io.kgraph.library.clustering

Class SemiClustering.SemiCluster

java.lang.Object

io.kgraph.library.clustering.SemiClustering.SemiCluster

All Implemented Interfaces:

Comparable<SemiClustering.SemiCluster>

Enclosing class:

SemiClustering

public static class SemiClustering.SemiCluster
extends Object
implements Comparable<SemiClustering.SemiCluster>

This class represents a semi-cluster.

Constructor Summary

Constructors

Constructor and Description
SemiCluster() Constructor: Create a new empty Cluster.
SemiCluster(SemiClustering.SemiCluster cluster) Constructor: Initialize a new Cluster.

Method Summary

Modifier and Type	Method and Description
void	addVertex(VertexWithValue<Long,Set<SemiClustering.SemiCluster>> vertex, Iterable<EdgeWithValue<Long,Double>> edges, double scoreFactor) Adds a vertex to the cluster.
int	compareTo(SemiClustering.SemiCluster other) Two semi clusters are the same when: (i) they have the same number of vertices, (ii) all their vertices are the same
boolean	equals(Object o)
int	hashCode()
int	size() Returns size of semi cluster list.
String	toString()

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

SemiCluster

public SemiCluster()

Constructor: Create a new empty Cluster.

SemiCluster

public SemiCluster(SemiClustering.SemiCluster cluster)

Constructor: Initialize a new Cluster.

Parameters:

cluster - cluster object to initialize the new object

Method Detail

addVertex

public final void addVertex(VertexWithValue<Long,Set<SemiClustering.SemiCluster>> vertex,
                            Iterable<EdgeWithValue<Long,Double>> edges,
                            double scoreFactor)

Adds a vertex to the cluster.

Every time a vertex is added we also update the inner and boundary score. Because vertices are only added to a semi-cluster, we can save the inner and boundary scores and update them incrementally.

Otherwise, in order to re-compute it from scratch we would need every vertex to send a friends-of-friends list, which is very expensive.

Parameters:

vertex - The new vertex to be added into the cluster

edges - The edges of the vertex

scoreFactor - Boundary Edge Score Factor

size

public final int size()

Returns size of semi cluster list.

Returns:

Number of semi clusters in the list

compareTo

public final int compareTo(SemiClustering.SemiCluster other)

Two semi clusters are the same when: (i) they have the same number of vertices, (ii) all their vertices are the same

Specified by:

compareTo in interface Comparable<SemiClustering.SemiCluster>

Parameters:

other - Cluster to be compared with current cluster

Returns:

0 if two clusters are the same

equals

public boolean equals(Object o)

Overrides:

equals in class Object

hashCode

public int hashCode()

Overrides:

hashCode in class Object

toString

public final String toString()

Overrides:

toString in class Object