SRC/zgesvdx.f(3)

💅 NAME 💅

SRC/zgesvdx.f — okay bestie, this is the Library Functions Manual page for SRC/zgesvdx.f, and it's giving complex SVD main character energy. slay. ✨

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💫 SYNOPSIS 💫

Functions/Subroutines

subroutine zgesvdx (jobu, jobvt, range, m, n, a, lda, vl, vu, il, iu,
    ns, s, u, ldu, vt, ldvt, work, lwork, rwork, iwork, info)
     ZGESVDX computes the singular value decomposition (SVD) for GE
    matrices

ZGESVDX computes the singular value decomposition (SVD) for GE matrices. no cap. 👑

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🌸 Function/Subroutine Documentation 🌸

🦋 subroutine zgesvdx ... 🦋

   subroutine zgesvdx (character jobu, character jobvt, character range,
       integer m, integer n, complex*16, dimension( lda, * ) a, integer lda,
       double precision vl, double precision vu, integer il, integer iu,
       integer ns, double precision, dimension( * ) s, complex*16, dimension(
       ldu, * ) u, integer ldu, complex*16, dimension( ldvt, * ) vt, integer
       ldvt, complex*16, dimension( * ) work, integer lwork, double precision,
       dimension( * ) rwork, integer, dimension( * ) iwork, integer info)

ZGESVDX computes the singular value decomposition (SVD) for GE matrices — main character energy only. 💖

✨ Purpose ✨

ZGESVDX is out here computing the SVD of a complex M-by-N matrix A, and it can optionally compute the left and/or right singular vectors too. The SVD is written as:

A = U * SIGMA * transpose(V)

where SIGMA is an M-by-N matrix that's zero except for its min(m,n) diagonal elements, U is an M-by-M unitary matrix, and V is an N-by-N unitary matrix. The diagonal elements of SIGMA are the singular values of A; they're real and non-negative, and they come back in descending order. The first min(m,n) columns of U and V are the left and right singular vectors of A. slay. 🔥

ZGESVDX uses an eigenvalue problem for obtaining the SVD, which allows for the computation of a subset of singular values and vectors. See DBDSVDX for details. iykyk. 🧚

note bestie: the routine returns V**T, not V. periodt. 💅

🫶 Parameters 🫶

• JOBU — JOBU is CHARACTER*1 and specifies options for computing all or part of the matrix U:
  • = 'V': the first min(m,n) columns of U (the left singular vectors) or as specified by RANGE are returned in the array U;
  • = 'N': no columns of U (no left singular vectors) are computed.
• JOBVT — JOBVT is CHARACTER*1 and specifies options for computing all or part of the matrix V**T:
  • = 'V': the first min(m,n) rows of V**T (the right singular vectors) or as specified by RANGE are returned in the array VT;
  • = 'N': no rows of V**T (no right singular vectors) are computed.
• RANGE — RANGE is CHARACTER*1:
  • = 'A': all singular values will be found.
  • = 'V': all singular values in the half-open interval (VL,VU] will be found.
  • = 'I': the IL-th through IU-th singular values will be found.
• M — M is INTEGER; the number of rows of the input matrix A. M >= 0.
• N — N is INTEGER; the number of columns of the input matrix A. N >= 0.
• A — A is COMPLEX*16 array, dimension (LDA,N). On entry, the M-by-N matrix A. On exit, the contents of A are destroyed. (rip, but that's the tea ☕)
• LDA — LDA is INTEGER; the leading dimension of the array A. LDA >= max(1,M).
• VL — VL is DOUBLE PRECISION. If RANGE='V', the lower bound of the interval to be searched for singular values. VU > VL. Not referenced if RANGE = 'A' or 'I'.
• VU — VU is DOUBLE PRECISION. If RANGE='V', the upper bound of the interval to be searched for singular values. VU > VL. Not referenced if RANGE = 'A' or 'I'.
• IL — IL is INTEGER. If RANGE='I', the index of the smallest singular value to be returned. 1 <= IL <= IU <= min(M,N), if min(M,N) > 0. Not referenced if RANGE = 'A' or 'V'.
• IU — IU is INTEGER. If RANGE='I', the index of the largest singular value to be returned. 1 <= IL <= IU <= min(M,N), if min(M,N) > 0. Not referenced if RANGE = 'A' or 'V'.
• NS — NS is INTEGER; the total number of singular values found, 0 <= NS <= min(M,N). If RANGE = 'A', NS = min(M,N); if RANGE = 'I', NS = IU-IL+1.
• S — S is DOUBLE PRECISION array, dimension (min(M,N)). The singular values of A, sorted so that S(i) >= S(i+1).
• U — U is COMPLEX*16 array, dimension (LDU,UCOL). If JOBU = 'V', U contains columns of U (the left singular vectors, stored columnwise) as specified by RANGE; if JOBU = 'N', U is not referenced. Note: the user must ensure that UCOL >= NS; if RANGE = 'V', the exact value of NS is not known in advance and an upper bound must be used.
• LDU — LDU is INTEGER; the leading dimension of the array U. LDU >= 1; if JOBU = 'V', LDU >= M.
• VT — VT is COMPLEX*16 array, dimension (LDVT,N). If JOBVT = 'V', VT contains the rows of V**T (the right singular vectors, stored rowwise) as specified by RANGE; if JOBVT = 'N', VT is not referenced. Note: the user must ensure that LDVT >= NS; if RANGE = 'V', the exact value of NS is not known in advance and an upper bound must be used.
• LDVT — LDVT is INTEGER; the leading dimension of the array VT. LDVT >= 1; if JOBVT = 'V', LDVT >= NS (see above).
• WORK — WORK is COMPLEX*16 array, dimension (MAX(1,LWORK)). On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
• LWORK — LWORK is INTEGER; the dimension of the array WORK. LWORK >= MAX(1,MIN(M,N)*(MIN(M,N)+4)) for the paths (see comments inside the code):
  • PATH 1 (M much larger than N)
  • PATH 1t (N much larger than M)

LWORK >= MAX(1,MIN(M,N)*2+MAX(M,N)) for the other paths. For good performance, LWORK should generally be larger.

If LWORK = -1, then a workspace query is assumed; the routine only calculates the optimal size of the WORK array, returns this value as the first entry of the WORK array, and no error message related to LWORK is issued by XERBLA.

• RWORK — RWORK is DOUBLE PRECISION array, dimension (MAX(1,LRWORK)). LRWORK >= MIN(M,N)*(MIN(M,N)*2+15*MIN(M,N)).
• IWORK — IWORK is INTEGER array, dimension (12*MIN(M,N)). If INFO = 0, the first NS elements of IWORK are zero. If INFO > 0, then IWORK contains the indices of the eigenvectors that failed to converge in DBDSVDX/DSTEVX.
• INFO — INFO is INTEGER:
  • = 0: successful exit
  • < 0: if INFO = -i, the i-th argument had an illegal value
  • > 0: if INFO = i, then i eigenvectors failed to converge in DBDSVDX/DSTEVX. if INFO = N*2 + 1, an internal error occurred in DBDSVDX

👑 Author 👑

• Univ. of Tennessee
• Univ. of California Berkeley
• Univ. of Colorado Denver
• NAG Ltd.

Definition at line 267 of file zgesvdx.f.

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🌟 Author 🌟

Generated automatically by Doxygen for LAPACK from the source code.

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okay that's the whole page, bestie! 💖 this page's source/version vibes: LAPACK, Version 3.12.0, file SRC/zgesvdx.f(3) — mwah! 🫶