import jalview.datamodel.AlignmentView;
import jalview.datamodel.Point;
import jalview.math.MatrixI;
import jalview.datamodel.AlignmentView;
import jalview.datamodel.Point;
import jalview.math.MatrixI;
- public PCA(AlignmentView sequences, ScoreModelI sm, SimilarityParamsI options)
+ public PCA(AlignmentView sequences, ScoreModelI sm,
+ SimilarityParamsI options)
sb.append("PCA calculation using ").append(scoreModel.getName())
.append(" sequence similarity matrix\n========\n\n");
PrintStream ps = wrapOutputBuffer(sb);
sb.append("PCA calculation using ").append(scoreModel.getName())
.append(" sequence similarity matrix\n========\n\n");
PrintStream ps = wrapOutputBuffer(sb);
/*
* pairwise similarity scores
*/
sb.append(" --- OrigT * Orig ---- \n");
pairwiseScores.print(ps, "%8.2f");
/*
* pairwise similarity scores
*/
sb.append(" --- OrigT * Orig ---- \n");
pairwiseScores.print(ps, "%8.2f");
sb.append("--- E vector ---\n");
tridiagonal.printE(ps, "%15.4e");
ps.println();
sb.append("--- E vector ---\n");
tridiagonal.printE(ps, "%15.4e");
ps.println();
sb.append(" --- Eigenvalues ---\n");
eigenMatrix.printD(ps, "%15.4e");
ps.println();
sb.append(" --- Eigenvalues ---\n");
eigenMatrix.printD(ps, "%15.4e");
ps.println();