Import Debian changes 0.5.0-1

elki (0.5.0-1) unstable; urgency=low

  * New upstream release: 0.5.0 final.

1 files changed, 7 insertions, 4 deletions

diff --git a/src/de/lmu/ifi/dbs/elki/database/query/knn/LinearScanPrimitiveDistanceKNNQuery.java b/src/de/lmu/ifi/dbs/elki/database/query/knn/LinearScanPrimitiveDistanceKNNQuery.java
index 07632a34..59987282 100644
--- a/src/de/lmu/ifi/dbs/elki/database/query/knn/LinearScanPrimitiveDistanceKNNQuery.java
+++ b/src/de/lmu/ifi/dbs/elki/database/query/knn/LinearScanPrimitiveDistanceKNNQuery.java
@@ -30,6 +30,8 @@ import java.util.Map.Entry;
 
 import de.lmu.ifi.dbs.elki.database.ids.ArrayDBIDs;
 import de.lmu.ifi.dbs.elki.database.ids.DBID;
+import de.lmu.ifi.dbs.elki.database.ids.DBIDIter;
+import de.lmu.ifi.dbs.elki.database.ids.DBIDRef;
 import de.lmu.ifi.dbs.elki.database.query.distance.PrimitiveDistanceQuery;
 import de.lmu.ifi.dbs.elki.distance.distancevalue.Distance;
 import de.lmu.ifi.dbs.elki.utilities.datastructures.heap.KNNHeap;
@@ -63,7 +65,8 @@ public class LinearScanPrimitiveDistanceKNNQuery<O, D extends Distance<D>> exten
   protected void linearScanBatchKNN(List<O> objs, List<KNNHeap<D>> heaps) {
     final int size = objs.size();
     // Linear scan style KNN.
-    for(DBID candidateID : relation.iterDBIDs()) {
+    for(DBIDIter iter = relation.getDBIDs().iter(); iter.valid(); iter.advance()) {
+      DBID candidateID = iter.getDBID();
       O candidate = relation.get(candidateID);
       for(int index = 0; index < size; index++) {
         O object = objs.get(index);
@@ -74,7 +77,7 @@ public class LinearScanPrimitiveDistanceKNNQuery<O, D extends Distance<D>> exten
   }
 
   @Override
-  public KNNResult<D> getKNNForDBID(DBID id, int k) {
+  public KNNResult<D> getKNNForDBID(DBIDRef id, int k) {
     return getKNNForObject(relation.get(id), k);
   }
 
@@ -83,9 +86,9 @@ public class LinearScanPrimitiveDistanceKNNQuery<O, D extends Distance<D>> exten
     final int size = ids.size();
     final List<KNNHeap<D>> heaps = new ArrayList<KNNHeap<D>>(size);
     List<O> objs = new ArrayList<O>(size);
-    for(DBID id : ids) {
+    for(DBIDIter iter = ids.iter(); iter.valid(); iter.advance()) {
       heaps.add(new KNNHeap<D>(k));
-      objs.add(relation.get(id));
+      objs.add(relation.get(iter));
     }
     linearScanBatchKNN(objs, heaps);