dynare/mex/sources/libslicot/MB04MD.f

291 lines
8.4 KiB
Fortran

SUBROUTINE MB04MD( N, MAXRED, A, LDA, SCALE, INFO )
C
C SLICOT RELEASE 5.0.
C
C Copyright (c) 2002-2009 NICONET e.V.
C
C This program is free software: you can redistribute it and/or
C modify it under the terms of the GNU General Public License as
C published by the Free Software Foundation, either version 2 of
C the License, or (at your option) any later version.
C
C This program is distributed in the hope that it will be useful,
C but WITHOUT ANY WARRANTY; without even the implied warranty of
C MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
C GNU General Public License for more details.
C
C You should have received a copy of the GNU General Public License
C along with this program. If not, see
C <http://www.gnu.org/licenses/>.
C
C PURPOSE
C
C To reduce the 1-norm of a general real matrix A by balancing.
C This involves diagonal similarity transformations applied
C iteratively to A to make the rows and columns as close in norm as
C possible.
C
C This routine can be used instead LAPACK Library routine DGEBAL,
C when no reduction of the 1-norm of the matrix is possible with
C DGEBAL, as for upper triangular matrices. LAPACK Library routine
C DGEBAK, with parameters ILO = 1, IHI = N, and JOB = 'S', should
C be used to apply the backward transformation.
C
C ARGUMENTS
C
C Input/Output Parameters
C
C N (input) INTEGER
C The order of the matrix A. N >= 0.
C
C MAXRED (input/output) DOUBLE PRECISION
C On entry, the maximum allowed reduction in the 1-norm of
C A (in an iteration) if zero rows or columns are
C encountered.
C If MAXRED > 0.0, MAXRED must be larger than one (to enable
C the norm reduction).
C If MAXRED <= 0.0, then the value 10.0 for MAXRED is
C used.
C On exit, if the 1-norm of the given matrix A is non-zero,
C the ratio between the 1-norm of the given matrix and the
C 1-norm of the balanced matrix. Usually, this ratio will be
C larger than one, but it can sometimes be one, or even less
C than one (for instance, for some companion matrices).
C
C A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
C On entry, the leading N-by-N part of this array must
C contain the input matrix A.
C On exit, the leading N-by-N part of this array contains
C the balanced matrix.
C
C LDA INTEGER
C The leading dimension of the array A. LDA >= max(1,N).
C
C SCALE (output) DOUBLE PRECISION array, dimension (N)
C The scaling factors applied to A. If D(j) is the scaling
C factor applied to row and column j, then SCALE(j) = D(j),
C for j = 1,...,N.
C
C Error Indicator
C
C INFO INTEGER
C = 0: successful exit.
C < 0: if INFO = -i, the i-th argument had an illegal
C value.
C
C METHOD
C
C Balancing consists of applying a diagonal similarity
C transformation inv(D) * A * D to make the 1-norms of each row
C of A and its corresponding column nearly equal.
C
C Information about the diagonal matrix D is returned in the vector
C SCALE.
C
C REFERENCES
C
C [1] Anderson, E., Bai, Z., Bischof, C., Demmel, J., Dongarra, J.,
C Du Croz, J., Greenbaum, A., Hammarling, S., McKenney, A.,
C Ostrouchov, S., and Sorensen, D.
C LAPACK Users' Guide: Second Edition.
C SIAM, Philadelphia, 1995.
C
C NUMERICAL ASPECTS
C
C None.
C
C CONTRIBUTOR
C
C Release 3.0: V. Sima, Katholieke Univ. Leuven, Belgium, June 1997.
C Supersedes Release 2.0 routine MB04AD by T.W.C. Williams,
C Kingston Polytechnic, United Kingdom, October 1984.
C This subroutine is based on LAPACK routine DGEBAL, and routine
C BALABC (A. Varga, German Aerospace Research Establishment, DLR).
C
C
C REVISIONS
C
C -
C
C KEYWORDS
C
C Balancing, eigenvalue, matrix algebra, matrix operations,
C similarity transformation.
C
C *********************************************************************
C
C .. Parameters ..
DOUBLE PRECISION ZERO, ONE
PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 )
DOUBLE PRECISION SCLFAC
PARAMETER ( SCLFAC = 1.0D+1 )
DOUBLE PRECISION FACTOR, MAXR
PARAMETER ( FACTOR = 0.95D+0, MAXR = 10.0D+0 )
C ..
C .. Scalar Arguments ..
INTEGER INFO, LDA, N
DOUBLE PRECISION MAXRED
C ..
C .. Array Arguments ..
DOUBLE PRECISION A( LDA, * ), SCALE( * )
C ..
C .. Local Scalars ..
LOGICAL NOCONV
INTEGER I, ICA, IRA, J
DOUBLE PRECISION ANORM, C, CA, F, G, MAXNRM, R, RA, S, SFMAX1,
$ SFMAX2, SFMIN1, SFMIN2, SRED
C ..
C .. External Functions ..
INTEGER IDAMAX
DOUBLE PRECISION DLAMCH, DLANGE
EXTERNAL DLAMCH, DLANGE, IDAMAX
C ..
C .. External Subroutines ..
EXTERNAL DSCAL, XERBLA
C ..
C .. Intrinsic Functions ..
INTRINSIC ABS, MAX, MIN
C ..
C .. Executable Statements ..
C
C Test the scalar input arguments.
C
INFO = 0
C
IF( N.LT.0 ) THEN
INFO = -1
ELSE IF( MAXRED.GT.ZERO .AND. MAXRED.LT.ONE ) THEN
INFO = -2
ELSE IF( LDA.LT.MAX( 1, N ) ) THEN
INFO = -4
END IF
IF( INFO.NE.0 ) THEN
CALL XERBLA( 'MB04MD', -INFO )
RETURN
END IF
C
IF( N.EQ.0 )
$ RETURN
C
DO 10 I = 1, N
SCALE( I ) = ONE
10 CONTINUE
C
C Compute the 1-norm of matrix A and exit if it is zero.
C
ANORM = DLANGE( '1-norm', N, N, A, LDA, SCALE )
IF( ANORM.EQ.ZERO )
$ RETURN
C
C Set some machine parameters and the maximum reduction in the
C 1-norm of A if zero rows or columns are encountered.
C
SFMIN1 = DLAMCH( 'S' ) / DLAMCH( 'P' )
SFMAX1 = ONE / SFMIN1
SFMIN2 = SFMIN1*SCLFAC
SFMAX2 = ONE / SFMIN2
C
SRED = MAXRED
IF( SRED.LE.ZERO ) SRED = MAXR
C
MAXNRM = MAX( ANORM/SRED, SFMIN1 )
C
C Balance the matrix.
C
C Iterative loop for norm reduction.
C
20 CONTINUE
NOCONV = .FALSE.
C
DO 80 I = 1, N
C = ZERO
R = ZERO
C
DO 30 J = 1, N
IF( J.EQ.I )
$ GO TO 30
C = C + ABS( A( J, I ) )
R = R + ABS( A( I, J ) )
30 CONTINUE
ICA = IDAMAX( N, A( 1, I ), 1 )
CA = ABS( A( ICA, I ) )
IRA = IDAMAX( N, A( I, 1 ), LDA )
RA = ABS( A( I, IRA ) )
C
C Special case of zero C and/or R.
C
IF( C.EQ.ZERO .AND. R.EQ.ZERO )
$ GO TO 80
IF( C.EQ.ZERO ) THEN
IF( R.LE.MAXNRM)
$ GO TO 80
C = MAXNRM
END IF
IF( R.EQ.ZERO ) THEN
IF( C.LE.MAXNRM )
$ GO TO 80
R = MAXNRM
END IF
C
C Guard against zero C or R due to underflow.
C
G = R / SCLFAC
F = ONE
S = C + R
40 CONTINUE
IF( C.GE.G .OR. MAX( F, C, CA ).GE.SFMAX2 .OR.
$ MIN( R, G, RA ).LE.SFMIN2 )GO TO 50
F = F*SCLFAC
C = C*SCLFAC
CA = CA*SCLFAC
R = R / SCLFAC
G = G / SCLFAC
RA = RA / SCLFAC
GO TO 40
C
50 CONTINUE
G = C / SCLFAC
60 CONTINUE
IF( G.LT.R .OR. MAX( R, RA ).GE.SFMAX2 .OR.
$ MIN( F, C, G, CA ).LE.SFMIN2 )GO TO 70
F = F / SCLFAC
C = C / SCLFAC
G = G / SCLFAC
CA = CA / SCLFAC
R = R*SCLFAC
RA = RA*SCLFAC
GO TO 60
C
C Now balance.
C
70 CONTINUE
IF( ( C+R ).GE.FACTOR*S )
$ GO TO 80
IF( F.LT.ONE .AND. SCALE( I ).LT.ONE ) THEN
IF( F*SCALE( I ).LE.SFMIN1 )
$ GO TO 80
END IF
IF( F.GT.ONE .AND. SCALE( I ).GT.ONE ) THEN
IF( SCALE( I ).GE.SFMAX1 / F )
$ GO TO 80
END IF
G = ONE / F
SCALE( I ) = SCALE( I )*F
NOCONV = .TRUE.
C
CALL DSCAL( N, G, A( I, 1 ), LDA )
CALL DSCAL( N, F, A( 1, I ), 1 )
C
80 CONTINUE
C
IF( NOCONV )
$ GO TO 20
C
C Set the norm reduction parameter.
C
MAXRED = ANORM/DLANGE( '1-norm', N, N, A, LDA, SCALE )
C
RETURN
C *** End of MB04MD ***
END