Examples with CutDendrogramByHeight de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.CutDendrogramByHeight used on opensource projects

Example 1 with CutDendrogramByHeight

use of de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.CutDendrogramByHeight in project elki by elki-project.

the class FileBasedSparseDoubleDistanceFunctionTest method testExternalDistance.

@Test
public void testExternalDistance() throws IOException {
    Database db = // 
    new ELKIBuilder<>(StaticArrayDatabase.class).with(AbstractDatabase.Parameterizer.DATABASE_CONNECTION_ID, // 
    DBIDRangeDatabaseConnection.class).with(DBIDRangeDatabaseConnection.Parameterizer.COUNT_ID, // 
    4).build();
    db.initialize();
    FileBasedSparseDoubleDistanceFunction df = new // 
    FileBasedSparseDoubleDistanceFunction(new AsciiDistanceParser(CSVReaderFormat.DEFAULT_FORMAT), null, Double.POSITIVE_INFINITY);
    // We need to read from a resource, instead of a file.
    df.loadCache(4, FileUtil.openSystemFile(FILENAME));
    SLINK<DBID> slink = new SLINK<>(df);
    CutDendrogramByHeight clus = new CutDendrogramByHeight(slink, 0.5, false);
    Clustering<DendrogramModel> c = clus.run(db);
    testClusterSizes(c, new int[] { 2, 2 });
}

Example 2 with CutDendrogramByHeight

use of de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.CutDendrogramByHeight in project elki by elki-project.

the class FileBasedSparseFloatDistanceFunctionTest method testExternalDistance.

@Test
public void testExternalDistance() throws IOException {
    Database db = // 
    new ELKIBuilder<>(StaticArrayDatabase.class).with(AbstractDatabase.Parameterizer.DATABASE_CONNECTION_ID, // 
    DBIDRangeDatabaseConnection.class).with(DBIDRangeDatabaseConnection.Parameterizer.COUNT_ID, // 
    4).build();
    db.initialize();
    FileBasedSparseFloatDistanceFunction df = new // 
    FileBasedSparseFloatDistanceFunction(new AsciiDistanceParser(CSVReaderFormat.DEFAULT_FORMAT), null, Float.POSITIVE_INFINITY);
    // We need to read from a resource, instead of a file.
    df.loadCache(4, FileUtil.openSystemFile(FILENAME));
    SLINK<DBID> slink = new SLINK<>(df);
    CutDendrogramByHeight clus = new CutDendrogramByHeight(slink, 0.5, false);
    Clustering<DendrogramModel> c = clus.run(db);
    testClusterSizes(c, new int[] { 2, 2 });
}