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/**
*
* Written by Mrton Mnz and Philip C Biggin
* Copyright (c) University of Oxford, United Kingdom
* Visit http://sbcb.bioch.ox.ac.uk/jgromacs/
*
* This source code file is part of JGromacs v1.0.
*
* JGromacs v1.0 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.
*
* JGromacs v1.0. 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 JGromacs v1.0. If not, see <http://www.gnu.org/licenses/>.
*
*/
package jgromacs.analysis;
import Jama.Matrix;
import Jama.SingularValueDecomposition;
import java.util.ArrayList;
import jgromacs.data.Structure;
/**
* Objects of this class represent a Gaussian Network Model (GNM) of a protein
*
*/
public class GNM {
private Matrix cM = new Matrix(1,1,0);
private Matrix KM = new Matrix(1,1,0);
private Matrix U = new Matrix(1,1,0);
private Matrix Lambda = new Matrix(1,1,0);
/**
* Constructs a new Gaussian Network Model
* @param s structure to be modelled
* @param cutoff distance cutoff
* @param distanceBetween which atoms are used for calculating the distances (ALPHACARBON: alpha carbon atoms,
* CLOSEST: closest atoms of two residues, CLOSESTHEAVY: closest heavy atoms of two residues)
*/
public GNM(Structure s, double cutoff, int distanceBetween){
cM = Distances.getContactMatrix(s, distanceBetween, cutoff);
KM = calculateKirchhoffMatrix(cM);
SingularValueDecomposition svd = new SingularValueDecomposition(KM);
U = svd.getU();
Lambda = svd.getS();
}
/**
* Returns the contact matrix
* @return contact matrix
*/
public Matrix getContactMatrix(){
return cM;
}
/**
* Returns the Kirchhoff matrix
* @return Kirchhoff matrix
*/
public Matrix getKirchhoffMatrix(){
return KM;
}
/**
* Returns the diagonal matrix of eigenvalues (Lambda)
* @return Lambda matrix
*/
public Matrix getLambdaMatrix(){
return Lambda;
}
/**
* Returns the orthogonal matrix of eigenvectors (U)
* @return U matrix
*/
public Matrix getEigenvectorMatrix(){
return U;
}
/**
* Calculates the mean square fluctuation (MSF) profile
* @return MSF profile
*/
public ArrayList<Double> getMSFProfile(){
ArrayList<Double> ret = new ArrayList<Double>();
int resnum = Lambda.getRowDimension();
for (int i = 0; i < resnum; i++) {
double msf = 0;
for (int q = 0; q < resnum-1; q++)
msf+=Math.pow(U.get(i, q),2)/Lambda.get(q, q);
ret.add(msf);
}
return ret;
}
private static Matrix calculateKirchhoffMatrix(Matrix cM){
Matrix ret = cM.times(-1);
int resnum = ret.getRowDimension();
for (int i = 0; i < resnum; i++) {
double sum = 0;
for (int j = 0; j < resnum; j++)
if (j!=i) sum+=ret.get(i, j);
ret.set(i, i, -sum);
}
return ret;
}
}
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