SGESVX(3)

πŸ“¦ version 3.12.0, in opensuse-leap 16.0

Okay so this is SGESVX(3) from the Library Functions Manual, and the header is literally /home/abui...RC/sgesvx.f(3), then the manual name, then /home/abui...RC/sgesvx.f(3) again β€” a little header echo, we love that for us πŸ’…. The actual source file path is /home/abuild/rpmbuild/BUILD/lapack-static-3.12.0-build/lapack-3.12.0/SRC/sgesvx.f, bestie.

🌸 NAME

/home/abui...RC/sgesvx.f(3) β€” that's the name-ish path on this page. The source file is /home/abuild/rpmbuild/BUILD/lapack-static-3.12.0-build/lapack-3.12.0/SRC/sgesvx.f.

✨ SYNOPSIS ✨

🧚 Functions/Subroutines

subroutine SGESVX (fact, trans, n, nrhs, a, lda, af, ldaf, ipiv, equed,
    r, c, b, ldb, x, ldx, rcond, ferr, berr, work, iwork, info)

SGESVX computes the solution to system of linear equations A * X = B for GE matrices. No cap.

πŸ”₯ Function/Subroutine Documentation πŸ”₯

subroutine SGESVX (character fact, character trans, integer n, integer nrhs,
    real, dimension( lda, * ) a, integer lda, real, dimension( ldaf, * ) af,
    integer ldaf, integer, dimension( * ) ipiv, character equed, real,
    dimension( * ) r, real, dimension( * ) c, real, dimension( ldb, * ) b,
    integer ldb, real, dimension( ldx, * ) x, integer ldx, real rcond, real,
    dimension( * ) ferr, real, dimension( * ) berr, real, dimension( * )
    work, integer, dimension( * ) iwork, integer info)

SGESVX computes the solution to system of linear equations A * X = B for GE matrices.

πŸŽ€ Purpose

SGESVX uses the LU factorization to compute the solution to a real system of linear equations

A * X = B,

where A is an N-by-N matrix and X and B are N-by-NRHS matrices.

Error bounds on the solution and a condition estimate are also provided. Obsessed, honestly. πŸ’–

πŸ¦‹ Description

The following steps are performed:

  1. If FACT = 'E', real scaling factors are computed to equilibrate the system. The formulas are:
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 = P * L * U,

where P is a permutation matrix, L is a unit lower triangular matrix, and U is upper triangular.

  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. So, warning bestie, not a full stop. ⚠️
  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 β€” CHARACTER*1. 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, AF 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. A, AF, and IPIV are not modified.
    • = 'N': The matrix A will be copied to AF and factored.
    • = 'E': The matrix A will be equilibrated if necessary, then copied to AF and factored.
  • TRANS β€” CHARACTER*1. 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 (Transpose)
  • N β€” INTEGER. The number of linear equations, i.e., the order of the matrix A. N >= 0.
  • NRHS β€” INTEGER. The number of right hand sides, i.e., the number of columns of the matrices B and X. NRHS >= 0.
  • A β€” REAL array, dimension (LDA,N). On entry, the N-by-N matrix A. If FACT = 'F' and EQUED is not 'N', then A must have been equilibrated by the scaling factors in R and/or C. A 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)
  • LDA β€” INTEGER. The leading dimension of the array A. LDA >= max(1,N).
  • AF β€” REAL array, dimension (LDAF,N). If FACT = 'F', then AF is an input argument and on entry contains the factors L and U from the factorization A = P*L*U as computed by SGETRF. If EQUED .ne. 'N', then AF is the factored form of the equilibrated matrix A. If FACT = 'N', then AF is an output argument and on exit returns the factors L and U from the factorization A = P*L*U of the original matrix A. If FACT = 'E', then AF is an output argument and on exit returns the factors L and U from the factorization A = P*L*U of the equilibrated matrix A (see the description of A for the form of the equilibrated matrix).
  • LDAF β€” INTEGER. The leading dimension of the array AF. LDAF >= max(1,N).
  • IPIV β€” INTEGER array, dimension (N). If FACT = 'F', then IPIV is an input argument and on entry contains the pivot indices from the factorization A = P*L*U as computed by SGETRF; 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 = P*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 = P*L*U of the equilibrated matrix A.
  • EQUED β€” CHARACTER*1. 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 β€” REAL 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 β€” REAL 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 β€” REAL array, dimension (LDB,NRHS). On entry, the N-by-NRHS 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 β€” INTEGER. The leading dimension of the array B. LDB >= max(1,N).
  • X β€” REAL array, dimension (LDX,NRHS). If INFO = 0 or INFO = N+1, the N-by-NRHS solution matrix X to the original system of equations. Note that A and B are 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'.
  • LDX β€” INTEGER. The leading dimension of the array X. LDX >= max(1,N).
  • RCOND β€” REAL. The estimate of the reciprocal condition number of the matrix A after equilibration (if done). If RCOND is less than the machine precision (in particular, if RCOND = 0), the matrix is singular to working precision. This condition is indicated by a return code of INFO > 0.
  • FERR

Okay so we’re deep in the output-argument era now, and these are the little receipts SGESVX hands back after it does its thing. Stay with me, bestie β€” it’s all facts, just with better vibes. πŸ’…

πŸ’– FERR

FERR is a REAL array, dimension (NRHS). It’s the estimated forward error bound for each solution vector X(j) β€” aka the j-th column of the solution matrix X.

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). Math but make it fashion ✨

The estimate is as reliable as the estimate for RCOND, and is almost always a slight overestimate of the true error.

πŸ¦‹ BERR

BERR is a REAL array, dimension (NRHS). It’s the componentwise relative backward error of each solution vector X(j) β€” i.e., the smallest relative change in any element of A or B that makes X(j) an exact solution.

Backward error? More like backward bestie energy. 🫢

πŸŽ€ WORK

WORK is a REAL array, dimension (MAX(1,4*N)).

On exit, WORK(1) contains the reciprocal pivot growth factor norm(A)/norm(U). The norm is used.

If WORK(1) is much less than 1, then the stability of the LU factorization of the (equilibrated) matrix A could be poor. This also means that the solution X, condition estimator RCOND, and forward error bound FERR could be unreliable. Red-flag energy, ngl 🚩

If factorization fails with 0<INFO<=N, then WORK(1) contains the reciprocal pivot growth factor for the leading INFO columns of A.

🌸 IWORK

IWORK is an INTEGER array, dimension (N).

That’s it. That’s the whole vibe. πŸ’€

πŸ‘‘ INFO

INFO is an INTEGER. It’s basically the exit-status main character of this whole situation:

  • = 0: successful exit. We love a clean return. βœ…
  • < 0: if INFO = -i, the i-th argument had an illegal value.
  • > 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. Singular? Not the slay we wanted. 😭
    • = N+1: U is nonsingular, but RCOND is less than machine precision, meaning that 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. Plot twist: still computed. πŸŒ€

✨ Author

These are the credited legends:

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

Definition at line 346 of file sgesvx.f.

πŸ’… Author

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That’s the whole page, bestie β€” the footer is serving LAPACK Version 3.12.0 and the source path /home/abui...RC/sgesvx.f(3). Slay responsibly, and may all your factorizations be nonsingular. πŸ’–βœ¨

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