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);
}