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Diffstat (limited to 'elki/src/test/java/de/lmu/ifi/dbs/elki/algorithm/outlier/lof/OnlineLOFTest.java')
-rw-r--r-- | elki/src/test/java/de/lmu/ifi/dbs/elki/algorithm/outlier/lof/OnlineLOFTest.java | 171 |
1 files changed, 171 insertions, 0 deletions
diff --git a/elki/src/test/java/de/lmu/ifi/dbs/elki/algorithm/outlier/lof/OnlineLOFTest.java b/elki/src/test/java/de/lmu/ifi/dbs/elki/algorithm/outlier/lof/OnlineLOFTest.java new file mode 100644 index 00000000..947d6fcf --- /dev/null +++ b/elki/src/test/java/de/lmu/ifi/dbs/elki/algorithm/outlier/lof/OnlineLOFTest.java @@ -0,0 +1,171 @@ +package de.lmu.ifi.dbs.elki.algorithm.outlier.lof; +/* + This file is part of ELKI: + Environment for Developing KDD-Applications Supported by Index-Structures + + Copyright (C) 2015 + 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 static org.junit.Assert.fail; + +import java.util.ArrayList; +import java.util.Random; + +import org.junit.Ignore; +import org.junit.Test; + +import de.lmu.ifi.dbs.elki.JUnit4Test; +import de.lmu.ifi.dbs.elki.data.DoubleVector; +import de.lmu.ifi.dbs.elki.data.NumberVector; +import de.lmu.ifi.dbs.elki.data.VectorUtil; +import de.lmu.ifi.dbs.elki.data.type.TypeUtil; +import de.lmu.ifi.dbs.elki.database.HashmapDatabase; +import de.lmu.ifi.dbs.elki.database.UpdatableDatabase; +import de.lmu.ifi.dbs.elki.database.ids.DBIDIter; +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.relation.DoubleRelation; +import de.lmu.ifi.dbs.elki.database.relation.Relation; +import de.lmu.ifi.dbs.elki.database.relation.RelationUtil; +import de.lmu.ifi.dbs.elki.datasource.FileBasedDatabaseConnection; +import de.lmu.ifi.dbs.elki.datasource.bundle.MultipleObjectsBundle; +import de.lmu.ifi.dbs.elki.distance.distancefunction.CosineDistanceFunction; +import de.lmu.ifi.dbs.elki.distance.distancefunction.DistanceFunction; +import de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.EuclideanDistanceFunction; +import de.lmu.ifi.dbs.elki.result.outlier.OutlierResult; +import de.lmu.ifi.dbs.elki.utilities.ClassGenericsUtil; +import de.lmu.ifi.dbs.elki.utilities.exceptions.UnableToComplyException; +import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.ListParameterization; + +/** + * Tests the OnlineLOF algorithm. Compares the result of the static LOF + * algorithm to the result of the OnlineLOF algorithm, where some insertions and + * deletions (of the previously inserted objects) have been applied to the + * database. + * + * BUG: This currently does not appear to work correctly! + * + * @author Elke Achtert + * @since 0.4.0 + */ +@Ignore +public class OnlineLOFTest implements JUnit4Test { + // the following values depend on the data set used! + static String dataset = "data/testdata/unittests/3clusters-and-noise-2d.csv"; + + // parameter k for LOF and OnlineLOF + static int k = 5; + + // neighborhood distance function for LOF and OnlineLOF + @SuppressWarnings("rawtypes") + static DistanceFunction neighborhoodDistanceFunction = EuclideanDistanceFunction.STATIC; + + // reachability distance function for LOF and OnlineLOF + @SuppressWarnings("rawtypes") + static DistanceFunction reachabilityDistanceFunction = CosineDistanceFunction.STATIC; + + // seed for the generator + static int seed = 5; + + // size of the data set + static int size = 50; + + /** + * First, run the {@link LOF} algorithm on the database. Second, run the + * {@link OnlineLOF} algorithm on the database, insert new objects and + * afterwards delete them. Then, compare the two results for equality. + * + * @throws UnableToComplyException + */ + @SuppressWarnings("unchecked") + @Test + public void testOnlineLOF() throws UnableToComplyException { + // LoggingConfiguration.setLevelFor("de.lmu.ifi.dbs.elki.algorithm.outlier.lof", + // Level.FINEST.toString()); + + UpdatableDatabase db = getDatabase(); + + // 1. Run LOF + FlexibleLOF<DoubleVector> lof = new FlexibleLOF<>(k, k, neighborhoodDistanceFunction, reachabilityDistanceFunction); + OutlierResult result1 = lof.run(db); + + // 2. Run OnlineLOF (with insertions and removals) on database + OutlierResult result2 = runOnlineLOF(db); + + // 3. Compare results + DoubleRelation scores1 = result1.getScores(); + DoubleRelation scores2 = result2.getScores(); + + for(DBIDIter id = scores1.getDBIDs().iter(); id.valid(); id.advance()) { + double lof1 = scores1.doubleValue(id); + double lof2 = scores2.doubleValue(id); + assertEquals("lof(" + DBIDUtil.toString(id) + ") != lof(" + DBIDUtil.toString(id) + "): " + lof1 + " != " + lof2, lof1, lof2, 1e-10); + } + } + + /** + * Run OnlineLOF (with insertions and removals) on database. + */ + @SuppressWarnings("unchecked") + private static OutlierResult runOnlineLOF(UpdatableDatabase db) throws UnableToComplyException { + Relation<DoubleVector> rep = db.getRelation(TypeUtil.DOUBLE_VECTOR_FIELD); + + // setup algorithm + OnlineLOF<DoubleVector> lof = new OnlineLOF<>(k, k, neighborhoodDistanceFunction, reachabilityDistanceFunction); + + // run OnlineLOF on database + OutlierResult result = lof.run(db); + + // insert new objects + ArrayList<DoubleVector> insertions = new ArrayList<>(); + NumberVector.Factory<DoubleVector> o = RelationUtil.getNumberVectorFactory(rep); + int dim = RelationUtil.dimensionality(rep); + Random random = new Random(seed); + for(int i = 0; i < size; i++) { + DoubleVector obj = VectorUtil.randomVector(o, dim, random); + insertions.add(obj); + } + DBIDs deletions = db.insert(MultipleObjectsBundle.makeSimple(rep.getDataTypeInformation(), insertions)); + + // delete objects + db.delete(deletions); + + return result; + } + + /** + * Returns the database. + */ + private static UpdatableDatabase getDatabase() { + ListParameterization params = new ListParameterization(); + params.addParameter(FileBasedDatabaseConnection.Parameterizer.INPUT_ID, dataset); + + UpdatableDatabase db = ClassGenericsUtil.parameterizeOrAbort(HashmapDatabase.class, params); + params.failOnErrors(); + if(params.hasUnusedParameters()) { + fail("Unused parameters: " + params.getRemainingParameters()); + } + + // get database + db.initialize(); + return db; + } + +} |