org.netlib.lapack
Class SGESDD
java.lang.Object
org.netlib.lapack.SGESDD
public class SGESDD
- extends java.lang.Object
SGESDD is a simplified interface to the JLAPACK routine sgesdd.
This interface converts Java-style 2D row-major arrays into
the 1D column-major linearized arrays expected by the lower
level JLAPACK routines. Using this interface also allows you
to omit offset and leading dimension arguments. However, because
of these conversions, these routines will be slower than the low
level ones. Following is the description from the original Fortran
source. Contact seymour@cs.utk.edu with any questions.
* ..
*
* Purpose
* =======
*
* SGESDD computes the singular value decomposition (SVD) of a real
* M-by-N matrix A, optionally computing the left and right singular
* vectors. If singular vectors are desired, it uses a
* divide-and-conquer algorithm.
*
* The SVD is written
*
* A = U * SIGMA * transpose(V)
*
* where SIGMA is an M-by-N matrix which is zero except for its
* min(m,n) diagonal elements, U is an M-by-M orthogonal matrix, and
* V is an N-by-N orthogonal matrix. The diagonal elements of SIGMA
* are the singular values of A; they are real and non-negative, and
* are returned in descending order. The first min(m,n) columns of
* U and V are the left and right singular vectors of A.
*
* Note that the routine returns VT = V**T, not V.
*
* The divide and conquer algorithm makes very mild assumptions about
* floating point arithmetic. It will work on machines with a guard
* digit in add/subtract, or on those binary machines without guard
* digits which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or
* Cray-2. It could conceivably fail on hexadecimal or decimal machines
* without guard digits, but we know of none.
*
* Arguments
* =========
*
* JOBZ (input) CHARACTER*1
* Specifies options for computing all or part of the matrix U:
* = 'A': all M columns of U and all N rows of V**T are
* returned in the arrays U and VT;
* = 'S': the first min(M,N) columns of U and the first
* min(M,N) rows of V**T are returned in the arrays U
* and VT;
* = 'O': If M >= N, the first N columns of U are overwritten
* on the array A and all rows of V**T are returned in
* the array VT;
* otherwise, all columns of U are returned in the
* array U and the first M rows of V**T are overwritten
* in the array VT;
* = 'N': no columns of U or rows of V**T are computed.
*
* M (input) INTEGER
* The number of rows of the input matrix A. M >= 0.
*
* N (input) INTEGER
* The number of columns of the input matrix A. N >= 0.
*
* A (input/output) REAL array, dimension (LDA,N)
* On entry, the M-by-N matrix A.
* On exit,
* if JOBZ = 'O', A is overwritten with the first N columns
* of U (the left singular vectors, stored
* columnwise) if M >= N;
* A is overwritten with the first M rows
* of V**T (the right singular vectors, stored
* rowwise) otherwise.
* if JOBZ .ne. 'O', the contents of A are destroyed.
*
* LDA (input) INTEGER
* The leading dimension of the array A. LDA >= max(1,M).
*
* S (output) REAL array, dimension (min(M,N))
* The singular values of A, sorted so that S(i) >= S(i+1).
*
* U (output) REAL array, dimension (LDU,UCOL)
* UCOL = M if JOBZ = 'A' or JOBZ = 'O' and M < N;
* UCOL = min(M,N) if JOBZ = 'S'.
* If JOBZ = 'A' or JOBZ = 'O' and M < N, U contains the M-by-M
* orthogonal matrix U;
* if JOBZ = 'S', U contains the first min(M,N) columns of U
* (the left singular vectors, stored columnwise);
* if JOBZ = 'O' and M >= N, or JOBZ = 'N', U is not referenced.
*
* LDU (input) INTEGER
* The leading dimension of the array U. LDU >= 1; if
* JOBZ = 'S' or 'A' or JOBZ = 'O' and M < N, LDU >= M.
*
* VT (output) REAL array, dimension (LDVT,N)
* If JOBZ = 'A' or JOBZ = 'O' and M >= N, VT contains the
* N-by-N orthogonal matrix V**T;
* if JOBZ = 'S', VT contains the first min(M,N) rows of
* V**T (the right singular vectors, stored rowwise);
* if JOBZ = 'O' and M < N, or JOBZ = 'N', VT is not referenced.
*
* LDVT (input) INTEGER
* The leading dimension of the array VT. LDVT >= 1; if
* JOBZ = 'A' or JOBZ = 'O' and M >= N, LDVT >= N;
* if JOBZ = 'S', LDVT >= min(M,N).
*
* WORK (workspace/output) REAL array, dimension (LWORK)
* On exit, if INFO = 0, WORK(1) returns the optimal LWORK;
*
* LWORK (input) INTEGER
* The dimension of the array WORK. LWORK >= 1.
* If JOBZ = 'N',
* LWORK >= 3*min(M,N) + max(max(M,N),6*min(M,N)).
* If JOBZ = 'O',
* LWORK >= 3*min(M,N)*min(M,N) +
* max(max(M,N),5*min(M,N)*min(M,N)+4*min(M,N)).
* If JOBZ = 'S' or 'A'
* LWORK >= 3*min(M,N)*min(M,N) +
* max(max(M,N),4*min(M,N)*min(M,N)+4*min(M,N)).
* For good performance, LWORK should generally be larger.
* If LWORK < 0 but other input arguments are legal, WORK(1)
* returns the optimal LWORK.
*
* IWORK (workspace) INTEGER array, dimension (8*min(M,N))
*
* INFO (output) INTEGER
* = 0: successful exit.
* < 0: if INFO = -i, the i-th argument had an illegal value.
* > 0: SBDSDC did not converge, updating process failed.
*
* Further Details
* ===============
*
* Based on contributions by
* Ming Gu and Huan Ren, Computer Science Division, University of
* California at Berkeley, USA
*
* =====================================================================
*
* .. Parameters ..
|
Method Summary |
static void |
SGESDD(java.lang.String jobz,
int m,
int n,
float[][] a,
float[] s,
float[][] u,
float[][] vt,
float[] work,
int lwork,
int[] iwork,
intW info)
|
| Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
SGESDD
public SGESDD()
SGESDD
public static void SGESDD(java.lang.String jobz,
int m,
int n,
float[][] a,
float[] s,
float[][] u,
float[][] vt,
float[] work,
int lwork,
int[] iwork,
intW info)