X-Git-Url: http://source.jalview.org/gitweb/?a=blobdiff_plain;f=src%2Fjalview%2Fanalysis%2FPCA.java;h=c11610a28bc9e5f0fdc76aab450510827b7b6ba0;hb=7bc226b58110fa26d9dbd3f0c78095d06909ffc3;hp=7f3a06a8f6a1f6fe8091bcdc3c6a95935d491c4a;hpb=3481e71f3b4b1d7e703e10422a6ebbb4ecc9f21b;p=jalview.git

diff --git a/src/jalview/analysis/PCA.java b/src/jalview/analysis/PCA.java
index 7f3a06a..c11610a 100755
--- a/src/jalview/analysis/PCA.java
+++ b/src/jalview/analysis/PCA.java
@@ -1,33 +1,57 @@
-// PCA.java with an irrelevant comment
-
+/*
+ * Jalview - A Sequence Alignment Editor and Viewer
+ * Copyright (C) 2007 AM Waterhouse, J Procter, G Barton, M Clamp, S Searle
+ *
+ * This program 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 2
+ * of the License, or (at your option) any later version.
+ *
+ * This program 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 this program; if not, write to the Free Software
+ * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301, USA
+ */
 package jalview.analysis;
 
-import jalview.math.*;
-import jalview.datamodel.*;
-import jalview.util.*;
-
-import java.awt.*;
 import java.io.*;
 
-public class PCA implements Runnable {
+import jalview.datamodel.*;
+import jalview.math.*;
+
+/**
+ * Performs Principal Component Analysis on given sequences
+ *
+ * @author $author$
+ * @version $Revision$
+ */
+public class PCA
+    implements Runnable
+{
   Matrix m;
   Matrix symm;
   Matrix m2;
-
   double[] eigenvalue;
   Matrix eigenvector;
+  StringBuffer details = new StringBuffer();
 
-  public PCA(Matrix m) {
-    this.m = m;
-  }
-
-  public PCA(SequenceI[] s) {
-    Runtime rt = Runtime.getRuntime();
+  /**
+   * Creates a new PCA object.
+   *
+   * @param s Set of sequences to perform PCA on
+   */
+  public PCA(String[] s)
+  {
 
     BinarySequence[] bs = new BinarySequence[s.length];
     int ii = 0;
-    while (ii < s.length && s[ii] != null) {
 
+    while ( (ii < s.length) && (s[ii] != null))
+    {
       bs[ii] = new BinarySequence(s[ii]);
       bs[ii].encode();
       ii++;
@@ -35,157 +59,181 @@ public class PCA implements Runnable {
 
     BinarySequence[] bs2 = new BinarySequence[s.length];
     ii = 0;
-    while (ii < s.length && s[ii] != null) {
 
+    while ( (ii < s.length) && (s[ii] != null))
+    {
       bs2[ii] = new BinarySequence(s[ii]);
       bs2[ii].blosumEncode();
       ii++;
     }
 
-
     //System.out.println("Created binary encoding");
     //printMemory(rt);
+    int count = 0;
 
-    int count=0;
-    while (count < bs.length && bs[count] != null) {
+    while ( (count < bs.length) && (bs[count] != null))
+    {
       count++;
     }
+
     double[][] seqmat = new double[count][bs[0].getDBinary().length];
     double[][] seqmat2 = new double[count][bs2[0].getDBinary().length];
-    int i=0;
-    while (i < count) {
+    int i = 0;
+
+    while (i < count)
+    {
       seqmat[i] = bs[i].getDBinary();
       seqmat2[i] = bs2[i].getDBinary();
       i++;
     }
+
     //System.out.println("Created array");
     //printMemory(rt);
     //    System.out.println(" --- Original matrix ---- ");
-    m = new Matrix(seqmat,count,bs[0].getDBinary().length);
-    m2 = new Matrix(seqmat2,count,bs2[0].getDBinary().length);
+    m = new Matrix(seqmat, count, bs[0].getDBinary().length);
+    m2 = new Matrix(seqmat2, count, bs2[0].getDBinary().length);
 
-    //System.out.println("Created matrix");
-    printMemory(rt);
   }
 
-  public static void printMemory(Runtime rt) {
-    System.out.println("Free memory = " + rt.freeMemory());
-  }
+  /**
+   * Returns the matrix used in PCA calculation
+   *
+   * @return java.math.Matrix object
+   */
 
-  public Matrix getM() {
+  public Matrix getM()
+  {
     return m;
   }
 
-  public double[] getEigenvector(int i) {
-    return eigenvector.getColumn(i);
-  }
-
-  public double getEigenvalue(int i) {
+  /**
+   * Returns Eigenvalue
+   *
+   * @param i Index of diagonal within matrix
+   *
+   * @return Returns value of diagonal from matrix
+   */
+  public double getEigenvalue(int i)
+  {
     return eigenvector.d[i];
   }
-  public float[][] getComponents(int l, int n, int mm) {
-    return getComponents(l,n,mm,1);
-  }
-  public float[][] getComponents(int l, int n, int mm, float factor) {
+
+  /**
+   * DOCUMENT ME!
+   *
+   * @param l DOCUMENT ME!
+   * @param n DOCUMENT ME!
+   * @param mm DOCUMENT ME!
+   * @param factor DOCUMENT ME!
+   *
+   * @return DOCUMENT ME!
+   */
+  public float[][] getComponents(int l, int n, int mm, float factor)
+  {
     float[][] out = new float[m.rows][3];
 
-    for (int i = 0; i < m.rows;i++) {
-      out[i][0] = (float)component(i,l)*factor;
-      out[i][1] = (float)component(i,n)*factor;
-      out[i][2] = (float)component(i,mm)*factor;
+    for (int i = 0; i < m.rows; i++)
+    {
+      out[i][0] = (float) component(i, l) * factor;
+      out[i][1] = (float) component(i, n) * factor;
+      out[i][2] = (float) component(i, mm) * factor;
     }
+
     return out;
   }
 
-  public double[] component(int n) {
+  /**
+   * DOCUMENT ME!
+   *
+   * @param n DOCUMENT ME!
+   *
+   * @return DOCUMENT ME!
+   */
+  public double[] component(int n)
+  {
     // n = index of eigenvector
     double[] out = new double[m.rows];
 
-    for (int i=0; i < m.rows; i++) {
-      out[i] = component(i,n);
+    for (int i = 0; i < m.rows; i++)
+    {
+      out[i] = component(i, n);
     }
+
     return out;
   }
-  public double component(int row, int n) {
+
+  /**
+   * DOCUMENT ME!
+   *
+   * @param row DOCUMENT ME!
+   * @param n DOCUMENT ME!
+   *
+   * @return DOCUMENT ME!
+   */
+  double component(int row, int n)
+  {
     double out = 0.0;
 
-    for (int i = 0; i < symm.cols; i++) {
-      out += symm.value[row][i] * eigenvector.value[i][n];
+    for (int i = 0; i < symm.cols; i++)
+    {
+      out += (symm.value[row][i] * eigenvector.value[i][n]);
     }
-    return out/eigenvector.d[n];
+
+    return out / eigenvector.d[n];
   }
 
-  public void checkEigenvector(int n,PrintStream ps) {
-    ps.println(" --- Eigenvector " + n  + " --- ");
+  public String getDetails()
+  {
+    return details.toString();
+  }
 
-    double[] eigenv = eigenvector.getColumn(n);
+  /**
+   * DOCUMENT ME!
+   */
+  public void run()
+  {
+    Matrix mt = m.transpose();
 
-    for (int i=0; i < eigenv.length;i++) {
-      Format.print(ps,"%15.4f",eigenv[i]);
-    }
+    details.append(" --- OrigT * Orig ---- \n");
+    eigenvector = mt.preMultiply(m2);
 
-    System.out.println();
+    PrintStream ps = new PrintStream(System.out)
+    {
+      public void print(String x)
+      {
+        details.append(x);
+      }
 
-    double[] neigenv = symm.vectorPostMultiply(eigenv);
-    System.out.println(" --- symmat * eigenv / lambda --- ");
-    if (eigenvector.d[n] > 1e-4) {
-      for (int i=0; i < neigenv.length;i++) {
-        Format.print(System.out,"%15.4f",neigenv[i]/eigenvector.d[n]);
+      public void println()
+      {
+        details.append("\n");
       }
-    }
-    System.out.println();
-  }
+    };
+
+    eigenvector.print(ps);
 
-  public void run() {
-    Matrix mt = m.transpose();
-    //    System.out.println(" --- OrigT * Orig ---- ");
-    eigenvector = mt.preMultiply(m2);
-    //  eigenvector.print(System.out);
     symm = eigenvector.copy();
 
-    //TextArea ta = new TextArea(25,72);
-    //TextAreaPrintStream taps = new TextAreaPrintStream(System.out,ta);
-    //Frame f = new Frame("PCA output");
-    //f.resize(500,500);
-    //f.setLayout(new BorderLayout());
-    //f.add("Center",ta);
-    //f.show();
-    //symm.print(taps);
-    long tstart = System.currentTimeMillis();
     eigenvector.tred();
-    long tend = System.currentTimeMillis();
-    //taps.println("Time take for tred = " + (tend-tstart) + "ms");
-    //taps.println(" ---Tridiag transform matrix ---");
 
-    //taps.println(" --- D vector ---");
-    //eigenvector.printD(taps);
-    //taps.println();
-    //taps.println(" --- E vector ---");
-    //    eigenvector.printE(taps);
-    //taps.println();
+    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
-    tstart = System.currentTimeMillis();
     eigenvector.tqli();
-    tend = System.currentTimeMillis();
-    //System.out.println("Time take for tqli = " + (tend-tstart) + " ms");
-
-    //System.out.println(" --- New diagonalization matrix ---");
-
-    //System.out.println(" --- Eigenvalues ---");
-    //eigenvector.printD(taps);
-
-    //System.out.println();
-
-    // for (int i=0; i < eigenvector.cols; i++) {
-    // checkEigenvector(i,taps);
-    // taps.println();
-    // }
 
+    details.append(" --- New diagonalization matrix ---\n");
+    details.append(" --- Eigenvalues ---\n");
+    eigenvector.printD(ps);
+    ps.println();
     //  taps.println();
     //  taps.println("Transformed sequences = ");
     // Matrix trans =  m.preMultiply(eigenvector);
     //  trans.print(System.out);
   }
-
 }