package jalview.viewmodel;
import jalview.analysis.PCA;
-import jalview.analysis.scoremodels.ScoreModels;
import jalview.api.RotatableCanvasI;
import jalview.api.analysis.ScoreModelI;
import jalview.api.analysis.SimilarityParamsI;
public class PCAModel
{
- private volatile PCA pca;
-
- int top;
+ /*
+ * inputs
+ */
+ private final AlignmentView seqstrings;
- AlignmentView seqstrings;
+ private final SequenceI[] seqs;
- SequenceI[] seqs;
+ private final SimilarityParamsI similarityParams;
/*
- * Score model used to calculate PCA
+ * options - score model, nucleotide / protein
*/
- ScoreModelI scoreModel;
+ private ScoreModelI scoreModel;
private boolean nucleotide = false;
- private Vector<SequencePoint> points;
+ /*
+ * outputs
+ */
+ private PCA pca;
- private boolean jvCalcMode = true;
+ int top;
- private SimilarityParamsI similarityParams;
+ private Vector<SequencePoint> points;
/**
- * Constructor given sequence data and score calculation parameter options.
- * The initial state is to compute PCA using a default score model (BLOSUM62
- * for peptide, DNA for nucleotide).
+ * Constructor given sequence data, score model and score calculation
+ * parameter options.
*
* @param seqData
* @param sqs
* @param nuc
+ * @param modelName
* @param params
*/
public PCAModel(AlignmentView seqData, SequenceI[] sqs, boolean nuc,
- SimilarityParamsI params)
+ ScoreModelI modelName, SimilarityParamsI params)
{
seqstrings = seqData;
seqs = sqs;
nucleotide = nuc;
- scoreModel = ScoreModels.getInstance().getDefaultModel(!nucleotide);
+ scoreModel = modelName;
similarityParams = params;
}
- public boolean isJvCalcMode()
- {
- return jvCalcMode;
- }
-
- public void run()
+ /**
+ * Performs the PCA calculation (in the same thread) and extracts result data
+ * needed for visualisation by PCAPanel
+ */
+ public void calculate()
{
pca = new PCA(seqstrings, scoreModel, similarityParams);
- pca.setJvCalcMode(jvCalcMode);
- pca.run();
+ pca.run(); // executes in same thread, wait for completion
// Now find the component coordinates
int ii = 0;
// top = pca.getM().height() - 1;
top = height - 1;
- points = new Vector<SequencePoint>();
+ points = new Vector<>();
float[][] scores = pca.getComponents(top - 1, top - 2, top - 3, 100);
for (int i = 0; i < height; i++)
return pts;
}
- public void setJvCalcMode(boolean state)
- {
- jvCalcMode = state;
- }
-
public String getScoreModelName()
{
return scoreModel == null ? "" : scoreModel.getName();