+package jalview.viewmodel;
+
+import java.util.Vector;
+
+import jalview.analysis.PCA;
+import jalview.datamodel.AlignmentView;
+import jalview.datamodel.SequenceI;
+import jalview.datamodel.SequencePoint;
+import jalview.api.RotatableCanvasI;
+
+public class PCAModel
+{
+
+ public PCAModel(AlignmentView seqstrings2, SequenceI[] seqs2,
+ boolean nucleotide2)
+ {
+ seqstrings=seqstrings2;
+ seqs=seqs2;
+ nucleotide=nucleotide2;
+ }
+
+ PCA pca;
+
+ int top;
+
+ AlignmentView seqstrings;
+
+ SequenceI[] seqs;
+
+ /**
+ * use the identity matrix for calculating similarity between sequences.
+ */
+ private boolean nucleotide=false;
+
+ private Vector<SequencePoint> points;
+
+ public void run()
+ {
+
+ pca = new PCA(seqstrings.getSequenceStrings(' '), nucleotide);
+ pca.run();
+
+ // Now find the component coordinates
+ int ii = 0;
+
+ while ((ii < seqs.length) && (seqs[ii] != null))
+ {
+ ii++;
+ }
+
+ double[][] comps = new double[ii][ii];
+
+ for (int i = 0; i < ii; i++)
+ {
+ if (pca.getEigenvalue(i) > 1e-4)
+ {
+ comps[i] = pca.component(i);
+ }
+ }
+
+ top = pca.getM().rows - 1;
+
+ points = new Vector<SequencePoint>();
+ float[][] scores = pca.getComponents(top - 1, top - 2, top - 3, 100);
+
+ for (int i = 0; i < pca.getM().rows; i++)
+ {
+ SequencePoint sp = new SequencePoint(seqs[i], scores[i]);
+ points.addElement(sp);
+ }
+
+ }
+
+ public void updateRc(RotatableCanvasI rc)
+ {
+ rc.setPoints(points, pca.getM().rows);
+ }
+
+ public boolean isNucleotide()
+ {
+ return nucleotide;
+ }
+ public void setNucleotide(boolean nucleotide)
+ {
+ this.nucleotide=nucleotide;
+ }
+
+ /**
+ *
+ *
+ * @return index of principle dimension of PCA
+ */
+ public int getTop()
+ {
+ return top;
+ }
+
+ /**
+ * update the 2d coordinates for the list of points to the given dimensions
+ * Principal dimension is getTop(). Next greated eigenvector is getTop()-1.
+ * Note - pca.getComponents starts counting the spectrum from zero rather than one, so getComponents(dimN ...) == updateRcView(dimN+1 ..)
+ * @param dim1
+ * @param dim2
+ * @param dim3
+ */
+ public void updateRcView(int dim1, int dim2, int dim3)
+ {
+ float[][] scores = pca.getComponents(dim1-1, dim2-1, dim3-1, 100);
+
+ for (int i = 0; i < pca.getM().rows; i++)
+ {
+ ((SequencePoint) points.elementAt(i)).coord = scores[i];
+ }
+ }
+
+ public String getDetails()
+ {
+ return pca.getDetails();
+ }
+
+ public AlignmentView getSeqtrings()
+ {
+ return seqstrings;
+ }
+ public String getPointsasCsv(boolean transformed, int xdim, int ydim, int zdim)
+ {
+ StringBuffer csv = new StringBuffer();
+ csv.append("\"Sequence\"");
+ if (transformed)
+ {
+ csv.append(",");
+ csv.append(xdim);
+ csv.append(",");
+ csv.append(ydim);
+ csv.append(",");
+ csv.append(zdim);
+ }
+ else
+ {
+ for (int d = 1, dmax = pca.component(1).length; d <= dmax; d++)
+ {
+ csv.append("," + d);
+ }
+ }
+ csv.append("\n");
+ for (int s = 0; s < seqs.length; s++)
+ {
+ csv.append("\"" + seqs[s].getName() + "\"");
+ double fl[];
+ if (!transformed)
+ {
+ // output pca in correct order
+ fl = pca.component(s);
+ for (int d = fl.length - 1; d >= 0; d--)
+ {
+ csv.append(",");
+ csv.append(fl[d]);
+ }
+ }
+ 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]);
+ }
+ }
+ csv.append("\n");
+ }
+ return csv.toString();
+ }
+
+ /**
+ *
+ * @return x,y,z positions of point s (index into points) under current
+ * transform.
+ */
+ 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];
+ return pts;
+ }
+
+}