+/*
+ * Jalview - A Sequence Alignment Editor and Viewer ($$Version-Rel$$)
+ * Copyright (C) $$Year-Rel$$ The Jalview Authors
+ *
+ * This file is part of Jalview.
+ *
+ * Jalview is free software: you can redistribute it and/or
+ * modify it under the terms of the GNU General Public License
+ * as published by the Free Software Foundation, either version 3
+ * of the License, or (at your option) any later version.
+ *
+ * Jalview is distributed in the hope that it will be useful, but
+ * WITHOUT ANY WARRANTY; without even the implied warranty
+ * of MERCHANTABILITY or FITNESS FOR A PARTICULAR
+ * PURPOSE. See the GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with Jalview. If not, see <http://www.gnu.org/licenses/>.
+ * The Jalview Authors are detailed in the 'AUTHORS' file.
+ */
package jalview.viewmodel;
-import java.util.Vector;
-
import jalview.analysis.PCA;
+import jalview.api.RotatableCanvasI;
import jalview.datamodel.AlignmentView;
import jalview.datamodel.SequenceI;
import jalview.datamodel.SequencePoint;
-import jalview.api.RotatableCanvasI;
+
+import java.util.Vector;
public class PCAModel
{
+ /*
+ * Jalview 2.10.1 treated gaps as X (peptide) or N (nucleotide)
+ * for pairwise scoring; 2.10.2 uses gap score (last column) in
+ * score matrix (JAL-2397)
+ * Set this flag to true (via Groovy) for 2.10.1 behaviour
+ */
+ private static boolean scoreGapAsAny = false;
public PCAModel(AlignmentView seqstrings2, SequenceI[] seqs2,
boolean nucleotide2)
{
- seqstrings=seqstrings2;
- seqs=seqs2;
- nucleotide=nucleotide2;
+ seqstrings = seqstrings2;
+ seqs = seqs2;
+ nucleotide = nucleotide2;
+ score_matrix = nucleotide2 ? "PID" : "BLOSUM62";
}
private volatile PCA pca;
-
+
int top;
-
+
AlignmentView seqstrings;
SequenceI[] seqs;
/**
- * use the identity matrix for calculating similarity between sequences.
+ * Score matrix used to calculate PC
*/
- private boolean nucleotide=false;
+ String score_matrix;
+
+ /**
+ * use the identity matrix for calculating similarity between sequences.
+ */
+ private boolean nucleotide = false;
private Vector<SequencePoint> points;
- private boolean jvCalcMode=true;
+ private boolean jvCalcMode = true;
public boolean isJvCalcMode()
{
public void run()
{
-
- pca = new PCA(seqstrings.getSequenceStrings(' '), nucleotide);
+ char gapChar = scoreGapAsAny ? (nucleotide ? 'N' : 'X') : ' ';
+ String[] sequenceStrings = seqstrings.getSequenceStrings(gapChar);
+ pca = new PCA(sequenceStrings, nucleotide,
+ score_matrix);
pca.setJvCalcMode(jvCalcMode);
pca.run();
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;
+ int height = pca.getHeight();
+ // top = pca.getM().height() - 1;
+ top = height - 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++)
+ for (int i = 0; i < height; i++)
{
SequencePoint sp = new SequencePoint(seqs[i], scores[i]);
points.addElement(sp);
}
-
}
public void updateRc(RotatableCanvasI rc)
{
- rc.setPoints(points, pca.getM().rows);
+ rc.setPoints(points, pca.getHeight());
}
public boolean isNucleotide()
{
return nucleotide;
}
+
public void setNucleotide(boolean nucleotide)
{
- this.nucleotide=nucleotide;
+ this.nucleotide = nucleotide;
}
/**
/**
* update the 2d coordinates for the list of points to the given dimensions
* Principal dimension is getTop(). Next greatest eigenvector is getTop()-1.
- * Note - pca.getComponents starts counting the spectrum from rank-2 to zero, rather than rank-1, so getComponents(dimN ...) == updateRcView(dimN+1 ..)
- * @param dim1
+ * Note - pca.getComponents starts counting the spectrum from rank-2 to zero,
+ * rather than rank-1, so getComponents(dimN ...) == updateRcView(dimN+1 ..)
+ *
+ * @param dim1
* @param dim2
* @param dim3
*/
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);
+ float[][] scores = pca.getComponents(dim1 - 1, dim2 - 1, dim3 - 1, 100);
- for (int i = 0; i < pca.getM().rows; i++)
+ for (int i = 0; i < pca.getHeight(); i++)
{
- ((SequencePoint) points.elementAt(i)).coord = scores[i];
+ points.elementAt(i).coord = scores[i];
}
}
{
return seqstrings;
}
- public String getPointsasCsv(boolean transformed, int xdim, int ydim, int zdim)
+
+ public String getPointsasCsv(boolean transformed, int xdim, int ydim,
+ int zdim)
{
StringBuffer csv = new StringBuffer();
csv.append("\"Sequence\"");
public void setJvCalcMode(boolean state)
{
- jvCalcMode=state;
+ jvCalcMode = state;
+ }
+
+ public String getScore_matrix()
+ {
+ return score_matrix;
+ }
+
+ public void setScore_matrix(String score_matrix)
+ {
+ this.score_matrix = score_matrix;
}
}