baseCode - 0.2.5

Clover coverage report - baseCode - 0.2.5

Coverage timestamp: Tue Apr 12 2005 11:31:58 EDT

FRAMES NO FRAMES

file stats:	LOC:	46		Methods:	1
	NCLOC:	21		Classes:	1

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Source file

Conditionals

Statements

Methods

TOTAL

AverageLinkageDistancer.java

 package baseCode.algorithm.learning.unsupervised.cluster;
 
 import java.util.Collection;
 import java.util.Iterator;
 
 import baseCode.common.Distanceable;
 
 /**
  * <hr>
  * <p>
  * Copyright (c) 2004 Columbia University
  * 
  * @author pavlidis
  * @version $Id: AverageLinkageDistancer.java,v 1.3 2004/08/02 15:03:43 pavlidis Exp $
  */
 public class AverageLinkageDistancer implements Distancer {
 
    /*
     * (non-Javadoc)
     * 
     * @see baseCode.algorithm.learning.unsupervised.cluster.Distance#distance(java.lang.Object, java.lang.Object)
     */
    public double distance( Distanceable a, Distanceable b ) {
 
       double mean = 0.0;
       int numComparisons = 0;
       
       Collection ac = a.toCollection();
       Collection bc = b.toCollection();
       
       for ( Iterator iter = ac.iterator(); iter.hasNext(); ) {
          Distanceable elementA = ( Distanceable ) iter.next();
 
          for ( Iterator iterator = bc.iterator(); iterator
                .hasNext(); ) {
             Distanceable elementB = ( Distanceable ) iterator.next();
             mean += elementA.distanceTo( elementB );
             numComparisons++;
          }
 
       }
 
       return mean / numComparisons;
 
    }
 }

1		package baseCode.algorithm.learning.unsupervised.cluster;
2
3		import java.util.Collection;
4		import java.util.Iterator;
5
6		import baseCode.common.Distanceable;
7
8		/**
9		* <hr>
10		* <p>
11		* Copyright (c) 2004 Columbia University
12		*
13		* @author pavlidis
14		* @version $Id: AverageLinkageDistancer.java,v 1.3 2004/08/02 15:03:43 pavlidis Exp $
15		*/
16		public class AverageLinkageDistancer implements Distancer {
17
18		/*
19		* (non-Javadoc)
20		*
21		* @see baseCode.algorithm.learning.unsupervised.cluster.Distance#distance(java.lang.Object, java.lang.Object)
22		*/
23	0	public double distance( Distanceable a, Distanceable b ) {
24
25	0	double mean = 0.0;
26	0	int numComparisons = 0;
27
28	0	Collection ac = a.toCollection();
29	0	Collection bc = b.toCollection();
30
31	0	for ( Iterator iter = ac.iterator(); iter.hasNext(); ) {
32	0	Distanceable elementA = ( Distanceable ) iter.next();
33
34	0	for ( Iterator iterator = bc.iterator(); iterator
35		.hasNext(); ) {
36	0	Distanceable elementB = ( Distanceable ) iterator.next();
37	0	mean += elementA.distanceTo( elementB );
38	0	numComparisons++;
39		}
40
41		}
42
43	0	return mean / numComparisons;
44
45		}
46		}