Dsymv.java
package org.mklab.sdpj.gpack.blaswrap;
import org.mklab.nfc.matrix.ComplexNumericalMatrix;
import org.mklab.nfc.matrix.RealNumericalMatrix;
import org.mklab.nfc.scalar.ComplexNumericalScalar;
import org.mklab.nfc.scalar.RealNumericalScalar;
/**
* @author koga
* @version $Revision$, 2009/04/24
* @param <RS> 実スカラーの型
* @param <RM> 実行列の型
* @param <CS> 複素スカラーの型
* @param <CM> 複素行列の型
*/
public class Dsymv<RS extends RealNumericalScalar<RS, RM, CS, CM>, RM extends RealNumericalMatrix<RS, RM, CS, CM>, CS extends ComplexNumericalScalar<RS, RM, CS, CM>, CM extends ComplexNumericalMatrix<RS, RM, CS, CM>> {
/* Purpose
=======
DSYMV performs the matrix-vector operation
y := alpha*A*x + beta*y,
where alpha and beta are scalars, x and y are n element vectors and
A is an n by n symmetric matrix.
Parameters
==========
UPLO - CHARACTER*1.
On entry, UPLO specifies whether the upper or lower
triangular part of the array A is to be referenced as
follows:
UPLO = 'U' or 'u' Only the upper triangular part of A
is to be referenced.
UPLO = 'L' or 'l' Only the lower triangular part of A
is to be referenced.
Unchanged on exit.
N - INTEGER.
On entry, N specifies the order of the matrix A.
N must be at least zero.
Unchanged on exit.
ALPHA - DOUBLE PRECISION.
On entry, ALPHA specifies the scalar alpha.
Unchanged on exit.
A - DOUBLE PRECISION array of DIMENSION ( LDA, n ).
Before entry with UPLO = 'U' or 'u', the leading n by n
upper triangular part of the array A must contain the upper
triangular part of the symmetric matrix and the strictly
lower triangular part of A is not referenced.
Before entry with UPLO = 'L' or 'l', the leading n by n
lower triangular part of the array A must contain the lower
triangular part of the symmetric matrix and the strictly
upper triangular part of A is not referenced.
Unchanged on exit.
LDA - INTEGER.
On entry, LDA specifies the first dimension of A as declared
in the calling (sub) program. LDA must be at least
max( 1, n ).
Unchanged on exit.
X - DOUBLE PRECISION array of dimension at least
( 1 + ( n - 1 )*abs( INCX ) ).
Before entry, the incremented array X must contain the n
element vector x.
Unchanged on exit.
INCX - INTEGER.
On entry, INCX specifies the increment for the elements of
X. INCX must not be zero.
Unchanged on exit.
BETA - DOUBLE PRECISION.
On entry, BETA specifies the scalar beta. When BETA is
supplied as zero then Y need not be set on input.
Unchanged on exit.
Y - DOUBLE PRECISION array of dimension at least
( 1 + ( n - 1 )*abs( INCY ) ).
Before entry, the incremented array Y must contain the n
element vector y. On exit, Y is overwritten by the updated
vector y.
INCY - INTEGER.
On entry, INCY specifies the increment for the elements of
Y. INCY must not be zero.
Unchanged on exit.
Level 2 Blas routine.
-- Written on 22-October-1986.
Jack Dongarra, Argonne National Lab.
Jeremy Du Croz, Nag Central Office.
Sven Hammarling, Nag Central Office.
Richard Hanson, Sandia National Labs.
Test the input parameters.
Parameter adjustments */
/**
* @param uplo uplo
* @param n n
* @param alpha alpha
* @param a a
* @param lda lda
* @param x x
* @param incx incx
* @param beta beta
* @param y y
* @param incy incy
* @return result
*/
int execute(String uplo, int n, RS alpha, RS[] a, int lda, RS[] x, int incx, RS beta, RS[] y, int incy) {
final RS unit = a[0].createUnit();
int a_dim1 = lda;
int a_offset = 1 + a_dim1 * 1;
int pointer_a = -a_offset;
int info = 0;
if (!BLAS.lsame(uplo, "U") && !BLAS.lsame(uplo, "L")) { //$NON-NLS-1$ //$NON-NLS-2$
info = 1;
} else if (n < 0) {
info = 2;
} else if (lda < Math.max(1, n)) {
info = 5;
} else if (incx == 0) {
info = 7;
} else if (incy == 0) {
info = 10;
}
if (info != 0) {
BLAS.xerbla("DSYMV ", info); //$NON-NLS-1$
return 0;
}
// Quick return if possible.
if (n == 0 || alpha.isZero() && beta.equals(unit.createUnit())) {
return 0;
}
// Set up the start points in X and Y.
int kx;
if (incx > 0) {
kx = 1;
} else {
kx = 1 - (n - 1) * incx;
}
int ky;
if (incy > 0) {
ky = 1;
} else {
ky = 1 - (n - 1) * incy;
}
/* Start the operations. In this version the elements of A are
* accessed sequentially with one pass through the triangular part of A.
* First form y := beta*y.
*/
if (!beta.equals(unit.createUnit())) {
if (incy == 1) {
if (beta.isZero()) {
for (int i = 1; i <= n; ++i) {
y[i - 1] = unit.createZero();
}
} else {
for (int i = 1; i <= n; ++i) {
y[i - 1] = beta.multiply(y[i - 1]);
}
}
} else {
int iy = ky;
if (beta.isZero()) {
for (int i = 1; i <= n; ++i) {
y[iy - 1] = unit.createZero();
iy += incy;
}
} else {
for (int i = 1; i <= n; ++i) {
y[iy - 1] = beta.multiply(y[iy - 1]);
iy += incy;
}
}
}
}
if (alpha.isZero()) {
return 0;
}
if (BLAS.lsame(uplo, "U")) { //$NON-NLS-1$
// Form y when A is stored in upper triangle.
if (incx == 1 && incy == 1) {
for (int j = 1; j <= n; ++j) {
RS temp1 = alpha.multiply(x[j - 1]);
RS temp2 = unit.createZero();
for (int i = 1; i <= j - 1; ++i) {
int p = j * a_dim1 + i + pointer_a;
y[i - 1] = y[i - 1].add(temp1.multiply(a[p]));
temp2 = temp2.add(a[p].multiply(x[i - 1]));
}
y[j - 1] = y[j - 1].add(temp1.multiply(a[j * a_dim1 + j + pointer_a])).add(alpha.multiply(temp2));
}
} else {
int jx = kx;
int jy = ky;
for (int j = 1; j <= n; ++j) {
RS temp1 = alpha.multiply(x[-1 + jx]);
RS temp2 = unit.createZero();
int ix = kx;
int iy = ky;
for (int i = 1; i <= j - 1; ++i) {
int p = j * a_dim1 + i + pointer_a;
y[iy - 1] = y[iy - 1].add(temp1.multiply(a[p]));
temp2 = temp2.add(a[p].multiply(x[-1 + ix]));
ix += incx;
iy += incy;
}
y[jy - 1] = y[jy - 1].add(temp1.multiply(a[j * a_dim1 + j + pointer_a])).add(alpha.multiply(temp2));
jx += incx;
jy += incy;
}
}
} else {
// Form y when A is stored in lower triangle.
if (incx == 1 && incy == 1) {
for (int j = 1; j <= n; ++j) {
RS temp1 = alpha.multiply(x[j - 1]);
RS temp2 = unit.createZero();
y[j - 1] = y[j - 1].add(temp1.multiply(a[j * a_dim1 + j + pointer_a]));
for (int i = j + 1; i <= n; ++i) {
int p = j * a_dim1 + i + pointer_a;
y[i - 1] = y[i - 1].add(temp1.multiply(a[p]));
temp2 = temp2.add(a[p].multiply(x[i - 1]));
}
y[j - 1] = y[j - 1].add(alpha.multiply(temp2));
}
} else {
int jx = kx;
int jy = ky;
for (int j = 1; j <= n; ++j) {
RS temp1 = alpha.multiply(x[-1 + jx]);
RS temp2 = unit.createZero();
y[jy - 1] = y[jy - 1].add(temp1.multiply(a[j * a_dim1 + j + pointer_a]));
int ix = jx;
int iy = jy;
for (int i = j + 1; i <= n; ++i) {
ix += incx;
iy += incy;
int p = j * a_dim1 + i + pointer_a;
y[iy - 1] = y[iy - 1].add(temp1.multiply(a[p]));
temp2 = temp2.add(a[p].multiply(x[-1 + ix]));
}
y[jy - 1] = y[jy - 1].add(alpha.multiply(temp2));
jx += incx;
jy += incy;
}
}
}
return 0;
}
}