public void HugeSimpleCPU()
{
int nDescriptors = 350000;
int descriptorDiension = 4096;
int nClusters = 25;// 128;
int iterationCount = 10;
int nDescriptorsDiv5 = nDescriptors / 5;
Descriptor[] descriptors = HelperTestClass.GenerateHierarchicalDescriptors(seed, nDescriptorsDiv5, descriptorDiension);
ClusteringSimple clustering = new ClusteringSimple(descriptors);
TestClusteringSimple(clustering);
Stopwatch stopWatch = new Stopwatch();
stopWatch.Start();
clustering.Clusterize(nClusters, iterationCount, seed);
stopWatch.Stop();
double elapsedSeconds = (stopWatch.ElapsedMilliseconds * 0.001);
double nPerSecond = nDescriptorsDiv5 * 5 * nClusters / elapsedSeconds;
Console.WriteLine("Computing time: " + elapsedSeconds + " seconds (" + nPerSecond + " per second).");
HelperTestClass.VisualizeClustering(clustering.Descriptors, clustering.Centroids, windowSize, windowSize);
}
public void VisualizeIterationsSimpleCPU()
{
ClusteringSimple clustering = new ClusteringSimple(descriptors);
TestClusteringSimple(clustering);
clustering.Clusterize(0.1, 1, 5334);
Centroid[] centroids1 = clustering.Centroids;
clustering.Clusterize(0.1, 2, 5334);
Centroid[] centroids2 = clustering.Centroids;
clustering.Clusterize(0.1, 4, 5334);
Centroid[] centroids4 = clustering.Centroids;
clustering.Clusterize(0.1, 8, 5334);
Centroid[] centroids8 = clustering.Centroids;
clustering.Clusterize(0.1, 16, 5334);
Centroid[] centroids16 = clustering.Centroids;
clustering.Clusterize(0.1, 32, 5334);
Centroid[] centroids32 = clustering.Centroids;
clustering.Clusterize(0.1, 64, 5334);
Centroid[] centroids64 = clustering.Centroids;
HelperTestClass.VisualizeClustering(clustering.Descriptors, centroids1, windowSize, windowSize);
HelperTestClass.VisualizeClustering(clustering.Descriptors, centroids2, windowSize, windowSize);
HelperTestClass.VisualizeClustering(clustering.Descriptors, centroids4, windowSize, windowSize);
HelperTestClass.VisualizeClustering(clustering.Descriptors, centroids8, windowSize, windowSize);
HelperTestClass.VisualizeClustering(clustering.Descriptors, centroids16, windowSize, windowSize);
HelperTestClass.VisualizeClustering(clustering.Descriptors, centroids32, windowSize, windowSize);
HelperTestClass.VisualizeClustering(clustering.Descriptors, centroids64, windowSize, windowSize);
}
public void VisualizeHeuristicDivisive3Layer()
{
int[] seedCounts = new int[] { 10, 10, 10 };
int[] iterationCounts = new int[] { 10, 10, 10 };
ClusteringDivisive clustering = new ClusteringDivisive(descriptors);
clustering.Clusterize(seedCounts, iterationCounts, seed);
HelperTestClass.VisualizeClustering(clustering.Descriptors, clustering.Centroids, windowSize, windowSize);
}
public void VisualizeSimpleCPU()
{
double seedPercentage = 0.1;
int iterationCount = 10;
ClusteringSimple clustering = new ClusteringSimple(descriptors);
TestClusteringSimple(clustering);
clustering.Clusterize(seedPercentage, iterationCount, seed);
HelperTestClass.VisualizeClustering(clustering.Descriptors, clustering.Centroids, windowSize, windowSize);
}
public void VisualizeAgglomerative()
{
int nDescriptors = 100;
int descriptorDimension = 2;
int nDescriptorsDiv5 = nDescriptors / 5;
Descriptor[] descriptors = HelperTestClass.GenerateHierarchicalDescriptors(seed, nDescriptorsDiv5, descriptorDimension);
ClusteringAgglomerative clustering = new ClusteringAgglomerative(descriptors);
clustering.Clusterize();
HelperTestClass.TestDescriptorAssignment(descriptors.Length, clustering.Centroids[0]);
HelperTestClass.VisualizeClustering(clustering.Descriptors, clustering.Centroids[23], windowSize, windowSize);
}
