QtClustering API qtclustering-163 (20111029234107)

edu.cornell.med.icb.clustering
Class MCLClusterer

java.lang.Object
  extended by edu.cornell.med.icb.clustering.MCLClusterer
All Implemented Interfaces:
Clusterer

public final class MCLClusterer
extends Object
implements Clusterer

http://micans.org/mcl/


Constructor Summary
MCLClusterer(int numberOfInstances)
          Construct a new quality threshold clusterer.
MCLClusterer(int numberOfInstances, String mclExecutable)
           
MCLClusterer(Reader reader)
          Creates clusters that are read directly from an MCL output file.
 
Method Summary
 List<int[]> cluster(SimilarityDistanceCalculator calculator, double qualityThreshold)
          Groups instances into clusters.
 List<int[]> getClusters()
          Returns the list of clusters produced by clustering.
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

MCLClusterer

public MCLClusterer(int numberOfInstances)
Construct a new quality threshold clusterer.

Parameters:
numberOfInstances - The number of instances to cluster. i.e., |G| where G is the set of instances

MCLClusterer

public MCLClusterer(int numberOfInstances,
                    String mclExecutable)

MCLClusterer

public MCLClusterer(Reader reader)
             throws IOException
Creates clusters that are read directly from an MCL output file. This constructor is simply intended to take MCL output and conform it to the Clusterer interface. When you already have an MCL output file, you would skip the call to cluster(SimilarityDistanceCalculator, double) and jump directly to getClusters() after calling this constructor.

Parameters:
reader - The reader/file to read from
Throws:
IOException - if there is a problem reading from the Reader
Method Detail

cluster

public List<int[]> cluster(SimilarityDistanceCalculator calculator,
                           double qualityThreshold)
Groups instances into clusters. Returns the indices of the instances that belong to a cluster as an int array in the list result.

Specified by:
cluster in interface Clusterer
Parameters:
calculator - The SimilarityDistanceCalculator that should be used when clustering
qualityThreshold - The QT clustering algorithm quality threshold (d)
Returns:
The list of clusters.

getClusters

public List<int[]> getClusters()
Returns the list of clusters produced by clustering.

Specified by:
getClusters in interface Clusterer
Returns:
A list of integer arrays, where each array represents a cluster and contains the index of the instance that belongs to a given cluster.

QtClustering API qtclustering-163 (20111029234107)

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