Import Upstream version 0.6.0

1 files changed, 31 insertions, 30 deletions

diff --git a/src/de/lmu/ifi/dbs/elki/algorithm/outlier/spatial/TrimmedMeanApproach.java b/src/de/lmu/ifi/dbs/elki/algorithm/outlier/spatial/TrimmedMeanApproach.java
index e07ce480..1a1f9a82 100644
--- a/src/de/lmu/ifi/dbs/elki/algorithm/outlier/spatial/TrimmedMeanApproach.java
+++ b/src/de/lmu/ifi/dbs/elki/algorithm/outlier/spatial/TrimmedMeanApproach.java
@@ -1,26 +1,27 @@
 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) 2013
-Ludwig-Maximilians-Universität München
-Lehr- und Forschungseinheit für Datenbanksysteme
-ELKI Development Team
-
-This program is free software: you can redistribute it and/or modify
-it under the terms of the GNU Affero General Public License as published by
-the Free Software Foundation, either version 3 of the License, or
-(at your option) any later version.
-
-This program is distributed in the hope that it will be useful,
-but WITHOUT ANY WARRANTY; without even the implied warranty of
-MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
-GNU Affero General Public License for more details.
-
-You should have received a copy of the GNU Affero General Public License
-along with this program.  If not, see <http://www.gnu.org/licenses/>.
-*/
+

+/*

+ This file is part of ELKI:

+ Environment for Developing KDD-Applications Supported by Index-Structures
+

+ Copyright (C) 2013

+ Ludwig-Maximilians-Universität München

+ Lehr- und Forschungseinheit für Datenbanksysteme

+ ELKI Development Team
+

+ This program is free software: you can redistribute it and/or modify

+ it under the terms of the GNU Affero General Public License as published by

+ the Free Software Foundation, either version 3 of the License, or

+ (at your option) any later version.
+

+ This program is distributed in the hope that it will be useful,

+ but WITHOUT ANY WARRANTY; without even the implied warranty of

+ MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the

+ GNU Affero General Public License for more details.
+

+ You should have received a copy of the GNU Affero General Public License

+ along with this program.  If not, see <http://www.gnu.org/licenses/>.

+ */

 

 import java.util.Arrays;

 

@@ -50,15 +51,15 @@ import de.lmu.ifi.dbs.elki.utilities.documentation.Description;
 import de.lmu.ifi.dbs.elki.utilities.documentation.Reference;

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

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

-import de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints.GreaterConstraint;

-import de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints.LessConstraint;

+import de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints.CommonConstraints;

 import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.Parameterization;

 import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.DoubleParameter;

 

 /**

  * A Trimmed Mean Approach to Finding Spatial Outliers.

  * 

- * Outliers are defined by their value deviation from a trimmed mean of the neighbors.

+ * Outliers are defined by their value deviation from a trimmed mean of the

+ * neighbors.

  * 

  * <p>

  * Reference: <br>

@@ -116,7 +117,7 @@ public class TrimmedMeanApproach<N> extends AbstractNeighborhoodOutlier<N> {
     WritableDoubleDataStore scores = DataStoreUtil.makeDoubleStorage(relation.getDBIDs(), DataStoreFactory.HINT_STATIC);

 

     FiniteProgress progress = LOG.isVerbose() ? new FiniteProgress("Computing trimmed means", relation.size(), LOG) : null;

-    for(DBIDIter iditer = relation.iterDBIDs(); iditer.valid(); iditer.advance()) {
+    for(DBIDIter iditer = relation.iterDBIDs(); iditer.valid(); iditer.advance()) {

       DBIDs neighbors = npred.getNeighborDBIDs(iditer);

       int num = 0;

       double[] values = new double[neighbors.size()];

@@ -161,7 +162,7 @@ public class TrimmedMeanApproach<N> extends AbstractNeighborhoodOutlier<N> {
       double[] ei = new double[relation.size()];

       {

         int i = 0;

-        for(DBIDIter iditer = relation.iterDBIDs(); iditer.valid(); iditer.advance()) {
+        for(DBIDIter iditer = relation.iterDBIDs(); iditer.valid(); iditer.advance()) {

           ei[i] = errors.doubleValue(iditer);

           i++;

         }

@@ -180,7 +181,7 @@ public class TrimmedMeanApproach<N> extends AbstractNeighborhoodOutlier<N> {
     }

     // calculate score

     DoubleMinMax minmax = new DoubleMinMax();

-    for(DBIDIter iditer = relation.iterDBIDs(); iditer.valid(); iditer.advance()) {
+    for(DBIDIter iditer = relation.iterDBIDs(); iditer.valid(); iditer.advance()) {

       double score = Math.abs(errors.doubleValue(iditer)) * 0.6745 / median_dev_from_median;

       scores.putDouble(iditer, score);

       minmax.put(score);

@@ -228,8 +229,8 @@ public class TrimmedMeanApproach<N> extends AbstractNeighborhoodOutlier<N> {
     protected void makeOptions(Parameterization config) {

       super.makeOptions(config);

       DoubleParameter pP = new DoubleParameter(P_ID);

-      pP.addConstraint(new GreaterConstraint(0.0));
-      pP.addConstraint(new LessConstraint(0.5));

+      pP.addConstraint(CommonConstraints.GREATER_THAN_ZERO_DOUBLE);

+      pP.addConstraint(CommonConstraints.LESS_THAN_HALF_DOUBLE);

       if(config.grab(pP)) {

         p = pP.getValue();

       }