org.netlib.lapack
Class SBDSDC
java.lang.Object
org.netlib.lapack.SBDSDC
public class SBDSDC
- extends java.lang.Object
SBDSDC is a simplified interface to the JLAPACK routine sbdsdc.
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
* =======
*
* SBDSDC computes the singular value decomposition (SVD) of a real
* N-by-N (upper or lower) bidiagonal matrix B: B = U * S * VT,
* using a divide and conquer method, where S is a diagonal matrix
* with non-negative diagonal elements (the singular values of B), and
* U and VT are orthogonal matrices of left and right singular vectors,
* respectively. SBDSDC can be used to compute all singular values,
* and optionally, singular vectors or singular vectors in compact form.
*
* This code 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. See SLASD3 for details.
*
* The code currently call SLASDQ if singular values only are desired.
* However, it can be slightly modified to compute singular values
* using the divide and conquer method.
*
* Arguments
* =========
*
* UPLO (input) CHARACTER*1
* = 'U': B is upper bidiagonal.
* = 'L': B is lower bidiagonal.
*
* COMPQ (input) CHARACTER*1
* Specifies whether singular vectors are to be computed
* as follows:
* = 'N': Compute singular values only;
* = 'P': Compute singular values and compute singular
* vectors in compact form;
* = 'I': Compute singular values and singular vectors.
*
* N (input) INTEGER
* The order of the matrix B. N >= 0.
*
* D (input/output) REAL array, dimension (N)
* On entry, the n diagonal elements of the bidiagonal matrix B.
* On exit, if INFO=0, the singular values of B.
*
* E (input/output) REAL array, dimension (N)
* On entry, the elements of E contain the offdiagonal
* elements of the bidiagonal matrix whose SVD is desired.
* On exit, E has been destroyed.
*
* U (output) REAL array, dimension (LDU,N)
* If COMPQ = 'I', then:
* On exit, if INFO = 0, U contains the left singular vectors
* of the bidiagonal matrix.
* For other values of COMPQ, U is not referenced.
*
* LDU (input) INTEGER
* The leading dimension of the array U. LDU >= 1.
* If singular vectors are desired, then LDU >= max( 1, N ).
*
* VT (output) REAL array, dimension (LDVT,N)
* If COMPQ = 'I', then:
* On exit, if INFO = 0, VT' contains the right singular
* vectors of the bidiagonal matrix.
* For other values of COMPQ, VT is not referenced.
*
* LDVT (input) INTEGER
* The leading dimension of the array VT. LDVT >= 1.
* If singular vectors are desired, then LDVT >= max( 1, N ).
*
* Q (output) REAL array, dimension (LDQ)
* If COMPQ = 'P', then:
* On exit, if INFO = 0, Q and IQ contain the left
* and right singular vectors in a compact form,
* requiring O(N log N) space instead of 2*N**2.
* In particular, Q contains all the REAL data in
* LDQ >= N*(11 + 2*SMLSIZ + 8*INT(LOG_2(N/(SMLSIZ+1))))
* words of memory, where SMLSIZ is returned by ILAENV and
* is equal to the maximum size of the subproblems at the
* bottom of the computation tree (usually about 25).
* For other values of COMPQ, Q is not referenced.
*
* IQ (output) INTEGER array, dimension (LDIQ)
* If COMPQ = 'P', then:
* On exit, if INFO = 0, Q and IQ contain the left
* and right singular vectors in a compact form,
* requiring O(N log N) space instead of 2*N**2.
* In particular, IQ contains all INTEGER data in
* LDIQ >= N*(3 + 3*INT(LOG_2(N/(SMLSIZ+1))))
* words of memory, where SMLSIZ is returned by ILAENV and
* is equal to the maximum size of the subproblems at the
* bottom of the computation tree (usually about 25).
* For other values of COMPQ, IQ is not referenced.
*
* WORK (workspace) REAL array, dimension (LWORK)
* If COMPQ = 'N' then LWORK >= (4 * N).
* If COMPQ = 'P' then LWORK >= (6 * N).
* If COMPQ = 'I' then LWORK >= (3 * N**2 + 4 * N).
*
* IWORK (workspace) INTEGER array, dimension (8*N)
*
* INFO (output) INTEGER
* = 0: successful exit.
* < 0: if INFO = -i, the i-th argument had an illegal value.
* > 0: The algorithm failed to compute an singular value.
* The update process of divide and conquer 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 |
SBDSDC(java.lang.String uplo,
java.lang.String compq,
int n,
float[] d,
float[] e,
float[][] u,
float[][] vt,
float[] q,
int[] iq,
float[] work,
int[] iwork,
intW info)
|
| Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
SBDSDC
public SBDSDC()
SBDSDC
public static void SBDSDC(java.lang.String uplo,
java.lang.String compq,
int n,
float[] d,
float[] e,
float[][] u,
float[][] vt,
float[] q,
int[] iq,
float[] work,
int[] iwork,
intW info)