package jalview.analysis;
-import static org.testng.Assert.assertEquals;
+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 testComputePairwiseScores()
+ 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()
{
- String[] seqs = new String[] { "FKL", "R-D", "QIA", "GWC" };
- PCA pca = new PCA(seqs, false, "BLOSUM62");
+ af = new FileLoader().LoadFileWaitTillLoaded(TESTSEQS,
+ DataSourceType.PASTE);
+ }
- MatrixI pairwise = pca.computePairwiseScores();
+ @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();
+
/*
- * should be NxN where N = number of sequences
+ * no features = no scores!
*/
- assertEquals(pairwise.height(), 4);
- assertEquals(pairwise.width(), 4);
+ 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);
/*
- * should be symmetrical (because BLOSUM62 is)
+ * 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
*/
- for (int i = 0; i < pairwise.height(); i++)
- {
- for (int j = 0; j < pairwise.width(); j++)
- {
- assertEquals(pairwise.getValue(i, j), pairwise.getValue(j, i),
- "Not symmetric");
- }
- }
+ 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);
+
/*
- * verify expected BLOSUM dot product scores
- * Note: gap is treated like 'X' [22] in the matrix
+ * 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
+ * }
*/
- // F.F + K.K + L.L = 6 + 5 + 4 = 15
- assertEquals(pairwise.getValue(0, 0), 15d);
- // R.R + X.X + D.D = 5 + -1 + 6 = 10
- assertEquals(pairwise.getValue(1, 1), 10d);
- // Q.Q + I.I + A.A = 5 + 4 + 4 = 13
- assertEquals(pairwise.getValue(2, 2), 13d);
- // G.G + W.W + C.C = 6 + 11 + 9 = 26
- assertEquals(pairwise.getValue(3, 3), 26d);
- // F.R + K.X + L.D = -3 + -1 + -3 = -8
- assertEquals(pairwise.getValue(0, 1), -8d);
- // F.Q + K.I + L.A = -3 + -3 + -1 = -7
- assertEquals(pairwise.getValue(0, 2), -7d);
- // F.G + K.W + L.C = -3 + -3 + -1 = -7
- assertEquals(pairwise.getValue(0, 3), -7d);
- // R.Q + X.I + D.A = 1 + -1 + -2 = -2
- assertEquals(pairwise.getValue(1, 2), -2d);
- // R.G + X.W + D.C = -2 + -2 + -3 = -7
- assertEquals(pairwise.getValue(1, 3), -7d);
- // Q.G + I.W + A.C = -2 + -3 + 0 = -5
- assertEquals(pairwise.getValue(2, 3), -5d);
+ 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);
}
}
git://source.jalview.org / jalview.git / blobdiff