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A comprehensive collection of matrix data structures, linear solvers, least squares methods,
eigenvalue, and singular value decompositions.
Forked from: https://github.com/fommil/matrix-toolkits-java
and added support for eigenvalue computation of general matrices
The newest version!
/*
* Copyright (C) 2003-2006 Bjørn-Ove Heimsund
*
* This file is part of MTJ.
*
* This library is free software; you can redistribute it and/or modify it
* under the terms of the GNU Lesser General Public License as published by the
* Free Software Foundation; either version 2.1 of the License, or (at your
* option) any later version.
*
* This library 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 Lesser General Public License
* for more details.
*
* You should have received a copy of the GNU Lesser General Public License
* along with this library; if not, write to the Free Software Foundation,
* Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
*/
package no.uib.cipr.matrix.sparse;
import no.uib.cipr.matrix.NotConvergedException;
import no.uib.cipr.matrix.Vector;
/**
* Iteration monitor based on matrix norms. Extends the default linear iteration
* object to compare with the norm of the system matrix and the right hand side.
* Can often be a better convergence criteria than the default, but requires the
* computation of the matrix norm.
*/
public class MatrixIterationMonitor extends DefaultIterationMonitor {
/**
* Norm of the system matrix
*/
private double normA;
/**
* Norm of the right hand side
*/
private double normb;
/**
* Constructor for MatrixIterationMonitor
*
* @param normA
* Norm of the matrix A
* @param normb
* Norm of the vector b
* @param maxIter
* Maximum number of iterations
* @param rtol
* Relative convergence tolerance (to initial residual)
* @param atol
* Absolute convergence tolerance
* @param dtol
* Relative divergence tolerance (to initial residual)
*/
public MatrixIterationMonitor(double normA, double normb, int maxIter,
double rtol, double atol, double dtol) {
this.normA = normA;
this.normb = normb;
this.maxIter = maxIter;
this.rtol = rtol;
this.atol = atol;
this.dtol = dtol;
}
/**
* Constructor for MatrixIterationMonitor. Default is 100000 iterations at
* most, relative tolerance of 1e-5, absolute tolerance of 1e-50 and a
* divergence tolerance of 1e+5.
*/
public MatrixIterationMonitor(double normA, double normb) {
this.normA = normA;
this.normb = normb;
}
/**
* Sets the norm of the system matrix
*
* @param normA
* Norm of the matrix A
*/
public void setMatrixNorm(double normA) {
this.normA = normA;
}
/**
* Sets the norm of the right hand side vector
*
* @param normb
* Norm of the vector b
*/
public void setVectorNorm(double normb) {
this.normb = normb;
}
@Override
protected boolean convergedI(double r, Vector x)
throws IterativeSolverNotConvergedException {
// Store initial residual
if (isFirst())
initR = r;
// Check for convergence
if (r < Math.max(rtol * (normA * x.norm(normType) + normb), atol))
return true;
// Check for divergence
if (r > dtol * initR)
throw new IterativeSolverNotConvergedException(
NotConvergedException.Reason.Divergence, this);
if (iter >= maxIter)
throw new IterativeSolverNotConvergedException(
NotConvergedException.Reason.Iterations, this);
if (Double.isNaN(r))
throw new IterativeSolverNotConvergedException(
NotConvergedException.Reason.Divergence, this);
// Neither convergence nor divergence
return false;
}
@Override
protected boolean convergedI(double r) {
throw new UnsupportedOperationException();
}
}