X-Git-Url: http://source.jalview.org/gitweb/?a=blobdiff_plain;f=src%2Fjalview%2Fanalysis%2FPCA.java;h=9babaee1ea6928a1731b3906c1a4cbada0fa5bee;hb=34d5dfb25731d7d797177cadfce954258ae90991;hp=1a4060ced77e9bbf51eb17846276c7be8fe3aa88;hpb=07394c1c2d9d4ae05c85cd6d9644e4d17f2818a2;p=jalview.git diff --git a/src/jalview/analysis/PCA.java b/src/jalview/analysis/PCA.java index 1a4060c..9babaee 100755 --- a/src/jalview/analysis/PCA.java +++ b/src/jalview/analysis/PCA.java @@ -20,7 +20,6 @@ */ package jalview.analysis; -import jalview.math.Matrix; import jalview.math.MatrixI; import jalview.schemes.ResidueProperties; import jalview.schemes.ScoreMatrix; @@ -77,17 +76,6 @@ public class PCA implements Runnable { this.seqs = s; - // BinarySequence[] bs = new BinarySequence[s.length]; - // int ii = 0; - // - // while ((ii < s.length) && (s[ii] != null)) - // { - // bs[ii] = new BinarySequence(s[ii], nucleotides); - // bs[ii].encode(); - // ii++; - // } - // - // BinarySequence[] bs2 = new BinarySequence[s.length]; scoreMatrix = null; String sm = s_m; if (sm != null) @@ -103,47 +91,6 @@ public class PCA implements Runnable } details.append("PCA calculation using " + sm + " sequence similarity matrix\n========\n\n"); - // ii = 0; - // while ((ii < s.length) && (s[ii] != null)) - // { - // bs2[ii] = new BinarySequence(s[ii], nucleotides); - // if (scoreMatrix != null) - // { - // try - // { - // bs2[ii].matrixEncode(scoreMatrix); - // } catch (InvalidSequenceTypeException x) - // { - // details.append("Unexpected mismatch of sequence type and score matrix. Calculation will not be valid!\n\n"); - // } - // } - // ii++; - // } - // - // int count = 0; - // while ((count < bs.length) && (bs[count] != null)) - // { - // count++; - // } - // - // double[][] seqmat = new double[count][]; - // double[][] seqmat2 = new double[count][]; - // - // int i = 0; - // while (i < count) - // { - // seqmat[i] = bs[i].getDBinary(); - // seqmat2[i] = bs2[i].getDBinary(); - // i++; - // } - // - // /* - // * using a SparseMatrix to hold the encoded sequences matrix - // * greatly speeds up matrix multiplication as these are mostly zero - // */ - // m = new SparseMatrix(seqmat); - // m2 = new Matrix(seqmat2); - } /** @@ -263,9 +210,7 @@ public class PCA implements Runnable + (jvCalcMode ? "Jalview variant" : "Original SeqSpace") + "\n"); - // MatrixI mt = m.transpose(); - // eigenvector = mt.preMultiply(jvCalcMode ? m2 : m); - eigenvector = computePairwiseScores(); + eigenvector = scoreMatrix.computePairwiseScores(seqs); details.append(" --- OrigT * Orig ---- \n"); eigenvector.print(ps, "%8.2f"); @@ -307,48 +252,6 @@ public class PCA implements Runnable // + (System.currentTimeMillis() - now) + "ms")); } - /** - * Computes an NxN matrix where N is the number of sequences, and entry [i, j] - * is sequence[i] pairwise multiplied with sequence[j], as a sum of scores - * computed using the current score matrix. For example - * - */ - MatrixI computePairwiseScores() - { - double[][] values = new double[seqs.length][]; - for (int row = 0; row < seqs.length; row++) - { - values[row] = new double[seqs.length]; - for (int col = 0; col < seqs.length; col++) - { - int total = 0; - int width = Math.min(seqs[row].length(), seqs[col].length()); - for (int i = 0; i < width; i++) - { - char c1 = seqs[row].charAt(i); - char c2 = seqs[col].charAt(i); - int score = scoreMatrix.getPairwiseScore(c1, c2); - total += score; - } - values[row][col] = total; - } - } - return new Matrix(values); - } - public void setJvCalcMode(boolean calcMode) { this.jvCalcMode = calcMode;