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;
import jalview.datamodel.AlignmentView;
+import jalview.datamodel.Point;
import jalview.datamodel.SequenceI;
import jalview.datamodel.SequencePoint;
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>();
- float[][] scores = pca.getComponents(top - 1, top - 2, top - 3, 100);
+ points = new Vector<>();
+ Point[] scores = pca.getComponents(top - 1, top - 2, top - 3, 100);
for (int i = 0; i < height; i++)
{
public void updateRcView(int dim1, int dim2, int dim3)
{
// note: actual indices for components are dim1-1, etc (patch for JAL-1123)
- float[][] scores = pca.getComponents(dim1 - 1, dim2 - 1, dim3 - 1, 100);
+ Point[] scores = pca.getComponents(dim1 - 1, dim2 - 1, dim3 - 1, 100);
for (int i = 0; i < pca.getHeight(); i++)
{
}
else
{
- // output current x,y,z coords for points
- fl = getPointPosition(s);
- for (int d = 0; d < fl.length; d++)
- {
- csv.append(",");
- csv.append(fl[d]);
- }
+ Point p = points.elementAt(s).coord;
+ csv.append(",").append(p.x);
+ csv.append(",").append(p.y);
+ csv.append(",").append(p.z);
}
csv.append("\n");
}
public double[] getPointPosition(int s)
{
double pts[] = new double[3];
- float[] p = points.elementAt(s).coord;
- pts[0] = p[0];
- pts[1] = p[1];
- pts[2] = p[2];
+ Point p = points.elementAt(s).coord;
+ pts[0] = p.x;
+ pts[1] = p.y;
+ pts[2] = p.z;
return pts;
}
- public void setJvCalcMode(boolean state)
- {
- jvCalcMode = state;
- }
-
public String getScoreModelName()
{
return scoreModel == null ? "" : scoreModel.getName();