From: TZVanaalten Date: Fri, 18 Aug 2017 13:49:38 +0000 (+0100) Subject: JAL-2668 add tests for HMMER commands, annotation and io X-Git-Url: http://source.jalview.org/gitweb/?a=commitdiff_plain;h=46406ae21c62b964714ce136c9d692985c17211d;p=jalview.git JAL-2668 add tests for HMMER commands, annotation and io --- diff --git a/src/jalview/analysis/AAFrequency.java b/src/jalview/analysis/AAFrequency.java index 9f905f6..6a69c73 100755 --- a/src/jalview/analysis/AAFrequency.java +++ b/src/jalview/analysis/AAFrequency.java @@ -228,14 +228,13 @@ public class AAFrequency { ProfileI[] result = new ProfileI[width]; int symbolCount = hmm.getNumberOfSymbols(); - String alph = hmm.getAlphabetType(); for (int column = start; column < end; column++) { ResidueCount counts = new ResidueCount(); for (char symbol : hmm.getSymbols()) { - int value = getAnalogueCount(hmm, column, removeBelowBackground, - alph, symbol); + int value = getAnalogueCount(hmm, column, symbol, + removeBelowBackground); counts.put(symbol, value); } int maxCount = counts.getModalCount(); @@ -902,7 +901,6 @@ public class AAFrequency if (hmm != null) { - String alph = hmm.getAlphabetType(); int size = hmm.getNumberOfSymbols(); char symbols[] = new char[size]; int values[] = new int[size]; @@ -913,8 +911,8 @@ public class AAFrequency { char symbol = charList.get(i); symbols[i] = symbol; - int value = getAnalogueCount(hmm, column, removeBelowBackground, - alph, symbol); + int value = getAnalogueCount(hmm, column, symbol, + removeBelowBackground); values[i] = value; totalCount += value; } @@ -961,20 +959,21 @@ public class AAFrequency * @param hmm * @param column * @param removeBelowBackground - * @param alph - * The alphabet the HMM is based on + * When true, this method returns 0 for any symbols with a match + * emission probability less than the background frequency. * @param symbol * @return */ - private static int getAnalogueCount(HiddenMarkovModel hmm, int column, - boolean removeBelowBackground, String alph, char symbol) + static int getAnalogueCount(HiddenMarkovModel hmm, int column, + char symbol, boolean removeBelowBackground) { Double value; value = hmm.getMatchEmissionProbability(column, symbol); double freq; - freq = ResidueProperties.backgroundFrequencies.get(alph).get(symbol); + freq = ResidueProperties.backgroundFrequencies + .get(hmm.getAlphabetType()).get(symbol); if (value < freq && removeBelowBackground) { return 0; diff --git a/src/jalview/datamodel/HiddenMarkovModel.java b/src/jalview/datamodel/HiddenMarkovModel.java index 2b9bd3b..086f5cd 100644 --- a/src/jalview/datamodel/HiddenMarkovModel.java +++ b/src/jalview/datamodel/HiddenMarkovModel.java @@ -4,7 +4,6 @@ import java.util.ArrayList; import java.util.HashMap; import java.util.List; import java.util.Map; -import java.util.Scanner; /** * Data structure which stores a hidden Markov model. Currently contains file @@ -41,8 +40,6 @@ public class HiddenMarkovModel final static String YES = "yes"; final static String NO = "no"; - - int numberOfSymbols; // keys for file properties hashmap private final String NAME = "NAME"; @@ -129,7 +126,6 @@ public class HiddenMarkovModel this.nodeLookup = new HashMap<>(hmm.nodeLookup); this.symbolIndexLookup = new HashMap<>( hmm.symbolIndexLookup); - this.numberOfSymbols = hmm.numberOfSymbols; this.fileHeader = new String(hmm.fileHeader); } @@ -454,7 +450,6 @@ public class HiddenMarkovModel public Double getStateTransitionProbability(int alignColumn, int transition) { - int transitionIndex; int nodeIndex; Double probability; if (nodeLookup.containsKey(alignColumn)) @@ -499,7 +494,8 @@ public class HiddenMarkovModel } /** - * Returns the consensus at a given alignment column. + * Returns the consensus at a given alignment column. If the character is + * lower case, its emission probability is less than 0.5. * * @param columnIndex * The index of the column in the alignment for which the consensus @@ -532,6 +528,10 @@ public class HiddenMarkovModel mostLikely = character; } } + if (highestProb < 0.5) + { + mostLikely = Character.toLowerCase(mostLikely); + } return mostLikely; } @@ -597,28 +597,7 @@ public class HiddenMarkovModel */ public int getNumberOfSymbols() { - return numberOfSymbols; - } - - /** - * Fills symbol array and whilst doing so, updates the value of the number of - * symbols. - * - * @param parser - * The scanner scanning the symbol line in the file. - */ - public void fillSymbols(Scanner parser) - { - int i = 0; - while (parser.hasNext()) - { - String strSymbol = parser.next(); - char[] symbol = strSymbol.toCharArray(); - symbols.add(symbol[0]); - symbolIndexLookup.put(symbol[0], i); - i++; - } - numberOfSymbols = symbols.size(); + return symbols.size(); } /** @@ -1028,6 +1007,15 @@ public class HiddenMarkovModel return consensus; } + public int getSymbolIndex(char c) + { + return symbolIndexLookup.get(c); + } + + public void setSymbolIndex(Character c, Integer i) + { + symbolIndexLookup.put(c, i); + } } diff --git a/src/jalview/hmmer/HMMERCommands.java b/src/jalview/hmmer/HMMERCommands.java index a5a4d7d..6a538fc 100644 --- a/src/jalview/hmmer/HMMERCommands.java +++ b/src/jalview/hmmer/HMMERCommands.java @@ -136,11 +136,6 @@ public class HMMERCommands if (seqs != null) { StockholmFile file = new StockholmFile(new Alignment(seqs)); - boolean removeAnnots = false; - if (hmm == null) - { - removeAnnots = true; - } String output = file.print(seqs, false); PrintWriter writer = new PrintWriter(stoLocation); writer.println(output); @@ -150,7 +145,9 @@ public class HMMERCommands if (hmm != null) { HMMFile file = new HMMFile(hmm); - file.exportFile(hmmLocation); + PrintWriter writer = new PrintWriter(hmmLocation); + writer.print(file.print()); + writer.close(); } } diff --git a/src/jalview/schemes/HMMERColourScheme.java b/src/jalview/schemes/HMMERColourScheme.java index 7a8ef94..f3691f0 100644 --- a/src/jalview/schemes/HMMERColourScheme.java +++ b/src/jalview/schemes/HMMERColourScheme.java @@ -79,13 +79,13 @@ public class HMMERColourScheme extends ResidueColourScheme { return new Color(230, 0, 0); } - Double value = Math.log(prob / freq) / Math.log(2); + Double value = Math.log(prob / freq); Color colour = null; if (value > 0) { colour = ColorUtils.getGraduatedColour(value.floatValue(), 0, - Color.WHITE, 6.52f, Color.blue); + Color.WHITE, 4.52f, Color.blue); } else if (value < 0) { diff --git a/test/jalview/analysis/AAFrequencyTest.java b/test/jalview/analysis/AAFrequencyTest.java index 86a2a0c..9a0b33f 100644 --- a/test/jalview/analysis/AAFrequencyTest.java +++ b/test/jalview/analysis/AAFrequencyTest.java @@ -25,11 +25,20 @@ import static org.testng.AssertJUnit.assertNull; import jalview.datamodel.AlignmentAnnotation; import jalview.datamodel.Annotation; +import jalview.datamodel.HiddenMarkovModel; +import jalview.datamodel.Profile; import jalview.datamodel.ProfileI; +import jalview.datamodel.Profiles; import jalview.datamodel.ProfilesI; import jalview.datamodel.Sequence; import jalview.datamodel.SequenceI; import jalview.gui.JvOptionPane; +import jalview.io.DataSourceType; +import jalview.io.FileParse; +import jalview.io.HMMFile; + +import java.io.IOException; +import java.net.MalformedURLException; import org.testng.annotations.BeforeClass; import org.testng.annotations.Test; @@ -37,6 +46,8 @@ import org.testng.annotations.Test; public class AAFrequencyTest { + HiddenMarkovModel hmm; + @BeforeClass(alwaysRun = true) public void setUpJvOptionPane() { @@ -233,43 +244,78 @@ public class AAFrequencyTest assertEquals("T", ann.displayCharacter); } - /* - @Test(groups = { "Functional" }) - public void testGetHMMProfileFor() + + @Test(groups = { "Functional" }, priority = 1) + public void testExtractHMMProfile() throws MalformedURLException, IOException { HMMFile hmmFile = new HMMFile(new FileParse( "test/jalview/io/test_MADE1_hmm.txt", DataSourceType.FILE)); - hmmFile.parse(); - HiddenMarkovModel hmm = hmmFile.getHMM(); + hmm = hmmFile.getHMM(); int[] expected = { 0, 4, 100, 'T', 71, 'C', 12, 'G', 9, 'A', 9 }; - int[] actual = AAFrequency.getHMMProfileFor(hmm, 17, false); + int[] actual = AAFrequency.extractHMMProfile(hmm, 17, false); for (int i = 0; i < actual.length; i++) { if (i == 2) { - assertEquals(actual[i], expected[i], 5); + assertEquals(actual[i], expected[i]); } else { - assertEquals(actual[i], expected[i], 1); + assertEquals(actual[i], expected[i]); } } - int[] expected2 = { 0, 4, 85, 'A', 85, 'C', 0, 'G', 0, 'T', 0 }; - int[] actual2 = AAFrequency.getHMMProfileFor(hmm, 2, true); - for (int i = 0; i < actual.length; i++) + int[] expected2 = { 0, 4, 100, 'A', 85, 'C', 0, 'G', 0, 'T', 0 }; + int[] actual2 = AAFrequency.extractHMMProfile(hmm, 2, true); + for (int i = 0; i < actual2.length; i++) { if (i == 2) { - assertEquals(actual[i], expected[i], 5); + assertEquals(actual[i], expected[i]); } else { - assertEquals(actual[i], expected[i], 1); + assertEquals(actual[i], expected[i]); } } + + assertNull(AAFrequency.extractHMMProfile(null, 98978867, true)); + } + + @Test(groups = { "Functional" }, priority = 2) + public void testGetAnalogueCount() + { + int count; + count = AAFrequency.getAnalogueCount(hmm, 0, 'T', false); + assertEquals(7859, count); + count = AAFrequency.getAnalogueCount(hmm, 20, 'G', false); + assertEquals(7546, count); + count = AAFrequency.getAnalogueCount(hmm, 1077, 'G', true); + assertEquals(0, count); } - */ + + @Test(groups = { "Functional" }, priority = 3) + public void testCompleteInformation() + { + ProfileI prof1 = new Profile(1, 0, 100, "A"); + ProfileI prof2 = new Profile(1, 0, 100, "-"); + + ProfilesI profs = new Profiles(new ProfileI[] { prof1, prof2 }); + Annotation ann1 = new Annotation(6.5f); + Annotation ann2 = new Annotation(0f); + Annotation[] annots = new Annotation[] { ann1, ann2 }; + SequenceI seq = new Sequence("", "AA", 0, 0); + seq.setHMM(hmm); + AlignmentAnnotation annot = new AlignmentAnnotation("", "", annots); + annot.setSequenceRef(seq); + AAFrequency.completeInformation(annot, profs, 0, 1, false, true, 1); + float ic = annot.annotations[0].value; + assertEquals(0.91532f, ic, 0.0001f); + ic = annot.annotations[1].value; + assertEquals(0f, ic, 0.0001f); + int i = 0; + } + } diff --git a/test/jalview/datamodel/HiddenMarkovModelTest.java b/test/jalview/datamodel/HiddenMarkovModelTest.java new file mode 100644 index 0000000..069978d --- /dev/null +++ b/test/jalview/datamodel/HiddenMarkovModelTest.java @@ -0,0 +1,118 @@ +package jalview.datamodel; + +import static org.testng.Assert.assertEquals; + +import jalview.io.DataSourceType; +import jalview.io.FileParse; +import jalview.io.HMMFile; + +import java.io.IOException; +import java.net.MalformedURLException; + +import org.testng.annotations.Test; + +public class HiddenMarkovModelTest { + + HiddenMarkovModel hmm; + + @Test(priority = 0) + public void testGetMatchEmissionProbabilities() + throws MalformedURLException, IOException + { + HMMFile file = new HMMFile(new FileParse( + "test/jalview/io/test_PKinase_hmm.txt", DataSourceType.FILE)); + hmm = file.getHMM(); + + double[] actual = new double[4]; + actual[0] = hmm.getMatchEmissionProbability(0, 'R'); + actual[1] = hmm.getMatchEmissionProbability(19, 'W'); + actual[2] = hmm.getMatchEmissionProbability(160, 'G'); + actual[3] = hmm.getMatchEmissionProbability(475, 'A'); + + double[] expected = new double[4]; + expected[0] = 0.02537400637; + expected[1] = 0.00588228492; + expected[2] = 0; + expected[3] = 0.04995163708; + + for (int i = 0; i < 4; i++) + { + assertEquals(actual[i], expected[i], 0.001d); + } + } + + @Test(priority = 1) + public void testGetInsertEmissionProbabilities() + { + double[] actual = new double[4]; + actual[0] = hmm.getInsertEmissionProbability(2, 'A'); + actual[1] = hmm.getInsertEmissionProbability(5, 'T'); + actual[2] = hmm.getInsertEmissionProbability(161, 'K'); + actual[3] = hmm.getInsertEmissionProbability(472, 'L'); + + double[] expected = new double[4]; + expected[0] = 0.06841384927; + expected[1] = 0.06233763141; + expected[2] = 0; + expected[3] = 0.06764038926; + + for (int i = 0; i < 4; i++) + { + assertEquals(actual[i], expected[i], 0.001d); + } + } + + @Test(priority = 1) + public void testGetStateTransitionProbabilities() + { + double[] actual = new double[4]; + actual[0] = hmm.getStateTransitionProbability(475, hmm.MATCHTODELETE); + actual[1] = hmm.getStateTransitionProbability(8, hmm.MATCHTOINSERT); + actual[2] = hmm.getStateTransitionProbability(80, hmm.INSERTTOINSERT); + actual[3] = hmm.getStateTransitionProbability(475, hmm.DELETETOMATCH); + + double[] expected = new double[4]; + expected[0] = Double.NEGATIVE_INFINITY; + expected[1] = 0.00662894243; + expected[2] = 0.46183388908; + expected[3] = 1; + + for (int i = 0; i < 4; i++) + { + assertEquals(actual[i], expected[i], 0.001d); + } + } + + @Test(priority = 1) + public void testGetConsensusAtAlignColumn() + { + char[] cons = new char[4]; + cons[0] = hmm.getConsensusAtAlignColumn(10); + cons[1] = hmm.getConsensusAtAlignColumn(50); + hmm.setConsensusResidueStatus(false); + cons[2] = hmm.getConsensusAtAlignColumn(100); + cons[3] = hmm.getConsensusAtAlignColumn(400); + + char[] expected = new char[4]; + expected[0] = 's'; + expected[1] = 'k'; + expected[2] = 'l'; + expected[3] = 'k'; + + for (int i = 0; i < 4; i++) + { + assertEquals(cons[i], expected[i]); + } + + } + + @Test(priority = 1) + public void testGetConsensusSequence() + { + SequenceI seq = hmm.getConsensusSequence(); + String subStr = seq.getSequenceAsString().substring(0, 10); + assertEquals(subStr, "YELLEKLGSG"); + subStr = seq.getSequenceAsString().substring(150, 161); + assertEquals(subStr, "-DLLK------"); + } +} diff --git a/test/jalview/hmmer/HMMERTest.java b/test/jalview/hmmer/HMMERTest.java new file mode 100644 index 0000000..17ce2cf --- /dev/null +++ b/test/jalview/hmmer/HMMERTest.java @@ -0,0 +1,106 @@ +package jalview.hmmer; + +import static org.testng.Assert.assertEquals; +import static org.testng.Assert.assertNotEquals; +import static org.testng.Assert.fail; + +import jalview.bin.Jalview; +import jalview.datamodel.Alignment; +import jalview.datamodel.AlignmentI; +import jalview.datamodel.HiddenMarkovModel; +import jalview.datamodel.SequenceI; +import jalview.gui.AlignFrame; +import jalview.gui.Desktop; +import jalview.io.DataSourceType; +import jalview.io.FastaFile; +import jalview.io.FileParse; + +import java.io.IOException; +import java.net.MalformedURLException; +import java.util.List; + +import org.testng.annotations.AfterClass; +import org.testng.annotations.BeforeClass; +import org.testng.annotations.Test; + + +public class HMMERTest { + + AlignFrame frame; + + @BeforeClass(alwaysRun = true) + public static void setUpBeforeClass() throws Exception + { + Jalview.main( + new String[] + { "-noquestionnaire", "-nonews", "-props", + "test/jalview/hmmer/testProps.jvprops" }); + } + + @AfterClass(alwaysRun = true) + public static void tearDownAfterClass() throws Exception + { + Desktop.instance.closeAll_actionPerformed(null); + } + + @Test(priority = 0) + public void testHMMBuild() throws MalformedURLException, IOException + { + FastaFile file = null; + try + { + file = new FastaFile( + new FileParse("examples/uniref50.fa", DataSourceType.FILE)); + } catch (IOException e) + { + e.printStackTrace(); + fail(); + } + SequenceI[] seqs = file.getSeqsAsArray(); + AlignmentI al = new Alignment(seqs); + frame = new AlignFrame(al, 150, 20); + + HMMBuildThread thread = new HMMBuildThread(frame); + thread.hmmbuildWaitTillComplete(); + + SequenceI seq = frame.getViewport().getAlignment().getSequenceAt(0); + HiddenMarkovModel hmm = seq.getHMM(); + if (hmm == null) + { + fail(); + } + + assertEquals(hmm.getLength().intValue(), 148); + assertEquals(hmm.getAlphabetType(), "amino"); + assertEquals(hmm.getName(), "Alignment"); + assertEquals(hmm.getEffectiveNumberOfSequences(), 0.648193, 0.0001); + assertEquals(hmm.getConsensusAtAlignColumn(15), 's'); + } + + @Test(priority = 1) + public void testHMMAlign() throws MalformedURLException, IOException + { + HMMAlignThread thread = new HMMAlignThread(frame, true); + try + { + thread.hmmalignWaitTillComplete(); + } catch (Exception e) + { + e.printStackTrace(); + fail(); + } + + if (Desktop.getAlignFrames() == null) + { + fail(); + } + + AlignFrame frame = Desktop.getAlignFrames()[0]; + AlignmentI al = frame.getViewport().getAlignment(); + assertNotEquals(al, null); + List hmmSeqs = al.getHMMConsensusSequences(false); + assertNotEquals(hmmSeqs, null); + + } +} + diff --git a/test/jalview/io/HMMFileTest.java b/test/jalview/io/HMMFileTest.java index f16d6f5..be4178b 100644 --- a/test/jalview/io/HMMFileTest.java +++ b/test/jalview/io/HMMFileTest.java @@ -22,17 +22,14 @@ public class HMMFileTest { - HMMFile fn3 = new HMMFile( - new FileParse("test/jalview/io/test_fn3_hmm.txt", - DataSourceType.FILE)); + HMMFile fn3 = new HMMFile(new BufferedReader( + new FileReader(("test/jalview/io/test_fn3_hmm.txt")))); - HMMFile pKinase = new HMMFile( - new FileParse("test/jalview/io/test_PKinase_hmm.txt", - DataSourceType.FILE)); + HMMFile pKinase = new HMMFile(new BufferedReader( + new FileReader(("test/jalview/io/test_PKinase_hmm.txt")))); - HMMFile made1 = new HMMFile( - new FileParse("test/jalview/io/test_MADE1_hmm.txt", - DataSourceType.FILE)); + HMMFile made1 = new HMMFile(new BufferedReader( + new FileReader(("test/jalview/io/test_MADE1_hmm.txt")))); HMMFileTest() throws IOException { @@ -93,28 +90,34 @@ public class HMMFileTest { assertEquals(hmm.getSymbols(), symbols); - assertEquals(getMatchEmission(0, 19, hmm), 0.032298, 0.001d); - assertEquals(getMatchEmission(12, 12, hmm), 0.0130, 0.001d); - assertEquals(getMatchEmission(23, 7, hmm), 0.02583, 0.001d); - assertEquals(getMatchEmission(54, 1, hmm), 0.008549, 0.001d); - assertEquals(getMatchEmission(178, 3, hmm), 0.07998, 0.001d); - assertEquals(getMatchEmission(210, 2, hmm), 0.014465, 0.001d); - assertEquals(getMatchEmission(260, 19, hmm), 0.02213, 0.001d); - - assertEquals(getInsertEmission(2, 1, hmm), 0.012, 0.001d); - assertEquals(getInsertEmission(15, 6, hmm), 0.02411, 0.001d); - assertEquals(getInsertEmission(22, 9, hmm), 0.06764, 0.001d); - assertEquals(getInsertEmission(57, 2, hmm), 0.0623, 0.001d); - assertEquals(getInsertEmission(203, 16, hmm), 0.0623, 0.001d); - assertEquals(getInsertEmission(255, 12, hmm), 0.0647, 0.001d); - - assertEquals(getStateTransition(0, 6, hmm), - Double.NEGATIVE_INFINITY); - assertEquals(getStateTransition(3, 6, hmm), 0.3848, 0.001d); - assertEquals(getStateTransition(29, 3, hmm), 0.5382, 0.001d); - assertEquals(getStateTransition(169, 3, hmm), 0.2916, 0.001d); - assertEquals(getStateTransition(209, 0, hmm), 0.99, 0.001d); - assertEquals(getStateTransition(243, 1, hmm), 0.0066, 0.001d); + assertEquals(hmm.getMatchEmissionProbability(0, 'Y'), 0.16102, 0.001d); + assertEquals(hmm.getMatchEmissionProbability(11, 'P'), 0.0130, 0.001d); + assertEquals(hmm.getMatchEmissionProbability(24, 'I'), 0.02583, 0.001d); + assertEquals(hmm.getMatchEmissionProbability(83, 'C'), 0.008549, + 0.001d); + assertEquals(hmm.getMatchEmissionProbability(332, 'E'), 0.07998, + 0.001d); + assertEquals(hmm.getMatchEmissionProbability(381, 'D'), 0.014465, + 0.001d); + assertEquals(hmm.getMatchEmissionProbability(475, 'Y'), 0.02213, + 0.001d); + + assertEquals(hmm.getInsertEmissionProbability(1, 'C'), 0.012, 0.001d); + assertEquals(hmm.getInsertEmissionProbability(14, 'H'), 0.02411, + 0.001d); + assertEquals(hmm.getInsertEmissionProbability(23, 'L'), 0.06764, + 0.001d); + assertEquals(hmm.getInsertEmissionProbability(90, 'D'), 0.0623, 0.001d); + assertEquals(hmm.getInsertEmissionProbability(374, 'T'), 0.0623, + 0.001d); + assertEquals(hmm.getInsertEmissionProbability(470, 'P'), 0.0647, + 0.001d); + + assertEquals(hmm.getStateTransitionProbability(2, 6), 0.3848, 0.001d); + assertEquals(hmm.getStateTransitionProbability(38, 3), 0.5382, 0.001d); + assertEquals(hmm.getStateTransitionProbability(305, 3), 0.2916, 0.001d); + assertEquals(hmm.getStateTransitionProbability(380, 0), 0.99, 0.001d); + assertEquals(hmm.getStateTransitionProbability(453, 1), 0.0066, 0.001d); assertEquals(hmm.getNodeAlignmentColumn(3).intValue(), 2); assertEquals(hmm.getReferenceAnnotation(7), '-'); @@ -130,12 +133,13 @@ public class HMMFileTest { } - @Test + @Test(priority = 0) public void testParseFileProperties() throws IOException { FileReader fr = new FileReader( new File("test/jalview/io/test_fn3_hmm.txt")); BufferedReader br = new BufferedReader(fr); + fn3.setHMM(new HiddenMarkovModel()); fn3.parseFileProperties(br); fn3.parseModel(br); // this is for a later test HiddenMarkovModel testHMM = new HiddenMarkovModel(); @@ -171,6 +175,7 @@ public class HMMFileTest { FileReader fr3 = new FileReader( new File("test/jalview/io/test_MADE1_hmm.txt")); BufferedReader br3 = new BufferedReader(fr3); + made1.setHMM(new HiddenMarkovModel()); made1.parseFileProperties(br3); testHMM = made1.getHMM(); br3.close(); @@ -258,29 +263,42 @@ public class HMMFileTest { { br.readLine(); } + made1.parseModel(br); testHMM = made1.getHMM(); + br.close(); fr.close(); - assertEquals(getMatchEmission(0, 2, testHMM), 0.1961, 0.001d); - assertEquals(getMatchEmission(2, 1, testHMM), 0.09267, 0.001d); - assertEquals(getMatchEmission(12, 2, testHMM), 0.07327, 0.001d); - assertEquals(getMatchEmission(69, 1, testHMM), 0.04184, 0.001d); - assertEquals(getMatchEmission(76, 2, testHMM), 0.07, 0.001d); - - assertEquals(getInsertEmission(0, 1, testHMM), 0.25, 0.001d); - assertEquals(getInsertEmission(1, 2, testHMM), 0.25, 0.001d); - assertEquals(getInsertEmission(31, 3, testHMM), 0.2776, 0.001d); - assertEquals(getInsertEmission(70, 3, testHMM), 0.25, 0.001d); - assertEquals(getInsertEmission(80, 3, testHMM), 0.25, 0.001d); + assertEquals(testHMM.getMatchEmissionProbability(1, 'C'), 0.09267, + 0.001d); + assertEquals(testHMM.getMatchEmissionProbability(25, 'G'), 0.07327, + 0.001d); + assertEquals(testHMM.getMatchEmissionProbability(1092, 'C'), 0.04184, + 0.001d); + assertEquals(testHMM.getMatchEmissionProbability(1107, 'G'), 0.07, + 0.001d); + + assertEquals(testHMM.getInsertEmissionProbability(0, 'G'), 0.25, + 0.001d); + assertEquals(testHMM.getInsertEmissionProbability(247, 'T'), 0.2776, + 0.001d); + assertEquals(testHMM.getInsertEmissionProbability(1096, 'T'), 0.25, + 0.001d); + assertEquals(testHMM.getInsertEmissionProbability(1111, 'T'), 0.25, + 0.001d); - assertEquals(getStateTransition(2, 0, testHMM), 0.9634, 0.001d); - assertEquals(getStateTransition(6, 1, testHMM), 0.0203, 0.001d); - assertEquals(getStateTransition(9, 3, testHMM), 0.2515, 0.001d); - assertEquals(getStateTransition(20, 4, testHMM), 0.78808, 0.001d); - assertEquals(getStateTransition(68, 2, testHMM), 0.01845, 0.001d); - assertEquals(getStateTransition(80, 6, testHMM), + assertEquals(testHMM.getStateTransitionProbability(1, 0), 0.9634, + 0.001d); + assertEquals(testHMM.getStateTransitionProbability(5, 1), 0.0203, + 0.001d); + assertEquals(testHMM.getStateTransitionProbability(14, 3), 0.2515, + 0.001d); + assertEquals(testHMM.getStateTransitionProbability(65, 4), 0.78808, + 0.001d); + assertEquals(testHMM.getStateTransitionProbability(1080, 2), 0.01845, + 0.001d); + assertEquals(testHMM.getStateTransitionProbability(1111, 6), Double.NEGATIVE_INFINITY); } @@ -289,6 +307,7 @@ public class HMMFileTest { public void testParseAnnotations() { HMMFile testFile = new HMMFile(); + testFile.setHMM(new HiddenMarkovModel()); testFile.getHMM().getNodes().add(new HMMNode()); testFile.getHMM().getNodes().add(new HMMNode()); testFile.getHMM().getNodes().add(new HMMNode()); @@ -332,13 +351,16 @@ public class HMMFileTest { @Test(priority = 3) - public void testExportFile() throws IOException + public void testPrint() throws IOException { - pKinase.exportFile("test/jalview/io/test_export_hmm.txt"); + PrintWriter writer = new PrintWriter( + "test/jalview/io/test_export_hmm.txt"); + String output = pKinase.print(); + writer.print(output); + writer.close(); HMMFile pKinaseClone = new HMMFile( new FileParse("test/jalview/io/test_export_hmm.txt", DataSourceType.FILE)); - pKinaseClone.parse(); HiddenMarkovModel pKinaseHMM = new HiddenMarkovModel(); HiddenMarkovModel pKinaseCloneHMM = new HiddenMarkovModel(); pKinaseHMM = pKinase.getHMM(); @@ -397,17 +419,11 @@ public class HMMFileTest { } @Test(priority = 1) - public void testAppendFileProperties() throws FileNotFoundException + public void testGetFilePropertiesAsString() throws FileNotFoundException { - PrintWriter writer = new PrintWriter( - "test/jalview/io/test_export_hmm.txt"); - fn3.appendFileProperties(writer); - writer.close(); - String content; - File file = new File("test/jalview/io/test_export_hmm.txt"); + String string = fn3.getFilePropertiesAsString(); - Scanner testScanner = new Scanner(file); - testScanner.useDelimiter("\\Z"); + Scanner testScanner = new Scanner(string); String[] expected = new String[] { "HMMER3/f [3.1b1 | May 2013]", "NAME fn3", "ACC PF00041.13", @@ -428,17 +444,9 @@ public class HMMFileTest { } @Test(priority = 2) - public void testAppendModel() throws FileNotFoundException + public void testGetModelAsString() throws FileNotFoundException { - PrintWriter writer = new PrintWriter( - "test/jalview/io/test_export_hmm.txt"); - fn3.appendModel(writer); - writer.close(); - String string; - File file = new File("test/jalview/io/test_export_hmm.txt"); - Scanner scanner = new Scanner(file); - scanner.useDelimiter("\\Z"); - string = scanner.next(); + String string = fn3.getModelAsString(); assertEquals(findValue(2, 2, 2, string), "4.42225"); assertEquals(findValue(12, 14, 1, string), "2.79307"); @@ -472,19 +480,20 @@ public class HMMFileTest { { String value = ""; + String current; Scanner scanner = new Scanner(model); - scanner.nextLine(); - scanner.nextLine(); + current = scanner.nextLine(); + current = scanner.nextLine(); for (int lineIndex = 0; lineIndex < line - 1; lineIndex++) { - scanner.nextLine(); + current = scanner.nextLine(); } for (int node = 0; node < nodeIndex; node++) { - scanner.nextLine(); - scanner.nextLine(); - scanner.nextLine(); + current = scanner.nextLine(); + current = scanner.nextLine(); + current = scanner.nextLine(); } for (int symbol = 0; symbol < symbolIndex; symbol++) @@ -492,14 +501,15 @@ public class HMMFileTest { value = scanner.next(); if ("COMPO".equals(value)) { - scanner.next(); + current = scanner.next(); } else if (value.length() < 7) { - scanner.next(); + current = scanner.next(); } } + scanner.close(); return value; } @@ -522,56 +532,5 @@ public class HMMFileTest { return isDifferent; } - /** - * gets the match emission at a node for a symbol - * - * @param nodeIndex - * position of node in model - * @param symbolIndex - * index of symbol being searched - * @return negative log probability of a match emission of the given symbol - */ - public double getMatchEmission(int nodeIndex, int symbolIndex, - HiddenMarkovModel hmm) - { - double value = hmm.getNodes().get(nodeIndex).getMatchEmissions() - .get(symbolIndex); - return value; - } - - /** - * gets the insert emission at a node for a symbol - * - * @param nodeIndex - * position of node in model - * @param symbolIndex - * index of symbol being searched - * @return negative log probability of an insert emission of the given symbol - */ - public double getInsertEmission(int nodeIndex, int symbolIndex, - HiddenMarkovModel hmm) - { - double value = hmm.getNodes().get(nodeIndex).getInsertEmissions() - .get(symbolIndex); - return value; - } - - /** - * gets the state transition at a node for a specific transition - * - * @param nodeIndex - * position of node in model - * @param transitionIndex - * index of stransition being searched - * @return negative log probability of a state transition of the given type - */ - public double getStateTransition(int nodeIndex, int transitionIndex, - HiddenMarkovModel hmm) - { - double value = hmm.getNodes().get(nodeIndex).getStateTransitions() - .get(transitionIndex); - return value; - } - } diff --git a/test/jalview/io/test_export_hmm.txt b/test/jalview/io/test_export_hmm.txt index e69de29..be9aa57 100644 --- a/test/jalview/io/test_export_hmm.txt +++ b/test/jalview/io/test_export_hmm.txt @@ -0,0 +1,807 @@ +HMMER3/e [3.0 | March 2010] +NAME Pkinase +ACC PF00069.17 +DESC Protein kinase domain +LENG 260 +ALPH amino +RF no +MM no +CONS yes +CS yes +MAP yes +DATE Thu Jun 16 11:44:06 2011 +NSEQ 54 +EFFN 3.358521 +CKSUM 3106786190 +GA 70.30 70.30 +TC 70.30 70.30 +NC 70.20 70.20 +STATS LOCAL MSV -10.7215 0.70254 +STATS LOCAL VITERBI -11.6541 0.70254 +STATS LOCAL FORWARD -5.2305 0.70254 +HMM A C D E F G H I K L M N P Q R S T V W Y + m->m m->i m->d i->m i->i d->m d->d + COMPO 2.60017 4.19886 2.94089 2.63789 3.35087 2.89119 3.48337 2.79435 2.60265 2.43454 3.62613 3.06133 3.41286 3.09693 2.94507 2.65650 2.87761 2.67871 4.54052 3.43274 + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.00990 5.01631 5.73865 0.61958 0.77255 0.00000 * + 1 2.91704 4.31028 4.76351 3.63148 2.10912 3.47710 4.39734 2.27639 3.96619 1.99282 3.42844 4.19567 4.43771 4.11903 3.67403 3.22736 3.14918 2.35905 3.32515 1.82622 1 y - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.00990 5.01631 5.73865 0.61958 0.77255 0.48576 0.95510 + 2 2.77204 4.20708 3.06476 1.97968 4.66603 3.66509 3.19858 3.37903 2.25347 3.34018 4.38833 2.97180 4.05804 2.36838 2.43173 2.67542 2.50268 2.83403 5.78758 4.38976 2 e - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.00990 5.01631 5.73865 0.61958 0.77255 0.48576 0.95510 + 3 2.90076 4.04294 3.31590 2.80413 3.08157 3.87481 4.12616 2.18958 2.49735 1.97194 3.73714 3.32717 3.98753 3.23115 3.12315 2.99137 2.62008 2.29426 5.21478 3.75979 3 l - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.00990 5.01631 5.73865 0.61958 0.77255 0.48576 0.95510 + 4 2.89383 4.85429 3.10311 2.63174 3.71383 2.56808 3.47232 2.82076 2.61844 1.98342 3.72320 3.05498 4.17347 3.05527 3.32194 2.85608 2.93671 2.18878 5.40057 3.87183 4 l - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.00990 5.01631 5.73865 0.61958 0.77255 0.48576 0.95510 + 5 2.68261 5.39185 2.80437 1.87471 4.73638 2.79887 3.69591 4.22191 2.19487 3.69685 4.08896 3.12413 3.70490 2.48424 2.08916 2.53260 3.02309 3.43812 5.82480 4.41426 5 e - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.00990 5.01631 5.73865 0.61958 0.77255 0.48576 0.95510 + 6 2.77253 4.06085 3.07881 2.53373 4.10647 3.71564 3.68370 2.64290 2.00036 2.72968 4.17370 3.24239 3.08607 2.77632 2.72820 2.69921 2.54335 2.71931 5.60386 4.26496 6 k - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.00990 5.01631 5.73865 0.61958 0.77255 0.48576 0.95510 + 7 3.42930 4.74416 5.34765 4.76823 3.71832 4.71430 5.09461 1.33015 3.54417 1.12594 3.33523 4.84641 5.00427 4.73010 4.64986 4.05097 3.66327 1.83083 5.51142 4.37013 7 l - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.00990 5.01631 5.73865 0.61958 0.77255 0.48576 0.95510 + 8 2.57460 4.94286 4.00732 3.93216 5.40516 0.41612 5.15134 4.86315 4.18766 4.52736 5.33508 4.05990 4.45245 3.74651 4.46171 3.15888 3.14590 4.15180 6.71159 5.52767 8 G - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.00990 5.01631 5.73865 0.61958 0.77255 0.48576 0.95510 + 9 2.30218 5.38172 3.03799 2.02026 4.18991 3.65799 3.84554 3.67215 2.28945 3.68495 4.42365 2.84227 3.73039 2.44555 2.39428 2.00278 2.95859 3.63127 5.81726 4.40923 9 s - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.00990 5.01631 5.73865 0.61958 0.77255 0.48576 0.95510 + 10 4.54226 6.07621 5.39207 5.44513 6.34643 0.07137 6.34600 6.33790 5.73770 5.76452 6.83374 5.56171 5.46536 5.98137 5.73783 4.76037 5.08470 5.67502 7.03864 6.52156 10 G - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.00990 5.01631 5.73865 0.61958 0.77255 0.48576 0.95510 + 11 2.06444 5.37337 2.91595 2.40063 4.70969 2.61181 3.84889 4.18948 2.46835 3.67503 4.41668 2.62917 4.05392 2.88235 2.66711 2.00495 2.47288 3.39649 5.81159 4.40596 11 s - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.00990 5.01631 5.73865 0.61958 0.77255 0.48576 0.95510 + 12 2.90920 4.46494 4.12493 3.14570 1.52027 3.22992 4.24969 2.92840 3.46467 2.66529 3.12827 3.55640 4.33979 3.72214 3.72236 2.53517 2.98442 2.55125 5.06498 2.30159 12 f - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.00990 5.01631 5.73865 0.61958 0.77255 0.48576 0.95510 + 13 2.21104 4.80722 4.64199 4.55509 5.54982 0.52550 5.49025 5.04875 4.70671 4.72740 5.47955 4.30215 4.43233 4.84666 4.86038 1.95116 3.45005 4.17507 6.87595 5.79039 13 G - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.00990 5.01631 5.73865 0.61958 0.77255 0.48576 0.95510 + 14 2.71551 3.46186 3.01248 2.27453 4.55840 3.55853 3.50842 3.55064 2.03335 3.34882 4.31847 3.17065 4.07218 2.83960 2.83653 2.25762 2.26864 2.61469 5.72841 4.35037 14 k - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.00990 5.01631 5.73865 0.61958 0.77255 0.48576 0.95510 + 15 3.17885 3.97005 5.63014 5.16553 4.35293 4.89782 5.77682 2.09398 5.06494 2.94083 4.14496 5.20428 5.30924 5.30763 5.20260 4.32158 3.61414 0.44769 6.26043 5.04118 15 V - + 2.68625 4.42232 2.77526 2.73102 3.46361 2.40519 3.72501 3.29361 2.67747 2.69306 4.24696 2.90353 2.73746 3.18153 2.89807 2.37893 2.77526 2.98499 4.58484 3.61510 + 0.09563 2.43065 5.73865 0.67073 0.71608 0.48576 0.95510 + 16 2.91101 3.31342 4.36759 3.41772 2.45121 4.01227 4.31421 2.75922 2.81772 2.31733 3.50420 3.69862 4.38187 3.88257 3.14725 3.02772 3.14303 2.46483 3.37889 1.69905 18 y - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.00990 5.01631 5.73865 0.61958 0.77255 0.48576 0.95510 + 17 2.88484 5.28431 3.03179 2.31849 4.58595 3.47769 3.54625 2.98124 1.69233 2.43413 4.04064 3.16353 4.06907 2.72555 2.58277 2.55274 3.04512 3.20501 5.74377 4.36100 19 k - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 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