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Parallel Colt is a multithreaded version of Colt - a library for high performance scientific computing in Java. It contains efficient algorithms for data analysis, linear algebra, multi-dimensional arrays, Fourier transforms, statistics and histogramming.
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/*
* 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 cern.colt.matrix.tfloat.algo.solver;
import cern.colt.matrix.tfloat.FloatMatrix1D;
import cern.colt.matrix.tfloat.FloatMatrix2D;
import cern.jet.math.tfloat.FloatFunctions;
/**
* Conjugate Gradients squared solver. CGS solves the unsymmetric linear system
* Ax = b
using the Conjugate Gradient Squared method
*
* @author Templates
*/
public class FloatCGS extends AbstractFloatIterativeSolver {
/**
* Vectors for use in the iterative solution process
*/
private FloatMatrix1D p, q, u, phat, qhat, vhat, uhat, sum, r, rtilde;
/**
* Constructor for CGS. 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 FloatCGS(FloatMatrix1D template) {
p = template.copy();
q = template.copy();
u = template.copy();
phat = template.copy();
qhat = template.copy();
vhat = template.copy();
uhat = template.copy();
sum = template.copy();
r = template.copy();
rtilde = template.copy();
}
public FloatMatrix1D solve(FloatMatrix2D A, FloatMatrix1D b, FloatMatrix1D x)
throws IterativeSolverFloatNotConvergedException {
checkSizes(A, b, x);
float rho_1 = 0, rho_2 = 0, alpha = 0, beta = 0;
A.zMult(x, r.assign(b), -1, 1, false);
rtilde.assign(r);
for (iter.setFirst(); !iter.converged(r, x); iter.next()) {
rho_1 = rtilde.zDotProduct(r);
if (rho_1 == 0)
throw new IterativeSolverFloatNotConvergedException(FloatNotConvergedException.Reason.Breakdown, "rho",
iter);
if (iter.isFirst()) {
u.assign(r);
p.assign(u);
} else {
beta = rho_1 / rho_2;
u.assign(r).assign(q, FloatFunctions.plusMultSecond(beta));
sum.assign(q).assign(p, FloatFunctions.plusMultSecond(beta));
p.assign(u).assign(sum, FloatFunctions.plusMultSecond(beta));
}
M.apply(p, phat);
A.zMult(phat, vhat);
alpha = rho_1 / rtilde.zDotProduct(vhat);
q.assign(vhat, FloatFunctions.multSecond(-alpha)).assign(u, FloatFunctions.plus);
M.apply(sum.assign(u).assign(q, FloatFunctions.plus), uhat);
x.assign(uhat, FloatFunctions.plusMultSecond(alpha));
A.zMult(uhat, qhat);
r.assign(qhat, FloatFunctions.plusMultSecond(-alpha));
rho_2 = rho_1;
}
return x;
}
}
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