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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
/*
* 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
*/
/*
* Derived from public domain software at http://www.netlib.org/templates
*/
package no.uib.cipr.matrix.sparse;
import no.uib.cipr.matrix.Matrix;
import no.uib.cipr.matrix.NotConvergedException;
import no.uib.cipr.matrix.Vector;
/**
* BiCG stablized solver. BiCGstab solves the unsymmetric linear system
* Ax = b
using the Preconditioned BiConjugate Gradient Stabilized
* method
*
* @author Templates
*/
public class BiCGstab extends AbstractIterativeSolver {
/**
* Vectors for use in the iterative solution process
*/
private Vector p, s, phat, shat, t, v, temp, r, rtilde;
/**
* Constructor for BiCGstab. Uses the given vector as template for creating
* scratch vectors. Typically, the solution or the right hand side vector
* can be passed, and the template is not modified
*
* @param template
* Vector to use as template for the work vectors needed in the
* solution process
*/
public BiCGstab(Vector template) {
p = template.copy();
s = template.copy();
phat = template.copy();
shat = template.copy();
t = template.copy();
v = template.copy();
temp = template.copy();
r = template.copy();
rtilde = template.copy();
}
public Vector solve(Matrix A, Vector b, Vector x)
throws IterativeSolverNotConvergedException {
checkSizes(A, b, x);
double rho_1 = 1, rho_2 = 1, alpha = 1, beta = 1, omega = 1;
A.multAdd(-1, x, r.set(b));
rtilde.set(r);
for (iter.setFirst(); !iter.converged(r, x); iter.next()) {
rho_1 = rtilde.dot(r);
if (rho_1 == 0)
throw new IterativeSolverNotConvergedException(
NotConvergedException.Reason.Breakdown, "rho", iter);
if (omega == 0)
throw new IterativeSolverNotConvergedException(
NotConvergedException.Reason.Breakdown, "omega", iter);
if (iter.isFirst())
p.set(r);
else {
beta = (rho_1 / rho_2) * (alpha / omega);
// temp = p - omega * v
temp.set(-omega, v).add(p);
// p = r + beta * temp = r + beta * (p - omega * v)
p.set(r).add(beta, temp);
}
M.apply(p, phat);
A.mult(phat, v);
alpha = rho_1 / rtilde.dot(v);
s.set(r).add(-alpha, v);
x.add(alpha, phat);
if (iter.converged(s, x))
return x;
M.apply(s, shat);
A.mult(shat, t);
omega = t.dot(s) / t.dot(t);
x.add(omega, shat);
r.set(s).add(-omega, t);
rho_2 = rho_1;
}
return x;
}
}