public void TestKmedoidClustering()
{
FloatMatrixIndexer data = new FloatMatrixIndexer(new float[, ]
{
{ 2, 6 }, { 3, 4 }, { 3, 8 }, { 4, 7 }, { 6, 2 }, { 6, 4 }, { 7, 3 }, { 7, 4 }, { 8, 5 }, { 7, 6 }
});
GenericDistanceMatrix distance = new GenericDistanceMatrix(data, new L1Distance());
int[] clustering = KmedoidClustering.GenerateClusters(data, distance, 2);
Assert.IsTrue(new[] { 0, 0, 0, 0, 7, 7, 7, 7, 7, 7 }.SequenceEqual(clustering));
}
public void TestGeneralDistanceMatrix()
{
var distance = new EuclideanDistance();
var distanceMatrix = new GenericDistanceMatrix(new FloatMatrixIndexer(new float[, ] {
{ 0, 0 }, { 1, 0 }, { 3, 0 }
}), distance);
Assert.AreEqual(0, distanceMatrix[0, 0]);
Assert.AreEqual(0, distanceMatrix[2, 2]);
Assert.AreEqual(distanceMatrix[1, 2], distanceMatrix[2, 1]);
Assert.AreEqual(1, distanceMatrix[1, 0]);
Assert.AreEqual(2, distanceMatrix[1, 2]);
distanceMatrix[0, 1] = -1;
Assert.AreEqual(-1, distanceMatrix[0, 1]);
}
