private void Gravitational_clustering_test_Click(object sender, RoutedEventArgs e)
{
clustResultTxtBox.Document.Blocks.Clear();
var clusterization_stopwatch = Stopwatch.StartNew();
string message = null;
string path_data = @"F:\Magistry files\test_data\s1_data.txt";
List <DocumentVectorTest> vSpace = TestDocVectorCreator.CreatingTheDocVectorCollection(path_data);
List <DocumentVectorTest> normilized_vSpace = TestDocVectorCreator.NormalizationDocumentVectors(vSpace);
int M = 500;
float G = 6.67408313131313131F * (float)Math.Pow(10, (-6));
float deltaG = 0.001F;
float epsilon = 0.1F;
float alpha = 0.06F;
int clusterNumber = 6;
clusterNumber = Convert.ToInt32(txtboxClusterNumber.Text);
M = Convert.ToInt32(txtboxIterationCount.Text);
string gravitational_label_resul_path = @"F:\Magistry files\data\Gravitational_label_results11.txt";
string Gravitational_report_path = @"F:\Magistry files\reports\Gravitational_reports11.txt";
List <TestCentroid> result = new List <TestCentroid>(normilized_vSpace.Count);
var result1 = Tests.Gravitational.GravitationalAlg(normilized_vSpace, G, deltaG, M, epsilon);
var get_Clusters = Tests.Gravitational.GetClustersTest(result1, alpha, normilized_vSpace);
int[] label_matrix = Tests.Label_Matrix.Label_Matrix_Extractions(get_Clusters, gravitational_label_resul_path);
clusterization_stopwatch.Stop();
message = RaportGeneration.RaportGenerationFunction(get_Clusters, get_Clusters.Count, M, clusterization_stopwatch, Gravitational_report_path);
clustResultTxtBox.AppendText(message);
}
/*
* private void AHC_Click(object sender, RoutedEventArgs e)
* {
* List<string> docCollection = Logic.ClusteringAlgorithms.Used_functions.CreateDocumentCollection2.GenerateDocumentCollection_withoutLazyLoading();
* HashSet<string> termCollection = Logic.ClusteringAlgorithms.Used_functions.TFIDF2ndrealization.getTermCollection();
* Dictionary<string, int> wordIndex = Logic.ClusteringAlgorithms.Used_functions.TFIDF2ndrealization.DocumentsContainsTerm(docCollection, termCollection);
* List<DocumentVector> vSpace = VectorSpaceModel.DocumentCollectionProcessing(docCollection);
* int iterationCount = 100;
* var result = Primitive_Clustering_Hierarhical_Alg.Hierarchical_Clusterization(vSpace, iterationCount);
* List<string> docs = Tests.DocClasses.SurveyAndMeasurementsClassOfDocuments_ListCreations();
* List<List<string>> ClassCollection = Tests.DocClasses.ListOfClasses();
* var distance = Tests.InterclusterDistances.d_centroids(result);
* var min_centroid_distances = Tests.InterclusterDistances.d_min_centroids(result);
* var max_intracluster_d = Tests.IntraclusterDistances.d_max(result);
* var min_intracluster_d = Tests.IntraclusterDistances.d_min(result);
* var median_intracluster_d = Tests.IntraclusterDistances.d_sr(result);
* var Recall_result = Tests.Recall.Recall_Calculating(result, docs);
* var Precision_result = Tests.Precision.Precision_Calculating(result, docs);
* var Purity = Tests.Purity.Purity_Calculating(result, ClassCollection, vSpace);
* var Fmeasure = Tests.F1Measure.F1_Measure_Calculating(result, ClassCollection);
* var GMeasure = Tests.F1Measure.G_Measure_Calculating(result, ClassCollection);
* var NMI = Tests.NormilizedMutualInformation.NMI_Calculating(result, ClassCollection, vSpace);
* }
*/
#endregion
private void Kmeans_test(object sender, RoutedEventArgs e)
{
#region usual_KMeans_alg_invoke
clustResultTxtBox.Document.Blocks.Clear();
var clusterization_stopwatch = Stopwatch.StartNew();
string message = null;
string path_data = @"F:\Magistry files\test_data\s1_data.txt";
string KMeansPP_label_resul_path = @"F:\Magistry files\data\test\testData\20Clusters\KMeans_label_result20clust5.txt";
string K_means_report_path = @"F:\Magistry files\reports\KMeans_report20clust5.txt";
int clusterNumber = Convert.ToInt32(txtboxClusterNumber.Text);
int iterationCount = 500;
iterationCount = Convert.ToInt32(txtboxIterationCount.Text);
List <DocumentVectorTest> vSpace = TestDocVectorCreator.CreatingTheDocVectorCollection(path_data);
List <DocumentVectorTest> normilized_vSpace = TestDocVectorCreator.NormalizationDocumentVectors(vSpace);
List <TestCentroid> firstCentroidList = new List <TestCentroid>();
firstCentroidList = Test_KMeans.CentroidCalculationsForKMeans(normilized_vSpace, clusterNumber);
List <TestCentroid> resultSet = Tests.NewTestKMeansClustering.Cluster(vSpace, clusterNumber, iterationCount);
int[] KMeans_label_matrix = new int[vSpace.Count];
KMeans_label_matrix = Tests.Label_Matrix.Label_Matrix_Extractions(resultSet, KMeansPP_label_resul_path);
clusterization_stopwatch.Stop();
message = RaportGeneration.RaportGenerationFunction(resultSet, clusterNumber, iterationCount, clusterization_stopwatch, K_means_report_path);
clustResultTxtBox.AppendText(message);
#endregion
#region Iterational_test_Kmeans
/*
* int iteration = 5;
* string algorithmFlag = "KMeans";
* int clusterNumbers = Convert.ToInt32(txtboxClusterNumber.Text);
* int algiterationCount = 500;
* algiterationCount = Convert.ToInt32(txtboxIterationCount.Text);
* string test_path_data = @"F:\Magistry files\test_data\s1_data.txt";
* List<DocumentVectorTest>vSpaces = TestDocVectorCreator.CreatingTheDocVectorCollection(test_path_data);
* List<DocumentVectorTest> normilized_vSpaces = TestDocVectorCreator.NormalizationDocumentVectors(vSpaces);
* List<TestCentroid> firstCentroidLists = new List<TestCentroid>();
*
* for (int j = 5; j <= clusterNumbers;)
* {
* for (int i = 1; i <= iteration; i++)
* {
* clustResultTxtBox.Document.Blocks.Clear();
* var clusterization_stopwatchs = Stopwatch.StartNew();
* firstCentroidLists = Test_KMeans.CentroidCalculationsForKMeans(normilized_vSpaces, j);
* List<TestCentroid> IterationresultSets = Tests.NewTestKMeansClustering.Cluster(vSpaces, j, algiterationCount);
* clusterization_stopwatchs.Stop();
* Logic.IterationalReport.IterationalReportGenerationFunction(j, i, algorithmFlag, IterationresultSets, vSpaces.Count, algiterationCount, clusterization_stopwatchs);
* }
* j +=5;
* }
*/
#endregion
}
