X-Git-Url: http://source.jalview.org/gitweb/?a=blobdiff_plain;f=src%2Fjalview%2Fanalysis%2FPCA.java;fp=src%2Fjalview%2Fanalysis%2FPCA.java;h=3ec7995f9f67aa84c2553fcd154df0b4c934a223;hb=aba253e57b22ce7d1f4fe376935e42aeb4f6d591;hp=d8863f79426cd38706267ab81ce3bcbb59398c68;hpb=21d7606604dab27e62ed700a39425b983901cef1;p=jalview.git diff --git a/src/jalview/analysis/PCA.java b/src/jalview/analysis/PCA.java index d8863f7..3ec7995 100755 --- a/src/jalview/analysis/PCA.java +++ b/src/jalview/analysis/PCA.java @@ -20,11 +20,8 @@ */ package jalview.analysis; -import jalview.analysis.scoremodels.PIDModel; -import jalview.api.analysis.DistanceScoreModelI; import jalview.api.analysis.ScoreModelI; import jalview.api.analysis.SimilarityParamsI; -import jalview.api.analysis.SimilarityScoreModelI; import jalview.datamodel.AlignmentView; import jalview.math.MatrixI; @@ -172,7 +169,7 @@ public class PCA implements Runnable // long now = System.currentTimeMillis(); try { - eigenvector = computeSimilarity(); + eigenvector = scoreModel.findSimilarities(seqs, similarityParams); details.append(" --- OrigT * Orig ---- \n"); eigenvector.print(ps, "%8.2f"); @@ -215,50 +212,6 @@ public class PCA implements Runnable } /** - * Computes a pairwise similarity matrix for the given sequence regions using - * the configured score model. If the score model is a similarity model, then - * it computes the result directly. If it is a distance model, then use it to - * compute pairwise distances, and convert these to similarity scores. - * - * @param av - * @return - */ - MatrixI computeSimilarity() - { - MatrixI result = null; - if (scoreModel instanceof SimilarityScoreModelI) - { - result = ((SimilarityScoreModelI) scoreModel).findSimilarities(seqs, - similarityParams); - if (scoreModel instanceof PIDModel) - { - /* - * scale score to width of alignment for backwards - * compatibility with Jalview 2.10.1 SeqSpace PCA calculation - */ - result.multiply(seqs.getWidth() / 100d); - } - } - else if (scoreModel instanceof DistanceScoreModelI) - { - /* - * find distances and convert to similarity scores - * reverseRange(false) preserves but reverses the min-max range - */ - result = ((DistanceScoreModelI) scoreModel).findDistances(seqs, - similarityParams); - result.reverseRange(false); - } - else - { - System.err - .println("Unexpected type of score model, cannot calculate similarity"); - } - - return result; - } - - /** * Answers the N dimensions of the NxN PCA matrix. This is the number of * sequences involved in the pairwise score calculation. *