dbscan-clustering");
+    Clustering<Model> result = new Clustering<>("DBSCAN Clustering", "dbscan-clustering");
     for(ModifiableDBIDs res : resultList) {
       Cluster<Model> c = new Cluster<Model>(res, ClusterModel.CLUSTER);
-      result.addCluster(c);
+      result.addToplevelCluster(c);
     }
 
     Cluster<Model> n = new Cluster<Model>(noise, true, ClusterModel.CLUSTER);
-    result.addCluster(n);
+    result.addToplevelCluster(n);
 
     return result;
   }
@@ -193,7 +193,7 @@ public class DBSCAN<O, D extends Distance<D>> extends AbstractDistanceBasedAlgor
    * @param objprog the progress object for logging the current status
    */
   protected void expandCluster(Relation<O> relation, RangeQuery<O, D> rangeQuery, DBIDRef startObjectID, FiniteProgress objprog, IndefiniteProgress clusprog) {
-    DistanceDBIDResult<D> neighbors = rangeQuery.getRangeForDBID(startObjectID, epsilon);
+    DistanceDBIDList<D> neighbors = rangeQuery.getRangeForDBID(startObjectID, epsilon);
 
     // startObject is no core-object
     if(neighbors.size() < minpts) {
@@ -224,7 +224,7 @@ public class DBSCAN<O, D extends Distance<D>> extends AbstractDistanceBasedAlgor
 
     while(seeds.size() > 0) {
       DBIDMIter o = seeds.iter();
-      DistanceDBIDResult<D> neighborhood = rangeQuery.getRangeForDBID(o, epsilon);
+      DistanceDBIDList<D> neighborhood = rangeQuery.getRangeForDBID(o, epsilon);
       o.remove();
 
       if(neighborhood.size() >= minpts) {
@@ -289,7 +289,7 @@ public class DBSCAN<O, D extends Distance<D>> extends AbstractDistanceBasedAlgor
     @Override
     protected void makeOptions(Parameterization config) {
       super.makeOptions(config);
-      DistanceParameter<D> epsilonP = new DistanceParameter<D>(EPSILON_ID, distanceFunction);
+      DistanceParameter<D> epsilonP = new DistanceParameter<>(EPSILON_ID, distanceFunction);
       if(config.grab(epsilonP)) {
         epsilon = epsilonP.getValue();
       }
@@ -303,7 +303,7 @@ public class DBSCAN<O, D extends Distance<D>> extends AbstractDistanceBasedAlgor
 
     @Override
     protected DBSCAN<O, D> makeInstance() {
-      return new DBSCAN<O, D>(distanceFunction, epsilon, minpts);
+      return new DBSCAN<>(distanceFunction, epsilon, minpts);
     }
   }
 }
\ No newline at end of file