SRC/cgbequ.f(3)

✨ SRC/cgbequ.f ✨

okay so bestie, welcome to the glow-up era of SRC/cgbequ.f β€” this is the LAPACK page for cgbequ, and it's genuinely one of those little routines that quietly does the most. πŸ’…


πŸŽ€ SYNOPSIS πŸŽ€

Functions/Subroutines

  • subroutine cgbequ (m, n, kl, ku, ab, ldab, r, c, rowcnd, colcnd, amax, info) β€” the vibe check of the whole page, this is CGBEQU herself πŸ‘‘

πŸ’– Function/Subroutine Documentation πŸ’–

πŸ¦‹ subroutine cgbequ (integer m, integer n, integer kl, integer ku, complex, dimension( ldab, * ) ab, integer ldab, real, dimension( * ) r, real, dimension( * ) c, real rowcnd, real colcnd, real amax, integer info)

CGBEQU


🌸 Purpose

!>
!> CGBEQU computes row and column scalings intended to equilibrate an
!> M-by-N band matrix A and reduce its condition number.  R returns the
!> row scale factors and C the column scale factors, chosen to try to
!> make the largest element in each row and column of the matrix B with
!> elements B(i,j)=R(i)*A(i,j)*C(j) have absolute value 1.
!>
!> R(i) and C(j) are restricted to be between SMLNUM = smallest safe
!> number and BIGNUM = largest safe number.  Use of these scaling
!> factors is not guaranteed to reduce the condition number of A but
!> works well in practice.
!>

so like, CGBEQU is out here computing row and column scalings to equilibrate an M-by-N band matrix A and bring its condition number down. R comes back with the row scale factors, C with the column scale factors β€” picked so the biggest element in each row and column of the matrix B (that's the one where B(i,j)=R(i)*A(i,j)*C(j), keep up bestie) has absolute value 1. iconic behaviour tbh. 🫢

R(i) and C(j) are locked between SMLNUM = smallest safe number and BIGNUM = largest safe number. and real talk, using these scaling factors is not guaranteed to reduce the condition number of A, but it works well in practice β€” no cap, that's straight from the page. πŸ’―


πŸ’œ Parameters

  • M β€” is INTEGER. The number of rows of the matrix A. M >= 0. πŸ“
  • N β€” is INTEGER. The number of columns of the matrix A. N >= 0.
  • KL β€” is INTEGER. The number of subdiagonals within the band of A. KL >= 0. (the down-bad diagonals ✨)
  • KU β€” is INTEGER. The number of superdiagonals within the band of A. KU >= 0. (the up-and-over diagonals πŸ¦‹)
  • AB β€” is COMPLEX array, dimension (LDAB,N). The band matrix A, stored in rows 1 to KL+KU+1. The j-th column of A is stored in the j-th column of the array AB like this:
AB(ku+1+i-j,j) = A(i,j) for max(1,j-ku)<=i<=min(m,j+kl).
  • LDAB β€” is INTEGER. The leading dimension of the array AB. LDAB >= KL+KU+1. πŸ‘‘
  • R β€” is REAL array, dimension (M). If INFO = 0, or INFO > M, R contains the row scale factors for A. 🌈
  • C β€” is REAL array, dimension (N). If INFO = 0, C contains the column scale factors for A. ⭐
  • ROWCND β€” is REAL. If INFO = 0 or INFO > M, ROWCND contains the ratio of the smallest R(i) to the largest R(i). If ROWCND >= 0.1 and AMAX is neither too large nor too small, it is not worth scaling by R. πŸ’€
  • COLCND β€” is REAL. If INFO = 0, COLCND contains the ratio of the smallest C(i) to the largest C(i). If COLCND >= 0.1, it is not worth scaling by C.
  • AMAX β€” is REAL. Absolute value of largest matrix element. If AMAX is very close to overflow or very close to underflow, the matrix should be scaled. πŸ”₯
  • INFO β€” is INTEGER:
    • = 0: successful exit πŸŽ‰
    • < 0: if INFO = -i, the i-th argument had an illegal value πŸ™ˆ
    • > 0: if INFO = i, and i is
      • <= M: the i-th row of A is exactly zero
      • > M: the (i-M)-th column of A is exactly zero
lowkey important: those zero row / zero column situations are real and they come back to you in INFO, so don't sleep on checking it. 😭

🧚 Author

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

Definition at line 152 of file cgbequ.f. πŸ“


πŸ“ Author

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LAPACK Version 3.12.0 β€” that's the whole mood, mwah, ily, go equilibrate something πŸ’–πŸŽ€πŸ¦‹βœ¨

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