Import Debian changes 0.5.5-1

elki (0.5.5-1) unstable; urgency=low

  * New upstream release: 0.5.5 interim release.

1 files changed, 8 insertions, 10 deletions

diff --git a/src/de/lmu/ifi/dbs/elki/algorithm/outlier/GaussianModel.java b/src/de/lmu/ifi/dbs/elki/algorithm/outlier/GaussianModel.java
index 51833c8b..6aed60fe 100644
--- a/src/de/lmu/ifi/dbs/elki/algorithm/outlier/GaussianModel.java
+++ b/src/de/lmu/ifi/dbs/elki/algorithm/outlier/GaussianModel.java
@@ -29,10 +29,10 @@ import de.lmu.ifi.dbs.elki.data.type.TypeUtil;
 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.WritableDoubleDataStore;

-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.relation.MaterializedRelation;

 import de.lmu.ifi.dbs.elki.database.relation.Relation;

+import de.lmu.ifi.dbs.elki.database.relation.RelationUtil;

 import de.lmu.ifi.dbs.elki.logging.Logging;

 import de.lmu.ifi.dbs.elki.math.DoubleMinMax;

 import de.lmu.ifi.dbs.elki.math.MathUtil;

@@ -43,7 +43,6 @@ import de.lmu.ifi.dbs.elki.result.outlier.BasicOutlierScoreMeta;
 import de.lmu.ifi.dbs.elki.result.outlier.InvertedOutlierScoreMeta;

 import de.lmu.ifi.dbs.elki.result.outlier.OutlierResult;

 import de.lmu.ifi.dbs.elki.result.outlier.OutlierScoreMeta;

-import de.lmu.ifi.dbs.elki.utilities.DatabaseUtil;

 import de.lmu.ifi.dbs.elki.utilities.documentation.Description;

 import de.lmu.ifi.dbs.elki.utilities.documentation.Title;

 import de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizer;

@@ -61,16 +60,16 @@ import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.Flag;
  */

 @Title("Gaussian Model Outlier Detection")

 @Description("Fit a multivariate gaussian model onto the data, and use the PDF to compute an outlier score.")

-public class GaussianModel<V extends NumberVector<V, ?>> extends AbstractAlgorithm<OutlierResult> implements OutlierAlgorithm {

+public class GaussianModel<V extends NumberVector<?>> extends AbstractAlgorithm<OutlierResult> implements OutlierAlgorithm {

   /**

    * The logger for this class.

    */

-  private static final Logging logger = Logging.getLogger(GaussianModel.class);

+  private static final Logging LOG = Logging.getLogger(GaussianModel.class);

 

   /**

    * OptionID for inversion flag.

    */

-  public static final OptionID INVERT_ID = OptionID.getOrCreateOptionID("gaussod.invert", "Invert the value range to [0:1], with 1 being outliers instead of 0.");

+  public static final OptionID INVERT_ID = new OptionID("gaussod.invert", "Invert the value range to [0:1], with 1 being outliers instead of 0.");

 

   /**

    * Small value to increment diagonally of a matrix in order to avoid

@@ -113,7 +112,7 @@ public class GaussianModel<V extends NumberVector<V, ?>> extends AbstractAlgorit
     Matrix covarianceTransposed = covarianceMatrix.cheatToAvoidSingularity(SINGULARITY_CHEAT).inverse();

 

     // Normalization factors for Gaussian PDF

-    final double fakt = (1.0 / (Math.sqrt(Math.pow(MathUtil.TWOPI, DatabaseUtil.dimensionality(relation)) * covarianceMatrix.det())));

+    final double fakt = (1.0 / (Math.sqrt(Math.pow(MathUtil.TWOPI, RelationUtil.dimensionality(relation)) * covarianceMatrix.det())));

 

     // for each object compute Mahalanobis distance

     for(DBIDIter iditer = relation.iterDBIDs(); iditer.valid(); iditer.advance()) {
@@ -130,8 +129,7 @@ public class GaussianModel<V extends NumberVector<V, ?>> extends AbstractAlgorit
     if(invert) {

       double max = mm.getMax() != 0 ? mm.getMax() : 1.;

       for(DBIDIter iditer = relation.iterDBIDs(); iditer.valid(); iditer.advance()) {
-        DBID id  = iditer.getDBID();

-        oscores.putDouble(id, (max - oscores.doubleValue(id)) / max);

+        oscores.putDouble(iditer, (max - oscores.doubleValue(iditer)) / max);

       }

       meta = new BasicOutlierScoreMeta(0.0, 1.0);

     }

@@ -149,7 +147,7 @@ public class GaussianModel<V extends NumberVector<V, ?>> extends AbstractAlgorit
 

   @Override

   protected Logging getLogger() {

-    return logger;

+    return LOG;

   }

 

   /**

@@ -159,7 +157,7 @@ public class GaussianModel<V extends NumberVector<V, ?>> extends AbstractAlgorit
    * 

    * @apiviz.exclude

    */

-  public static class Parameterizer<V extends NumberVector<V, ?>> extends AbstractParameterizer {

+  public static class Parameterizer<V extends NumberVector<?>> extends AbstractParameterizer {

     protected boolean invert = false;

 

     @Override