/*
* 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 java.util.Iterator;
import com.github.fommil.netlib.BLAS;
import com.github.fommil.netlib.LAPACK;
import org.netlib.util.intW;
/**
* Partial implementation of a symmetrical, banded matrix
*/
abstract class AbstractSymmBandMatrix extends AbstractBandMatrix {
/**
* Upper or lower part stored?
*/
private UpLo uplo;
/**
* Diagonals in relevant band
*/
int kd;
/**
* Constructor for AbstractSymmBandMatrix
*/
AbstractSymmBandMatrix(int n, int kl, int ku, UpLo uplo) {
super(n, kl, ku);
kd = Math.max(kl, ku);
this.uplo = uplo;
}
/**
* Constructor for AbstractSymmBandMatrix
*/
AbstractSymmBandMatrix(Matrix A, int kl, int ku, UpLo uplo) {
this(A, kl, ku, true, uplo);
}
/**
* Constructor for AbstractSymmBandMatrix
*/
AbstractSymmBandMatrix(Matrix A, int kl, int ku, boolean deep, UpLo uplo) {
super(A, kl, ku, deep);
kd = Math.max(kl, ku);
this.uplo = uplo;
}
@Override
public Vector multAdd(double alpha, Vector x, Vector y) {
if (!(x instanceof DenseVector) || !(y instanceof DenseVector))
return super.multAdd(alpha, x, y);
checkMultAdd(x, y);
double[] xd = ((DenseVector) x).getData(), yd = ((DenseVector) y)
.getData();
BLAS.getInstance().dsbmv(uplo.netlib(), numRows, kd, alpha, data, kd + 1, xd, 1, 1, yd, 1);
return y;
}
@Override
public Vector transMultAdd(double alpha, Vector x, Vector y) {
return multAdd(alpha, x, y);
}
@Override
public Iterator<MatrixEntry> iterator() {
return new BandMatrixIterator(kd, kd);
}
@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);
// Allocate factorization matrix. The factorization matrix will be
// large enough to accomodate any pivots
BandMatrix Af = new BandMatrix(this, kd, kd + kd);
int[] ipiv = new int[numRows];
intW info = new intW(0);
LAPACK.getInstance().dgbsv(numRows, kd, kd, X.numColumns(),
Af.getData(), Matrices.ld(2 * kd + kd + 1), ipiv, Xd,
Matrices.ld(numRows), info);
if (info.val > 0)
throw new MatrixSingularException();
else if (info.val < 0)
throw new IllegalArgumentException();
return X;
}
@Override
public Vector solve(Vector b, Vector x) {
DenseMatrix B = new DenseMatrix(b, false), X = new DenseMatrix(x, false);
solve(B, X);
return x;
}
@Override
public Matrix transSolve(Matrix B, Matrix X) {
return solve(B, X);
}
@Override
public Vector transSolve(Vector b, Vector x) {
return solve(b, x);
}
Matrix SPDsolve(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().dpbsv(uplo.netlib(), numRows, kd, X.numColumns(),
data.clone(), Matrices.ld(kd + 1), Xd, Matrices.ld(numRows), info);
if (info.val > 0)
throw new MatrixNotSPDException();
else if (info.val < 0)
throw new IllegalArgumentException();
return X;
}
@Override
public Matrix transpose() {
return this;
}
}