ZGBSVX(3)

📦 version 3.12.0, in opensuse-leap 16.0

🎀 NAME 🎀

okay bestie, welcome to the zgbsvx.f(3) page from the Library Functions Manual — yes, the whole vibe is “linear algebra but make it cute.” 💖

The source path in the original is literally:

/home/abuild/rpmbuild/BUILD/lapack-
       static-3.12.0-build/lapack-3.12.0/SRC/zgbsvx.f

✨ SYNOPSIS ✨

🦋 Functions/Subroutines 🦋

       subroutine ZGBSVX (fact, trans, n, kl, ku, nrhs, ab, ldab, afb, ldafb,
           ipiv, equed, r, c, b, ldb, x, ldx, rcond, ferr, berr, work, rwork,
           info)

ZGBSVX computes the solution to system of linear equations A * X = B for GB matrices. periodt. 💅

💜 Function/Subroutine Documentation 💜

🦋 subroutine ZGBSVX 🦋

   subroutine ZGBSVX (character fact, character trans, integer n, integer kl,
       integer ku, integer nrhs, complex*16, dimension( ldab, * ) ab, integer
       ldab, complex*16, dimension( ldafb, * ) afb, integer ldafb, integer,
       dimension( * ) ipiv, character equed, double precision, dimension( * )
       r, double precision, dimension( * ) c, complex*16, dimension( ldb, * )
       b, integer ldb, complex*16, dimension( ldx, * ) x, integer ldx, double
       precision rcond, double precision, dimension( * ) ferr, double
       precision, dimension( * ) berr, complex*16, dimension( * ) work, double
       precision, dimension( * ) rwork, integer info)

ZGBSVX computes the solution to system of linear equations A * X = B for GB matrices. 🫶

🌟 Purpose 🌟

Okay so ZGBSVX uses the LU factorization to compute the solution to a complex system of linear equations:

A * X = B
A**T * X = B
A**H * X = B

where A is a band matrix of order N with KL subdiagonals and KU superdiagonals, and X and B are N-by-NRHS matrices. 🌈

Error bounds on the solution and a condition estimate are also provided. iykyk — it’s not just solving, it’s doing the whole wellness check too. ✨

🍓 Description 🍓

The following steps are performed by this subroutine: 💅

  1. If FACT = 'E', real scaling factors are computed to equilibrate the system:
TRANS = 'N':  diag(R)*A*diag(C)     *inv(diag(C))*X = diag(R)*B
TRANS = 'T': (diag(R)*A*diag(C))**T *inv(diag(R))*X = diag(C)*B
TRANS = 'C': (diag(R)*A*diag(C))**H *inv(diag(R))*X = diag(C)*B

Whether or not the system will be equilibrated depends on the scaling of the matrix A, but if equilibration is used, A is overwritten by diag(R)*A*diag(C) and B by diag(R)*B (if TRANS='N') or diag(C)*B (if TRANS = 'T' or 'C'). 🌀

  1. If FACT = 'N' or 'E', the LU decomposition is used to factor the matrix A (after equilibration if FACT = 'E') as
A = L * U,

where L is a product of permutation and unit lower triangular matrices with KL subdiagonals, and U is upper triangular with KL+KU superdiagonals. 👑

  1. If some U(i,i)=0, so that U is exactly singular, then the routine returns with INFO = i. Otherwise, the factored form of A is used to estimate the condition number of the matrix A. If the reciprocal of the condition number is less than machine precision, INFO = N+1 is returned as a warning, but the routine still goes on to solve for X and compute error bounds as described below. 😭 yes, a warning, but the show goes on.
  2. The system of equations is solved for X using the factored form of A. 🌸
  3. Iterative refinement is applied to improve the computed solution matrix and calculate error bounds and backward error estimates for it. ✨
  4. If equilibration was used, the matrix X is premultiplied by diag(C) (if TRANS = 'N') or diag(R) (if TRANS = 'T' or 'C') so that it solves the original system before equilibration. 💖

💅 Parameters 💅

🍓 FACT 🍓

FACT is CHARACTER*1. It specifies whether or not the factored form of the matrix A is supplied on entry, and if not, whether the matrix A should be equilibrated before it is factored. 🧚

  • = 'F' — On entry, AFB and IPIV contain the factored form of A. If EQUED is not 'N', the matrix A has been equilibrated with scaling factors given by R and C. AB, AFB, and IPIV are not modified. 💜
  • = 'N' — The matrix A will be copied to AFB and factored. 🌟
  • = 'E' — The matrix A will be equilibrated if necessary, then copied to AFB and factored. 🦋

🍓 TRANS 🍓

TRANS is CHARACTER*1. It specifies the form of the system of equations. 🔥

  • = 'N' — A * X = B (No transpose)
  • = 'T' — A**T * X = B (Transpose)
  • = 'C' — A**H * X = B (Conjugate transpose)

🍓 N 🍓

N is INTEGER. The number of linear equations, i.e., the order of the matrix A. N >= 0. 🌈

🍓 KL 🍓

KL is INTEGER. The number of subdiagonals within the band of A. KL >= 0. 🎀

🍓 KU 🍓

KU is INTEGER. The number of superdiagonals within the band of A. KU >= 0. 🎀

🍓 NRHS 🍓

NRHS is INTEGER. The number of right hand sides, i.e., the number of columns of the matrices B and X. NRHS >= 0. 💖

🍓 AB 🍓

AB is COMPLEX*16 array, dimension (LDAB,N). On entry, the matrix A in band storage, in rows 1 to KL+KU+1. The j-th column of A is stored in the j-th column of the array AB as follows: 🌀

AB(KU+1+i-j,j) = A(i,j) for max(1,j-KU)<=i<=min(N,j+kl)

If FACT = 'F' and EQUED is not 'N', then A must have been equilibrated by the scaling factors in R and/or C. AB is not modified if FACT = 'F' or 'N', or if FACT = 'E' and EQUED = 'N' on exit. 👑

On exit, if EQUED .ne. 'N', A is scaled as follows:

  • EQUED = 'R': A := diag(R) * A
  • EQUED = 'C': A := A * diag(C)
  • EQUED = 'B': A := diag(R) * A * diag(C).

🍓 LDAB 🍓

LDAB is INTEGER. The leading dimension of the array AB. LDAB >= KL+KU+1. ✨

🍓 AFB 🍓

AFB is COMPLEX*16 array, dimension (LDAFB,N). If FACT = 'F', then AFB is an input argument and on entry contains details of the LU factorization of the band matrix A, as computed by ZGBTRF. U is stored as an upper triangular band matrix with KL+KU superdiagonals in rows 1 to KL+KU+1, and the multipliers used during the factorization are stored in rows KL+KU+2 to 2*KL+KU+1. If EQUED .ne. 'N', then AFB is the factored form of the equilibrated matrix A. 💅

If FACT = 'N', then AFB is an output argument and on exit returns details of the LU factorization of A. 🌟

If FACT = 'E', then AFB is an output argument and on exit returns details of the LU factorization of the equilibrated matrix A (see the description of AB for the form of the equilibrated matrix). 🦋

🍓 LDAFB 🍓

LDAFB is INTEGER. The leading dimension of the array AFB. LDAFB >= 2*KL+KU+1. 🔥

🍓 IPIV 🍓

IPIV is INTEGER array, dimension (N). If FACT = 'F', then IPIV is an input argument and on entry contains the pivot indices from the factorization A = L*U as computed by ZGBTRF; row i of the matrix was interchanged with row IPIV(i). 👑

If FACT = 'N', then IPIV is an output argument and on exit contains the pivot indices from the factorization A = L*U of the original matrix A. 🌸

If FACT = 'E', then IPIV is an output argument and on exit contains the pivot indices from the factorization A = L*U of the equilibrated matrix A. 💖

🍓 EQUED 🍓

EQUED is CHARACTER*1. It specifies the form of equilibration that was done. 🌈

  • = 'N' — No equilibration (always true if FACT = 'N'). 💀
  • = 'R' — Row equilibration, i.e., A has been premultiplied by diag(R).
  • = 'C' — Column equilibration, i.e., A has been postmultiplied by diag(C).
  • = 'B' — Both row and column equilibration, i.e., A has been replaced by diag(R) * A * diag(C).

EQUED is an input argument if FACT = 'F'; otherwise, it is an output argument. 🫶

🍓 R 🍓

R is DOUBLE PRECISION array, dimension (N). The row scale factors for A. If EQUED = 'R' or 'B', A is multiplied on the left by diag(R); if EQUED = 'N' or 'C', R is not accessed. R is an input argument if FACT = 'F'; otherwise, R is an output argument. If FACT = 'F' and EQUED = 'R' or 'B', each element of R must be positive. ✨

🍓 C 🍓

C is DOUBLE PRECISION array, dimension (N). The column scale factors for A. If EQUED = 'C' or 'B', A is multiplied on the right by diag(C); if EQUED = 'N' or 'R', C is not accessed. C is an input argument if FACT = 'F'; otherwise, C is an output argument. If FACT = 'F' and EQUED = 'C' or 'B', each element of C must be positive. 💜

🍓 B 🍓

B is COMPLEX*16 array, dimension (LDB,NRHS). On entry, the right hand side matrix B. On exit, if EQUED = 'N', B is not modified; if TRANS = 'N' and EQUED = 'R' or 'B', B is overwritten by diag(R)*B; if TRANS = 'T' or 'C' and EQUED = 'C' or 'B', B is overwritten by diag(C)*B. 🌀

🍓 LDB 🍓

LDB is INTEGER. The leading dimension of the array B. LDB >= max(1,N). 🌟

🦋 X 🦋

  • X — a COMPLEX*16 array, dimension (LDX,NRHS). So if INFO = 0 or INFO = N+1, this is literally the N-by-NRHS solution matrix X for the original system of equations. 👑 But heads up bestie: A and B get modified on exit if EQUED .ne. 'N', and the solution to the equilibrated system is inv(diag(C))*X if TRANS = 'N' and EQUED = 'C' or 'B', or inv(diag(R))*X if TRANS = 'T' or 'C' and EQUED = 'R' or 'B'. No cap. 💅
  • LDX — an INTEGER. It's the leading dimension of the array X. Must be LDX >= max(1,N). Slay. ✨
  • RCOND — a DOUBLE PRECISION. It's the estimate of the reciprocal condition number of the matrix A after equilibration (if that happened). If RCOND is less than machine precision (especially if RCOND = 0), the matrix is singular to working precision — and that vibe is flagged by a return code of INFO > 0. 😭
  • FERR — a DOUBLE PRECISION array, dimension (NRHS). It's the estimated forward error bound for each solution vector X(j) (the j-th column of the solution matrix X). So if XTRUE is the true solution corresponding to X(j), then FERR(j) is an estimated upper bound for the magnitude of the largest element in (X(j) - XTRUE) divided by the magnitude of the largest element in X(j). The estimate is as reliable as the estimate for RCOND, and it's almost always a slight overestimate of the true error. Basically it's giving cautious math bestie. 🫶
  • BERR — a DOUBLE PRECISION array, dimension (NRHS). The componentwise relative backward error of each solution vector X(j) — i.e., the smallest relative change in any element of A or B that makes X(j) an exact solution. Lowkey iconic. 🔥
  • WORK — a COMPLEX*16 array, dimension (2*N). That's it, that's the whole vibe. 💜
  • RWORK — a DOUBLE PRECISION array, dimension (MAX(1,N)). On exit, RWORK(1) contains the reciprocal pivot growth factor norm(A)/norm(U). The norm is used. If RWORK(1) is much less than 1, then the stability of the LU factorization of the (equilibrated) matrix A could be poor — which also means the solution X, condition estimator RCOND, and forward error bound FERR could be unreliable. 😬 If factorization fails with 0<INFO<=N, then RWORK(1) contains the reciprocal pivot growth factor for the leading INFO columns of A. Noted. 📝
  • INFO — an INTEGER. Here's the breakdown:
    • = 0: successful exit. We love to see it. 🎉
    • < 0: if INFO = -i, the i-th argument had an illegal value. Rude. 🙈
    • > 0: if INFO = i, and i is:
      • <= N: U(i,i) is exactly zero. The factorization has been completed, but the factor U is exactly singular, so the solution and error bounds could not be computed. RCOND = 0 is returned. It's giving singular energy. 💀
      • = N+1: U is nonsingular, but RCOND is less than machine precision, meaning the matrix is singular to working precision. Nevertheless, the solution and error bounds are computed because there are a number of situations where the computed solution can be more accurate than the value of RCOND would suggest. Trust the process. 🌈

✨ Author ✨

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

Definition at line 367 of file zgbsvx.f. 📍

✨ Author (again) ✨

🎀 This page was generated automatically by Doxygen for LAPACK from the source code. 🎀

This iconic page is from LAPACK Version 3.12.0, path /home/abui...RC/zgbsvx.f(3), and it was auto-generated by Doxygen for LAPACK. Periodt. 💅✨

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