1 files changed, 26 insertions, 3 deletions
diff --git a/test/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/TestERiCResults.java b/test/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/TestERiCResults.java
index 06f3c723..ec030ec1 100644
--- a/test/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/TestERiCResults.java
+++ b/test/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/TestERiCResults.java
@@ -1,5 +1,28 @@
 package de.lmu.ifi.dbs.elki.algorithm.clustering.correlation;
 
+/*
+ This file is part of ELKI:
+ Environment for Developing KDD-Applications Supported by Index-Structures
+
+ Copyright (C) 2011
+ 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 org.junit.Test;
 
 import de.lmu.ifi.dbs.elki.JUnit4Test;
@@ -76,7 +99,7 @@ public class TestERiCResults extends AbstractSimpleAlgorithmTest implements JUni
   @Test
   public void testERiCOverlap() {
     Database db = makeSimpleDatabase(UNITTEST + "correlation-overlap-3-5d.ascii", 650);
-  
+
     // Setup algorithm
     ListParameterization params = new ListParameterization();
     // ERiC
@@ -95,10 +118,10 @@ public class TestERiCResults extends AbstractSimpleAlgorithmTest implements JUni
     params.addParameter(WeightedCovarianceMatrixBuilder.WEIGHT_ID, ErfcWeight.class);
     params.addParameter(PCAFilteredRunner.PCA_EIGENPAIR_FILTER, PercentageEigenPairFilter.class);
     params.addParameter(PercentageEigenPairFilter.ALPHA_ID, 0.6);
-  
+
     ERiC<DoubleVector> eric = ClassGenericsUtil.parameterizeOrAbort(ERiC.class, params);
     testParameterizationOk(params);
-  
+
     // run ERiC on database
     Clustering<CorrelationModel<DoubleVector>> result = eric.run(db);
     testFMeasure(db, result, 0.831136946);