/*
* 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 .
* The Jalview Authors are detailed in the 'AUTHORS' file.
*/
package jalview.analysis;
import jalview.api.analysis.ScoreModelI;
import jalview.api.analysis.SimilarityParamsI;
import jalview.bin.Console;
import jalview.datamodel.AlignmentView;
import jalview.datamodel.Point;
import jalview.datamodel.SequenceI;
import jalview.gui.PairwiseAlignPanel;
import jalview.gui.PaSiMapPanel;
import jalview.math.Matrix;
import jalview.math.MatrixI;
import jalview.viewmodel.AlignmentViewport;
import java.io.PrintStream;
import java.util.Hashtable;
import java.util.Enumeration;
/**
* Performs Principal Component Analysis on given sequences
* @AUTHOR MorellThomas
*/
public class PaSiMap implements Runnable
{
/*
* inputs
*/
final private AlignmentViewport seqs;
final private ScoreModelI scoreModel;
final private SimilarityParamsI similarityParams;
final private byte dim = 3;
/*
* outputs
*/
private MatrixI pairwiseScores;
private MatrixI eigenMatrix;
/**
* Constructor given the sequences to compute for, the similarity model to
* use, and a set of parameters for sequence comparison
*
* @param sequences
* @param sm
* @param options
*/
public PaSiMap(AlignmentViewport sequences, ScoreModelI sm,
SimilarityParamsI options)
{
this.seqs = sequences;
this.scoreModel = sm;
this.similarityParams = options;
}
/**
* Returns Eigenvalue
*
* @param i
* Index of diagonal within matrix
*
* @return Returns value of diagonal from matrix
*/
public double getEigenvalue(int i)
{
return eigenMatrix.getD()[i];
}
/**
* Returns coordinates for each datapoint
*
* @param l
* DOCUMENT ME!
* @param n
* DOCUMENT ME!
* @param mm
* DOCUMENT ME!
* @param factor ~ is 1
*
* @return DOCUMENT ME!
*/
public Point[] getComponents(int l, int n, int mm, float factor)
{
Point[] out = new Point[getHeight()];
for (int i = 0; i < out.length; i++)
{
float x = (float) component(i, l) * factor;
float y = (float) component(i, n) * factor;
float z = (float) component(i, mm) * factor;
out[i] = new Point(x, y, z);
}
return out;
}
/**
* DOCUMENT ME!
*
* @param n
* DOCUMENT ME!
*
* @return DOCUMENT ME!
*/
public double[] component(int n)
{
// n = index of eigenvector
double[] out = new double[getHeight()];
for (int i = 0; i < out.length; i++)
{
out[i] = component(i, n);
}
return out;
}
/**
* DOCUMENT ME!
*
* @param row
* DOCUMENT ME!
* @param n
* DOCUMENT ME!
*
* @return DOCUMENT ME!
*/
double component(int row, int n)
{
return eigenMatrix.getValue(row, n);
}
/**
* Answers a formatted text report of the PaSiMap calculation results (matrices
* and eigenvalues) suitable for display
*
* @return
*/
public String getDetails()
{
StringBuilder sb = new StringBuilder(1024);
sb.append("PaSiMap calculation using ").append(scoreModel.getName())
.append(" sequence similarity matrix\n========\n\n");
PrintStream ps = wrapOutputBuffer(sb);
/*
* coordinates matrix, with D vector
*/
sb.append(" --- Pairwise correlation coefficients ---\n");
pairwiseScores.print(ps, "%8.6f ");
ps.println();
sb.append(" --- Eigenvalues ---\n");
eigenMatrix.printD(ps, "%15.4e");
ps.println();
sb.append(" --- Coordinates ---\n");
eigenMatrix.print(ps, "%8.6f ");
ps.println();
return sb.toString();
}
/**
* Performs the PaSiMap calculation
*
* creates a new gui/PairwiseAlignPanel with the input sequences (AlignmentViewport)
* uses analysis/AlignSeq to creatue the pairwise alignments and calculate the AlignmentScores (float for each pair)
* gets all float[][] scores from the gui/PairwiseAlignPanel
* checks the connections for each sequence with AlignmentViewport seqs.calculateConnectivity(float[][] scores, int dim) (from analysis/Connectivity) -- throws an Exception if insufficient
* creates a math/MatrixI pairwiseScores of the float[][] scores
* copys the scores and fills the diagonal to create a symmetric matrix using math/Matrix.fillDiagonal()
* performs the analysis/ccAnalysis with the symmetric matrix
* gets the eigenmatrix and the eigenvalues using math/Matrix.tqli()
*/
@Override
public void run()
{
try
{
PairwiseAlignPanel alignment = new PairwiseAlignPanel(seqs, true, 100, 5);
float[][] scores = alignment.getAlignmentScores(); //bigger index first -- eg scores[14][13]
Hashtable connectivity = seqs.calculateConnectivity(scores, dim);
pairwiseScores = new Matrix(scores);
pairwiseScores.fillDiagonal();
eigenMatrix = pairwiseScores.copy();
ccAnalysis cc = new ccAnalysis(pairwiseScores, dim);
eigenMatrix = cc.run();
} catch (Exception q)
{
Console.error("Error computing PaSiMap: " + q.getMessage());
q.printStackTrace();
}
}
/**
* Returns a PrintStream that wraps (appends its output to) the given
* StringBuilder
*
* @param sb
* @return
*/
protected PrintStream wrapOutputBuffer(StringBuilder sb)
{
PrintStream ps = new PrintStream(System.out)
{
@Override
public void print(String x)
{
sb.append(x);
}
@Override
public void println()
{
sb.append("\n");
}
};
return ps;
}
/**
* Answers the N dimensions of the NxM PaSiMap matrix. This is the number of
* sequences involved in the pairwise score calculation.
*
* @return
*/
public int getHeight()
{
// TODO can any of seqs[] be null?
return eigenMatrix.height();// seqs.getSequences().length;
}
/**
* Answers the M dimensions of the NxM PaSiMap matrix. This is the number of
* sequences involved in the pairwise score calculation.
*
* @return
*/
public int getWidth()
{
// TODO can any of seqs[] be null?
return eigenMatrix.width();// seqs.getSequences().length;
}
/**
* Answers the sequence pairwise similarity scores which were the first step
* of the PaSiMap calculation
*
* @return
*/
public MatrixI getPairwiseScores()
{
return pairwiseScores;
}
public void setPairwiseScores(MatrixI m)
{
pairwiseScores = m;
}
public MatrixI getEigenmatrix()
{
return eigenMatrix;
}
public void setEigenmatrix(MatrixI m)
{
eigenMatrix = m;
}
}