JAL-2629 tidy unit tests, constants etc

[jalview.git] / test / jalview / analysis / AAFrequencyTest.java

diff --git a/test/jalview/analysis/AAFrequencyTest.java b/test/jalview/analysis/AAFrequencyTest.java
index 05a72e4..fc4063a 100644 (file)
--- a/test/jalview/analysis/AAFrequencyTest.java
+++ b/test/jalview/analysis/AAFrequencyTest.java
@@ -45,7 +45,6 @@ import org.testng.annotations.Test;
 
 public class AAFrequencyTest
 {
-
   HiddenMarkovModel hmm;
 
   @BeforeClass(alwaysRun = true)
@@ -55,6 +54,17 @@ public class AAFrequencyTest
     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()
   {
@@ -244,15 +254,10 @@ public class AAFrequencyTest
     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++)
@@ -266,7 +271,7 @@ public class AAFrequencyTest
         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++)
@@ -284,19 +289,39 @@ public class AAFrequencyTest
     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");