Import Debian changes 0.6.0~beta2-1

elki (0.6.0~beta2-1) unstable; urgency=low

  * New upstream beta release.
  * 3DPC extension is not yet included.

1 files changed, 14 insertions, 14 deletions

diff --git a/src/de/lmu/ifi/dbs/elki/algorithm/benchmark/RangeQueryBenchmarkAlgorithm.java b/src/de/lmu/ifi/dbs/elki/algorithm/benchmark/RangeQueryBenchmarkAlgorithm.java
index f483321d..1b5e827b 100644
--- a/src/de/lmu/ifi/dbs/elki/algorithm/benchmark/RangeQueryBenchmarkAlgorithm.java
+++ b/src/de/lmu/ifi/dbs/elki/algorithm/benchmark/RangeQueryBenchmarkAlgorithm.java
@@ -4,7 +4,7 @@ package de.lmu.ifi.dbs.elki.algorithm.benchmark;
  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
@@ -34,6 +34,7 @@ import de.lmu.ifi.dbs.elki.database.ids.DBIDIter;
 import de.lmu.ifi.dbs.elki.database.ids.DBIDRange;
 import de.lmu.ifi.dbs.elki.database.ids.DBIDUtil;
 import de.lmu.ifi.dbs.elki.database.ids.DBIDs;
+import de.lmu.ifi.dbs.elki.database.ids.distance.DistanceDBIDList;
 import de.lmu.ifi.dbs.elki.database.query.distance.DistanceQuery;
 import de.lmu.ifi.dbs.elki.database.query.range.RangeQuery;
 import de.lmu.ifi.dbs.elki.database.relation.Relation;
@@ -41,7 +42,6 @@ import de.lmu.ifi.dbs.elki.database.relation.RelationUtil;
 import de.lmu.ifi.dbs.elki.datasource.DatabaseConnection;
 import de.lmu.ifi.dbs.elki.datasource.bundle.MultipleObjectsBundle;
 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.NumberDistance;
 import de.lmu.ifi.dbs.elki.logging.Logging;
 import de.lmu.ifi.dbs.elki.logging.progress.FiniteProgress;
@@ -160,12 +160,12 @@ public class RangeQueryBenchmarkAlgorithm<O extends NumberVector<?>, D extends N
       int size = (int) Math.min(sampling, relation.size());
       sample = DBIDUtil.randomSample(relation.getDBIDs(), size, random);
     }
-    FiniteProgress prog = LOG.isVerbose() ? new FiniteProgress("kNN queries", sample.size(), LOG) : null;
+    FiniteProgress prog = LOG.isVeryVerbose() ? new FiniteProgress("kNN queries", sample.size(), LOG) : null;
     int hash = 0;
     MeanVariance mv = new MeanVariance();
     for (DBIDIter iditer = sample.iter(); iditer.valid(); iditer.advance()) {
       D r = dfactory.fromDouble(radrel.get(iditer).doubleValue(0));
-      DistanceDBIDResult<D> rres = rangeQuery.getRangeForDBID(iditer, r);
+      DistanceDBIDList<D> rres = rangeQuery.getRangeForDBID(iditer, r);
       int ichecksum = 0;
       for (DBIDIter it = rres.iter(); it.valid(); it.advance()) {
         ichecksum += it.internalGetIndex();
@@ -179,9 +179,9 @@ public class RangeQueryBenchmarkAlgorithm<O extends NumberVector<?>, D extends N
     if (prog != null) {
       prog.ensureCompleted(LOG);
     }
-    if (LOG.isVerbose()) {
-      LOG.verbose("Result hashcode: " + hash);
-      LOG.verbose("Mean number of results: "+mv.toString());
+    if (LOG.isStatistics()) {
+      LOG.statistics("Result hashcode: " + hash);
+      LOG.statistics("Mean number of results: " + mv.getMean() + " +- " + mv.getNaiveStddev());
     }
     return null;
   }
@@ -241,7 +241,7 @@ public class RangeQueryBenchmarkAlgorithm<O extends NumberVector<?>, D extends N
       int size = (int) Math.min(sampling, sids.size());
       sample = DBIDUtil.randomSample(sids, size, random);
     }
-    FiniteProgress prog = LOG.isVerbose() ? new FiniteProgress("kNN queries", sample.size(), LOG) : null;
+    FiniteProgress prog = LOG.isVeryVerbose() ? new FiniteProgress("kNN queries", sample.size(), LOG) : null;
     int hash = 0;
     MeanVariance mv = new MeanVariance();
     double[] buf = new double[dim];
@@ -254,7 +254,7 @@ public class RangeQueryBenchmarkAlgorithm<O extends NumberVector<?>, D extends N
       }
       O v = ofactory.newNumberVector(buf);
       D r = dfactory.fromDouble(o.doubleValue(dim));
-      DistanceDBIDResult<D> rres = rangeQuery.getRangeForObject(v, r);
+      DistanceDBIDList<D> rres = rangeQuery.getRangeForObject(v, r);
       int ichecksum = 0;
       for (DBIDIter it = rres.iter(); it.valid(); it.advance()) {
         ichecksum += it.internalGetIndex();
@@ -268,9 +268,9 @@ public class RangeQueryBenchmarkAlgorithm<O extends NumberVector<?>, D extends N
     if (prog != null) {
       prog.ensureCompleted(LOG);
     }
-    if (LOG.isVerbose()) {
-      LOG.verbose("Result hashcode: " + hash);
-      LOG.verbose("Mean number of results: "+mv.toString());
+    if (LOG.isStatistics()) {
+      LOG.statistics("Result hashcode: " + hash);
+      LOG.statistics("Mean number of results: " + mv.getMean() + " +- " + mv.getNaiveStddev());
     }
     return null;
   }
@@ -333,7 +333,7 @@ public class RangeQueryBenchmarkAlgorithm<O extends NumberVector<?>, D extends N
     @Override
     protected void makeOptions(Parameterization config) {
       super.makeOptions(config);
-      ObjectParameter<DatabaseConnection> queryP = new ObjectParameter<DatabaseConnection>(QUERY_ID, DatabaseConnection.class);
+      ObjectParameter<DatabaseConnection> queryP = new ObjectParameter<>(QUERY_ID, DatabaseConnection.class);
       queryP.setOptional(true);
       if (config.grab(queryP)) {
         queries = queryP.instantiateClass(config);
@@ -351,7 +351,7 @@ public class RangeQueryBenchmarkAlgorithm<O extends NumberVector<?>, D extends N
 
     @Override
     protected RangeQueryBenchmarkAlgorithm<O, D> makeInstance() {
-      return new RangeQueryBenchmarkAlgorithm<O, D>(distanceFunction, queries, sampling, random);
+      return new RangeQueryBenchmarkAlgorithm<>(distanceFunction, queries, sampling, random);
     }
   }
 }