Classes

Class	Line #	Total Statements	Complexity	Uncovered Elements	TOTAL Coverage	Actions
PCAModel	33	60	24	93	0.00%	Show methods

Class PCAModel

Class PCAModel	Line # 33	Total Statements 60	Complexity 24	Uncovered Elements 93	TOTAL Coverage 0.00%
PCAModel(AlignmentView,SequenceI[],boolean,ScoreModelI,SimilarityParamsI)   PCAModel(AlignmentView,SequenceI[],boolean,ScoreModelI,SimilarityParamsI)	6464	5.05	1.01	5.05	0.0 0.00%
run() : void   run() : void	7474	12.012	4.04	16.016	0.0 0.00%
updateRc(RotatableCanvasI) : void   updateRc(RotatableCanvasI) : void	101101	1.01	1.01	1.01	0.0 0.00%
isNucleotide() : boolean   isNucleotide() : boolean	106106	1.01	1.01	1.01	0.0 0.00%
setNucleotide(boolean) : void   setNucleotide(boolean) : void	111111	1.01	1.01	1.01	0.0 0.00%
getTop() : int   getTop() : int	121121	1.01	1.01	1.01	0.0 0.00%
updateRcView(int,int,int) : void   updateRcView(int,int,int) : void	136136	3.03	2.02	5.05	0.0 0.00%
getDetails() : String   getDetails() : String	147147	1.01	1.01	1.01	0.0 0.00%
getSeqtrings() : AlignmentView   getSeqtrings() : AlignmentView	152152	1.01	1.01	1.01	0.0 0.00%
getPointsasCsv(boolean,int,int,int) : String   getPointsasCsv(boolean,int,int,int) : String	157157	26.026	7.07	38.038	0.0 0.00%
getPointPosition(int) : double[]   getPointPosition(int) : double[]	213213	6.06	1.01	6.06	0.0 0.00%
getScoreModelName() : String   getScoreModelName() : String	223223	1.01	2.02	3.03	0.0 0.00%
setScoreModel(ScoreModelI) : void   setScoreModel(ScoreModelI) : void	228228	1.01	1.01	1.01	0.0 0.00%

 

Contributing tests

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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.viewmodel;
22
23		import jalview.analysis.PCA;
24		import jalview.api.RotatableCanvasI;
25		import jalview.api.analysis.ScoreModelI;
26		import jalview.api.analysis.SimilarityParamsI;
27		import jalview.datamodel.AlignmentView;
28		import jalview.datamodel.SequenceI;
29		import jalview.datamodel.SequencePoint;
30
31		import java.util.Vector;
32
		0% Uncovered Elements: 93 (93) Complexity: 24 Complexity Density: 0.4
33		public class PCAModel
34		{
35		private volatile PCA pca;
36
37		int top;
38
39		AlignmentView seqstrings;
40
41		SequenceI[] seqs;
42
43		/*
44		* Name of score model used to calculate PCA
45		*/
46		ScoreModelI scoreModel;
47
48		private boolean nucleotide = false;
49
50		private Vector<SequencePoint> points;
51
52		private SimilarityParamsI similarityParams;
53
54		/**
55		* Constructor given sequence data, score model and score calculation
56		* parameter options.
57		*
58		* @param seqData
59		* @param sqs
60		* @param nuc
61		* @param modelName
62		* @param params
63		*/
		0% Uncovered Elements: 5 (5) Complexity: 1 Complexity Density: 0.2
64	0	public PCAModel(AlignmentView seqData, SequenceI[] sqs, boolean nuc,...
65		ScoreModelI modelName, SimilarityParamsI params)
66		{
67	0	seqstrings = seqData;
68	0	seqs = sqs;
69	0	nucleotide = nuc;
70	0	scoreModel = modelName;
71	0	similarityParams = params;
72		}
73
		0% Uncovered Elements: 16 (16) Complexity: 4 Complexity Density: 0.33
74	0	public void run()...
75		{
76	0	pca = new PCA(seqstrings, scoreModel, similarityParams);
77	0	pca.run();
78
79		// Now find the component coordinates
80	0	int ii = 0;
81
82	0	while ((ii < seqs.length) && (seqs[ii] != null))
83		{
84	0	ii++;
85		}
86
87	0	int height = pca.getHeight();
88		// top = pca.getM().height() - 1;
89	0	top = height - 1;
90
91	0	points = new Vector<SequencePoint>();
92	0	float[][] scores = pca.getComponents(top - 1, top - 2, top - 3, 100);
93
94	0	for (int i = 0; i < height; i++)
95		{
96	0	SequencePoint sp = new SequencePoint(seqs[i], scores[i]);
97	0	points.addElement(sp);
98		}
99		}
100
		0% Uncovered Elements: 1 (1) Complexity: 1 Complexity Density: 1
101	0	public void updateRc(RotatableCanvasI rc)...
102		{
103	0	rc.setPoints(points, pca.getHeight());
104		}
105
		0% Uncovered Elements: 1 (1) Complexity: 1 Complexity Density: 1
106	0	public boolean isNucleotide()...
107		{
108	0	return nucleotide;
109		}
110
		0% Uncovered Elements: 1 (1) Complexity: 1 Complexity Density: 1
111	0	public void setNucleotide(boolean nucleotide)...
112		{
113	0	this.nucleotide = nucleotide;
114		}
115
116		/**
117		*
118		*
119		* @return index of principle dimension of PCA
120		*/
		0% Uncovered Elements: 1 (1) Complexity: 1 Complexity Density: 1
121	0	public int getTop()...
122		{
123	0	return top;
124		}
125
126		/**
127		* update the 2d coordinates for the list of points to the given dimensions
128		* Principal dimension is getTop(). Next greatest eigenvector is getTop()-1.
129		* Note - pca.getComponents starts counting the spectrum from rank-2 to zero,
130		* rather than rank-1, so getComponents(dimN ...) == updateRcView(dimN+1 ..)
131		*
132		* @param dim1
133		* @param dim2
134		* @param dim3
135		*/
		0% Uncovered Elements: 5 (5) Complexity: 2 Complexity Density: 0.67
136	0	public void updateRcView(int dim1, int dim2, int dim3)...
137		{
138		// note: actual indices for components are dim1-1, etc (patch for JAL-1123)
139	0	float[][] scores = pca.getComponents(dim1 - 1, dim2 - 1, dim3 - 1, 100);
140
141	0	for (int i = 0; i < pca.getHeight(); i++)
142		{
143	0	points.elementAt(i).coord = scores[i];
144		}
145		}
146
		0% Uncovered Elements: 1 (1) Complexity: 1 Complexity Density: 1
147	0	public String getDetails()...
148		{
149	0	return pca.getDetails();
150		}
151
		0% Uncovered Elements: 1 (1) Complexity: 1 Complexity Density: 1
152	0	public AlignmentView getSeqtrings()...
153		{
154	0	return seqstrings;
155		}
156
		0% Uncovered Elements: 38 (38) Complexity: 7 Complexity Density: 0.27
157	0	public String getPointsasCsv(boolean transformed, int xdim, int ydim,...
158		int zdim)
159		{
160	0	StringBuffer csv = new StringBuffer();
161	0	csv.append("\"Sequence\"");
162	0	if (transformed)
163		{
164	0	csv.append(",");
165	0	csv.append(xdim);
166	0	csv.append(",");
167	0	csv.append(ydim);
168	0	csv.append(",");
169	0	csv.append(zdim);
170		}
171		else
172		{
173	0	for (int d = 1, dmax = pca.component(1).length; d <= dmax; d++)
174		{
175	0	csv.append("," + d);
176		}
177		}
178	0	csv.append("\n");
179	0	for (int s = 0; s < seqs.length; s++)
180		{
181	0	csv.append("\"" + seqs[s].getName() + "\"");
182	0	double fl[];
183	0	if (!transformed)
184		{
185		// output pca in correct order
186	0	fl = pca.component(s);
187	0	for (int d = fl.length - 1; d >= 0; d--)
188		{
189	0	csv.append(",");
190	0	csv.append(fl[d]);
191		}
192		}
193		else
194		{
195		// output current x,y,z coords for points
196	0	fl = getPointPosition(s);
197	0	for (int d = 0; d < fl.length; d++)
198		{
199	0	csv.append(",");
200	0	csv.append(fl[d]);
201		}
202		}
203	0	csv.append("\n");
204		}
205	0	return csv.toString();
206		}
207
208		/**
209		*
210		* @return x,y,z positions of point s (index into points) under current
211		* transform.
212		*/
		0% Uncovered Elements: 6 (6) Complexity: 1 Complexity Density: 0.17
213	0	public double[] getPointPosition(int s)...
214		{
215	0	double pts[] = new double[3];
216	0	float[] p = points.elementAt(s).coord;
217	0	pts[0] = p[0];
218	0	pts[1] = p[1];
219	0	pts[2] = p[2];
220	0	return pts;
221		}
222
		0% Uncovered Elements: 3 (3) Complexity: 2 Complexity Density: 2
223	0	public String getScoreModelName()...
224		{
225	0	return scoreModel == null ? "" : scoreModel.getName();
226		}
227
		0% Uncovered Elements: 1 (1) Complexity: 1 Complexity Density: 1
228	0	public void setScoreModel(ScoreModelI sm)...
229		{
230	0	this.scoreModel = sm;
231		}
232
233		}