Classes

Class	Line #	Total Statements	Complexity	TOTAL Coverage	Actions
AverageDistanceTree	32	32	15	0.00%	Show methods

Class AverageDistanceTree

Class AverageDistanceTree	Line # 32	Total Statements 32	Complexity 15	TOTAL Coverage 0.00%
AverageDistanceTree(AlignmentViewport,ScoreModelI,SimilarityParamsI)   AverageDistanceTree(AlignmentViewport,ScoreModelI,SimilarityParamsI)	4141	1.01	1.01	0.0 0.00%
findClusterDistance(int,int) : void   findClusterDistance(int,int) : void	5656	10.010	5.05	0.0 0.00%
findMinDistance() : double   findMinDistance() : double	8888	9.09	6.06	0.0 0.00%
findNewDistances(BinaryNode,BinaryNode,double) : void   findNewDistances(BinaryNode,BinaryNode,double) : void	115115	12.012	3.03	0.0 0.00%

 

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1		/*
2		* Jalview - A Sequence Alignment Editor and Viewer ($$Version-Rel$$)
3		* Copyright (C) $$Year-Rel$$ The Jalview Authors
4		*
5		* This file is part of Jalview.
6		*
7		* Jalview is free software: you can redistribute it and/or
8		* modify it under the terms of the GNU General Public License
9		* as published by the Free Software Foundation, either version 3
10		* of the License, or (at your option) any later version.
11		*
12		* Jalview is distributed in the hope that it will be useful, but
13		* WITHOUT ANY WARRANTY; without even the implied warranty
14		* of MERCHANTABILITY or FITNESS FOR A PARTICULAR
15		* PURPOSE. See the GNU General Public License for more details.
16		*
17		* You should have received a copy of the GNU General Public License
18		* along with Jalview. If not, see <http://www.gnu.org/licenses/>.
19		* The Jalview Authors are detailed in the 'AUTHORS' file.
20		*/
21		package jalview.analysis;
22
23		import jalview.api.analysis.ScoreModelI;
24		import jalview.api.analysis.SimilarityParamsI;
25		import jalview.datamodel.BinaryNode;
26		import jalview.viewmodel.AlignmentViewport;
27
28		/**
29		* This class implements distance calculations used in constructing a Average
30		* Distance tree (also known as UPGMA)
31		*/
		0% Uncovered Elements: 54 (54) Complexity: 15 Complexity Density: 0.47
32		public class AverageDistanceTree extends TreeBuilder
33		{
34		/**
35		* Constructor
36		*
37		* @param av
38		* @param sm
39		* @param scoreParameters
40		*/
		0% Uncovered Elements: 1 (1) Complexity: 1 Complexity Density: 1
41	0	public AverageDistanceTree(AlignmentViewport av, ScoreModelI sm,...
42		SimilarityParamsI scoreParameters)
43		{
44	0	super(av, sm, scoreParameters);
45		}
46
47		/**
48		* Calculates and saves the distance between the combination of cluster(i) and
49		* cluster(j) and all other clusters. An average of the distances from
50		* cluster(i) and cluster(j) is calculated, weighted by the sizes of each
51		* cluster.
52		*
53		* @param i
54		* @param j
55		*/
		0% Uncovered Elements: 16 (16) Complexity: 5 Complexity Density: 0.5
56	0	@Override...
57		protected void findClusterDistance(int i, int j)
58		{
59	0	int noi = clusters.elementAt(i).cardinality();
60	0	int noj = clusters.elementAt(j).cardinality();
61
62		// New distances from cluster i to others
63	0	double[] newdist = new double[noseqs];
64
65	0	for (int l = 0; l < noseqs; l++)
66		{
67	0	if ((l != i) && (l != j))
68		{
69	0	newdist[l] = ((distances.getValue(i, l) * noi)
70		+ (distances.getValue(j, l) * noj)) / (noi + noj);
71		}
72		else
73		{
74	0	newdist[l] = 0;
75		}
76		}
77
78	0	for (int ii = 0; ii < noseqs; ii++)
79		{
80	0	distances.setValue(i, ii, newdist[ii]);
81	0	distances.setValue(ii, i, newdist[ii]);
82		}
83		}
84
85		/**
86		* {@inheritDoc}
87		*/
		0% Uncovered Elements: 17 (17) Complexity: 6 Complexity Density: 0.67
88	0	@Override...
89		protected double findMinDistance()
90		{
91	0	double min = Double.MAX_VALUE;
92
93	0	for (int i = 0; i < (noseqs - 1); i++)
94		{
95	0	for (int j = i + 1; j < noseqs; j++)
96		{
97	0	if (!done.get(i) && !done.get(j))
98		{
99	0	if (distances.getValue(i, j) < min)
100		{
101	0	mini = i;
102	0	minj = j;
103
104	0	min = distances.getValue(i, j);
105		}
106		}
107		}
108		}
109	0	return min;
110		}
111
112		/**
113		* {@inheritDoc}
114		*/
		0% Uncovered Elements: 16 (16) Complexity: 3 Complexity Density: 0.25
115	0	@Override...
116		protected void findNewDistances(BinaryNode nodei, BinaryNode nodej,
117		double dist)
118		{
119	0	double ih = 0;
120	0	double jh = 0;
121
122	0	BinaryNode sni = nodei;
123	0	BinaryNode snj = nodej;
124
125	0	while (sni != null)
126		{
127	0	ih = ih + sni.dist;
128	0	sni = (BinaryNode) sni.left();
129		}
130
131	0	while (snj != null)
132		{
133	0	jh = jh + snj.dist;
134	0	snj = (BinaryNode) snj.left();
135		}
136
137	0	nodei.dist = ((dist / 2) - ih);
138	0	nodej.dist = ((dist / 2) - jh);
139		}
140
141		}