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A comprehensive collection of matrix data structures, linear solvers, least squares methods,
eigenvalue, and singular value decompositions.
/*
* 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;
import com.github.fommil.netlib.LAPACK;
import org.netlib.util.intW;
/**
* Symmetrical positive definite tridiagonal matrix. Same as
* {@link no.uib.cipr.matrix.SymmTridiagMatrix SymmTridiagMatrix}, and is used
* as a marker class to allow for more efficient solvers.
*/
public class SPDTridiagMatrix extends SymmTridiagMatrix {
/**
* Constructor for SPDTridiagMatrix
*
* @param n
* Size of the matrix. Since the matrix must be square, this
* equals both the number of rows and columns
*/
public SPDTridiagMatrix(int n) {
super(n);
}
/**
* Constructor for SPDTridiagMatrix
*
* @param A
* Matrix to copy contents from. Only main and the superdiagonal
* is copied over
*/
public SPDTridiagMatrix(Matrix A) {
super(A);
}
/**
* Constructor for SPDTridiagMatrix
*
* @param A
* Matrix to copy contents from. Only main and the superdiagonal
* is copied over
* @param deep
* True for a deep copy. For shallow copies A
must
* be a SymmTridiagMatrix
*/
public SPDTridiagMatrix(Matrix A, boolean deep) {
super(A, deep);
}
@Override
public SPDTridiagMatrix copy() {
return new SPDTridiagMatrix(this);
}
@Override
public Matrix solve(Matrix B, Matrix X) {
if (!(X instanceof DenseMatrix))
throw new UnsupportedOperationException("X must be a DenseMatrix");
checkSolve(B, X);
double[] Xd = ((DenseMatrix) X).getData();
X.set(B);
intW info = new intW(0);
LAPACK.getInstance().dptsv(numRows, X.numColumns(), diag.clone(),
offDiag.clone(), Xd, Matrices.ld(numRows), info);
if (info.val > 0)
throw new MatrixNotSPDException();
else if (info.val < 0)
throw new IllegalArgumentException();
return X;
}
}