Solves a real symmetric positive definite system of linear equations given the factorization of the coefficient matrix in band symmetric storage mode.
FACT — NCODA + 1 by N array containing the RT R factorization of the positive definite band matrix A in band symmetric storage mode as output from subroutine LFCQS/DLFCQS or LFTQS/DLFTQS. (Input)
NCODA — Number of upper codiagonals of A. (Input)
B — Vector of length N containing the right-hand side of the linear system. (Input)
X — Vector of length N containing the
solution to the linear system. (Output)
If B is not needed, B and X an share the same
storage locations.
N — Number of equations.
(Input)
Default: N = size (FACT,2).
LDFACT — Leading dimension of FACT exactly as
specified in the dimension statement of the calling program.
(Input)
Default: LDFACT = size (FACT,1).
Generic: CALL LFSQS (FACT, NCODA, B, X [,…])
Specific: The specific interface names are S_LFSQS and D_LFSQS.
Single: CALL LFSQS (N, FACT, LDFACT, NCODA, B, X)
Double: The double precision name is DLFSQS.
Routine LFSQS computes the solution for a system of linear algebraic equations having a real symmetric positive definite band coefficient matrix. To compute the solution, the coefficient matrix must first undergo an RT R factorization. This may be done by calling either LFCQS or LFTQS. R is an upper triangular band matrix.
The solution to Ax = b is found by solving the triangular systems RTy = b and Rx = y.
LFSQS and LFIQS both solve a linear system given its RT R factorization. LFIQS generally takes more time and produces a more accurate answer than LFSQS. Each iteration of the iterative refinement algorithm used by LFIQS calls LFSQS.
LFSQS is based on the LINPACK routine SPBSL; see Dongarra et al. (1979).
Informational error
Type Code
4 1 The factored matrix is singular.
A set of linear systems is solved successively. LFTQS is called to factor the coefficient matrix. LFSQS is called to compute the four solutions for the four right-hand sides. In this case the coefficient matrix is assumed to be well-conditioned and correctly scaled. Otherwise, it would be better to call LFCQS to perform the factorization, and LFIQS to compute the solutions.
USE
LFSQS_INT
USE
LFTQS_INT
USE WRRRN_INT
! Declare variables
INTEGER LDA, LDFACT, N, NCODA
PARAMETER (LDA=3, LDFACT=3, N=4, NCODA=2)
REAL A(LDA,N), B(N,4), FACT(LDFACT,N), X(N,4)
!
!
! Set values for A in band symmetric form, and B
!
! A = ( 0.0 0.0 -1.0 1.0 )
! ( 0.0 0.0 2.0 -1.0 )
! ( 2.0 4.0 7.0 3.0 )
!
! B = ( 4.0 -3.0 9.0 -1.0 )
! ( 6.0 10.0 29.0 3.0 )
! ( 15.0 12.0 11.0 6.0 )
! ( -7.0 1.0 14.0 2.0 )
!
DATA A/2*0.0, 2.0, 2*0.0, 4.0, -1.0, 2.0, 7.0, 1.0, -1.0, 3.0/
DATA B/4.0, 6.0, 15.0, -7.0, -3.0, 10.0, 12.0, 1.0, 9.0, 29.0,&
11.0, 14.0, -1.0, 3.0, 6.0, 2.0/
! Factor the matrix A
CALL LFTQS (A, NCODA, FACT)
! Compute the solutions
DO 10 I=1, 4
CALL LFSQS (FACT, NCODA, B(:,I), X(:,I))
10 CONTINUE
! Print solutions
CALL WRRRN ('X', X)
!
END
X
1 2
3 4
1 3.000
-1.000 5.000 0.000
2 1.000
2.000 6.000 0.000
3 2.000
1.000 1.000 1.000
4 -2.000
0.000 3.000 1.000
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