X-Git-Url: http://source.jalview.org/gitweb/?a=blobdiff_plain;f=src%2Fjalview%2Fanalysis%2FPCA.java;h=733e7f99e333f60532e73d9ccf32f33971159c7c;hb=b2f9a8d7bce642ff4011bc6d49e02bb0569fbb11;hp=f9a034334a2b78e0be9fd50b7c89ebc20de95a5c;hpb=506d60f0e188723ddc91c26824b41ac7034df3fe;p=jalview.git diff --git a/src/jalview/analysis/PCA.java b/src/jalview/analysis/PCA.java index f9a0343..733e7f9 100755 --- a/src/jalview/analysis/PCA.java +++ b/src/jalview/analysis/PCA.java @@ -1,27 +1,30 @@ /* - * Jalview - A Sequence Alignment Editor and Viewer (Version 2.4) - * Copyright (C) 2008 AM Waterhouse, J Procter, G Barton, M Clamp, S Searle + * Jalview - A Sequence Alignment Editor and Viewer (Version 2.8.1) + * Copyright (C) 2014 The Jalview Authors * - * 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 file is part of Jalview. * - * 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. + * 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. + * + * 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 this program; if not, write to the Free Software - * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA + * You should have received a copy of the GNU General Public License along with Jalview. If not, see . + * The Jalview Authors are detailed in the 'AUTHORS' file. */ package jalview.analysis; import java.io.*; import jalview.datamodel.*; +import jalview.datamodel.BinarySequence.InvalidSequenceTypeException; import jalview.math.*; +import jalview.schemes.ResidueProperties; +import jalview.schemes.ScoreMatrix; /** * Performs Principal Component Analysis on given sequences @@ -44,31 +47,72 @@ public class PCA implements Runnable StringBuffer details = new StringBuffer(); /** - * Creates a new PCA object. + * Creates a new PCA object. By default, uses blosum62 matrix to generate + * sequence similarity matrices * * @param s - * Set of sequences to perform PCA on + * Set of amino acid sequences to perform PCA on */ public PCA(String[] s) { + this(s, false); + } + + /** + * Creates a new PCA object. By default, uses blosum62 matrix to generate + * sequence similarity matrices + * + * @param s + * Set of sequences to perform PCA on + * @param nucleotides + * if true, uses standard DNA/RNA matrix for sequence similarity + * calculation. + */ + 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; while ((ii < s.length) && (s[ii] != null)) { - bs[ii] = new BinarySequence(s[ii]); + bs[ii] = new BinarySequence(s[ii], nucleotides); bs[ii].encode(); ii++; } BinarySequence[] bs2 = new BinarySequence[s.length]; ii = 0; - + 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)) { - bs2[ii] = new BinarySequence(s[ii]); - bs2[ii].blosumEncode(); + bs2[ii] = new BinarySequence(s[ii], nucleotides); + if (smtrx != null) + { + try + { + bs2[ii].matrixEncode(smtrx); + } catch (InvalidSequenceTypeException x) + { + details.append("Unexpected mismatch of sequence type and score matrix. Calculation will not be valid!\n\n"); + } + } ii++; } @@ -115,7 +159,7 @@ public class PCA implements Runnable * Returns Eigenvalue * * @param i - * Index of diagonal within matrix + * Index of diagonal within matrix * * @return Returns value of diagonal from matrix */ @@ -128,13 +172,13 @@ public class PCA implements Runnable * DOCUMENT ME! * * @param l - * DOCUMENT ME! + * DOCUMENT ME! * @param n - * DOCUMENT ME! + * DOCUMENT ME! * @param mm - * DOCUMENT ME! + * DOCUMENT ME! * @param factor - * DOCUMENT ME! + * DOCUMENT ME! * * @return DOCUMENT ME! */ @@ -156,7 +200,7 @@ public class PCA implements Runnable * DOCUMENT ME! * * @param n - * DOCUMENT ME! + * DOCUMENT ME! * * @return DOCUMENT ME! */ @@ -177,9 +221,9 @@ public class PCA implements Runnable * DOCUMENT ME! * * @param row - * DOCUMENT ME! + * DOCUMENT ME! * @param n - * DOCUMENT ME! + * DOCUMENT ME! * * @return DOCUMENT ME! */ @@ -205,11 +249,6 @@ public class PCA implements Runnable */ public void run() { - Matrix mt = m.transpose(); - - details.append(" --- OrigT * Orig ---- \n"); - eigenvector = mt.preMultiply(m2); - PrintStream ps = new PrintStream(System.out) { public void print(String x) @@ -223,6 +262,21 @@ 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) + { + eigenvector = mt.preMultiply(m); // standard seqspace comparison matrix + } + else + { + eigenvector = mt.preMultiply(m2); // jalview variation on seqsmace method + } + eigenvector.print(ps); symm = eigenvector.copy(); @@ -239,14 +293,30 @@ 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); details.append(" --- Eigenvalues ---\n"); eigenvector.printD(ps); ps.println(); - // taps.println(); - // taps.println("Transformed sequences = "); - // Matrix trans = m.preMultiply(eigenvector); - // trans.print(System.out); + /* + * for (int seq=0;seq