sgtsvx (l) - Linux Manuals
sgtsvx: uses the LU factorization to compute the solution to a real system of linear equations A * X = B or A**T * X = B,
NAME
SGTSVX - uses the LU factorization to compute the solution to a real system of linear equations A * X = B or A**T * X = B,SYNOPSIS
- SUBROUTINE SGTSVX(
- FACT, TRANS, N, NRHS, DL, D, DU, DLF, DF, DUF, DU2, IPIV, B, LDB, X, LDX, RCOND, FERR, BERR, WORK, IWORK, INFO )
- CHARACTER FACT, TRANS
- INTEGER INFO, LDB, LDX, N, NRHS
- REAL RCOND
- INTEGER IPIV( * ), IWORK( * )
- REAL B( LDB, * ), BERR( * ), D( * ), DF( * ), DL( * ), DLF( * ), DU( * ), DU2( * ), DUF( * ), FERR( * ), WORK( * ), X( LDX, * )
PURPOSE
SGTSVX uses the LU factorization to compute the solution to a real system of linear equations A * X = B or A**T * X = B, where A is a tridiagonal matrix of order N and X and B are N-by-NRHS matrices.Error bounds on the solution and a condition estimate are also provided.
DESCRIPTION
The following steps are performed:1. If FACT = aqNaq, the LU decomposition is used to factor the matrix A
as A
bidiagonal matrices and U is upper triangular with nonzeros in
only the main diagonal and first two superdiagonals.
2. If some U(i,i)=0, so that U is exactly singular, then the routine
returns with INFO
to estimate the condition number of the matrix A.
reciprocal of the condition number is less than machine precision,
INFO
to solve for X and compute error bounds as described below. 3. The system of equations is solved for X using the factored form
of A.
4. Iterative refinement is applied to improve the computed solution
matrix and calculate error bounds and backward error estimates
for it.
ARGUMENTS
- FACT (input) CHARACTER*1
- Specifies whether or not the factored form of A has been supplied on entry. = aqFaq: DLF, DF, DUF, DU2, and IPIV contain the factored form of A; DL, D, DU, DLF, DF, DUF, DU2 and IPIV will not be modified. = aqNaq: The matrix will be copied to DLF, DF, and DUF and factored.
- TRANS (input) CHARACTER*1
-
Specifies the form of the system of equations:
= aqNaq: A * X = B (No transpose)
= aqTaq: A**T * X = B (Transpose)
= aqCaq: A**H * X = B (Conjugate transpose = Transpose) - N (input) INTEGER
- The order of the matrix A. N >= 0.
- NRHS (input) INTEGER
- The number of right hand sides, i.e., the number of columns of the matrix B. NRHS >= 0.
- DL (input) REAL array, dimension (N-1)
- The (n-1) subdiagonal elements of A.
- D (input) REAL array, dimension (N)
- The n diagonal elements of A.
- DU (input) REAL array, dimension (N-1)
- The (n-1) superdiagonal elements of A.
- DLF (input or output) REAL array, dimension (N-1)
- If FACT = aqFaq, then DLF is an input argument and on entry contains the (n-1) multipliers that define the matrix L from the LU factorization of A as computed by SGTTRF. If FACT = aqNaq, then DLF is an output argument and on exit contains the (n-1) multipliers that define the matrix L from the LU factorization of A.
- DF (input or output) REAL array, dimension (N)
- If FACT = aqFaq, then DF is an input argument and on entry contains the n diagonal elements of the upper triangular matrix U from the LU factorization of A. If FACT = aqNaq, then DF is an output argument and on exit contains the n diagonal elements of the upper triangular matrix U from the LU factorization of A.
- DUF (input or output) REAL array, dimension (N-1)
- If FACT = aqFaq, then DUF is an input argument and on entry contains the (n-1) elements of the first superdiagonal of U. If FACT = aqNaq, then DUF is an output argument and on exit contains the (n-1) elements of the first superdiagonal of U.
- DU2 (input or output) REAL array, dimension (N-2)
- If FACT = aqFaq, then DU2 is an input argument and on entry contains the (n-2) elements of the second superdiagonal of U. If FACT = aqNaq, then DU2 is an output argument and on exit contains the (n-2) elements of the second superdiagonal of U.
- IPIV (input or output) INTEGER array, dimension (N)
- If FACT = aqFaq, then IPIV is an input argument and on entry contains the pivot indices from the LU factorization of A as computed by SGTTRF. If FACT = aqNaq, then IPIV is an output argument and on exit contains the pivot indices from the LU factorization of A; row i of the matrix was interchanged with row IPIV(i). IPIV(i) will always be either i or i+1; IPIV(i) = i indicates a row interchange was not required.
- B (input) REAL array, dimension (LDB,NRHS)
- The N-by-NRHS right hand side matrix B.
- LDB (input) INTEGER
- The leading dimension of the array B. LDB >= max(1,N).
- X (output) REAL array, dimension (LDX,NRHS)
- If INFO = 0 or INFO = N+1, the N-by-NRHS solution matrix X.
- LDX (input) INTEGER
- The leading dimension of the array X. LDX >= max(1,N).
- RCOND (output) REAL
- The estimate of the reciprocal condition number of the matrix A. 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 (output) 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), 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 (output) 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).
- WORK (workspace) REAL array, dimension (3*N)
- IWORK (workspace) INTEGER array, dimension (N)
- INFO (output) 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 not been completed unless i = N, 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.