@Test
public void testSingleLinkage() {
Dataset<? extends Instance> dataset = FakeClustering.kumarData();
assertEquals(6, dataset.size());
Props pref = new Props();
pref.put(AlgParams.LINKAGE, SingleLinkage.name);
pref.put(AlgParams.CLUSTERING_TYPE, ClusteringType.ROWS_CLUSTERING);
pref.put(PropType.PERFORMANCE, AlgParams.KEEP_PROXIMITY, true);
HierarchicalResult result = subject.hierarchy(dataset, pref);
Matrix similarityMatrix = result.getProximityMatrix();
assertNotNull(similarityMatrix);
assertEquals(similarityMatrix.rowsCount(), dataset.size());
assertEquals(similarityMatrix.columnsCount(), dataset.size());
System.out.println("kumar - single");
DendroTreeData tree = result.getTreeData();
tree.print();
assertEquals(dataset.size(), tree.numLeaves());
DendroNode root = tree.getRoot();
assertEquals(0.21587033144922904, root.getHeight(), DELTA);
int levels = tree.distinctHeights(1e-7);
// TODO: in this example nodes #7 and #8 are on different level,
// but their height is the same. should we consider those as different
assertEquals(4, levels);
}
@Test
public void testColumnClustering() throws IOException {
Dataset<? extends Instance> dataset = FakeClustering.schoolData();
Props pref = new Props();
pref.put(AlgParams.LINKAGE, SingleLinkage.name);
pref.put(AlgParams.CLUSTERING_TYPE, ClusteringType.COLUMNS_CLUSTERING);
pref.put(PropType.PERFORMANCE, AlgParams.KEEP_PROXIMITY, true);
HierarchicalResult result = subject.hierarchy(dataset, pref);
Matrix similarityMatrix = result.getProximityMatrix();
assertNotNull(similarityMatrix);
assertEquals(similarityMatrix.rowsCount(), dataset.attributeCount());
assertEquals(similarityMatrix.columnsCount(), dataset.attributeCount());
result.getTreeData().print();
}
@Test
public void testSingleLinkageSchool() {
Dataset<? extends Instance> dataset = FakeClustering.schoolData();
assertEquals(17, dataset.size());
Props pref = new Props();
pref.put(AlgParams.LINKAGE, SingleLinkage.name);
pref.put(AlgParams.CLUSTERING_TYPE, ClusteringType.ROWS_CLUSTERING);
HierarchicalResult result = subject.hierarchy(dataset, pref);
System.out.println("school - single");
DendroTreeData tree = result.getTreeData();
tree.print();
assertEquals(dataset.size(), tree.numLeaves());
DendroNode root = tree.getRoot();
assertEquals(32.542734980330046, root.getHeight(), DELTA);
assertEquals(2 * dataset.size() - 1, tree.numNodes());
assertEquals(16, tree.distinctHeights());
assertEquals(8, tree.treeLevels());
}
@Test
public void testInverseSorting() {
Dataset<? extends Instance> dataset = FakeClustering.kumarData();
assertEquals(6, dataset.size());
Props pref = new Props();
pref.put(AlgParams.LINKAGE, SingleLinkage.name);
pref.put(AlgParams.CLUSTERING_TYPE, ClusteringType.ROWS_CLUSTERING);
// inverse ordering
pref.put(AlgParams.SMALLEST_FIRST, false);
HierarchicalResult result = subject.hierarchy(dataset, pref);
System.out.println("kumar - inverse");
DendroTreeData tree = result.getTreeData();
tree.print();
assertEquals(dataset.size(), tree.numLeaves());
DendroNode root = tree.getRoot();
assertEquals(0.10198039027185574, root.getHeight(), DELTA);
assertEquals(5, tree.distinctHeights());
assertEquals(4, tree.treeLevels());
}