de.unibi.techfak.jpredictor.clustering
Class GreedyClustering

java.lang.Object
  de.unibi.techfak.jpredictor.clustering.Clustering
      de.unibi.techfak.jpredictor.clustering.GreedyClustering

public class GreedyClustering
extends Clustering

This agglomerative clustering strategy builds up clusters by means of the optimal relation between any two consensus motifs.

Field Summary

(package private) double[][]

alignmentResults Contains the results of all alignments in-between cluster representatives.

Fields inherited from class de.unibi.techfak.jpredictor.clustering.Clustering

clusters, comm, consensus, mma, n, nucleotideVector, sma

Constructor Summary

GreedyClustering(ICommunicator comm, SingleMotifAlignment sma, MultiMotifAlignment mma)
Inits the greedy clustering.

Method Summary

(package private) void	clusterStep() The second step in the clustering loop.
(package private) void	initClustering() Inits the clustering.
(package private) boolean	stopTest(double threshold, int clusternumber) The first step in the clustering loop.

Methods inherited from class de.unibi.techfak.jpredictor.clustering.Clustering

alignMotifs, outputResults, setMotifList, start

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

alignmentResults

double[][] alignmentResults

Contains the results of all alignments in-between cluster representatives.

Let the number of motifs in the motif list be n. Then the length of the matrix would be n. Its arrays vary in length. The first, with index zero, has length 1. The second, index 1, has length 2, and so forth. The last array, index n-1, has length n. The matrix is therefore build up as a triangle. If two clusters are combined to one their respective row and column entries are deleted. Unused entries, or invalid entries, are set to null (Double.NaN ).

Constructor Detail

GreedyClustering

public GreedyClustering(ICommunicator comm,
                        SingleMotifAlignment sma,
                        MultiMotifAlignment mma)
                 throws java.lang.NullPointerException

Inits the greedy clustering. Simply calls the constructor from the Clustering class.

Throws:

java.lang.NullPointerException

Method Detail

initClustering

void initClustering()

Description copied from class: Clustering

Inits the clustering. It may mean, that all distances between every two motifs are calculated or such. This method is the first in start(double, int) to be called.

Specified by:

initClustering in class Clustering

See Also:

Clustering.start(double, int)

clusterStep

void clusterStep()
           throws java.lang.IllegalStateException

Description copied from class: Clustering

The second step in the clustering loop. It may mean to select two clusters which get combined, to combine them and to calculate the relation measure to all other clusters

Specified by:

clusterStep in class Clustering

Throws:

java.lang.IllegalStateException - If a clustering could not be performed due to some reason.

stopTest

boolean stopTest(double threshold,
                 int clusternumber)

Description copied from class: Clustering

The first step in the clustering loop. It may mean to check for the distances between clusters to exceed a certain threshold or for loglikelihoods to get to worse.

Specified by:

stopTest in class Clustering

Parameters:

threshold - The threshold to end the clustering. Might be Double.NaN to indicate, that the clustering should continue fully.

clusternumber - The number of clusters wished. Give zero or -1 to have a full clustering.

Returns:

true if the clustering has to stop, false otherwise.