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diff --git a/test/de/lmu/ifi/dbs/elki/algorithm/clustering/TestDeLiCluResults.java b/test/de/lmu/ifi/dbs/elki/algorithm/clustering/TestDeLiCluResults.java
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--- a/test/de/lmu/ifi/dbs/elki/algorithm/clustering/TestDeLiCluResults.java
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-package de.lmu.ifi.dbs.elki.algorithm.clustering;
-
-/*
- This file is part of ELKI:
- Environment for Developing KDD-Applications Supported by Index-Structures
-
- Copyright (C) 2012
- 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 static org.junit.Assert.assertEquals;
-
-import org.junit.Test;
-
-import de.lmu.ifi.dbs.elki.JUnit4Test;
-import de.lmu.ifi.dbs.elki.algorithm.AbstractSimpleAlgorithmTest;
-import de.lmu.ifi.dbs.elki.algorithm.clustering.trivial.ByLabelClustering;
-import de.lmu.ifi.dbs.elki.data.Clustering;
-import de.lmu.ifi.dbs.elki.data.model.Model;
-import de.lmu.ifi.dbs.elki.database.Database;
-import de.lmu.ifi.dbs.elki.database.StaticArrayDatabase;
-import de.lmu.ifi.dbs.elki.distance.distancevalue.DoubleDistance;
-import de.lmu.ifi.dbs.elki.evaluation.clustering.ClusterContingencyTable;
-import de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu.DeLiCluTreeFactory;
-import de.lmu.ifi.dbs.elki.persistent.AbstractPageFileFactory;
-import de.lmu.ifi.dbs.elki.utilities.ClassGenericsUtil;
-import de.lmu.ifi.dbs.elki.utilities.optionhandling.ParameterException;
-import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.ListParameterization;
-
-/**
- * Performs a full DeLiClu run, and compares the result with a clustering
- * derived from the data set labels. This test ensures that DeLiClu's
- * performance doesn't unexpectedly drop on this data set (and also ensures that
- * the algorithms work, as a side effect).
- *
- * @author Katharina Rausch
- * @author Erich Schubert
- */
-public class TestDeLiCluResults extends AbstractSimpleAlgorithmTest implements JUnit4Test {
- /**
- * Run DeLiClu with fixed parameters and compare the result to a golden
- * standard.
- *
- * @throws ParameterException
- */
- @Test
- public void testDeLiCluResults() {
- ListParameterization indexparams = new ListParameterization();
- // We need a special index for this algorithm:
- indexparams.addParameter(StaticArrayDatabase.Parameterizer.INDEX_ID, DeLiCluTreeFactory.class);
- indexparams.addParameter(AbstractPageFileFactory.Parameterizer.PAGE_SIZE_ID, 1000);
- Database db = makeSimpleDatabase(UNITTEST + "hierarchical-2d.ascii", 710, indexparams, null);
-
- // Setup actual algorithm
- ListParameterization params = new ListParameterization();
- params.addParameter(DeLiClu.MINPTS_ID, 18);
- params.addParameter(OPTICSXi.XI_ID, 0.038);
- params.addParameter(OPTICSXi.XIALG_ID, DeLiClu.class);
- OPTICSXi<DoubleDistance> opticsxi = ClassGenericsUtil.parameterizeOrAbort(OPTICSXi.class, params);
- testParameterizationOk(params);
-
- // run DeLiClu on database
- Clustering<?> clustering = opticsxi.run(db);
-
- // Test F-Measure
- ByLabelClustering bylabel = new ByLabelClustering();
- Clustering<Model> rbl = bylabel.run(db);
- ClusterContingencyTable ct = new ClusterContingencyTable(true, false);
- ct.process(clustering, rbl);
- double score = ct.getPaircount().f1Measure();
- // We cannot test exactly - due to Hashing, DeLiClu sequence is not
- // identical each time, the results will vary slightly.
- assertEquals(this.getClass().getSimpleName() + ": Score does not match: " + score, score, 0.807415, 1E-5);
- }
-} \ No newline at end of file