net.seninp.jmotif.cluster

Class Cluster

java.lang.Object

net.seninp.jmotif.cluster.Cluster

public class Cluster
extends Object

Implements a cluster node for SAX terms clustering.

Author:

psenin

Field Summary

Fields

Modifier and Type	Field and Description
double	distanceBetween The distance between left and right sub-clusters.
Cluster	left The left sub-cluster.
int	level The level from the root.
Cluster	right The right sub-cluster.

Constructor Summary

Constructors

Constructor and Description
Cluster() Constructor.
Cluster(String key) Constructor.

Method Summary

Modifier and Type	Method and Description
Double	distanceTo(Cluster otherCluster, HashMap<String,HashMap<String,Double>> data, CosineDistanceMatrix distanceMatrix, LinkageCriterion criterion) Compute the distance between words clusters.
boolean	equals(Object obj)
int	hashCode()
boolean	isTerminal() Returns true if left and right sub-nodes of this node are NULLs.
void	merge(Cluster left, Cluster right, Double distance) Merging together clusters.
String	toNewick() Returns the NEWICK format representation of this node cluster.
String	toString()

Methods inherited from class java.lang.Object

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

Field Detail

left

public Cluster left

The left sub-cluster.

right

public Cluster right

The right sub-cluster.

level

public int level

The level from the root.

distanceBetween

public double distanceBetween

The distance between left and right sub-clusters.

Constructor Detail

Cluster

public Cluster()

Constructor.

Cluster

public Cluster(String key)

Constructor.

Parameters:

key - The single name of the cluster.

Method Detail

merge

public void merge(Cluster left,
                  Cluster right,
                  Double distance)

Merging together clusters.

Parameters:

left - the left cluster.

right - the right cluster.

distance - the distance between clusters.

distanceTo

public Double distanceTo(Cluster otherCluster,
                         HashMap<String,HashMap<String,Double>> data,
                         CosineDistanceMatrix distanceMatrix,
                         LinkageCriterion criterion)

Compute the distance between words clusters.

Parameters:

otherCluster - the other cluster.

data - this cluster.

distanceMatrix - the pre-computed distance matrix.

criterion - the linkage criterion.

Returns:

the distance between clusters based on the distances and the linkage.

hashCode

public int hashCode()

Overrides:

hashCode in class Object

equals

public boolean equals(Object obj)

Overrides:

equals in class Object

toString

public String toString()

Overrides:

toString in class Object

toNewick

public String toNewick()

Returns the NEWICK format representation of this node cluster. You still need to take it in parenthesis if this is your ROOT.

Returns:

The newick string representation of the cluster.

isTerminal

public boolean isTerminal()

Returns true if left and right sub-nodes of this node are NULLs.

Returns:

true if the node is terminal.