no.uib.cipr.matrix.AbstractSymmDenseMatrix Maven / Gradle / Ivy
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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 org.netlib.blas.BLAS;
import org.netlib.lapack.LAPACK;
import org.netlib.util.intW;
/**
* Partial implementation of a symmetrical, dense matrix
*/
abstract class AbstractSymmDenseMatrix extends AbstractDenseMatrix {
/**
* Upper or lower part stored?
*/
private UpLo uplo;
/**
* Constructor for AbstractSymmDenseMatrix
*/
AbstractSymmDenseMatrix(int n, UpLo uplo) {
super(n, n);
this.uplo = uplo;
}
/**
* Constructor for AbstractSymmDenseMatrix
*/
AbstractSymmDenseMatrix(Matrix A, UpLo uplo) {
this(A, true, uplo);
}
/**
* Constructor for AbstractSymmDenseMatrix
*/
AbstractSymmDenseMatrix(Matrix A, boolean deep, UpLo uplo) {
super(A, deep);
if (!isSquare())
throw new IllegalArgumentException(
"Symmetric matrix must be square");
this.uplo = uplo;
}
@Override
public Matrix multAdd(double alpha, Matrix B, Matrix C) {
if (!(B instanceof DenseMatrix) || !(C instanceof DenseMatrix))
return super.multAdd(alpha, B, C);
checkMultAdd(B, C);
double[] Bd = ((DenseMatrix) B).getData(), Cd = ((DenseMatrix) C)
.getData();
BLAS.getInstance().dsymm(Side.Left.netlib(), uplo.netlib(), C.numRows(), C.numColumns(),
alpha, data, Math.max(1, C.numRows()), Bd,
Math.max(1, C.numRows()), 1, Cd, Math.max(1, C.numRows()));
return C;
}
@Override
public Matrix transAmultAdd(double alpha, Matrix B, Matrix C) {
return multAdd(alpha, B, C);
}
@Override
public Matrix rank1(double alpha, Vector x, Vector y) {
if (x != y)
throw new IllegalArgumentException("x != y");
if (!(x instanceof DenseVector))
return super.rank1(alpha, x, y);
checkRank1(x, y);
double[] xd = ((DenseVector) x).getData();
BLAS.getInstance().dsyr(uplo.netlib(), numRows, alpha, xd, 1, data,
Math.max(1, numRows));
return this;
}
@Override
public Matrix rank2(double alpha, Vector x, Vector y) {
if (!(x instanceof DenseVector) || !(y instanceof DenseVector))
return super.rank2(alpha, x, y);
checkRank2(x, y);
double[] xd = ((DenseVector) x).getData(), yd = ((DenseVector) y)
.getData();
BLAS.getInstance().dsyr2(uplo.netlib(), numRows, alpha, xd, 1, yd, 1, data,
Math.max(1, numRows));
return this;
}
@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().dsymv(uplo.netlib(), numRows, alpha, data, Math.max(1, numRows),
xd, 1, 1, yd, 1);
return y;
}
@Override
public Vector transMultAdd(double alpha, Vector x, Vector y) {
return multAdd(alpha, x, y);
}
@Override
public Matrix rank1(double alpha, Matrix C) {
if (!(C instanceof DenseMatrix))
return super.rank1(alpha, C);
checkRank1(C);
double[] Cd = ((DenseMatrix) C).getData();
BLAS.getInstance().dsyrk(uplo.netlib(), Transpose.NoTranspose.netlib(), numRows,
C.numColumns(), alpha, Cd, Math.max(1, numRows), 1, data,
Math.max(1, numRows));
return this;
}
@Override
public Matrix transRank1(double alpha, Matrix C) {
if (!(C instanceof DenseMatrix))
return super.transRank1(alpha, C);
checkTransRank1(C);
double[] Cd = ((DenseMatrix) C).getData();
BLAS.getInstance().dsyrk(uplo.netlib(), Transpose.Transpose.netlib(), numRows, numRows,
alpha, Cd, Math.max(1, numRows), 1, data, Math.max(1, numRows));
return this;
}
@Override
public Matrix rank2(double alpha, Matrix B, Matrix C) {
if (!(B instanceof DenseMatrix) || !(C instanceof DenseMatrix))
return super.rank2(alpha, B, C);
checkRank2(B, C);
double[] Bd = ((DenseMatrix) B).getData(), Cd = ((DenseMatrix) C)
.getData();
BLAS.getInstance().dsyr2k(uplo.netlib(), Transpose.NoTranspose.netlib(), numRows,
B.numColumns(), alpha, Bd, Math.max(1, numRows), Cd,
Math.max(1, numRows), 1, data, Math.max(1, numRows));
return this;
}
@Override
public Matrix transRank2(double alpha, Matrix B, Matrix C) {
if (!(B instanceof DenseMatrix) || !(C instanceof DenseMatrix))
return super.transRank2(alpha, B, C);
checkTransRank2(B, C);
double[] Bd = ((DenseMatrix) B).getData(), Cd = ((DenseMatrix) C)
.getData();
BLAS.getInstance().dsyr2k(uplo.netlib(), Transpose.Transpose.netlib(), numRows, B.numRows(),
alpha, Bd, Math.max(1, B.numRows()), Cd,
Math.max(1, B.numRows()), 1, data, Math.max(1, numRows));
return 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);
// Allocate factorization matrix
double[] newData = data.clone();
int[] ipiv = new int[numRows];
// Query optimal workspace
double[] work = new double[1];
intW info = new intW(0);
LAPACK.getInstance().dsysv(uplo.netlib(), numRows, X.numColumns(),
newData, Matrices.ld(numRows), ipiv, Xd, Matrices.ld(numRows),
work, -1, info);
// Allocate workspace
int lwork = -1;
if (info.val != 0)
lwork = 1;
else
lwork = Math.max((int) work[0], 1);
work = new double[lwork];
// Solve
info.val = 0;
LAPACK.getInstance().dsysv(uplo.netlib(), numRows, X.numColumns(), newData,
Matrices.ld(numRows), ipiv, Xd, Matrices.ld(numRows), work, lwork, 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().dposv(uplo.netlib(), numRows, X.numColumns(),
data.clone(), Matrices.ld(numRows), 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;
}
}