public void TestDistances()
{
var dist = new WeightedEuclideanDistance <UMCClusterLight>();
var clusterA = CreateCluster(500, .2, 27);
var clusterB = CreateCluster(500, .2, 27);
var N = 50;
var stepMass = .5;
var stepNET = .001;
var stepDrift = .01;
Console.WriteLine("Walk in drift time");
for (var i = 0; i < N; i++)
{
clusterB.DriftTime += stepDrift;
var distance = dist.EuclideanDistance(clusterA, clusterB);
Console.WriteLine("{0}, {1}, {3}, {2}", clusterB.DriftTime, clusterB.DriftTime, distance, clusterB.DriftTime - clusterA.DriftTime);
}
Console.WriteLine();
Console.WriteLine("Walk in net ");
clusterB.DriftTime = 27;
for (var i = 0; i < N; i++)
{
clusterB.Net += stepNET;
var distance = dist.EuclideanDistance(clusterA, clusterB);
Console.WriteLine("{0}, {1}, {3}, {2}", clusterB.Net, clusterB.Net, distance, clusterB.Net - clusterA.Net);
}
Console.WriteLine();
Console.WriteLine("Walk in mass ");
clusterB.Net = .2;
for (var i = 0; i < N; i++)
{
var d = FeatureLight.ComputeDaDifferenceFromPPM(clusterA.MassMonoisotopic, stepMass * i);
clusterB.MassMonoisotopic = d;
var distance = dist.EuclideanDistance(clusterA, clusterB);
Console.WriteLine("{0}, {1}, {3}, {2}", clusterB.MassMonoisotopic,
clusterB.MassMonoisotopic,
distance,
FeatureLight.ComputeMassPPMDifference(clusterA.MassMonoisotopic, clusterB.MassMonoisotopic));
}
}
//[TestCase(@"ClusterData\clusterData-merged-nodelin.txt")]
public void TestWeightedAverageLinkage(string path)
{
Console.WriteLine("Test: " + path);
var features = GetClusterData(Path.Combine(TestPaths.TestFilesDirectory, path));
Assert.IsNotEmpty(features);
var cluster = new UMCClusterLight();
cluster.Id = features[0].Id;
features.ForEach(x => cluster.AddChildFeature(x));
var maps = new Dictionary <int, UMCClusterLight>();
var average = new UMCAverageLinkageClusterer <UMCLight, UMCClusterLight>();
average.Parameters = new FeatureClusterParameters <UMCLight>();
average.Parameters.CentroidRepresentation = ClusterCentroidRepresentation.Mean;
average.Parameters.Tolerances = new Algorithms.FeatureTolerances();
var distance = new WeightedEuclideanDistance <UMCLight>();
average.Parameters.DistanceFunction = distance.EuclideanDistance;
var clusters = average.Cluster(features);
Console.WriteLine("dataset\tfeature\tmass\tnet\tdrift");
foreach (var newCluster in clusters)
{
foreach (var feature in newCluster.Features)
{
Console.WriteLine("{0},{1},{2},{3},{4}", feature.GroupId,
feature.Id,
feature.Net,
feature.MassMonoisotopicAligned,
feature.DriftTime);
}
}
}
//[TestCase(@"ClusterData\clusterData-single-1500.txt")]
public void TestAverageLinkage(string path)
{
Console.WriteLine("Average Linkage Test: " + path);
var features = GetClusterData(Path.Combine(TestPaths.TestFilesDirectory, path));
Assert.IsNotEmpty(features);
var cluster = new UMCClusterLight();
cluster.Id = features[0].Id;
features.ForEach(x => cluster.AddChildFeature(x));
var maps = new Dictionary <int, UMCClusterLight>();
var average = new UMCAverageLinkageClusterer <UMCLight, UMCClusterLight>();
average.Parameters = new FeatureClusterParameters <UMCLight>();
average.Parameters.CentroidRepresentation = ClusterCentroidRepresentation.Median;
average.Parameters.Tolerances = new Algorithms.FeatureTolerances();
average.Parameters.Tolerances.Net = .02;
average.Parameters.Tolerances.Mass = 6;
average.Parameters.Tolerances.DriftTime = .3;
var distance = new WeightedEuclideanDistance <UMCLight>();
average.Parameters.DistanceFunction = distance.EuclideanDistance;
var euclid = new EuclideanDistanceMetric <UMCLight>();
average.Parameters.DistanceFunction = euclid.EuclideanDistance;
var clusters = average.Cluster(features);
Console.WriteLine("Clusters = {0}", clusters.Count);
var id = 1;
foreach (var testCluster in clusters)
{
testCluster.CalculateStatistics(ClusterCentroidRepresentation.Mean);
var distances = new List <double>();
// Show a sampling of 5 results
var threshold = (int)(testCluster.Features.Count / (double)5);
if (threshold < 1)
{
threshold = 1;
}
testCluster.Id = id++;
var featureID = 0;
foreach (var feature in testCluster.Features)
{
featureID++;
if (featureID % threshold == 0)
{
Console.WriteLine("{0},{1},{2},{3}",
feature.Net,
feature.MassMonoisotopicAligned,
feature.DriftTime,
testCluster.Id);
}
var newDistance = distance.EuclideanDistance(feature, testCluster);
distances.Add(newDistance);
}
//Console.WriteLine();
//Console.WriteLine("Distances");
//distances.ForEach(x => Console.WriteLine(x));
//Console.WriteLine();
}
}
//[TestCase(@"ClusterData\clusterData-single-1500.txt", 4)]
//[TestCase(@"ClusterData\clusterData-single-1500-two.txt", 4)]
public void TestPrimsWeighted(string path, double sigma)
{
sigma = 1;
Console.WriteLine();
Console.WriteLine("Tests: " + path);
Console.WriteLine("Sigma Cutoff: {0}", sigma);
var features = GetClusterData(Path.Combine(TestPathSingleton.TestDirectory, path));
Assert.IsNotEmpty(features);
var cluster = new UMCClusterLight();
cluster.Id = features[0].Id;
features.ForEach(x => cluster.AddChildFeature(x));
var maps = new Dictionary <int, UMCClusterLight>();
var prims = new UMCPrimsClustering <UMCLight, UMCClusterLight>(sigma);
prims.Parameters = new FeatureClusterParameters <UMCLight>();
prims.Parameters.CentroidRepresentation = ClusterCentroidRepresentation.Mean;
prims.Parameters.Tolerances = new FeatureTolerances();
prims.Parameters.OnlyClusterSameChargeStates = false;
prims.Parameters.Tolerances.DriftTime = .3;
prims.Parameters.Tolerances.Mass = 15;
prims.Parameters.Tolerances.Net = .02;
prims.DumpLinearRelationship = false;
var distance = new WeightedEuclideanDistance <UMCLight>();
prims.Parameters.DistanceFunction = distance.EuclideanDistance;
var clusters = prims.Cluster(features);
Console.WriteLine();
Console.WriteLine("Clusters = {0}", clusters.Count);
var id = 1;
foreach (var testCluster in clusters)
{
testCluster.CalculateStatistics(ClusterCentroidRepresentation.Mean);
var distances = new List <double>();
// Show a sampling of 15 results
var threshold = (int)(testCluster.Features.Count / (double)15);
if (threshold < 1)
{
threshold = 1;
}
testCluster.Id = id++;
var featureID = 0;
foreach (var feature in testCluster.Features)
{
featureID++;
if (featureID % threshold == 0)
{
Console.WriteLine("{0},{1},{2},{3}",
feature.Net,
feature.MassMonoisotopicAligned,
feature.DriftTime,
testCluster.Id);
}
var newDistance = distance.EuclideanDistance(feature, testCluster);
distances.Add(newDistance);
}
//Console.WriteLine();
//Console.WriteLine("Distances");
//distances.ForEach(x => Console.WriteLine(x));
//Console.WriteLine();
}
Console.WriteLine();
Console.WriteLine("Test Done:");
Console.WriteLine();
}
