X-Git-Url: http://source.jalview.org/gitweb/?a=blobdiff_plain;f=src%2Fjalview%2Fanalysis%2FPCA.java;h=42a168dab78a24d40c6f572fd4e10d404f6dcaab;hb=refs%2Fheads%2Ffeature%2FJAL-3190jalviewjsChimera;hp=9babaee1ea6928a1731b3906c1a4cbada0fa5bee;hpb=bf64f4d798bf695600cc16cb7e421c77ac8b1da3;p=jalview.git diff --git a/src/jalview/analysis/PCA.java b/src/jalview/analysis/PCA.java index 9babaee..42a168d 100755 --- a/src/jalview/analysis/PCA.java +++ b/src/jalview/analysis/PCA.java @@ -20,9 +20,10 @@ */ package jalview.analysis; +import jalview.api.analysis.ScoreModelI; +import jalview.api.analysis.SimilarityParamsI; +import jalview.datamodel.AlignmentView; import jalview.math.MatrixI; -import jalview.schemes.ResidueProperties; -import jalview.schemes.ScoreMatrix; import java.io.PrintStream; @@ -31,8 +32,6 @@ import java.io.PrintStream; */ public class PCA implements Runnable { - boolean jvCalcMode = true; - MatrixI symm; double[] eigenvalue; @@ -41,55 +40,19 @@ public class PCA implements Runnable StringBuilder details = new StringBuilder(1024); - private String[] seqs; - - private ScoreMatrix scoreMatrix; + final private AlignmentView seqs; - /** - * Creates a new PCA object. By default, uses blosum62 matrix to generate - * sequence similarity matrices - * - * @param s - * Set of amino acid sequences to perform PCA on - */ - public PCA(String[] s) - { - this(s, false); - } + private ScoreModelI scoreModel; - /** - * 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); - } + private SimilarityParamsI similarityParams; - public PCA(String[] s, boolean nucleotides, String s_m) + public PCA(AlignmentView s, ScoreModelI sm, SimilarityParamsI options) { this.seqs = s; + this.similarityParams = options; + this.scoreModel = sm; - scoreMatrix = null; - String sm = s_m; - if (sm != null) - { - scoreMatrix = ResidueProperties.getScoreMatrix(sm); - } - if (scoreMatrix == null) - { - // either we were given a non-existent score matrix or a scoremodel that - // isn't based on a pairwise symbol score matrix - scoreMatrix = ResidueProperties - .getScoreMatrix(sm = (nucleotides ? "DNA" : "BLOSUM62")); - } - details.append("PCA calculation using " + sm + details.append("PCA calculation using " + sm.getName() + " sequence similarity matrix\n========\n\n"); } @@ -206,11 +169,7 @@ public class PCA implements Runnable // long now = System.currentTimeMillis(); try { - details.append("PCA Calculation Mode is " - + (jvCalcMode ? "Jalview variant" : "Original SeqSpace") - + "\n"); - - eigenvector = scoreMatrix.computePairwiseScores(seqs); + eigenvector = scoreModel.findSimilarities(seqs, similarityParams); details.append(" --- OrigT * Orig ---- \n"); eigenvector.print(ps, "%8.2f"); @@ -234,7 +193,8 @@ public class PCA implements Runnable 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( + "*** Matrices below may not be fully diagonalised. ***\n"); } details.append(" --- New diagonalization matrix ---\n"); @@ -252,11 +212,6 @@ public class PCA implements Runnable // + (System.currentTimeMillis() - now) + "ms")); } - public void setJvCalcMode(boolean calcMode) - { - this.jvCalcMode = calcMode; - } - /** * Answers the N dimensions of the NxN PCA matrix. This is the number of * sequences involved in the pairwise score calculation. @@ -266,6 +221,6 @@ public class PCA implements Runnable public int getHeight() { // TODO can any of seqs[] be null? - return seqs.length; + return seqs.getSequences().length; } }