--- /dev/null
+package jalview.analysis;
+
+import static org.testng.Assert.assertNotNull;
+import static org.testng.internal.junit.ArrayAsserts.assertArrayEquals;
+
+import jalview.analysis.scoremodels.FeatureDistanceModel;
+import jalview.analysis.scoremodels.PIDModel;
+import jalview.analysis.scoremodels.ScoreModels;
+import jalview.analysis.scoremodels.SimilarityParams;
+import jalview.api.analysis.ScoreModelI;
+import jalview.api.analysis.SimilarityParamsI;
+import jalview.api.analysis.ViewBasedAnalysisI;
+import jalview.datamodel.AlignmentView;
+import jalview.datamodel.SequenceFeature;
+import jalview.datamodel.SequenceI;
+import jalview.gui.AlignFrame;
+import jalview.io.DataSourceType;
+import jalview.io.FileLoader;
+import jalview.math.MatrixI;
+
+import org.testng.annotations.BeforeTest;
+import org.testng.annotations.Test;
+
+public class PCATest
+{
+
+ private static final String TESTSEQS = ">s1\nAFRK\n>s2\nAFSS\n>s3\nAFTL\n>s4\nARSL\n";
+ private AlignFrame af;
+
+ @Test(groups = "Functional")
+ public void testComputeSimilarity_blosum62()
+ {
+ setUp();
+ SimilarityParamsI params = new SimilarityParams(true, false, true,
+ false);
+ AlignmentView view = af.getViewport().getAlignmentView(false);
+ ScoreModelI blosum62 = ScoreModels.getInstance().getBlosum62();
+ PCA pca = new PCA(view, blosum62, params);
+
+ MatrixI result = pca.computeSimilarity();
+ assertNotNull(result);
+
+ /*
+ * AFRK^AFRK = 4+6+5+5 = 20
+ * AFRK^AFSS = 4+6+-1+0 = 9
+ * AFRK^AFTL = 4+6+-1+-2 = 7
+ * AFRK^ARSL = 4+-3+-1+-2 = -2
+ */
+ assertArrayEquals(result.getRow(0), new double[] { 20, 9, 7, -2 },
+ 0.00001d);
+ }
+
+ @BeforeTest(alwaysRun = true)
+ public void setUp()
+ {
+ af = new FileLoader().LoadFileWaitTillLoaded(TESTSEQS,
+ DataSourceType.PASTE);
+ }
+
+ @Test(groups = "Functional")
+ public void testComputeSimilarity_PID()
+ {
+ setUp();
+ SimilarityParamsI params = new SimilarityParams(true, false, true,
+ false);
+ AlignmentView view = af.getViewport().getAlignmentView(false);
+ ScoreModelI pid = new PIDModel();
+ PCA pca = new PCA(view, pid, params);
+
+ MatrixI result = pca.computeSimilarity();
+ assertNotNull(result);
+
+ /*
+ * AFRK^AFRK = 4 scaled to width
+ * AFRK^AFSS = 2
+ * AFRK^AFTL = 2
+ * AFRK^ARSL = 1
+ */
+ assertArrayEquals(new double[] { 4d, 2d, 2d, 1d },
+ result.getRow(0), 0.00001d);
+ }
+
+ @Test(groups = "Functional")
+ public void testComputeSimilarity_featureDistances()
+ {
+ setUp();
+ SimilarityParamsI params = new SimilarityParams(true, false, true,
+ false);
+ AlignmentView view = af.getViewport().getAlignmentView(false);
+ ScoreModelI featureModel = new FeatureDistanceModel();
+ PCA pca = new PCA(view, featureModel, params);
+
+ MatrixI result = pca.computeSimilarity();
+
+ /*
+ * no features = no scores!
+ */
+ assertArrayEquals(new double[] { 0d, 0d, 0d, 0d },
+ result.getRow(0), 0.00001d);
+
+ SequenceI[] seqs = af.getViewport().getAlignment().getSequencesArray();
+ seqs[0].addSequenceFeature(new SequenceFeature("Cath", "", 1, 4, 0f,
+ null));
+ seqs[1].addSequenceFeature(new SequenceFeature("Cath", "", 1, 4, 0f,
+ null));
+ seqs[2].addSequenceFeature(new SequenceFeature("Pfam", "", 1, 4, 0f,
+ null));
+ seqs[3].addSequenceFeature(new SequenceFeature("Pfam", "", 2, 3, 0f,
+ null));
+
+ af.getFeatureRenderer().findAllFeatures(true);
+ ((ViewBasedAnalysisI) featureModel)
+ .configureFromAlignmentView(af.alignPanel);
+
+ /*
+ * feature distance scores are (average number of features not shared):
+ * diagonal: 0
+ * seq1^seq2 0
+ * seq1^seq3 8 / 4 = 2
+ * seq1^seq4 6 / 4 = 1.5
+ * seq2^seq3 8 / 4 = 2
+ * seq2^seq4 6 / 3 = 1.5
+ * seq3^seq4 2 / 4 = 0.5
+ * so
+ * { 0, 0, 2, 1.5
+ * 0, 0, 2, 1.5
+ * 2, 2, 0, 0.5
+ * 1.5, 1.5, 0.5, 0
+ * }
+ * subtract each value from the max value to get similarity scores
+ */
+ result = pca.computeSimilarity();
+ // assertArrayEquals(new double[] { 2d, 2d, 0d, 0.5d }, result.getRow(0),
+ // 0.00001d);
+ // assertArrayEquals(new double[] { 2d, 2d, 0d, 0.5d }, result.getRow(1),
+ // 0.00001d);
+ // assertArrayEquals(new double[] { 0d, 0d, 2d, 1.5d }, result.getRow(2),
+ // 0.00001d);
+ // assertArrayEquals(new double[] { 0.5d, 0.5d, 1.5d, 2d },
+ // result.getRow(3), 0.00001d);
+
+ /*
+ * JAL-2424 bug means instead we get distance scores of
+ * 8 / 5 = 1.6
+ * 6 / 5 = 1.2
+ * 2 / 5 = 0.4
+ * so (until bug is fixed)
+ * { 0, 0, 1.6, 1.2
+ * 0, 0, 1.6, 1.2
+ * 1.6, 1.6, 0, 0.4
+ * 1.2, 1.2, 0.4, 0
+ * }
+ */
+ assertArrayEquals(new double[] { 1.6d, 1.6d, 0d, 0.4d },
+ result.getRow(0),
+ 0.00001d);
+ assertArrayEquals(new double[] { 1.6d, 1.6d, 0d, 0.4d },
+ result.getRow(1),
+ 0.00001d);
+ assertArrayEquals(new double[] { 0d, 0d, 1.6d, 1.2d },
+ result.getRow(2),
+ 0.00001d);
+ assertArrayEquals(new double[] { 0.4d, 0.4d, 1.2d, 1.6d },
+ result.getRow(3), 0.00001d);
+ }
+}