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template<typename T>
T la_porpvgrw(char *uplo, integer *ncols, T *a, integer *lda, T *af, integer *ldaf, T *work)# LA_PORPVGRW computes the reciprocal pivot growth factor norm(A)/norm(U) for a symmetric or Hermitian positive-definite matrix.
Purpose:
LA_PORPVGRW computes the reciprocal pivot growth factor norm(A)/norm(U). The "max absolute element" norm is used. If this is much less than 1, the stability of the LU factorization of the (equilibrated) matrix A could be poor. This also means that the solution X, estimated condition numbers, and error bounds could be unreliable.
- Parameters:
UPLO – [in]
UPLO is CHARACTER*1
= ‘U’: Upper triangle of A is stored;
= ‘L’: Lower triangle of A is stored.NCOLS – [in]
NCOLS is INTEGER
The number of columns of the matrix A. NCOLS >= 0.
A – [in]
A is REAL array, dimension (LDA,N)
On entry, the N-by-N matrix A.
LDA – [in]
LDA is INTEGER
The leading dimension of the array A. LDA >= fla_max(1,N).
AF – [in]
AF is REAL array, dimension (LDAF,N)
The triangular factor U or L from the Cholesky factorization A = U**T*U or A = L*L**T, as computed by SPOTRF.
LDAF – [in]
LDAF is INTEGER
The leading dimension of the array AF. LDAF >= fla_max(1,N).
WORK – [out] WORK is REAL array, dimension (2*N)