Example #1
0
        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);
        }
Example #2
0
        /*
         * 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
        }
Example #3
0
        private void FuzzyKMeansTest_Click(object sender, RoutedEventArgs e)
        {
            #region usual_KMeansPP_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";
            List <DocumentVectorTest> vSpace = TestDocVectorCreator.CreatingTheDocVectorCollection(path_data);
            float fuzziness                    = 2f;
            float epsilon                      = 0.1f;
            int   clusterNumber                = Convert.ToInt32(txtboxClusterNumber.Text);
            List <TestCentroid> resultSet      = new List <TestCentroid>(clusterNumber);
            List <TestCentroid> resultSetRTest = new List <TestCentroid>();
            //List<DocumentVectorTest> normilized_vSpace = TestDocVectorCreator.NormalizationDocumentVectors(vSpace);
            float[,] Result_fcm;
            //List<string> docs = Tests.DocClasses.SurveyAndMeasurementsClassOfDocuments_ListCreations();
            var result = Tests.FuzzyKmeansTest.Fcm(vSpace, clusterNumber, epsilon, fuzziness);
            Result_fcm = result.Item1;
            int iterationCount = result.Item2;
            resultSet = Tests.FuzzyKmeansTest.CreateClusterSet(clusterNumber);
            var resultSetArray = Tests.FuzzyKmeansTest.AssignDocsToClusters(Result_fcm, clusterNumber, vSpace, resultSet);
            //resultSetRTest = Tests.FuzzyKmeansTest.AssignDocsToClusters(Result_fcm, clusterNumber, vSpace);
            string FuzzyKMeans_label_resul_path = @"F:\Magistry files\data\testData\FuzzyKMeans_label_result.txt";
            string Fuzzy_K_means_report_path    = @"F:\Magistry files\reports\Fuzzy_KMeans_report.txt";
            //string RTest_FuzzyKMeans_label_resul_path = @"F:\Magistry files\data\testData\5Clusters\RTest_FuzzyKMeans_label_result5clust1.txt";
            string[] string_label_matrix = new string[resultSetArray.Item1.Length];
            for (int k = 0; k < resultSetArray.Item1.Length; k++)
            {
                string_label_matrix[k] = resultSetArray.Item1[k].ToString();
            }
            var result_Centroid_Set = resultSetArray.Item2;
            System.IO.File.WriteAllLines(FuzzyKMeans_label_resul_path, string_label_matrix);
            //string membership_matrix_file_path = @"F:\Magistry files\data\R_membership_matrix.txt";
            //var memberShipMatrix = Tests.MemberShipMatrixReader.ReadDataFromFile(membership_matrix_file_path, vSpace.Count, clusterNumber);
            //resultSet = Tests.FuzzyKmeansTest.CreateClusterSet(clusterNumber);
            //var resultSetArray1 = Tests.FuzzyKmeansTest.AssignDocsToClusters(memberShipMatrix, clusterNumber, vSpace, resultSet);
            //for (int k = 0; k < resultSetArray.Item1.Length; k++)
            //string_label_matrix[k] = resultSetArray1.Item1[k].ToString();
            //System.IO.File.WriteAllLines(RTest_FuzzyKMeans_label_resul_path, string_label_matrix);
            clusterization_stopwatch.Stop();
            message = RaportGeneration.RaportGenerationFunction(resultSet, clusterNumber, iterationCount, clusterization_stopwatch, Fuzzy_K_means_report_path);
            clustResultTxtBox.AppendText(message);
            #endregion


            #region Iterational_test_FuzzyKmeans

            /*
             * int iteration = 5;
             * float fuzzinesss = 2f;
             * float epsilons = 0.1f;
             * int clusterNumbers = Convert.ToInt32(txtboxClusterNumber.Text);
             * int algiterationCount = 500;
             * string algorithm = "FuzzyKMeans";
             * algiterationCount = Convert.ToInt32(txtboxIterationCount.Text);
             * string test_path_data = @"F:\Magistry files\test_data\s1_data.txt";
             * List<TestCentroid> resultSets = new List<TestCentroid>(clusterNumbers);
             * List<DocumentVectorTest> vSpaces = TestDocVectorCreator.CreatingTheDocVectorCollection(test_path_data);
             * List<DocumentVectorTest> normilized_vSpaces = TestDocVectorCreator.NormalizationDocumentVectors(vSpaces);
             *
             * for (int j = 5; j <= clusterNumbers;)
             * {
             *  for (int i = 1; i <= iteration; i++)
             *  {
             *
             *      clustResultTxtBox.Document.Blocks.Clear();
             *      var clusterizations_stopwatchs = Stopwatch.StartNew();
             *      float[,] Result_fcms;
             *      var results = Tests.FuzzyKmeansTest.Fcm(vSpaces, j, epsilons, fuzzinesss);
             *      Result_fcms = results.Item1;
             *      int AlgiterationCounts = results.Item2;
             *      resultSets = Tests.FuzzyKmeansTest.CreateClusterSet(j);
             *      var resultSetArrays = Tests.FuzzyKmeansTest.AssignDocsToClusters(Result_fcms, j, vSpaces, resultSets);
             *      string[] string_label_matrixs = new string[resultSetArrays.Item1.Length];
             *      for (int k = 0; k < resultSetArrays.Item1.Length; k++)
             *          string_label_matrixs[k] = resultSetArrays.Item1[k].ToString();
             *      string FuzzyKMeans_label_resul_paths = @"F:\Magistry files\data\test\testData\" + j.ToString() + "Clusters\\FuzzyKMeans_label_result" + j.ToString() + "clust" + i.ToString() + ".txt";
             *      string Fuzzy_K_means_report_paths = @"F:\Magistry files\reports\test\Fuzzy_KMeans_report" + j.ToString() + "clust" + i.ToString() + ".txt";
             *      clusterizations_stopwatchs.Stop();
             *      using (StreamWriter w = File.AppendText(FuzzyKMeans_label_resul_paths))
             *      {
             *          for (int k = 0; k < string_label_matrixs.Length; k++)
             *              w.WriteLine(string_label_matrixs[k]);
             *      }
             *      RaportGeneration.VoidRaportGenerationFunction(algorithm, resultSetArrays.Item2, j, AlgiterationCounts, clusterizations_stopwatchs, Fuzzy_K_means_report_paths);
             *  }
             *  j += 5;
             * }
             */
            #endregion
        }