X-Git-Url: http://source.jalview.org/gitweb/?a=blobdiff_plain;f=src%2Fjalview%2Fanalysis%2FPCA.java;h=fb74029c3a6d11dd5a024cbbed77b2ebf6aa0139;hb=c19d2a91ca05e052e3408bf5852d88eb5d0608f1;hp=979968f092b5cd57d3c61feedf9191ae53ba9e00;hpb=27b77d2219147d3741d4af7377e13918a8ae972a;p=jalview.git

diff --git a/src/jalview/analysis/PCA.java b/src/jalview/analysis/PCA.java
index 979968f..fb74029 100755
--- a/src/jalview/analysis/PCA.java
+++ b/src/jalview/analysis/PCA.java
@@ -1,31 +1,33 @@
 /*
- * Jalview - A Sequence Alignment Editor and Viewer (Version 2.8.0b1)
- * Copyright (C) 2014 The Jalview Authors
+ * Jalview - A Sequence Alignment Editor and Viewer (Version 2.9.0b2)
+ * Copyright (C) 2015 The Jalview Authors
  * 
  * This file is part of Jalview.
  * 
  * Jalview is free software: you can redistribute it and/or
  * modify it under the terms of the GNU General Public License 
- * as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
+ * as published by the Free Software Foundation, either version 3
+ * of the License, or (at your option) any later version.
  *  
  * Jalview is distributed in the hope that it will be useful, but 
  * WITHOUT ANY WARRANTY; without even the implied warranty 
  * of MERCHANTABILITY or FITNESS FOR A PARTICULAR 
  * PURPOSE.  See the GNU General Public License for more details.
  * 
- * You should have received a copy of the GNU General Public License along with Jalview.  If not, see <http://www.gnu.org/licenses/>.
+ * You should have received a copy of the GNU General Public License
+ * along with Jalview.  If not, see <http://www.gnu.org/licenses/>.
  * The Jalview Authors are detailed in the 'AUTHORS' file.
  */
 package jalview.analysis;
 
-import java.io.*;
-
-import jalview.datamodel.*;
+import jalview.datamodel.BinarySequence;
 import jalview.datamodel.BinarySequence.InvalidSequenceTypeException;
-import jalview.math.*;
+import jalview.math.Matrix;
 import jalview.schemes.ResidueProperties;
 import jalview.schemes.ScoreMatrix;
 
+import java.io.PrintStream;
+
 /**
  * Performs Principal Component Analysis on given sequences
  * 
@@ -72,6 +74,7 @@ public class PCA implements Runnable
   {
     this(s, nucleotides, null);
   }
+
   public PCA(String[] s, boolean nucleotides, String s_m)
   {
 
@@ -88,15 +91,17 @@ public class PCA implements Runnable
     BinarySequence[] bs2 = new BinarySequence[s.length];
     ii = 0;
     ScoreMatrix smtrx = null;
-    String sm=s_m;
-    if (sm!=null)
+    String sm = s_m;
+    if (sm != null)
     {
       smtrx = ResidueProperties.getScoreMatrix(sm);
     }
-    if (smtrx==null)
+    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"));
+      // 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");
@@ -262,41 +267,45 @@ public class PCA implements Runnable
       }
     };
 
-    try {
-    details.append("PCA Calculation Mode is "
-            + (jvCalcMode ? "Jalview variant" : "Original SeqSpace") + "\n");
-    Matrix mt = m.transpose();
-
-    details.append(" --- OrigT * Orig ---- \n");
-    if (!jvCalcMode)
+    try
     {
-      eigenvector = mt.preMultiply(m); // standard seqspace comparison matrix
-    }
-    else
-    {
-      eigenvector = mt.preMultiply(m2); // jalview variation on seqsmace method
-    }
+      details.append("PCA Calculation Mode is "
+              + (jvCalcMode ? "Jalview variant" : "Original SeqSpace")
+              + "\n");
+      Matrix mt = m.transpose();
 
-    eigenvector.print(ps);
+      details.append(" --- OrigT * Orig ---- \n");
+      if (!jvCalcMode)
+      {
+        eigenvector = mt.preMultiply(m); // standard seqspace comparison matrix
+      }
+      else
+      {
+        eigenvector = mt.preMultiply(m2); // jalview variation on seqsmace
+                                          // method
+      }
 
-    symm = eigenvector.copy();
+      eigenvector.print(ps);
 
-    eigenvector.tred();
+      symm = eigenvector.copy();
 
-    details.append(" ---Tridiag transform matrix ---\n");
-    details.append(" --- D vector ---\n");
-    eigenvector.printD(ps);
-    ps.println();
-    details.append("--- E vector ---\n");
-    eigenvector.printE(ps);
-    ps.println();
+      eigenvector.tred();
+
+      details.append(" ---Tridiag transform matrix ---\n");
+      details.append(" --- D vector ---\n");
+      eigenvector.printD(ps);
+      ps.println();
+      details.append("--- E vector ---\n");
+      eigenvector.printE(ps);
+      ps.println();
 
-    // Now produce the diagonalization matrix
-    eigenvector.tqli();
+      // 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("\n*** Unexpected exception when performing PCA ***\n"
+              + q.getLocalizedMessage());
       details.append("*** Matrices below may not be fully diagonalised. ***\n");
     }