Classes

Class	Line #	Total Statements	Complexity	TOTAL Coverage	Actions
PCAModel	38	65	29	0.4705882447.1%	Show methods

Class PCAModel

Class PCAModel	Line # 38	Total Statements 65	Complexity 29	TOTAL Coverage 0.4705882447.1%
PCAModel(AlignmentView,SequenceI[],boolean,ScoreModelI,SimilarityParamsI)   PCAModel(AlignmentView,SequenceI[],boolean,ScoreModelI,SimilarityParamsI)	8686	5.05	1.01	1.0 1.0100%
calculate() : void   calculate() : void	100100	16.016	4.04	1.0 1.0100%
updateRc(RotatableCanvasI) : void   updateRc(RotatableCanvasI) : void	135135	1.01	1.01	1.0 1.0100%
isNucleotide() : boolean   isNucleotide() : boolean	140140	1.01	1.01	0.0 0.00%
setNucleotide(boolean) : void   setNucleotide(boolean) : void	145145	1.01	1.01	0.0 0.00%
getTop() : int   getTop() : int	155155	1.01	1.01	1.0 1.0100%
setTop(int) : void   setTop(int) : void	160160	1.01	1.01	1.0 1.0100%
updateRcView(int,int,int) : void   updateRcView(int,int,int) : void	175175	3.03	2.02	0.0 0.00%
getDetails() : String   getDetails() : String	186186	1.01	1.01	0.0 0.00%
getInputData() : AlignmentView   getInputData() : AlignmentView	191191	1.01	1.01	0.0 0.00%
setInputData(AlignmentView) : void   setInputData(AlignmentView) : void	196196	1.01	1.01	1.0 1.0100%
getPointsasCsv(boolean,int,int,int) : String   getPointsasCsv(boolean,int,int,int) : String	201201	26.026	6.06	0.0 0.00%
getScoreModelName() : String   getScoreModelName() : String	249249	1.01	2.02	0.6666667 0.666666766.7%
setScoreModel(ScoreModelI) : void   setScoreModel(ScoreModelI) : void	254254	1.01	1.01	0.0 0.00%
getSimilarityParameters() : SimilarityParamsI   getSimilarityParameters() : SimilarityParamsI	264264	1.01	1.01	1.0 1.0100%
getSequencePoints() : List<SequencePoint>   getSequencePoints() : List<SequencePoint>	269269	1.01	1.01	1.0 1.0100%
setSequencePoints(List<SequencePoint>) : void   setSequencePoints(List<SequencePoint>) : void	274274	1.01	1.01	1.0 1.0100%
getPcaData() : PCA   getPcaData() : PCA	284284	1.01	1.01	1.0 1.0100%
setPCA(PCA) : void   setPCA(PCA) : void	289289	1.01	1.01	1.0 1.0100%

 

Contributing tests

Contributing tests

Select all

	Test contribution	Test	Result	Actions
	0.47058824	jalview.project.Jalview2xmlTests.testPcaViewAssociationjalview.project.Jalview2xmlTests.testPcaViewAssociation	1PASS

 

Source view

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.AlignmentAnnotation;
28		import jalview.datamodel.AlignmentView;
29		import jalview.datamodel.Point;
30		import jalview.datamodel.SequenceI;
31		import jalview.datamodel.SequencePoint;
32
33		import java.util.ArrayList;
34		import java.util.HashMap;
35		import java.util.List;
36		import java.util.Vector;
37
		47.1% Uncovered Elements: 54 (102) Complexity: 29 Complexity Density: 0.45
38		public class PCAModel
39		{
40		/*
41		* inputs
42		*/
43		private AlignmentView inputData;
44
45		private SequenceI[] seqs;
46
47		private final SimilarityParamsI similarityParams;
48
49		/*
50		* options - score model, nucleotide / protein
51		*/
52		private ScoreModelI scoreModel;
53
54		private boolean nucleotide = false;
55
56		/*
57		* outputs
58		*/
59		private PCA pca;
60
61		int top;
62
63		private List<SequencePoint> points;
64
65		// Map to store node pos : annotation details
66		// (additional details from annotation property)
67		protected HashMap<Integer, String> annotationDetails;
68
69
70		protected List<String> labels;
71
72
73		ArrayList<AlignmentAnnotation> ssAnnotationForSeqs;
74
75
76		/**
77		* Constructor given sequence data, score model and score calculation
78		* parameter options.
79		*
80		* @param seqData
81		* @param sqs
82		* @param nuc
83		* @param modelName
84		* @param params
85		*/
		100% Uncovered Elements: 0 (5) Complexity: 1 Complexity Density: 0.2
86	2	public PCAModel(AlignmentView seqData, SequenceI[] sqs, boolean nuc,...
87		ScoreModelI modelName, SimilarityParamsI params)
88		{
89	2	inputData = seqData;
90	2	seqs = sqs;
91	2	nucleotide = nuc;
92	2	scoreModel = modelName;
93	2	similarityParams = params;
94		}
95
96		/**
97		* Performs the PCA calculation (in the same thread) and extracts result data
98		* needed for visualisation by PCAPanel
99		*/
		100% Uncovered Elements: 0 (20) Complexity: 4 Complexity Density: 0.25
100	1	public void calculate()...
101		{
102	1	pca = new PCA(inputData, scoreModel, similarityParams);
103
104	1	labels = new ArrayList<String>();
105	1	annotationDetails = new HashMap<Integer, String>();
106	1	ssAnnotationForSeqs = new ArrayList<AlignmentAnnotation>();
107	1	seqs = scoreModel.expandSeqData(seqs, inputData, similarityParams,
108		labels, ssAnnotationForSeqs, annotationDetails);
109
110
111	1	pca.run(); // executes in same thread, wait for completion
112
113		// Now find the component coordinates
114	1	int ii = 0;
115
116	16	while ((ii < seqs.length) && (seqs[ii] != null))
117		{
118	15	ii++;
119		}
120
121	1	int height = pca.getHeight();
122		// top = pca.getM().height() - 1;
123	1	top = height - 1;
124
125	1	points = new Vector<>();
126	1	Point[] scores = pca.getComponents(top - 1, top - 2, top - 3, 1);
127
128	16	for (int i = 0; i < height; i++)
129		{
130	15	SequencePoint sp = new SequencePoint(seqs[i], scores[i]);
131	15	points.add(sp);
132		}
133		}
134
		100% Uncovered Elements: 0 (1) Complexity: 1 Complexity Density: 1
135	1	public void updateRc(RotatableCanvasI rc)...
136		{
137	1	rc.setPoints(points, pca.getHeight());
138		}
139
		0% Uncovered Elements: 1 (1) Complexity: 1 Complexity Density: 1
140	0	public boolean isNucleotide()...
141		{
142	0	return nucleotide;
143		}
144
		0% Uncovered Elements: 1 (1) Complexity: 1 Complexity Density: 1
145	0	public void setNucleotide(boolean nucleotide)...
146		{
147	0	this.nucleotide = nucleotide;
148		}
149
150		/**
151		* Answers the index of the principal dimension of the PCA
152		*
153		* @return
154		*/
		100% Uncovered Elements: 0 (1) Complexity: 1 Complexity Density: 1
155	1	public int getTop()...
156		{
157	1	return top;
158		}
159
		100% Uncovered Elements: 0 (1) Complexity: 1 Complexity Density: 1
160	1	public void setTop(int t)...
161		{
162	1	top = t;
163		}
164
165		/**
166		* Updates the 3D coordinates for the list of points to the given dimensions.
167		* Principal dimension is getTop(). Next greatest eigenvector is getTop()-1.
168		* Note - pca.getComponents starts counting the spectrum from rank-2 to zero,
169		* rather than rank-1, so getComponents(dimN ...) == updateRcView(dimN+1 ..)
170		*
171		* @param dim1
172		* @param dim2
173		* @param dim3
174		*/
		0% Uncovered Elements: 5 (5) Complexity: 2 Complexity Density: 0.67
175	0	public void updateRcView(int dim1, int dim2, int dim3)...
176		{
177		// note: actual indices for components are dim1-1, etc (patch for JAL-1123)
178	0	Point[] scores = pca.getComponents(dim1 - 1, dim2 - 1, dim3 - 1, 1);
179
180	0	for (int i = 0; i < pca.getHeight(); i++)
181		{
182	0	points.get(i).coord = scores[i];
183		}
184		}
185
		0% Uncovered Elements: 1 (1) Complexity: 1 Complexity Density: 1
186	0	public String getDetails()...
187		{
188	0	return pca.getDetails();
189		}
190
		0% Uncovered Elements: 1 (1) Complexity: 1 Complexity Density: 1
191	0	public AlignmentView getInputData()...
192		{
193	0	return inputData;
194		}
195
		100% Uncovered Elements: 0 (1) Complexity: 1 Complexity Density: 1
196	1	public void setInputData(AlignmentView data)...
197		{
198	1	inputData = data;
199		}
200
		0% Uncovered Elements: 36 (36) Complexity: 6 Complexity Density: 0.23
201	0	public String getPointsasCsv(boolean transformed, int xdim, int ydim,...
202		int zdim)
203		{
204	0	StringBuffer csv = new StringBuffer();
205	0	csv.append("\"Sequence\"");
206	0	if (transformed)
207		{
208	0	csv.append(",");
209	0	csv.append(xdim);
210	0	csv.append(",");
211	0	csv.append(ydim);
212	0	csv.append(",");
213	0	csv.append(zdim);
214		}
215		else
216		{
217	0	for (int d = 1, dmax = pca.component(1).length; d <= dmax; d++)
218		{
219	0	csv.append("," + d);
220		}
221		}
222	0	csv.append("\n");
223	0	for (int s = 0; s < seqs.length; s++)
224		{
225	0	csv.append("\"" + seqs[s].getName() + "\"");
226	0	double fl[];
227	0	if (!transformed)
228		{
229		// output pca in correct order
230	0	fl = pca.component(s);
231	0	for (int d = fl.length - 1; d >= 0; d--)
232		{
233	0	csv.append(",");
234	0	csv.append(fl[d]);
235		}
236		}
237		else
238		{
239	0	Point p = points.get(s).coord;
240	0	csv.append(",").append(p.x);
241	0	csv.append(",").append(p.y);
242	0	csv.append(",").append(p.z);
243		}
244	0	csv.append("\n");
245		}
246	0	return csv.toString();
247		}
248
		66.7% Uncovered Elements: 1 (3) Complexity: 2 Complexity Density: 2
249	3	public String getScoreModelName()...
250		{
251	3	return scoreModel == null ? "" : scoreModel.getName();
252		}
253
		0% Uncovered Elements: 1 (1) Complexity: 1 Complexity Density: 1
254	0	public void setScoreModel(ScoreModelI sm)...
255		{
256	0	this.scoreModel = sm;
257		}
258
259		/**
260		* Answers the parameters configured for pairwise similarity calculations
261		*
262		* @return
263		*/
		100% Uncovered Elements: 0 (1) Complexity: 1 Complexity Density: 1
264	1	public SimilarityParamsI getSimilarityParameters()...
265		{
266	1	return similarityParams;
267		}
268
		100% Uncovered Elements: 0 (1) Complexity: 1 Complexity Density: 1
269	1	public List<SequencePoint> getSequencePoints()...
270		{
271	1	return points;
272		}
273
		100% Uncovered Elements: 0 (1) Complexity: 1 Complexity Density: 1
274	1	public void setSequencePoints(List<SequencePoint> sp)...
275		{
276	1	points = sp;
277		}
278
279		/**
280		* Answers the object holding the values of the computed PCA
281		*
282		* @return
283		*/
		100% Uncovered Elements: 0 (1) Complexity: 1 Complexity Density: 1
284	1	public PCA getPcaData()...
285		{
286	1	return pca;
287		}
288
		100% Uncovered Elements: 0 (1) Complexity: 1 Complexity Density: 1
289	1	public void setPCA(PCA data)...
290		{
291	1	pca = data;
292		}
293		}