1 files changed, 6 insertions, 5 deletions
diff --git a/src/de/lmu/ifi/dbs/elki/algorithm/outlier/spatial/CTLuRandomWalkEC.java b/src/de/lmu/ifi/dbs/elki/algorithm/outlier/spatial/CTLuRandomWalkEC.java
index 0fe65fee..a6425d43 100644
--- a/src/de/lmu/ifi/dbs/elki/algorithm/outlier/spatial/CTLuRandomWalkEC.java
+++ b/src/de/lmu/ifi/dbs/elki/algorithm/outlier/spatial/CTLuRandomWalkEC.java
@@ -3,7 +3,7 @@ package de.lmu.ifi.dbs.elki.algorithm.outlier.spatial;
 This file is part of ELKI:
 Environment for Developing KDD-Applications Supported by Index-Structures
 
-Copyright (C) 2011
+Copyright (C) 2012
 Ludwig-Maximilians-Universität München
 Lehr- und Forschungseinheit für Datenbanksysteme
 ELKI Development Team
@@ -31,6 +31,7 @@ import de.lmu.ifi.dbs.elki.data.type.VectorFieldTypeInformation;
 import de.lmu.ifi.dbs.elki.database.datastore.DataStoreFactory;
 import de.lmu.ifi.dbs.elki.database.datastore.DataStoreUtil;
 import de.lmu.ifi.dbs.elki.database.datastore.WritableDataStore;
+import de.lmu.ifi.dbs.elki.database.datastore.WritableDoubleDataStore;
 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.DBIDUtil;
@@ -196,13 +197,13 @@ public class CTLuRandomWalkEC<N, D extends NumberDistance<D, ?>> extends Abstrac
     for(int i = 0; i < ids.size(); i++) {
       DBID id = ids.get(i);
       // Note: matrix times ith unit vector = ith column
-      Vector sim = E.getColumnVector(i);
+      Vector sim = E.getCol(i);
       similarityVectors.put(id, sim);
     }
     E = null;
     // compute the relevance scores between specified Object and its neighbors
     DoubleMinMax minmax = new DoubleMinMax();
-    WritableDataStore<Double> scores = DataStoreUtil.makeStorage(spatial.getDBIDs(), DataStoreFactory.HINT_STATIC, Double.class);
+    WritableDoubleDataStore scores = DataStoreUtil.makeDoubleStorage(spatial.getDBIDs(), DataStoreFactory.HINT_STATIC);
     for(int i = 0; i < ids.size(); i++) {
       DBID id = ids.get(i);
       double gmean = 1.0;
@@ -211,13 +212,13 @@ public class CTLuRandomWalkEC<N, D extends NumberDistance<D, ?>> extends Abstrac
         if(id.equals(n)) {
           continue;
         }
-        double sim = MathUtil.cosineSimilarity(similarityVectors.get(id), similarityVectors.get(n));
+        double sim = MathUtil.angle(similarityVectors.get(id), similarityVectors.get(n));
         gmean *= sim;
         cnt++;
       }
       final double score = Math.pow(gmean, 1.0 / cnt);
       minmax.put(score);
-      scores.put(id, score);
+      scores.putDouble(id, score);
     }
 
     Relation<Double> scoreResult = new MaterializedRelation<Double>("randomwalkec", "RandomWalkEC", TypeUtil.DOUBLE, scores, relation.getDBIDs());