Merge branch 'docs/2_8_1_Release' into Release_2_8_1_Branch

[jalview.git] / src / jalview / analysis / PCA.java

diff --git a/src/jalview/analysis/PCA.java b/src/jalview/analysis/PCA.java
index 7a506cc..733e7f9 100755 (executable)
--- a/src/jalview/analysis/PCA.java
+++ b/src/jalview/analysis/PCA.java
@@ -1,5 +1,5 @@
 /*
- * Jalview - A Sequence Alignment Editor and Viewer (Version 2.8.0b1)
+ * Jalview - A Sequence Alignment Editor and Viewer (Version 2.8.1)
  * Copyright (C) 2014 The Jalview Authors
  * 
  * This file is part of Jalview.
@@ -70,6 +70,10 @@ public class PCA implements Runnable
    */
   public PCA(String[] s, boolean nucleotides)
   {
+    this(s, nucleotides, null);
+  }
+  public PCA(String[] s, boolean nucleotides, String s_m)
+  {
 
     BinarySequence[] bs = new BinarySequence[s.length];
     int ii = 0;
@@ -83,9 +87,17 @@ public class PCA implements Runnable
 
     BinarySequence[] bs2 = new BinarySequence[s.length];
     ii = 0;
-
-    String sm = nucleotides ? "DNA" : "BLOSUM62";
-    ScoreMatrix smtrx = ResidueProperties.getScoreMatrix(sm);
+    ScoreMatrix smtrx = null;
+    String sm=s_m;
+    if (sm!=null)
+    {
+      smtrx = ResidueProperties.getScoreMatrix(sm);
+    }
+    if (smtrx==null)
+    {
+      // either we were given a non-existent score matrix or a scoremodel that isn't based on a pairwise symbol score matrix
+      smtrx = ResidueProperties.getScoreMatrix(sm=(nucleotides ? "DNA" : "BLOSUM62"));
+    }
     details.append("PCA calculation using " + sm
             + " sequence similarity matrix\n========\n\n");
     while ((ii < s.length) && (s[ii] != null))
@@ -237,6 +249,20 @@ public class PCA implements Runnable
    */
   public void run()
   {
+    PrintStream ps = new PrintStream(System.out)
+    {
+      public void print(String x)
+      {
+        details.append(x);
+      }
+
+      public void println()
+      {
+        details.append("\n");
+      }
+    };
+
+    try {
     details.append("PCA Calculation Mode is "
             + (jvCalcMode ? "Jalview variant" : "Original SeqSpace") + "\n");
     Matrix mt = m.transpose();
@@ -251,19 +277,6 @@ public class PCA implements Runnable
       eigenvector = mt.preMultiply(m2); // jalview variation on seqsmace method
     }
 
-    PrintStream ps = new PrintStream(System.out)
-    {
-      public void print(String x)
-      {
-        details.append(x);
-      }
-
-      public void println()
-      {
-        details.append("\n");
-      }
-    };
-
     eigenvector.print(ps);
 
     symm = eigenvector.copy();
@@ -280,6 +293,12 @@ public class PCA implements Runnable
 
     // Now produce the diagonalization matrix
     eigenvector.tqli();
+    } catch (Exception q)
+    {
+      q.printStackTrace();
+      details.append("\n*** Unexpected exception when performing PCA ***\n"+q.getLocalizedMessage());
+      details.append("*** Matrices below may not be fully diagonalised. ***\n");
+    }
 
     details.append(" --- New diagonalization matrix ---\n");
     eigenvector.print(ps);