public override Structuring BuildStructuring()
{
try
{
if (IContainerProgressBar != null)
{
IContainerProgressBar.ResetProgressBar(1, 1, true);
IContainerProgressBar.UpdateProgressBar(1, "Running WSPA algorithm...", true);
}
VerifyPartitions(Structurings);
List <double[, ]> MatrixsOf_dit = new List <double[, ]>();
double[,] Max_row = new double[Set.ElementsCount, StructuringsCount];
List <double[, ]> MatrixsObjectRepresentation = new List <double[, ]>();
for (int i = 0; i < StructuringsCount; i++)
{
double[,] Matrix = new double[Set.ElementsCount, Structurings[i].ClustersCount];
MatrixsOf_dit.Add(Matrix);
double[,] MatrixRepresentation = new double[Set.ElementsCount, Structurings[i].ClustersCount];
MatrixsObjectRepresentation.Add(MatrixRepresentation);
for (int j = 0; j < Set.ElementsCount; j++)
{
int k = 0;
double _max = double.MinValue;
//Aqui se llena la matrix por fila
foreach (var cluster in Structurings[i].Clusters.Values)
{
Matrix[j, k] = Calculate_dit(Set[j], cluster);
if (Matrix[j, k] > _max)
{
_max = Matrix[j, k];
}
if (j > 0)
{
int _q = Structurings[i].ClustersCount;
double _numerator = Max_row[j - 1, i] - Matrix[j - 1, k] + 1;
double _denominator = _q * Max_row[j - 1, i] + _q - SumRow(Matrix, j - 1);
MatrixRepresentation[j - 1, k] = _numerator / _denominator;
}
k++;
}
Max_row[j, i] = _max;
}
//Calcula la ultima fila de la representacion, es decir del ultimo objeto
for (int k = 0; k < Structurings[i].ClustersCount; k++)
{
int j = Set.ElementsCount;
int _q = Structurings[i].ClustersCount;
double _numerator = Max_row[j - 1, i] - Matrix[j - 1, k] + 1;
double _denominator = _q * Max_row[j - 1, i] + _q - SumRow(Matrix, j - 1);
MatrixRepresentation[j - 1, k] = _numerator / _denominator;
}
}
double[,] _Similarities = new double[Set.ElementsCount, Set.ElementsCount];
double m = StructuringsCount;
for (int i = 0; i < Set.ElementsCount; i++)
{
for (int j = 0; j < Set.ElementsCount; j++)
{
double _Sij = 0;
for (int k = 0; k < MatrixsObjectRepresentation.Count; k++)
{
double[,] A = MatrixsObjectRepresentation[k];
if (i != j)
{
_Sij += EscalarProduct(A, i, j) / (Norm(A, i) * Norm(A, j));
}
}
_Similarities[i, j] = _Sij / m;
}
}
SimilarityWSPA _sim = new SimilarityWSPA(_Similarities);
Metis _metis = new Metis(Set, _sim);
_metis.IContainerProgressBar = IContainerProgressBar;
_metis.ClustersCount = ClustersCount;
Structuring = _metis.BuildStructuring();
return(Structuring);
}
catch (Exception _ex)
{
if (IContainerProgressBar != null)
{
IContainerProgressBar.ShowError("Error occurred in WSPA algorithm.\n" + _ex.Message);
}
return(null);
}
}
public override Structuring BuildStructuring()
{
try
{
if (Set == null || Structurings == null)
{
throw new NullReferenceException();
}
int _current = 1, _maxpb = Set.ElementsCount * Structurings.Count;
if (IContainerProgressBar != null)
{
IContainerProgressBar.ResetProgressBar(1, _maxpb, true);
IContainerProgressBar.UpdateProgressBar(1, "Running HGPA algorithm...", true);
}
if (ClustersCount <= 0)
{
throw new Exception("La cantidad de clusters debe ser mayor que cero");
}
else if (ClustersCount == 1)
{
Dictionary <string, Cluster> dic_clus = new Dictionary <string, Cluster>();
string name = "C-0";
List <Element> temp = new List <Element>();
for (int i = 0; i < Set.ElementsCount; i++)
{
temp.Add(Set[i]);
}
dic_clus.Add(name, new Cluster(name)
{
Elements = temp
});
Structuring = new Partition()
{
Clusters = dic_clus
};
if (IContainerProgressBar != null)
{
IContainerProgressBar.FinishProgressBar();
}
return(Structuring);
}
else
{
#region Algorithm
//Construir un conjunto de elementos donde ahora cada elemento es un label,
//o lo que es lo mismo una hyperedge. Este seria el meta-grafo
Set hyperedgeSet = new Set("HyperEdge Set");
int dimH = 0;
foreach (Structuring s in Structurings)
{
dimH += s.ClustersCount;
}
byte[,] metagraph = new byte[Set.ElementsCount, dimH];
//Ahora por cada label annadir un nuevo elemento al conjunto, recordar que cada label
//seria cada hyperedges, lo que ahora cada hyperedges estaria representada por la clase Element
//pero la lista de Values seria el vector binario o mejor dicho los elementos que pertenecen
//a la hyperedges.
//La matriz metagraph es la representacion en vectores binarios del conjunto hyperedges.
// Ojo esto ya ///////Es mejor representar cada hyperedges de esta forma es decir con los elementos que pertenecen
// no se hace ///////a dicha hyperedges ya que si se representa por el vector binario entonces necesitariamos mucha memoria.
int index = 0;
foreach (Structuring structuring in Structurings)
{
foreach (Cluster cluster in structuring.Clusters.Values)
{
Element element = new Element();
element.Index = index;
element.Name = "hyperedge-" + index;
foreach (Element temp in cluster.Elements)
{
metagraph[temp.Index, index] = 1;
if (IContainerProgressBar != null)
{
IContainerProgressBar.UpdateProgressBar(_current++, "Running HGPA algorithm...", false);
}
}
hyperedgeSet.AddElement(element);
index++;
}
}
if (IContainerProgressBar != null)
{
IContainerProgressBar.UpdateProgressBar(_maxpb, "Running HGPA algorithm...", true);
}
Similarity _sim = new BinaryJaccardMeasure(metagraph);
ClusterAlgorithm ca = new Metis(hyperedgeSet, _sim);
ca.ClustersCount = ClustersCount;
ca.BuildStructuring();
Partition metaClusters = (Partition)ca.Structuring;
//Asignar cada elemento original a su metacluster correspondiente
//double[] va a tener dimension igual a la cantidad de elementos iniciales y en cada posicion va a estar un numero entre 0 y 1
List <double[]> _meta_hyperedges = new List <double[]>();
foreach (Cluster _c in metaClusters.Clusters.Values)
{
double[] _meta_hyperedge = new double[metagraph.GetLength(0)];
foreach (Element _e in _c.Elements)
{
//_e.Index es la columna de la matrix metgraph, que dicha columna representa a ese elemento
for (int row = 0; row < metagraph.GetLength(0); row++)
{
_meta_hyperedge[row] += metagraph[row, _e.Index];
}
}
//LLevar cada posicion a un valor enre 0 y 1
for (int i = 0; i < _meta_hyperedge.Length; i++)
{
_meta_hyperedge[i] = _meta_hyperedge[i] / _c.ElementsCount;
}
_meta_hyperedges.Add(_meta_hyperedge);
}
//Construir la particion final
Dictionary <string, Cluster> _dic_clusters = new Dictionary <string, Cluster>();
for (int i = 0; i < Set.ElementsCount; i++)
{
Element _e = Set[i];
double _max = -1;
int _meta_hyperedge = -1;
for (int j = 0; j < _meta_hyperedges.Count; j++)
{
if (_meta_hyperedges[j][_e.Index] > _max)
{
_max = _meta_hyperedges[j][_e.Index];
_meta_hyperedge = j;
}
}
string _nameOfCluster = "C-" + _meta_hyperedge;
if (_dic_clusters.ContainsKey(_nameOfCluster))
{
_dic_clusters[_nameOfCluster].AddElement(_e);
}
else
{
Cluster c = new Cluster(_nameOfCluster);
c.AddElement(_e);
_dic_clusters.Add(_nameOfCluster, c);
}
}
Structuring = new Partition()
{
Clusters = _dic_clusters
};
if (IContainerProgressBar != null)
{
IContainerProgressBar.FinishProgressBar();
}
return(Structuring);
#endregion
}
}
catch
{
if (IContainerProgressBar != null)
{
IContainerProgressBar.ShowError("Error occurred in MCLA algorithm.");
}
return(null);
}
}
public override Structuring BuildStructuring()
{
try
{
if (IContainerProgressBar != null)
{
IContainerProgressBar.ResetProgressBar(1, 1, true);
IContainerProgressBar.UpdateProgressBar(1, "Running WBPA algorithm...", true);
}
WSPA.VerifyPartitions(Structurings);
List <double[, ]> MatrixsOf_dit = new List <double[, ]>();
double[,] Max_row = new double[Set.ElementsCount, StructuringsCount];
List <double[, ]> MatrixsObjectRepresentation = new List <double[, ]>();
int q_m = StructuringsCount * Structurings[0].ClustersCount;
double[,] A = new double[Set.ElementsCount, q_m];
for (int i = 0; i < StructuringsCount; i++)
{
double[,] Matrix = new double[Set.ElementsCount, Structurings[i].ClustersCount];
MatrixsOf_dit.Add(Matrix);
double[,] MatrixRepresentation = new double[Set.ElementsCount, Structurings[i].ClustersCount];
MatrixsObjectRepresentation.Add(MatrixRepresentation);
for (int j = 0; j < Set.ElementsCount; j++)
{
int k = 0;
double _max = double.MinValue;
//Aqui se llena la matrix por fila
foreach (var cluster in Structurings[i].Clusters.Values)
{
Matrix[j, k] = WSPA.Calculate_dit(Set[j], cluster);
if (Matrix[j, k] > _max)
{
_max = Matrix[j, k];
}
if (j > 0)
{
int _q = Structurings[i].ClustersCount;
double _numerator = Max_row[j - 1, i] - Matrix[j - 1, k] + 1;
double _denominator = _q * Max_row[j - 1, i] + _q - WSPA.SumRow(Matrix, j - 1);
MatrixRepresentation[j - 1, k] = _numerator / _denominator;
A[j - 1, i *_q + k] = MatrixRepresentation[j - 1, k];
}
k++;
}
Max_row[j, i] = _max;
}
//Calcula la ultima fila de la representacion, es decir del ultimo objeto
for (int k = 0; k < Structurings[i].ClustersCount; k++)
{
int j = Set.ElementsCount;
int _q = Structurings[i].ClustersCount;
double _numerator = Max_row[j - 1, i] - Matrix[j - 1, k] + 1;
double _denominator = _q * Max_row[j - 1, i] + _q - WSPA.SumRow(Matrix, j - 1);
MatrixRepresentation[j - 1, k] = _numerator / _denominator;
A[j - 1, i *_q + k] = MatrixRepresentation[j - 1, k];
}
}
int _ElementsCount = Set.ElementsCount;
for (int i = 0; i < q_m; i++)
{
Element _element = new Element();
_element.Name = "Element cluster - " + i;
_element.Index = i;
_element.Attributes = Set.Attributes;
Set.Elements.Insert(0, _element);
}
//Actualizar los indices de los elementos originales
for (int i = q_m; i < Set.ElementsCount; i++)
{
Set[i].Index = i;
}
SimilarityWBPA _sim = new SimilarityWBPA(A, _ElementsCount, Structurings[0].ClustersCount, StructuringsCount);
Metis _metis = new Metis(Set, _sim);
_metis.IContainerProgressBar = IContainerProgressBar;
_metis.ClustersCount = ClustersCount;
Structuring _StructTemp = _metis.BuildStructuring();
Dictionary <string, Cluster> dic_clusters = new Dictionary <string, Cluster>();
foreach (var cluster in _StructTemp.Clusters.Values)
{
for (int i = 0; i < cluster.ElementsCount; i++)
{
if (cluster.Elements[i].Index < q_m)
{
cluster.Elements.RemoveAt(i);
i--;
}
}
if (cluster.ElementsCount > 0)
{
dic_clusters.Add(cluster.Name, cluster);
}
}
Structuring = new Partition()
{
Clusters = dic_clusters
};
//Borrar los elementos annadidos en el conjunto
for (int i = 0; i < q_m; i++)
{
Set.Elements.RemoveAt(0);
}
//Actualizar los indices de los elementos que estan en el SET, que eran los originales
for (int i = 0; i < Set.ElementsCount; i++)
{
Set[i].Index = i;
}
return(Structuring);
}
catch (Exception _ex)
{
if (IContainerProgressBar != null)
{
IContainerProgressBar.ShowError("Error occurred in WBPA algorithm.\n" + _ex.Message);
}
return(null);
}
}
public override Structuring BuildStructuring()
{
try
{
if (Set == null || Structurings == null)
{
throw new NullReferenceException();
}
int _current = 1, _max = Set.ElementsCount * Structurings.Count;
if (IContainerProgressBar != null)
{
IContainerProgressBar.ResetProgressBar(1, _max, true);
IContainerProgressBar.UpdateProgressBar(1, "Running CSPA algorithm...", true);
}
if (ClustersCount <= 0)
{
throw new Exception("La cantidad de clusters debe ser mayor que cero");
}
else if (ClustersCount == 1)
{
Dictionary <string, Cluster> dic_clus = new Dictionary <string, Cluster>();
string name = "C-0";
List <Element> temp = new List <Element>();
for (int i = 0; i < Set.ElementsCount; i++)
{
temp.Add(Set[i]);
}
dic_clus.Add(name, new Cluster(name)
{
Elements = temp
});
Structuring = new Partition()
{
Clusters = dic_clus
};
if (IContainerProgressBar != null)
{
IContainerProgressBar.FinishProgressBar();
}
return(Structuring);
}
else
{
#region Algorithm
//Calcular la matrix V x H
int dimH = 0;
foreach (Structuring s in Structurings)
{
dimH += s.ClustersCount;
}
byte[,] VxH = new byte[Set.ElementsCount, dimH];
//rellenar VxH
int currentColumn = 0;//cada columna representa un cluster
//Recordar tbn que los elementos tienen un indice que los representa
foreach (Structuring s in Structurings)
{
foreach (Cluster cluster in s.Clusters.Values)
{
foreach (Element e in cluster.Elements)
{
VxH[e.Index, currentColumn] = 1;
if (IContainerProgressBar != null)
{
IContainerProgressBar.UpdateProgressBar(_current++, "Running CSPA algorithm...", false);
}
}
//Debo actualizar currentColumn ya que cada cluser representa una columna
currentColumn++;
}
}
//Construir CoAsociationMatrixDissToMetis para pasarselo como similitud entre elementos
//al algoritmo Metis
Similarity _sim = new CoAsociationMatrixDissToMetis(Set, VxH, Structurings.Count);
ClusterAlgorithm ca = new Metis(Set, _sim);
//Llamar al algoritmo Metis
ca.ClustersCount = ClustersCount;
ca.BuildStructuring();
Structuring = ca.Structuring;
if (IContainerProgressBar != null)
{
IContainerProgressBar.FinishProgressBar();
}
return(Structuring);
#endregion
}
}
catch
{
if (IContainerProgressBar != null)
{
IContainerProgressBar.ShowError("Error occurred in CSPA algorithm.");
}
return(null);
}
}