de.uni_leipzig.cvk.data.cluster
Class ClusterAlgorithmMCL

java.lang.Object
  de.uni_leipzig.cvk.data.cluster.ClusterAlgorithm
      de.uni_leipzig.cvk.data.cluster.ClusterAlgorithmMCL

All Implemented Interfaces:

ClusterTableSettings

public class ClusterAlgorithmMCL
extends ClusterAlgorithm

Is a ClusterAlgorithm and an adapt for mcl algorithm of MarkovClustering class. Implements the clustering(String[], double, String, String, String, String) method and overrides default available settings in abstract class.

Field Summary

Fields inherited from class de.uni_leipzig.cvk.data.cluster.ClusterAlgorithm

config_A, config_B, config_C, config_D, filename

Fields inherited from interface de.uni_leipzig.cvk.data.cluster.ClusterTableSettings

CLUSTER_COLUMN_ID, CLUSTER_COLUMN_ID_TYPE, CLUSTER_COLUMN_NAME, CLUSTER_COLUMN_NAME_TYPE, CLUSTER_COLUMN_SIZE, CLUSTER_COLUMN_SIZE_TYPE

Constructor Summary

ClusterAlgorithmMCL()

Method Summary

protected prefuse.data.Table

clustering(java.lang.String[] seeds, double threshold, java.lang.String values_A, java.lang.String values_B, java.lang.String values_C, java.lang.String values_D) An abstract method for a concrete clustering algorithm implementation or adaption.

Methods inherited from class de.uni_leipzig.cvk.data.cluster.ClusterAlgorithm

cluster, getA, getB, getC, getD, getSeparator, getTable, setFilename

Methods inherited from class java.lang.Object

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

Constructor Detail

ClusterAlgorithmMCL

public ClusterAlgorithmMCL()

Method Detail

clustering

protected prefuse.data.Table clustering(java.lang.String[] seeds,
                                        double threshold,
                                        java.lang.String values_A,
                                        java.lang.String values_B,
                                        java.lang.String values_C,
                                        java.lang.String values_D)

Description copied from class: ClusterAlgorithm

An abstract method for a concrete clustering algorithm implementation or adaption. The clustering method gets the cluster back in a table with a column name of ClusterTableSettings.CLUSTER_COLUMN_NAME and with a column type of ClusterTableSettings.CLUSTER_COLUMN_NAME_TYPE. The column ClusterTableSettings.CLUSTER_COLUMN_SIZE is reserved for a inner sort operation, you don't have to use it, but you can use this column to add the size of a cluster with type of ClusterTableSettings.CLUSTER_COLUMN_SIZE_TYPE, but be sure that every row is set with a value. This size defines the order of printing the clusters, the highest value of size for a cluster will print first.

Specified by:

clustering in class ClusterAlgorithm

Parameters:

seeds - selected nodes that will be used as seeds

threshold - threshold is between 0 and 1 or -1 for all nodes

values_A - value of config_A array

values_B - value of config_B array

values_C - value of config_C array

values_D - value of config_D array

Returns:

table with one or more columns