public void TestClusterGeneration(string databasePath, string crossPath, int charge, int minimumClusterSize) { File.Delete(databasePath); NHibernateUtil.ConnectToDatabase(databasePath, true); IDatasetDAO datasetCache = new DatasetDAOHibernate(); IUmcClusterDAO clusterCache = new UmcClusterDAOHibernate(); IUmcDAO featureCache = new UmcDAOHibernate(); // Creating a dataset Console.WriteLine("Creating dummy datasets"); var datasets = new List<DatasetInformation>(); var total = 10; for (var i = 0; i < total; i++) { var dataset = new DatasetInformation(); dataset.DatasetId = i; dataset.DatasetName = "test" + i; datasets.Add(dataset); } datasetCache.AddAll(datasets); datasets.Clear(); datasets = datasetCache.FindAll(); // Create features Console.WriteLine("Creating features"); var features = new List<UMCLight>(); var clusters = new List<UMCClusterLight>(); var x = new Random(); var featureId = 0; for (var i = 0; i < 100; i++) { var cluster = new UMCClusterLight(); cluster.Id = i; cluster.AmbiguityScore = i; cluster.Tightness = i; var N = x.Next(1, total); cluster.Id = i; cluster.ChargeState = charge; var hash = new HashSet<int>(); for (var j = 0; j < N; j++) { var did = -1; do { did = x.Next(0, total); if (!hash.Contains(did)) { hash.Add(did); break; } } while (true); var feature = new UMCLight(); feature.GroupId = did; feature.Id = featureId++; feature.ChargeState = charge; feature.MassMonoisotopic = x.NextDouble(); feature.Net = x.NextDouble(); feature.AbundanceSum = x.Next(100, 200); feature.Abundance = feature.Abundance; feature.ClusterId = cluster.Id; cluster.AddChildFeature(feature); features.Add(feature); } cluster.CalculateStatistics(ClusterCentroidRepresentation.Mean); clusters.Add(cluster); } featureCache.AddAll(features); clusterCache.AddAll(clusters); clusters = clusterCache.FindAll(); Console.WriteLine("Find all clusters"); clusters = clusterCache.FindByCharge(charge); WriteClusters(datasets, clusters, minimumClusterSize, charge, crossPath, databasePath, 300000); }
public void TestCreateDummyDatabase(string databasePath, int totalDatasets, int totalClusters) { File.Delete(databasePath); NHibernateUtil.ConnectToDatabase(databasePath, true); IDatasetDAO datasetCache = new DatasetDAOHibernate(); IUmcClusterDAO clusterCache = new UmcClusterDAOHibernate(); IUmcDAO featureCache = new UmcDAOHibernate(); // Creating a dataset Console.WriteLine("Creating dummy datasets"); var datasets = new List <DatasetInformation>(); var total = totalDatasets; for (var i = 0; i < total; i++) { var dataset = new DatasetInformation(); dataset.DatasetId = i; dataset.DatasetName = "test" + i; datasets.Add(dataset); } datasetCache.AddAll(datasets); datasets.Clear(); datasets = datasetCache.FindAll(); // Create features Console.WriteLine("Creating features"); var features = new List <UMCLight>(); var clusters = new List <UMCClusterLight>(); var x = new Random(); var featureId = 0; for (var i = 0; i < totalClusters; i++) { var N = x.Next(1, total); var charge = x.Next(1, 10); var hash = new HashSet <int>(); var net = x.NextDouble(); var mass = 400 + (1600 * x.NextDouble()); var dt = 60 * x.NextDouble(); for (var j = 0; j < N; j++) { var did = -1; do { did = x.Next(0, total); if (!hash.Contains(did)) { hash.Add(did); break; } } while (true); var feature = new UMCLight(); feature.GroupId = did; feature.Id = featureId++; feature.ChargeState = charge; feature.MassMonoisotopic = FeatureLight.ComputeDaDifferenceFromPPM(mass, 3); feature.MassMonoisotopicAligned = feature.MassMonoisotopic; feature.Net = net + .03 * x.NextDouble(); feature.NetAligned = feature.Net; feature.Net = feature.Net; feature.DriftTime = dt; feature.AbundanceSum = x.Next(100, 200); feature.Abundance = feature.Abundance; feature.ClusterId = -1; features.Add(feature); } } featureCache.AddAll(features); }
public void TestCreateDummyDatabase(string databasePath, int totalDatasets, int totalClusters) { File.Delete(databasePath); NHibernateUtil.ConnectToDatabase(databasePath, true); IDatasetDAO datasetCache = new DatasetDAOHibernate(); IUmcClusterDAO clusterCache = new UmcClusterDAOHibernate(); IUmcDAO featureCache = new UmcDAOHibernate(); // Creating a dataset Console.WriteLine("Creating dummy datasets"); var datasets = new List<DatasetInformation>(); var total = totalDatasets; for (var i = 0; i < total; i++) { var dataset = new DatasetInformation(); dataset.DatasetId = i; dataset.DatasetName = "test" + i; datasets.Add(dataset); } datasetCache.AddAll(datasets); datasets.Clear(); datasets = datasetCache.FindAll(); // Create features Console.WriteLine("Creating features"); var features = new List<UMCLight>(); var clusters = new List<UMCClusterLight>(); var x = new Random(); var featureId = 0; for (var i = 0; i < totalClusters; i++) { var N = x.Next(1, total); var charge = x.Next(1, 10); var hash = new HashSet<int>(); var net = x.NextDouble(); var mass = 400 + (1600*x.NextDouble()); var dt = 60*x.NextDouble(); for (var j = 0; j < N; j++) { var did = -1; do { did = x.Next(0, total); if (!hash.Contains(did)) { hash.Add(did); break; } } while (true); var feature = new UMCLight { GroupId = did, Id = featureId++, ChargeState = charge, MassMonoisotopic = FeatureLight.ComputeDaDifferenceFromPPM(mass, 3) }; feature.MassMonoisotopicAligned = feature.MassMonoisotopic; feature.Net = net + 0.03 * x.NextDouble(); feature.NetAligned = feature.Net; feature.Net = feature.Net; feature.DriftTime = dt; feature.AbundanceSum = x.Next(100, 200); feature.Abundance = feature.Abundance; feature.ClusterId = -1; features.Add(feature); } } featureCache.AddAll(features); }
public void TestClusterGeneration(string databasePath, string crossPath, int charge, int minimumClusterSize) { File.Delete(databasePath); NHibernateUtil.ConnectToDatabase(databasePath, true); IDatasetDAO datasetCache = new DatasetDAOHibernate(); IUmcClusterDAO clusterCache = new UmcClusterDAOHibernate(); IUmcDAO featureCache = new UmcDAOHibernate(); // Creating a dataset Console.WriteLine("Creating dummy datasets"); var datasets = new List <DatasetInformation>(); var total = 10; for (var i = 0; i < total; i++) { var dataset = new DatasetInformation(); dataset.DatasetId = i; dataset.DatasetName = "test" + i; datasets.Add(dataset); } datasetCache.AddAll(datasets); datasets.Clear(); datasets = datasetCache.FindAll(); // Create features Console.WriteLine("Creating features"); var features = new List <UMCLight>(); var clusters = new List <UMCClusterLight>(); var x = new Random(); var featureId = 0; for (var i = 0; i < 100; i++) { var cluster = new UMCClusterLight(); cluster.Id = i; cluster.AmbiguityScore = i; cluster.Tightness = i; var N = x.Next(1, total); cluster.Id = i; cluster.ChargeState = charge; var hash = new HashSet <int>(); for (var j = 0; j < N; j++) { var did = -1; do { did = x.Next(0, total); if (!hash.Contains(did)) { hash.Add(did); break; } } while (true); var feature = new UMCLight(); feature.GroupId = did; feature.Id = featureId++; feature.ChargeState = charge; feature.MassMonoisotopic = x.NextDouble(); feature.Net = x.NextDouble(); feature.AbundanceSum = x.Next(100, 200); feature.Abundance = feature.Abundance; feature.ClusterId = cluster.Id; cluster.AddChildFeature(feature); features.Add(feature); } cluster.CalculateStatistics(ClusterCentroidRepresentation.Mean); clusters.Add(cluster); } featureCache.AddAll(features); clusterCache.AddAll(clusters); clusters = clusterCache.FindAll(); Console.WriteLine("Find all clusters"); clusters = clusterCache.FindByCharge(charge); WriteClusters(datasets, clusters, minimumClusterSize, charge, crossPath, databasePath, 300000); }