public class AAFrequencyTest
{
-
HiddenMarkovModel hmm;
@BeforeClass(alwaysRun = true)
JvOptionPane.setMockResponse(JvOptionPane.CANCEL_OPTION);
}
+ @BeforeClass(alwaysRun = true)
+ public void setUp() throws IOException, MalformedURLException
+ {
+ /*
+ * load a dna (ACGT) HMM file to a HiddenMarkovModel
+ */
+ HMMFile hmmFile = new HMMFile(new FileParse(
+ "test/jalview/io/test_MADE1_hmm.txt", DataSourceType.FILE));
+ hmm = hmmFile.getHMM();
+ }
+
@Test(groups = { "Functional" })
public void testCalculate_noProfile()
{
assertEquals("T", ann.displayCharacter);
}
-
- @Test(groups = { "Functional" }, priority = 1)
+ @Test(groups = { "Functional" })
public void testExtractHMMProfile()
throws MalformedURLException, IOException
{
-
- HMMFile hmmFile = new HMMFile(new FileParse(
- "test/jalview/io/test_MADE1_hmm.txt", DataSourceType.FILE));
- hmm = hmmFile.getHMM();
int[] expected = { 0, 4, 100, 'T', 71, 'C', 12, 'G', 9, 'A', 9 };
int[] actual = AAFrequency.extractHMMProfile(hmm, 17, false, false);
for (int i = 0; i < actual.length; i++)
assertEquals(actual[i], expected[i]);
}
}
-
+
int[] expected2 = { 0, 4, 100, 'A', 85, 'C', 0, 'G', 0, 'T', 0 };
int[] actual2 = AAFrequency.extractHMMProfile(hmm, 2, true, false);
for (int i = 0; i < actual2.length; i++)
assertNull(AAFrequency.extractHMMProfile(null, 98978867, true, false));
}
- @Test(groups = { "Functional" }, priority = 2)
+ @Test(groups = { "Functional" })
public void testGetAnalogueCount()
{
- int count;
- count = AAFrequency.getAnalogueCount(hmm, 0, 'T', false, false);
+ /*
+ * 'T' in column 0 has emission probability 0.7859, scales to 7859
+ */
+ int count = AAFrequency.getAnalogueCount(hmm, 0, 'T', false, false);
assertEquals(7859, count);
+
+ /*
+ * same with 'use info height': value is multiplied by log ratio
+ * log(value / background) / log(2) = log(0.7859/0.25)/0.693
+ * = log(3.1)/0.693 = 1.145/0.693 = 1.66
+ * so value becomes 1.2987 and scales up to 12987
+ */
+ count = AAFrequency.getAnalogueCount(hmm, 0, 'T', false, true);
+ assertEquals(12987, count);
+
+ /*
+ * 'G' in column 20 has emission probability 0.75457, scales to 7546
+ */
count = AAFrequency.getAnalogueCount(hmm, 20, 'G', false, false);
assertEquals(7546, count);
+
+ /*
+ * 'G' in column 1077 has emission probability 0.0533, here
+ * ignored (set to 0) since below background of 0.25
+ */
count = AAFrequency.getAnalogueCount(hmm, 1077, 'G', true, false);
assertEquals(0, count);
}
- @Test(groups = { "Functional" }, priority = 3)
+ @Test(groups = { "Functional" })
public void testCompleteInformation()
{
ProfileI prof1 = new Profile(1, 0, 100, "A");
seq.setHMM(hmm);
AlignmentAnnotation annot = new AlignmentAnnotation("", "", annots);
annot.setSequenceRef(seq);
- AAFrequency.completeInformation(annot, profs, 0, 1, 1, 1f);
+ AAFrequency.completeInformation(annot, profs, 0, 1);
float ic = annot.annotations[0].value;
assertEquals(0.91532f, ic, 0.0001f);
ic = annot.annotations[1].value;