LAPACK
3.4.2
LAPACK: Linear Algebra PACKage

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Functions/Subroutines  
subroutine  sbdsqr (UPLO, N, NCVT, NRU, NCC, D, E, VT, LDVT, U, LDU, C, LDC, WORK, INFO) 
SBDSQR 
subroutine sbdsqr  (  character  UPLO, 
integer  N,  
integer  NCVT,  
integer  NRU,  
integer  NCC,  
real, dimension( * )  D,  
real, dimension( * )  E,  
real, dimension( ldvt, * )  VT,  
integer  LDVT,  
real, dimension( ldu, * )  U,  
integer  LDU,  
real, dimension( ldc, * )  C,  
integer  LDC,  
real, dimension( * )  WORK,  
integer  INFO  
) 
SBDSQR
Download SBDSQR + dependencies [TGZ] [ZIP] [TXT]SBDSQR computes the singular values and, optionally, the right and/or left singular vectors from the singular value decomposition (SVD) of a real NbyN (upper or lower) bidiagonal matrix B using the implicit zeroshift QR algorithm. The SVD of B has the form B = Q * S * P**T where S is the diagonal matrix of singular values, Q is an orthogonal matrix of left singular vectors, and P is an orthogonal matrix of right singular vectors. If left singular vectors are requested, this subroutine actually returns U*Q instead of Q, and, if right singular vectors are requested, this subroutine returns P**T*VT instead of P**T, for given real input matrices U and VT. When U and VT are the orthogonal matrices that reduce a general matrix A to bidiagonal form: A = U*B*VT, as computed by SGEBRD, then A = (U*Q) * S * (P**T*VT) is the SVD of A. Optionally, the subroutine may also compute Q**T*C for a given real input matrix C. See "Computing Small Singular Values of Bidiagonal Matrices With Guaranteed High Relative Accuracy," by J. Demmel and W. Kahan, LAPACK Working Note #3 (or SIAM J. Sci. Statist. Comput. vol. 11, no. 5, pp. 873912, Sept 1990) and "Accurate singular values and differential qd algorithms," by B. Parlett and V. Fernando, Technical Report CPAM554, Mathematics Department, University of California at Berkeley, July 1992 for a detailed description of the algorithm.
[in]  UPLO  UPLO is CHARACTER*1 = 'U': B is upper bidiagonal; = 'L': B is lower bidiagonal. 
[in]  N  N is INTEGER The order of the matrix B. N >= 0. 
[in]  NCVT  NCVT is INTEGER The number of columns of the matrix VT. NCVT >= 0. 
[in]  NRU  NRU is INTEGER The number of rows of the matrix U. NRU >= 0. 
[in]  NCC  NCC is INTEGER The number of columns of the matrix C. NCC >= 0. 
[in,out]  D  D is 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 in decreasing order. 
[in,out]  E  E is REAL array, dimension (N1) On entry, the N1 offdiagonal elements of the bidiagonal matrix B. On exit, if INFO = 0, E is destroyed; if INFO > 0, D and E will contain the diagonal and superdiagonal elements of a bidiagonal matrix orthogonally equivalent to the one given as input. 
[in,out]  VT  VT is REAL array, dimension (LDVT, NCVT) On entry, an NbyNCVT matrix VT. On exit, VT is overwritten by P**T * VT. Not referenced if NCVT = 0. 
[in]  LDVT  LDVT is INTEGER The leading dimension of the array VT. LDVT >= max(1,N) if NCVT > 0; LDVT >= 1 if NCVT = 0. 
[in,out]  U  U is REAL array, dimension (LDU, N) On entry, an NRUbyN matrix U. On exit, U is overwritten by U * Q. Not referenced if NRU = 0. 
[in]  LDU  LDU is INTEGER The leading dimension of the array U. LDU >= max(1,NRU). 
[in,out]  C  C is REAL array, dimension (LDC, NCC) On entry, an NbyNCC matrix C. On exit, C is overwritten by Q**T * C. Not referenced if NCC = 0. 
[in]  LDC  LDC is INTEGER The leading dimension of the array C. LDC >= max(1,N) if NCC > 0; LDC >=1 if NCC = 0. 
[out]  WORK  WORK is REAL array, dimension (4*N) 
[out]  INFO  INFO is INTEGER = 0: successful exit < 0: If INFO = i, the ith argument had an illegal value > 0: if NCVT = NRU = NCC = 0, = 1, a split was marked by a positive value in E = 2, current block of Z not diagonalized after 30*N iterations (in inner while loop) = 3, termination criterion of outer while loop not met (program created more than N unreduced blocks) else NCVT = NRU = NCC = 0, the algorithm did not converge; D and E contain the elements of a bidiagonal matrix which is orthogonally similar to the input matrix B; if INFO = i, i elements of E have not converged to zero. 
TOLMUL REAL, default = max(10,min(100,EPS**(1/8))) TOLMUL controls the convergence criterion of the QR loop. If it is positive, TOLMUL*EPS is the desired relative precision in the computed singular values. If it is negative, abs(TOLMUL*EPS*sigma_max) is the desired absolute accuracy in the computed singular values (corresponds to relative accuracy abs(TOLMUL*EPS) in the largest singular value. abs(TOLMUL) should be between 1 and 1/EPS, and preferably between 10 (for fast convergence) and .1/EPS (for there to be some accuracy in the results). Default is to lose at either one eighth or 2 of the available decimal digits in each computed singular value (whichever is smaller). MAXITR INTEGER, default = 6 MAXITR controls the maximum number of passes of the algorithm through its inner loop. The algorithms stops (and so fails to converge) if the number of passes through the inner loop exceeds MAXITR*N**2.
Definition at line 230 of file sbdsqr.f.