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SUBROUTINE IB01PY( METH, JOB, NOBR, N, M, L, RANKR1, UL, LDUL,
$ R1, LDR1, TAU1, PGAL, LDPGAL, K, LDK, R, LDR,
$ H, LDH, B, LDB, D, LDD, TOL, IWORK, DWORK,
$ LDWORK, IWARN, INFO )
C
C PURPOSE
C
C 1. To compute the triangular (QR) factor of the p-by-L*s
C structured matrix Q,
C
C [ Q_1s Q_1,s-1 Q_1,s-2 ... Q_12 Q_11 ]
C [ 0 Q_1s Q_1,s-1 ... Q_13 Q_12 ]
C Q = [ 0 0 Q_1s ... Q_14 Q_13 ],
C [ : : : : : ]
C [ 0 0 0 ... 0 Q_1s ]
C
C and apply the transformations to the p-by-m matrix Kexpand,
C
C [ K_1 ]
C [ K_2 ]
C Kexpand = [ K_3 ],
C [ : ]
C [ K_s ]
C
C where, for MOESP approach (METH = 'M'), p = s*(L*s-n), and
C Q_1i = u2(L*(i-1)+1:L*i,:)' is (Ls-n)-by-L, for i = 1:s,
C u2 = Un(1:L*s,n+1:L*s), K_i = K(:,(i-1)*m+1:i*m) (i = 1:s)
C is (Ls-n)-by-m, and for N4SID approach (METH = 'N'), p = s*(n+L),
C and
C
C [ -L_1|1 ] [ M_i-1 - L_1|i ]
C Q_11 = [ ], Q_1i = [ ], i = 2:s,
C [ I_L - L_2|1 ] [ -L_2|i ]
C
C are (n+L)-by-L matrices, and
C K_i = K(:,(i-1)*m+1:i*m), i = 1:s, is (n+L)-by-m.
C The given matrices are:
C For METH = 'M', u2 = Un(1:L*s,n+1:L*s),
C K(1:Ls-n,1:m*s);
C
C [ L_1|1 ... L_1|s ]
C For METH = 'N', L = [ ], (n+L)-by-L*s,
C [ L_2|1 ... L_2|s ]
C
C M = [ M_1 ... M_s-1 ], n-by-L*(s-1), and
C K, (n+L)-by-m*s.
C Matrix M is the pseudoinverse of the matrix GaL,
C built from the first n relevant singular
C vectors, GaL = Un(1:L(s-1),1:n), and computed
C by SLICOT Library routine IB01PD for METH = 'N'.
C
C Matrix Q is triangularized (in R), exploiting its structure,
C and the transformations are applied from the left to Kexpand.
C
C 2. To estimate the matrices B and D of a linear time-invariant
C (LTI) state space model, using the factor R, transformed matrix
C Kexpand, and the singular value decomposition information provided
C by other routines.
C
C IB01PY routine is intended for speed and efficient use of the
C memory space. It is generally not recommended for METH = 'N', as
C IB01PX routine can produce more accurate results.
C
C ARGUMENTS
C
C Mode Parameters
C
C METH CHARACTER*1
C Specifies the subspace identification method to be used,
C as follows:
C = 'M': MOESP algorithm with past inputs and outputs;
C = 'N': N4SID algorithm.
C
C JOB CHARACTER*1
C Specifies whether or not the matrices B and D should be
C computed, as follows:
C = 'B': compute the matrix B, but not the matrix D;
C = 'D': compute both matrices B and D;
C = 'N': do not compute the matrices B and D, but only the
C R factor of Q and the transformed Kexpand.
C
C Input/Output Parameters
C
C NOBR (input) INTEGER
C The number of block rows, s, in the input and output
C Hankel matrices processed by other routines. NOBR > 1.
C
C N (input) INTEGER
C The order of the system. NOBR > N > 0.
C
C M (input) INTEGER
C The number of system inputs. M >= 0.
C
C L (input) INTEGER
C The number of system outputs. L > 0.
C
C RANKR1 (input) INTEGER
C The effective rank of the upper triangular matrix r1,
C i.e., the triangular QR factor of the matrix GaL,
C computed by SLICOT Library routine IB01PD. It is also
C the effective rank of the matrix GaL. 0 <= RANKR1 <= N.
C If JOB = 'N', or M = 0, or METH = 'N', this
C parameter is not used.
C
C UL (input/workspace) DOUBLE PRECISION array, dimension
C ( LDUL,L*NOBR )
C On entry, if METH = 'M', the leading L*NOBR-by-L*NOBR
C part of this array must contain the matrix Un of
C relevant singular vectors. The first N columns of UN
C need not be specified for this routine.
C On entry, if METH = 'N', the leading (N+L)-by-L*NOBR
C part of this array must contain the given matrix L.
C On exit, the leading LDF-by-L*(NOBR-1) part of this array
C is overwritten by the matrix F of the algorithm in [4],
C where LDF = MAX( 1, L*NOBR-N-L ), if METH = 'M';
C LDF = N, if METH = 'N'.
C
C LDUL INTEGER
C The leading dimension of the array UL.
C LDUL >= L*NOBR, if METH = 'M';
C LDUL >= N+L, if METH = 'N'.
C
C R1 (input) DOUBLE PRECISION array, dimension ( LDR1,N )
C If JOB <> 'N', M > 0, METH = 'M', and RANKR1 = N,
C the leading L*(NOBR-1)-by-N part of this array must
C contain details of the QR factorization of the matrix
C GaL, as computed by SLICOT Library routine IB01PD.
C Specifically, the leading N-by-N upper triangular part
C must contain the upper triangular factor r1 of GaL,
C and the lower L*(NOBR-1)-by-N trapezoidal part, together
C with array TAU1, must contain the factored form of the
C orthogonal matrix Q1 in the QR factorization of GaL.
C If JOB = 'N', or M = 0, or METH = 'N', or METH = 'M'
C and RANKR1 < N, this array is not referenced.
C
C LDR1 INTEGER
C The leading dimension of the array R1.
C LDR1 >= L*(NOBR-1), if JOB <> 'N', M > 0, METH = 'M',
C and RANKR1 = N;
C LDR1 >= 1, otherwise.
C
C TAU1 (input) DOUBLE PRECISION array, dimension ( N )
C If JOB <> 'N', M > 0, METH = 'M', and RANKR1 = N,
C this array must contain the scalar factors of the
C elementary reflectors used in the QR factorization of the
C matrix GaL, computed by SLICOT Library routine IB01PD.
C If JOB = 'N', or M = 0, or METH = 'N', or METH = 'M'
C and RANKR1 < N, this array is not referenced.
C
C PGAL (input) DOUBLE PRECISION array, dimension
C ( LDPGAL,L*(NOBR-1) )
C If METH = 'N', or JOB <> 'N', M > 0, METH = 'M' and
C RANKR1 < N, the leading N-by-L*(NOBR-1) part of this
C array must contain the pseudoinverse of the matrix GaL,
C as computed by SLICOT Library routine IB01PD.
C If METH = 'M' and JOB = 'N', or M = 0, or
C RANKR1 = N, this array is not referenced.
C
C LDPGAL INTEGER
C The leading dimension of the array PGAL.
C LDPGAL >= N, if METH = 'N', or JOB <> 'N', M > 0,
C and METH = 'M' and RANKR1 < N;
C LDPGAL >= 1, otherwise.
C
C K (input/output) DOUBLE PRECISION array, dimension
C ( LDK,M*NOBR )
C On entry, the leading (p/s)-by-M*NOBR part of this array
C must contain the given matrix K defined above.
C On exit, the leading (p/s)-by-M*NOBR part of this array
C contains the transformed matrix K.
C
C LDK INTEGER
C The leading dimension of the array K. LDK >= p/s.
C
C R (output) DOUBLE PRECISION array, dimension ( LDR,L*NOBR )
C If JOB = 'N', or M = 0, or Q has full rank, the
C leading L*NOBR-by-L*NOBR upper triangular part of this
C array contains the R factor of the QR factorization of
C the matrix Q.
C If JOB <> 'N', M > 0, and Q has not a full rank, the
C leading L*NOBR-by-L*NOBR upper trapezoidal part of this
C array contains details of the complete orhogonal
C factorization of the matrix Q, as constructed by SLICOT
C Library routines MB03OD and MB02QY.
C
C LDR INTEGER
C The leading dimension of the array R. LDR >= L*NOBR.
C
C H (output) DOUBLE PRECISION array, dimension ( LDH,M )
C If JOB = 'N' or M = 0, the leading L*NOBR-by-M part
C of this array contains the updated part of the matrix
C Kexpand corresponding to the upper triangular factor R
C in the QR factorization of the matrix Q.
C If JOB <> 'N', M > 0, and METH = 'N' or METH = 'M'
C and RANKR1 < N, the leading L*NOBR-by-M part of this
C array contains the minimum norm least squares solution of
C the linear system Q*X = Kexpand, from which the matrices
C B and D are found. The first NOBR-1 row blocks of X
C appear in the reverse order in H.
C If JOB <> 'N', M > 0, METH = 'M' and RANKR1 = N, the
C leading L*(NOBR-1)-by-M part of this array contains the
C matrix product Q1'*X, and the subarray
C L*(NOBR-1)+1:L*NOBR-by-M contains the corresponding
C submatrix of X, with X defined in the phrase above.
C
C LDH INTEGER
C The leading dimension of the array H. LDH >= L*NOBR.
C
C B (output) DOUBLE PRECISION array, dimension ( LDB,M )
C If M > 0, JOB = 'B' or 'D' and INFO = 0, the leading
C N-by-M part of this array contains the system input
C matrix.
C If M = 0 or JOB = 'N', this array is not referenced.
C
C LDB INTEGER
C The leading dimension of the array B.
C LDB >= N, if M > 0 and JOB = 'B' or 'D';
C LDB >= 1, if M = 0 or JOB = 'N'.
C
C D (output) DOUBLE PRECISION array, dimension ( LDD,M )
C If M > 0, JOB = 'D' and INFO = 0, the leading
C L-by-M part of this array contains the system input-output
C matrix.
C If M = 0 or JOB = 'B' or 'N', this array is not
C referenced.
C
C LDD INTEGER
C The leading dimension of the array D.
C LDD >= L, if M > 0 and JOB = 'D';
C LDD >= 1, if M = 0 or JOB = 'B' or 'N'.
C
C Tolerances
C
C TOL DOUBLE PRECISION
C The tolerance to be used for estimating the rank of
C matrices. If the user sets TOL > 0, then the given value
C of TOL is used as a lower bound for the reciprocal
C condition number; an m-by-n matrix whose estimated
C condition number is less than 1/TOL is considered to
C be of full rank. If the user sets TOL <= 0, then an
C implicitly computed, default tolerance, defined by
C TOLDEF = m*n*EPS, is used instead, where EPS is the
C relative machine precision (see LAPACK Library routine
C DLAMCH).
C This parameter is not used if M = 0 or JOB = 'N'.
C
C Workspace
C
C IWORK INTEGER array, dimension ( LIWORK )
C where LIWORK >= 0, if JOB = 'N', or M = 0;
C LIWORK >= L*NOBR, if JOB <> 'N', and M > 0.
C
C DWORK DOUBLE PRECISION array, dimension ( LDWORK )
C On exit, if INFO = 0, DWORK(1) returns the optimal value
C of LDWORK, and, if JOB <> 'N', and M > 0, DWORK(2)
C contains the reciprocal condition number of the triangular
C factor of the matrix R.
C On exit, if INFO = -28, DWORK(1) returns the minimum
C value of LDWORK.
C
C LDWORK INTEGER
C The length of the array DWORK.
C LDWORK >= MAX( 2*L, L*NOBR, L+M*NOBR ),
C if JOB = 'N', or M = 0;
C LDWORK >= MAX( L+M*NOBR, L*NOBR + MAX( 3*L*NOBR+1, M ) ),
C if JOB <> 'N', and M > 0.
C For good performance, LDWORK should be larger.
C
C Warning Indicator
C
C IWARN INTEGER
C = 0: no warning;
C = 4: the least squares problem to be solved has a
C rank-deficient coefficient matrix.
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 = 3: a singular upper triangular matrix was found.
C
C METHOD
C
C The QR factorization is computed exploiting the structure,
C as described in [4].
C The matrices B and D are then obtained by solving certain
C linear systems in a least squares sense.
C
C REFERENCES
C
C [1] Verhaegen M., and Dewilde, P.
C Subspace Model Identification. Part 1: The output-error
C state-space model identification class of algorithms.
C Int. J. Control, 56, pp. 1187-1210, 1992.
C
C [2] Van Overschee, P., and De Moor, B.
C N4SID: Two Subspace Algorithms for the Identification
C of Combined Deterministic-Stochastic Systems.
C Automatica, Vol.30, No.1, pp. 75-93, 1994.
C
C [3] Van Overschee, P.
C Subspace Identification : Theory - Implementation -
C Applications.
C Ph. D. Thesis, Department of Electrical Engineering,
C Katholieke Universiteit Leuven, Belgium, Feb. 1995.
C
C [4] Sima, V.
C Subspace-based Algorithms for Multivariable System
C Identification.
C Studies in Informatics and Control, 5, pp. 335-344, 1996.
C
C NUMERICAL ASPECTS
C
C The implemented method for computing the triangular factor and
C updating Kexpand is numerically stable.
C
C FURTHER COMMENTS
C
C The computed matrices B and D are not the least squares solutions
C delivered by either MOESP or N4SID algorithms, except for the
C special case n = s - 1, L = 1. However, the computed B and D are
C frequently good enough estimates, especially for METH = 'M'.
C Better estimates could be obtained by calling SLICOT Library
C routine IB01PX, but it is less efficient, and requires much more
C workspace.
C
C CONTRIBUTOR
C
C V. Sima, Research Institute for Informatics, Bucharest, Oct. 1999.
C
C REVISIONS
C
C Feb. 2000, Sep. 2001, March 2005.
C
C KEYWORDS
C
C Identification methods; least squares solutions; multivariable
C systems; QR decomposition; singular value decomposition.
C
C ******************************************************************
C
C .. Parameters ..
DOUBLE PRECISION ZERO, ONE, TWO, THREE
PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0, TWO = 2.0D0,
$ THREE = 3.0D0 )
C .. Scalar Arguments ..
DOUBLE PRECISION TOL
INTEGER INFO, IWARN, L, LDB, LDD, LDH, LDK, LDPGAL,
$ LDR, LDR1, LDUL, LDWORK, M, N, NOBR, RANKR1
CHARACTER JOB, METH
C .. Array Arguments ..
DOUBLE PRECISION B(LDB, *), D(LDD, *), DWORK(*), H(LDH, *),
$ K(LDK, *), PGAL(LDPGAL, *), R(LDR, *),
$ R1(LDR1, *), TAU1(*), UL(LDUL, *)
INTEGER IWORK( * )
C .. Local Scalars ..
DOUBLE PRECISION EPS, RCOND, SVLMAX, THRESH, TOLL
INTEGER I, IERR, ITAU, J, JI, JL, JM, JWORK, LDUN2,
$ LNOBR, LP1, MAXWRK, MINWRK, MNOBR, NOBRH,
$ NROW, NROWML, RANK
LOGICAL MOESP, N4SID, WITHB, WITHD
C .. Local Array ..
DOUBLE PRECISION SVAL(3)
C .. External Functions ..
LOGICAL LSAME
INTEGER ILAENV
DOUBLE PRECISION DLAMCH
EXTERNAL DLAMCH, ILAENV, LSAME
C .. External Subroutines ..
EXTERNAL DGEMM, DGEQRF, DLACPY, DLASET, DORMQR, DSWAP,
$ DTRCON, DTRSM, DTRTRS, MA02AD, MB02QY, MB03OD,
$ MB04OD, MB04OY, XERBLA
C .. Intrinsic Functions ..
INTRINSIC INT, MAX, MOD
C .. Executable Statements ..
C
C Decode the scalar input parameters.
C
MOESP = LSAME( METH, 'M' )
N4SID = LSAME( METH, 'N' )
WITHD = LSAME( JOB, 'D' )
WITHB = LSAME( JOB, 'B' ) .OR. WITHD
MNOBR = M*NOBR
LNOBR = L*NOBR
LDUN2 = LNOBR - L
LP1 = L + 1
IF ( MOESP ) THEN
NROW = LNOBR - N
ELSE
NROW = N + L
END IF
NROWML = NROW - L
IWARN = 0
INFO = 0
C
C Check the scalar input parameters.
C
IF( .NOT.( MOESP .OR. N4SID ) ) THEN
INFO = -1
ELSE IF( .NOT.( WITHB .OR. LSAME( JOB, 'N' ) ) ) THEN
INFO = -2
ELSE IF( NOBR.LE.1 ) THEN
INFO = -3
ELSE IF( N.GE.NOBR .OR. N.LE.0 ) THEN
INFO = -4
ELSE IF( M.LT.0 ) THEN
INFO = -5
ELSE IF( L.LE.0 ) THEN
INFO = -6
ELSE IF( ( MOESP .AND. WITHB .AND. M.GT.0 ) .AND.
$ ( RANKR1.LT.ZERO .OR. RANKR1.GT.N ) ) THEN
INFO = -7
ELSE IF( ( MOESP .AND. LDUL.LT.LNOBR ) .OR.
$ ( N4SID .AND. LDUL.LT.NROW ) ) THEN
INFO = -9
ELSE IF( LDR1.LT.1 .OR. ( M.GT.0 .AND. WITHB .AND. MOESP .AND.
$ LDR1.LT.LDUN2 .AND. RANKR1.EQ.N ) ) THEN
INFO = -11
ELSE IF( LDPGAL.LT.1 .OR.
$ ( LDPGAL.LT.N .AND. ( N4SID .OR. ( WITHB .AND. M.GT.0
$ .AND. ( MOESP .AND. RANKR1.LT.N ) ) ) ) )
$ THEN
INFO = -14
ELSE IF( LDK.LT.NROW ) THEN
INFO = -16
ELSE IF( LDR.LT.LNOBR ) THEN
INFO = -18
ELSE IF( LDH.LT.LNOBR ) THEN
INFO = -20
ELSE IF( LDB.LT.1 .OR. ( M.GT.0 .AND. WITHB .AND. LDB.LT.N ) )
$ THEN
INFO = -22
ELSE IF( LDD.LT.1 .OR. ( M.GT.0 .AND. WITHD .AND. LDD.LT.L ) )
$ THEN
INFO = -24
ELSE
C
C Compute workspace.
C (Note: Comments in the code beginning "Workspace:" describe the
C minimal amount of workspace needed at that point in the code,
C as well as the preferred amount for good performance.
C NB refers to the optimal block size for the immediately
C following subroutine, as returned by ILAENV.)
C
MINWRK = MAX( 2*L, LNOBR, L + MNOBR )
MAXWRK = MINWRK
MAXWRK = MAX( MAXWRK, L + L*ILAENV( 1, 'DGEQRF', ' ', NROW, L,
$ -1, -1 ) )
MAXWRK = MAX( MAXWRK, L + LDUN2*ILAENV( 1, 'DORMQR', 'LT',
$ NROW, LDUN2, L, -1 ) )
MAXWRK = MAX( MAXWRK, L + MNOBR*ILAENV( 1, 'DORMQR', 'LT',
$ NROW, MNOBR, L, -1 ) )
C
IF( M.GT.0 .AND. WITHB ) THEN
MINWRK = MAX( MINWRK, 4*LNOBR+1, LNOBR + M )
MAXWRK = MAX( MINWRK, MAXWRK, LNOBR +
$ M*ILAENV( 1, 'DORMQR', 'LT', LNOBR, M, LNOBR,
$ -1 ) )
END IF
C
IF ( LDWORK.LT.MINWRK ) THEN
INFO = -28
DWORK( 1 ) = MINWRK
END IF
END IF
C
C Return if there are illegal arguments.
C
IF( INFO.NE.0 ) THEN
CALL XERBLA( 'IB01PY', -INFO )
RETURN
END IF
C
C Construct in R the first block-row of Q, i.e., the
C (p/s)-by-L*s matrix [ Q_1s ... Q_12 Q_11 ], where
C Q_1i, defined above, is (p/s)-by-L, for i = 1:s.
C
IF ( MOESP ) THEN
C
DO 10 I = 1, NOBR
CALL MA02AD( 'Full', L, NROW, UL(L*(I-1)+1,N+1), LDUL,
$ R(1,L*(NOBR-I)+1), LDR )
10 CONTINUE
C
ELSE
JL = LNOBR
JM = LDUN2
C
DO 50 JI = 1, LDUN2, L
C
DO 40 J = JI + L - 1, JI, -1
C
DO 20 I = 1, N
R(I,J) = PGAL(I,JM) - UL(I,JL)
20 CONTINUE
C
DO 30 I = N + 1, NROW
R(I,J) = -UL(I,JL)
30 CONTINUE
C
JL = JL - 1
JM = JM - 1
40 CONTINUE
C
50 CONTINUE
C
DO 70 J = LNOBR, LDUN2 + 1, -1
C
DO 60 I = 1, NROW
R(I,J) = -UL(I,JL)
60 CONTINUE
C
JL = JL - 1
R(N+J-LDUN2,J) = ONE + R(N+J-LDUN2,J)
70 CONTINUE
END IF
C
C Triangularize the submatrix Q_1s using an orthogonal matrix S.
C Workspace: need 2*L, prefer L+L*NB.
C
ITAU = 1
JWORK = ITAU + L
C
CALL DGEQRF( NROW, L, R, LDR, DWORK(ITAU), DWORK(JWORK),
$ LDWORK-JWORK+1, IERR )
C
C Apply the transformation S' to the matrix
C [ Q_1,s-1 ... Q_11 ]. Therefore,
C
C [ R P_s-1 P_s-2 ... P_2 P_1 ]
C S'[ Q_1,s ... Q_11 ] = [ ].
C [ 0 F_s-1 F_s-2 ... F_2 F_1 ]
C
C Workspace: need L*NOBR, prefer L+(L*NOBR-L)*NB.
C
CALL DORMQR( 'Left', 'Transpose', NROW, LDUN2, L, R, LDR,
$ DWORK(ITAU), R(1,LP1), LDR, DWORK(JWORK),
$ LDWORK-JWORK+1, IERR )
C
C Apply the transformation S' to each of the submatrices K_i of
C Kexpand = [ K_1' K_2' ... K_s' ]', K_i = K(:,(i-1)*m+1:i*m)
C (i = 1:s) being (p/s)-by-m. Denote ( H_i' G_i' )' = S'K_i
C (i = 1:s), where H_i has L rows.
C Finally, H_i is saved in H(L*(i-1)+1:L*i,1:m), i = 1:s.
C (G_i is in K(L+1:p/s,(i-1)*m+1:i*m), i = 1:s.)
C Workspace: need L+M*NOBR, prefer L+M*NOBR*NB.
C
CALL DORMQR( 'Left', 'Transpose', NROW, MNOBR, L, R, LDR,
$ DWORK(ITAU), K, LDK, DWORK(JWORK), LDWORK-JWORK+1,
$ IERR )
C
C Put the rows to be annihilated (matrix F) in UL(1:p/s-L,1:L*s-L).
C
CALL DLACPY( 'Full', NROWML, LDUN2, R(LP1,LP1), LDR, UL, LDUL )
C
C Now, the structure of the transformed matrices is:
C
C [ R P_s-1 P_s-2 ... P_2 P_1 ] [ H_1 ]
C [ 0 R P_s-1 ... P_3 P_2 ] [ H_2 ]
C [ 0 0 R ... P_4 P_3 ] [ H_3 ]
C [ : : : : : ] [ : ]
C [ 0 0 0 ... R P_s-1 ] [ H_s-1 ]
C Q = [ 0 0 0 ... 0 R ], Kexpand = [ H_s ],
C [ 0 F_s-1 F_s-2 ... F_2 F_1 ] [ G_1 ]
C [ 0 0 F_s-1 ... F_3 F_2 ] [ G_2 ]
C [ : : : : : ] [ : ]
C [ 0 0 0 ... 0 F_s-1 ] [ G_s-1 ]
C [ 0 0 0 ... 0 0 ] [ G_s ]
C
C where the block-rows have been permuted, to better exploit the
C structure. The block-rows having R on the diagonal are dealt
C with successively in the array R.
C The F submatrices are stored in the array UL, as a block-row.
C
C Copy H_1 in H(1:L,1:m).
C
CALL DLACPY( 'Full', L, M, K, LDK, H, LDH )
C
C Triangularize the transformed matrix exploiting its structure.
C Workspace: need L+MAX(L-1,L*NOBR-2*L,M*(NOBR-1)).
C
DO 90 I = 1, NOBR - 1
C
C Copy part of the preceding block-row and then annihilate the
C current submatrix F_s-i using an orthogonal matrix modifying
C the corresponding submatrix R. Simultaneously, apply the
C transformation to the corresponding block-rows of the matrices
C R and F.
C
CALL DLACPY( 'Upper', L, LNOBR-L*I, R(L*(I-1)+1,L*(I-1)+1),
$ LDR, R(L*I+1,L*I+1), LDR )
CALL MB04OD( 'Full', L, LNOBR-L*(I+1), NROWML, R(L*I+1,L*I+1),
$ LDR, UL(1,L*(I-1)+1), LDUL, R(L*I+1,L*(I+1)+1),
$ LDR, UL(1,L*I+1), LDUL, DWORK(ITAU), DWORK(JWORK)
$ )
C
C Apply the transformation to the corresponding block-rows of
C the matrix G and copy H_(i+1) in H(L*i+1:L*(i+1),1:m).
C
DO 80 J = 1, L
CALL MB04OY( NROWML, M*(NOBR-I), UL(1,L*(I-1)+J), DWORK(J),
$ K(J,M*I+1), LDK, K(LP1,1), LDK, DWORK(JWORK) )
80 CONTINUE
C
CALL DLACPY( 'Full', L, M, K(1,M*I+1), LDK, H(L*I+1,1), LDH )
90 CONTINUE
C
C Return if only the factorization is needed.
C
IF( M.EQ.0 .OR. .NOT.WITHB ) THEN
DWORK(1) = MAXWRK
RETURN
END IF
C
C Set the precision parameters. A threshold value EPS**(2/3) is
C used for deciding to use pivoting or not, where EPS is the
C relative machine precision (see LAPACK Library routine DLAMCH).
C
EPS = DLAMCH( 'Precision' )
THRESH = EPS**( TWO/THREE )
TOLL = TOL
IF( TOLL.LE.ZERO )
$ TOLL = LNOBR*LNOBR*EPS
SVLMAX = ZERO
C
C Compute the reciprocal of the condition number of the triangular
C factor R of Q.
C Workspace: need 3*L*NOBR.
C
CALL DTRCON( '1-norm', 'Upper', 'NonUnit', LNOBR, R, LDR, RCOND,
$ DWORK, IWORK, IERR )
C
IF ( RCOND.GT.MAX( TOLL, THRESH ) ) THEN
C
C The triangular factor R is considered to be of full rank.
C Solve for X, R*X = H.
C
CALL DTRSM( 'Left', 'Upper', 'NoTranspose', 'Non-unit',
$ LNOBR, M, ONE, R, LDR, H, LDH )
ELSE
C
C Rank-deficient triangular factor R. Compute the
C minimum-norm least squares solution of R*X = H using
C the complete orthogonal factorization of R.
C
DO 100 I = 1, LNOBR
IWORK(I) = 0
100 CONTINUE
C
C Workspace: need 4*L*NOBR+1;
C prefer 3*L*NOBR+(L*NOBR+1)*NB.
C
JWORK = ITAU + LNOBR
CALL DLASET( 'Lower', LNOBR-1, LNOBR, ZERO, ZERO, R(2,1), LDR )
CALL MB03OD( 'QR', LNOBR, LNOBR, R, LDR, IWORK, TOLL, SVLMAX,
$ DWORK(ITAU), RANK, SVAL, DWORK(JWORK),
$ LDWORK-JWORK+1, IERR )
MAXWRK = MAX( MAXWRK, INT( DWORK(JWORK) ) + JWORK - 1 )
C
C Workspace: need L*NOBR+M; prefer L*NOBR+M*NB.
C
CALL DORMQR( 'Left', 'Transpose', LNOBR, M, LNOBR, R, LDR,
$ DWORK(ITAU), H, LDH, DWORK(JWORK), LDWORK-JWORK+1,
$ IERR )
IF ( RANK.LT.LNOBR ) THEN
C
C The least squares problem is rank-deficient.
C
IWARN = 4
END IF
C
C Workspace: need L*NOBR+max(L*NOBR,M); prefer larger.
C
CALL MB02QY( LNOBR, LNOBR, M, RANK, R, LDR, IWORK, H, LDH,
$ DWORK(ITAU), DWORK(JWORK), LDWORK-JWORK+1, IERR )
MAXWRK = MAX( MAXWRK, INT( DWORK(JWORK) ) + JWORK - 1 )
END IF
C
C Construct the matrix D, if needed.
C
IF ( WITHD )
$ CALL DLACPY( 'Full', L, M, H(LDUN2+1,1), LDH, D, LDD )
C
C Compute B by solving another linear system (possibly in
C a least squares sense).
C
C Make a block-permutation of the rows of the right-hand side, H,
C to construct the matrix
C
C [ H(L*(s-2)+1:L*(s-1),:); ... H(L+1:L*2,:); H(1:L),:) ]
C
C in H(1:L*s-L,1:n).
C
NOBRH = NOBR/2 + MOD( NOBR, 2 ) - 1
C
DO 120 J = 1, M
C
DO 110 I = 1, NOBRH
CALL DSWAP( L, H(L*(I-1)+1,J), 1, H(L*(NOBR-I-1)+1,J), 1 )
110 CONTINUE
C
120 CONTINUE
C
C Solve for B the matrix equation GaL*B = H(1:L*s-L,:), using
C the available QR factorization of GaL, if METH = 'M' and
C rank(GaL) = n, or the available pseudoinverse of GaL, otherwise.
C
IF ( MOESP .AND. RANKR1.EQ.N ) THEN
C
C The triangular factor r1 of GaL is considered to be of
C full rank. Compute Q1'*H in H and then solve for B,
C r1*B = H(1:n,:) in B, where Q1 is the orthogonal matrix
C in the QR factorization of GaL.
C Workspace: need M; prefer M*NB.
C
CALL DORMQR( 'Left', 'Transpose', LDUN2, M, N, R1, LDR1,
$ TAU1, H, LDH, DWORK, LDWORK, IERR )
MAXWRK = MAX( MAXWRK, INT( DWORK(1) ) )
C
C Compute the solution in B.
C
CALL DLACPY( 'Full', N, M, H, LDH, B, LDB )
C
CALL DTRTRS( 'Upper', 'NoTranspose', 'NonUnit', N, M, R1, LDR1,
$ B, LDB, IERR )
IF ( IERR.GT.0 ) THEN
INFO = 3
RETURN
END IF
ELSE
C
C Rank-deficient triangular factor r1. Use the available
C pseudoinverse of GaL for computing B from GaL*B = H.
C
CALL DGEMM ( 'NoTranspose', 'NoTranspose', N, M, LDUN2, ONE,
$ PGAL, LDPGAL, H, LDH, ZERO, B, LDB )
END IF
C
C Return optimal workspace in DWORK(1) and reciprocal condition
C number in DWORK(2).
C
DWORK(1) = MAXWRK
DWORK(2) = RCOND
C
RETURN
C
C *** Last line of IB01PY ***
END