SRC/sgesvx.f(3)

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🎀 `SRC/sgesvx.f` 🎀

welcome to the Library Functions Manual bestie — this is the corner where we keep the Fortran heroes ✨

✨ NAME ✨

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 💅

🦋 Function/Subroutine Documentation 🦋

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 🔥

💜 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. yes bestie, it does the whole glow-up — solve it AND tell you how much you should trust it ✨

🧚 Description

The following steps are performed:

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').

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.

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. not it being like "bestie you're on thin ice but go off" 😭
The system of equations is solved for X using the factored form of A.
Iterative refinement is applied to improve the computed solution matrix and calculate error bounds and backward error estimates for it. ate and left no crumbs 💅
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 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`

TRANS is 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)

yes, 'T' and 'C' are both literally "Transpose" in the source — for real matrices that's the vibe, don't come for me 🫶

`N`

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

`A`

A is 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).

she gets a whole makeover on the way out, iconic 💖

`LDA`

LDA is INTEGER The leading dimension of the array A. LDA >= max(1,N).

`AF`

AF is 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`

LDAF is INTEGER The leading dimension of the array AF. LDAF >= max(1,N).

`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 = 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`

EQUED is 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. she switches roles depending on the situation — main character energy fr ✨

`R`

R is 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. positive, bestie — don't try it 🙈

`C`

C is 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`

B is 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`

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

`X`

X is 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'. the answer you actually wanted, after the whole detour 🦋

`LDX`

LDX is INTEGER The leading dimension of the array X. LDX >= max(1,N).

`RCOND`

RCOND is 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. translation: she's basically un-invertible, proceed with caution 💀

`FERR`

…and this is exactly where part 1 wraps — FERR onwards is coming in part 2, hold tight 🍓

FERR — REAL array, dimension (NRHS) ✨ The estimated forward error bound for each solution vector X(j) (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). The estimate is as reliable as the estimate for RCOND, and is almost always a slight overestimate of the true error. 💅

BERR — REAL 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). No cap, that's the vibe.

WORK — 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 (that's literally what it says, bestie 😭). 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. If factorization fails with 0<INFO<=N, then WORK(1) contains the reciprocal pivot growth factor for the leading INFO columns of A. 🦋

IWORK — INTEGER array, dimension (N) 🌸

INFO — INTEGER 👑

= 0: successful exit ✨
< 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. 💀
- = 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. 🔥

👑 Author

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

Definition at line 346 of file sgesvx.f. 🎀

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

And the cute little footer says LAPACK Version 3.12.0, source SRC/sgesvx.f(3) — no date on it, bestie, so don't @ me 😭. That's the whole page, periodt. 🫶🌈

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