.TH "la_porpvgrw" 3 "Wed Feb 7 2024 11:30:40" "Version 3.12.0" "LAPACK" \" -*- nroff -*- .ad l .nh .SH NAME la_porpvgrw \- la_porpvgrw: reciprocal pivot growth .SH SYNOPSIS .br .PP .SS "Functions" .in +1c .ti -1c .RI "real function \fBcla_porpvgrw\fP (uplo, ncols, a, lda, af, ldaf, work)" .br .RI "\fBCLA_PORPVGRW\fP computes the reciprocal pivot growth factor norm(A)/norm(U) for a symmetric or Hermitian positive-definite matrix\&. " .ti -1c .RI "double precision function \fBdla_porpvgrw\fP (uplo, ncols, a, lda, af, ldaf, work)" .br .RI "\fBDLA_PORPVGRW\fP computes the reciprocal pivot growth factor norm(A)/norm(U) for a symmetric or Hermitian positive-definite matrix\&. " .ti -1c .RI "real function \fBsla_porpvgrw\fP (uplo, ncols, a, lda, af, ldaf, work)" .br .RI "\fBSLA_PORPVGRW\fP computes the reciprocal pivot growth factor norm(A)/norm(U) for a symmetric or Hermitian positive-definite matrix\&. " .ti -1c .RI "double precision function \fBzla_porpvgrw\fP (uplo, ncols, a, lda, af, ldaf, work)" .br .RI "\fBZLA_PORPVGRW\fP computes the reciprocal pivot growth factor norm(A)/norm(U) for a symmetric or Hermitian positive-definite matrix\&. " .in -1c .SH "Detailed Description" .PP .SH "Function Documentation" .PP .SS "real function cla_porpvgrw (character*1 uplo, integer ncols, complex, dimension( lda, * ) a, integer lda, complex, dimension( ldaf, * ) af, integer ldaf, real, dimension( * ) work)" .PP \fBCLA_PORPVGRW\fP computes the reciprocal pivot growth factor norm(A)/norm(U) for a symmetric or Hermitian positive-definite matrix\&. .PP \fBPurpose:\fP .RS 4 .PP .nf CLA_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\&. .fi .PP .RE .PP \fBParameters\fP .RS 4 \fIUPLO\fP .PP .nf UPLO is CHARACTER*1 = 'U': Upper triangle of A is stored; = 'L': Lower triangle of A is stored\&. .fi .PP .br \fINCOLS\fP .PP .nf NCOLS is INTEGER The number of columns of the matrix A\&. NCOLS >= 0\&. .fi .PP .br \fIA\fP .PP .nf A is COMPLEX array, dimension (LDA,N) On entry, the N-by-N matrix A\&. .fi .PP .br \fILDA\fP .PP .nf LDA is INTEGER The leading dimension of the array A\&. LDA >= max(1,N)\&. .fi .PP .br \fIAF\fP .PP .nf AF is COMPLEX 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 CPOTRF\&. .fi .PP .br \fILDAF\fP .PP .nf LDAF is INTEGER The leading dimension of the array AF\&. LDAF >= max(1,N)\&. .fi .PP .br \fIWORK\fP .PP .nf WORK is REAL array, dimension (2*N) .fi .PP .RE .PP \fBAuthor\fP .RS 4 Univ\&. of Tennessee .PP Univ\&. of California Berkeley .PP Univ\&. of Colorado Denver .PP NAG Ltd\&. .RE .PP .SS "double precision function dla_porpvgrw (character*1 uplo, integer ncols, double precision, dimension( lda, * ) a, integer lda, double precision, dimension( ldaf, * ) af, integer ldaf, double precision, dimension( * ) work)" .PP \fBDLA_PORPVGRW\fP computes the reciprocal pivot growth factor norm(A)/norm(U) for a symmetric or Hermitian positive-definite matrix\&. .PP \fBPurpose:\fP .RS 4 .PP .nf DLA_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\&. .fi .PP .RE .PP \fBParameters\fP .RS 4 \fIUPLO\fP .PP .nf UPLO is CHARACTER*1 = 'U': Upper triangle of A is stored; = 'L': Lower triangle of A is stored\&. .fi .PP .br \fINCOLS\fP .PP .nf NCOLS is INTEGER The number of columns of the matrix A\&. NCOLS >= 0\&. .fi .PP .br \fIA\fP .PP .nf A is DOUBLE PRECISION array, dimension (LDA,N) On entry, the N-by-N matrix A\&. .fi .PP .br \fILDA\fP .PP .nf LDA is INTEGER The leading dimension of the array A\&. LDA >= max(1,N)\&. .fi .PP .br \fIAF\fP .PP .nf AF is DOUBLE PRECISION 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 DPOTRF\&. .fi .PP .br \fILDAF\fP .PP .nf LDAF is INTEGER The leading dimension of the array AF\&. LDAF >= max(1,N)\&. .fi .PP .br \fIWORK\fP .PP .nf WORK is DOUBLE PRECISION array, dimension (2*N) .fi .PP .RE .PP \fBAuthor\fP .RS 4 Univ\&. of Tennessee .PP Univ\&. of California Berkeley .PP Univ\&. of Colorado Denver .PP NAG Ltd\&. .RE .PP .SS "real function sla_porpvgrw (character*1 uplo, integer ncols, real, dimension( lda, * ) a, integer lda, real, dimension( ldaf, * ) af, integer ldaf, real, dimension( * ) work)" .PP \fBSLA_PORPVGRW\fP computes the reciprocal pivot growth factor norm(A)/norm(U) for a symmetric or Hermitian positive-definite matrix\&. .PP \fBPurpose:\fP .RS 4 .PP .nf SLA_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\&. .fi .PP .RE .PP \fBParameters\fP .RS 4 \fIUPLO\fP .PP .nf UPLO is CHARACTER*1 = 'U': Upper triangle of A is stored; = 'L': Lower triangle of A is stored\&. .fi .PP .br \fINCOLS\fP .PP .nf NCOLS is INTEGER The number of columns of the matrix A\&. NCOLS >= 0\&. .fi .PP .br \fIA\fP .PP .nf A is REAL array, dimension (LDA,N) On entry, the N-by-N matrix A\&. .fi .PP .br \fILDA\fP .PP .nf LDA is INTEGER The leading dimension of the array A\&. LDA >= max(1,N)\&. .fi .PP .br \fIAF\fP .PP .nf 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\&. .fi .PP .br \fILDAF\fP .PP .nf LDAF is INTEGER The leading dimension of the array AF\&. LDAF >= max(1,N)\&. .fi .PP .br \fIWORK\fP .PP .nf WORK is REAL array, dimension (2*N) .fi .PP .RE .PP \fBAuthor\fP .RS 4 Univ\&. of Tennessee .PP Univ\&. of California Berkeley .PP Univ\&. of Colorado Denver .PP NAG Ltd\&. .RE .PP .SS "double precision function zla_porpvgrw (character*1 uplo, integer ncols, complex*16, dimension( lda, * ) a, integer lda, complex*16, dimension( ldaf, * ) af, integer ldaf, double precision, dimension( * ) work)" .PP \fBZLA_PORPVGRW\fP computes the reciprocal pivot growth factor norm(A)/norm(U) for a symmetric or Hermitian positive-definite matrix\&. .PP \fBPurpose:\fP .RS 4 .PP .nf ZLA_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\&. .fi .PP .RE .PP \fBParameters\fP .RS 4 \fIUPLO\fP .PP .nf UPLO is CHARACTER*1 = 'U': Upper triangle of A is stored; = 'L': Lower triangle of A is stored\&. .fi .PP .br \fINCOLS\fP .PP .nf NCOLS is INTEGER The number of columns of the matrix A\&. NCOLS >= 0\&. .fi .PP .br \fIA\fP .PP .nf A is COMPLEX*16 array, dimension (LDA,N) On entry, the N-by-N matrix A\&. .fi .PP .br \fILDA\fP .PP .nf LDA is INTEGER The leading dimension of the array A\&. LDA >= max(1,N)\&. .fi .PP .br \fIAF\fP .PP .nf AF is COMPLEX*16 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 ZPOTRF\&. .fi .PP .br \fILDAF\fP .PP .nf LDAF is INTEGER The leading dimension of the array AF\&. LDAF >= max(1,N)\&. .fi .PP .br \fIWORK\fP .PP .nf WORK is DOUBLE PRECISION array, dimension (2*N) .fi .PP .RE .PP \fBAuthor\fP .RS 4 Univ\&. of Tennessee .PP Univ\&. of California Berkeley .PP Univ\&. of Colorado Denver .PP NAG Ltd\&. .RE .PP .SH "Author" .PP Generated automatically by Doxygen for LAPACK from the source code\&.