/// <summary>
/// Reads a .cluster file into a partition
/// </summary>
/// <param name="filename"></param>
public Partition(String filename)
{
Clusters = new List <Cluster>();
using (StreamReader sr = new StreamReader(filename))
{
String dataString = sr.ReadLine();
String dataType = dataString.Substring(0, dataString.IndexOf(' '));
String dataFileName = dataString.Substring(dataString.IndexOf(' ') + 1);
String folder = filename.Substring(0, filename.LastIndexOf('\\'));
//Get the DataPoints
switch (dataType)
{
case "Points":
Data = new PointSet(dataFileName);
break;
case "DistanceMatrix":
Data = new DistanceMatrix(dataFileName);
break;
case "Graph":
String extension = dataFileName.Substring(dataFileName.LastIndexOf('.') + 1);
if (extension == "gml")
{
Data = LightWeightGraph.GetGraphFromGML(dataFileName);
}
else if (extension == "graph")
{
Data = LightWeightGraph.GetGraphFromFile(dataFileName);
}
break;
default:
throw new InvalidDataException("dataType");
}
//Parse the Clusters
String line = sr.ReadLine();
int numClusters = int.Parse(line.Split(' ')[1]);
for (int i = 0; i < numClusters; i++)
{
Cluster C = new Cluster(i);
int numItems = int.Parse(sr.ReadLine());
line = sr.ReadLine();
String[] split = line.Split(' ');
for (int k = 0; k < numItems; k++)
{
int pointIndex = int.Parse(split[k]);
C.AddPoint(new ClusteredItem(pointIndex));
}
Clusters.Add(C);
}
}
}
public void DeleteDataset(AbstractDataset dataset)
{
if (dataset == null)
{
Log.Warn("[PersonController.DeleteDataset] try to delete empty dataset");
return;
}
StoreProvider.DeleteEntry(dataset.GetType().Name, dataset.ToDictionary());
}
public void SaveDataset(AbstractDataset dataset)
{
if (dataset == null)
{
Log.Warn("[PersonController.SavePerson] try to save empty dataset");
return;
}
// TODO: set Id as Primary-Field
// actual the first property is primary if Store does not exist
StoreProvider.UpdateStore(dataset.GetType().Name, dataset.ToDictionary());
}
/// <summary>
/// Creates a Dataset partition
/// </summary>
/// <param name="clusters">List of clusters</param>
/// <param name="data">The dataset used to create the partition</param>
/// <param name="m">Meta Data about the partition</param>
public Partition(List <Cluster> clusters, AbstractDataset data, String m = "")
{
Clusters = clusters;
MetaData = m;
Data = data;
}
public HIntegrityClust(LightWeightGraph data, int k, bool weighted, double alpha = 1.0f, double beta = 0.0f, bool reassignNodes = true, bool hillClimb = true)
: this(k, weighted, null, alpha, beta, reassignNodes, hillClimb)
{
_data = data;
}
public HIntegrityClust(AbstractDataset data, int k, IPointGraphGenerator graphGen, bool weighted = true, double alpha = 1.0f, double beta = 0.0f, bool reassignNodes = true, bool hillClimb = true)
: this(k, weighted, graphGen, alpha, beta, reassignNodes, hillClimb)
{
_data = data;
}
//public HVatABCClust(AbstractDataset data, int minK, IPointGraphGenerator graphGen, bool weighted = true, double alpha = 1.0f, double beta = 0.0f, bool reassignNodes = true, bool hillClimb = true)
// : this(minK, M, K, weighted, graphGen, alpha, beta, reassignNodes, hillClimb)
// {
// _data = data;
// }
public HVatABCClust(LightWeightGraph data, int minK, int myM, int myK, bool weighted, double alpha = 1.0f, double beta = 0.0f, bool reassignNodes = true, bool hillClimb = true)
: this(minK, weighted, myM, myK, null, alpha, beta, reassignNodes, hillClimb)
{
_data = data;
}
public HyperVATClust(List <List <int> > overlaps, LightWeightGraph data, int k, bool weighted, double alpha = 1.0f, double beta = 0.0f, bool reassignNodes = true, bool hillClimb = true)
: this(overlaps, k, weighted, null, alpha, beta, reassignNodes, hillClimb)
{
_data = data;
}
public HyperVATClust(List <List <int> > overlaps, AbstractDataset data, int k, IPointGraphGenerator graphGen, bool weighted = true, double alpha = 1.0f, double beta = 0.0f, bool reassignNodes = true, bool hillClimb = true)
: this(overlaps, k, weighted, graphGen, alpha, beta, reassignNodes, hillClimb)
{
_data = data;
}
public TransportDataset(AbstractDataset dataset) => this.dataset = dataset;
