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SUBROUTINE IB01MD( METH, ALG, BATCH, CONCT, NOBR, M, L, NSMP, U,
$ LDU, Y, LDY, R, LDR, IWORK, DWORK, LDWORK,
$ IWARN, 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 construct an upper triangular factor R of the concatenated
C block Hankel matrices using input-output data. The input-output
C data can, optionally, be processed sequentially.
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 ALG CHARACTER*1
C Specifies the algorithm for computing the triangular
C factor R, as follows:
C = 'C': Cholesky algorithm applied to the correlation
C matrix of the input-output data;
C = 'F': Fast QR algorithm;
C = 'Q': QR algorithm applied to the concatenated block
C Hankel matrices.
C
C BATCH CHARACTER*1
C Specifies whether or not sequential data processing is to
C be used, and, for sequential processing, whether or not
C the current data block is the first block, an intermediate
C block, or the last block, as follows:
C = 'F': the first block in sequential data processing;
C = 'I': an intermediate block in sequential data
C processing;
C = 'L': the last block in sequential data processing;
C = 'O': one block only (non-sequential data processing).
C NOTE that when 100 cycles of sequential data processing
C are completed for BATCH = 'I', a warning is
C issued, to prevent for an infinite loop.
C
C CONCT CHARACTER*1
C Specifies whether or not the successive data blocks in
C sequential data processing belong to a single experiment,
C as follows:
C = 'C': the current data block is a continuation of the
C previous data block and/or it will be continued
C by the next data block;
C = 'N': there is no connection between the current data
C block and the previous and/or the next ones.
C This parameter is not used if BATCH = 'O'.
C
C Input/Output Parameters
C
C NOBR (input) INTEGER
C The number of block rows, s, in the input and output
C block Hankel matrices to be processed. NOBR > 0.
C (In the MOESP theory, NOBR should be larger than n,
C the estimated dimension of state vector.)
C
C M (input) INTEGER
C The number of system inputs. M >= 0.
C When M = 0, no system inputs are processed.
C
C L (input) INTEGER
C The number of system outputs. L > 0.
C
C NSMP (input) INTEGER
C The number of rows of matrices U and Y (number of
C samples, t). (When sequential data processing is used,
C NSMP is the number of samples of the current data
C block.)
C NSMP >= 2*(M+L+1)*NOBR - 1, for non-sequential
C processing;
C NSMP >= 2*NOBR, for sequential processing.
C The total number of samples when calling the routine with
C BATCH = 'L' should be at least 2*(M+L+1)*NOBR - 1.
C The NSMP argument may vary from a cycle to another in
C sequential data processing, but NOBR, M, and L should
C be kept constant. For efficiency, it is advisable to use
C NSMP as large as possible.
C
C U (input) DOUBLE PRECISION array, dimension (LDU,M)
C The leading NSMP-by-M part of this array must contain the
C t-by-m input-data sequence matrix U,
C U = [u_1 u_2 ... u_m]. Column j of U contains the
C NSMP values of the j-th input component for consecutive
C time increments.
C If M = 0, this array is not referenced.
C
C LDU INTEGER
C The leading dimension of the array U.
C LDU >= NSMP, if M > 0;
C LDU >= 1, if M = 0.
C
C Y (input) DOUBLE PRECISION array, dimension (LDY,L)
C The leading NSMP-by-L part of this array must contain the
C t-by-l output-data sequence matrix Y,
C Y = [y_1 y_2 ... y_l]. Column j of Y contains the
C NSMP values of the j-th output component for consecutive
C time increments.
C
C LDY INTEGER
C The leading dimension of the array Y. LDY >= NSMP.
C
C R (output or input/output) DOUBLE PRECISION array, dimension
C ( LDR,2*(M+L)*NOBR )
C On exit, if INFO = 0 and ALG = 'Q', or (ALG = 'C' or 'F',
C and BATCH = 'L' or 'O'), the leading
C 2*(M+L)*NOBR-by-2*(M+L)*NOBR upper triangular part of
C this array contains the (current) upper triangular factor
C R from the QR factorization of the concatenated block
C Hankel matrices. The diagonal elements of R are positive
C when the Cholesky algorithm was successfully used.
C On exit, if ALG = 'C' and BATCH = 'F' or 'I', the leading
C 2*(M+L)*NOBR-by-2*(M+L)*NOBR upper triangular part of this
C array contains the current upper triangular part of the
C correlation matrix in sequential data processing.
C If ALG = 'F' and BATCH = 'F' or 'I', the array R is not
C referenced.
C On entry, if ALG = 'C', or ALG = 'Q', and BATCH = 'I' or
C 'L', the leading 2*(M+L)*NOBR-by-2*(M+L)*NOBR upper
C triangular part of this array must contain the upper
C triangular matrix R computed at the previous call of this
C routine in sequential data processing. The array R need
C not be set on entry if ALG = 'F' or if BATCH = 'F' or 'O'.
C
C LDR INTEGER
C The leading dimension of the array R.
C LDR >= 2*(M+L)*NOBR.
C
C Workspace
C
C IWORK INTEGER array, dimension (LIWORK)
C LIWORK >= M+L, if ALG = 'F';
C LIWORK >= 0, if ALG = 'C' or 'Q'.
C
C DWORK DOUBLE PRECISION array, dimension (LDWORK)
C On exit, if INFO = 0, DWORK(1) returns the optimal
C value of LDWORK.
C On exit, if INFO = -17, DWORK(1) returns the minimum
C value of LDWORK.
C Let
C k = 0, if CONCT = 'N' and ALG = 'C' or 'Q';
C k = 2*NOBR-1, if CONCT = 'C' and ALG = 'C' or 'Q';
C k = 2*NOBR*(M+L+1), if CONCT = 'N' and ALG = 'F';
C k = 2*NOBR*(M+L+2), if CONCT = 'C' and ALG = 'F'.
C The first (M+L)*k elements of DWORK should be preserved
C during successive calls of the routine with BATCH = 'F'
C or 'I', till the final call with BATCH = 'L'.
C
C LDWORK INTEGER
C The length of the array DWORK.
C LDWORK >= (4*NOBR-2)*(M+L), if ALG = 'C', BATCH <> 'O' and
C CONCT = 'C';
C LDWORK >= 1, if ALG = 'C', BATCH = 'O' or
C CONCT = 'N';
C LDWORK >= (M+L)*2*NOBR*(M+L+3), if ALG = 'F',
C BATCH <> 'O' and CONCT = 'C';
C LDWORK >= (M+L)*2*NOBR*(M+L+1), if ALG = 'F',
C BATCH = 'F', 'I' and CONCT = 'N';
C LDWORK >= (M+L)*4*NOBR*(M+L+1)+(M+L)*2*NOBR, if ALG = 'F',
C BATCH = 'L' and CONCT = 'N', or
C BATCH = 'O';
C LDWORK >= 4*(M+L)*NOBR, if ALG = 'Q', BATCH = 'F' or 'O',
C and LDR >= NS = NSMP - 2*NOBR + 1;
C LDWORK >= 6*(M+L)*NOBR, if ALG = 'Q', BATCH = 'F' or 'O',
C and LDR < NS, or BATCH = 'I' or
C 'L' and CONCT = 'N';
C LDWORK >= 4*(NOBR+1)*(M+L)*NOBR, if ALG = 'Q', BATCH = 'I'
C or 'L' and CONCT = 'C'.
C The workspace used for ALG = 'Q' is
C LDRWRK*2*(M+L)*NOBR + 4*(M+L)*NOBR,
C where LDRWRK = LDWORK/(2*(M+L)*NOBR) - 2; recommended
C value LDRWRK = NS, assuming a large enough cache size.
C For good performance, LDWORK should be larger.
C
C Warning Indicator
C
C IWARN INTEGER
C = 0: no warning;
C = 1: the number of 100 cycles in sequential data
C processing has been exhausted without signaling
C that the last block of data was get; the cycle
C counter was reinitialized;
C = 2: a fast algorithm was requested (ALG = 'C' or 'F'),
C but it failed, and the QR algorithm was then used
C (non-sequential data processing).
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 = 1: a fast algorithm was requested (ALG = 'C', or 'F')
C in sequential data processing, but it failed. The
C routine can be repeatedly called again using the
C standard QR algorithm.
C
C METHOD
C
C 1) For non-sequential data processing using QR algorithm, a
C t x 2(m+l)s matrix H is constructed, where
C
C H = [ Uf' Up' Y' ], for METH = 'M',
C s+1,2s,t 1,s,t 1,2s,t
C
C H = [ U' Y' ], for METH = 'N',
C 1,2s,t 1,2s,t
C
C and Up , Uf , U , and Y are block Hankel
C 1,s,t s+1,2s,t 1,2s,t 1,2s,t
C matrices defined in terms of the input and output data [3].
C A QR factorization is used to compress the data.
C The fast QR algorithm uses a QR factorization which exploits
C the block-Hankel structure. Actually, the Cholesky factor of H'*H
C is computed.
C
C 2) For sequential data processing using QR algorithm, the QR
C decomposition is done sequentially, by updating the upper
C triangular factor R. This is also performed internally if the
C workspace is not large enough to accommodate an entire batch.
C
C 3) For non-sequential or sequential data processing using
C Cholesky algorithm, the correlation matrix of input-output data is
C computed (sequentially, if requested), taking advantage of the
C block Hankel structure [7]. Then, the Cholesky factor of the
C correlation matrix is found, if possible.
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] Verhaegen M.
C Subspace Model Identification. Part 3: Analysis of the
C ordinary output-error state-space model identification
C algorithm.
C Int. J. Control, 58, pp. 555-586, 1993.
C
C [3] Verhaegen M.
C Identification of the deterministic part of MIMO state space
C models given in innovations form from input-output data.
C Automatica, Vol.30, No.1, pp.61-74, 1994.
C
C [4] Van Overschee, P., and De Moor, B.
C N4SID: Subspace Algorithms for the Identification of
C Combined Deterministic-Stochastic Systems.
C Automatica, Vol.30, No.1, pp. 75-93, 1994.
C
C [5] Peternell, K., Scherrer, W. and Deistler, M.
C Statistical Analysis of Novel Subspace Identification Methods.
C Signal Processing, 52, pp. 161-177, 1996.
C
C [6] Sima, V.
C Subspace-based Algorithms for Multivariable System
C Identification.
C Studies in Informatics and Control, 5, pp. 335-344, 1996.
C
C [7] Sima, V.
C Cholesky or QR Factorization for Data Compression in
C Subspace-based Identification ?
C Proceedings of the Second NICONET Workshop on ``Numerical
C Control Software: SLICOT, a Useful Tool in Industry'',
C December 3, 1999, INRIA Rocquencourt, France, pp. 75-80, 1999.
C
C NUMERICAL ASPECTS
C
C The implemented method is numerically stable (when QR algorithm is
C used), reliable and efficient. The fast Cholesky or QR algorithms
C are more efficient, but the accuracy could diminish by forming the
C correlation matrix.
C 2
C The QR algorithm needs 0(t(2(m+l)s) ) floating point operations.
C 2 3
C The Cholesky algorithm needs 0(2t(m+l) s)+0((2(m+l)s) ) floating
C point operations.
C 2 3 2
C The fast QR algorithm needs 0(2t(m+l) s)+0(4(m+l) s ) floating
C point operations.
C
C FURTHER COMMENTS
C
C For ALG = 'Q', BATCH = 'O' and LDR < NS, or BATCH <> 'O', the
C calculations could be rather inefficient if only minimal workspace
C (see argument LDWORK) is provided. It is advisable to provide as
C much workspace as possible. Almost optimal efficiency can be
C obtained for LDWORK = (NS+2)*(2*(M+L)*NOBR), assuming that the
C cache size is large enough to accommodate R, U, Y, and DWORK.
C
C CONTRIBUTOR
C
C V. Sima, Research Institute for Informatics, Bucharest, Aug. 1999.
C
C REVISIONS
C
C Feb. 2000, Aug. 2000, Feb. 2004.
C
C KEYWORDS
C
C Cholesky decomposition, Hankel matrix, identification methods,
C multivariable systems, QR decomposition.
C
C ******************************************************************
C
C .. Parameters ..
DOUBLE PRECISION ZERO, ONE
PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 )
INTEGER MAXCYC
PARAMETER ( MAXCYC = 100 )
C .. Scalar Arguments ..
INTEGER INFO, IWARN, L, LDR, LDU, LDWORK, LDY, M, NOBR,
$ NSMP
CHARACTER ALG, BATCH, CONCT, METH
C .. Array Arguments ..
INTEGER IWORK(*)
DOUBLE PRECISION DWORK(*), R(LDR, *), U(LDU, *), Y(LDY, *)
C .. Local Scalars ..
DOUBLE PRECISION UPD, TEMP
INTEGER I, ICOL, ICYCLE, ID, IERR, II, INICYC, INIT,
$ INITI, INU, INY, IREV, ISHFT2, ISHFTU, ISHFTY,
$ ITAU, J, JD, JWORK, LDRWMX, LDRWRK, LLDRW,
$ LMNOBR, LNOBR, MAXWRK, MINWRK, MLDRW, MMNOBR,
$ MNOBR, NCYCLE, NICYCL, NOBR2, NOBR21, NOBRM1,
$ NR, NS, NSF, NSL, NSLAST, NSMPSM
LOGICAL CHALG, CONNEC, FIRST, FQRALG, INTERM, LAST,
$ LINR, MOESP, N4SID, ONEBCH, QRALG
C .. Local Arrays ..
DOUBLE PRECISION DUM( 1 )
C .. External Functions ..
LOGICAL LSAME
INTEGER ILAENV
EXTERNAL ILAENV, LSAME
C .. External Subroutines ..
EXTERNAL DAXPY, DCOPY, DGEMM, DGEQRF, DGER, DLACPY,
$ DLASET, DPOTRF, DSWAP, DSYRK, IB01MY, MB04OD,
$ XERBLA
C .. Intrinsic Functions ..
INTRINSIC INT, MAX, MIN
C .. Save Statement ..
C ICYCLE is used to count the cycles for BATCH = 'I'. It is
C reinitialized at each MAXCYC cycles.
C MAXWRK is used to store the optimal workspace.
C NSMPSM is used to sum up the NSMP values for BATCH <> 'O'.
SAVE ICYCLE, MAXWRK, NSMPSM
C ..
C .. Executable Statements ..
C
C Decode the scalar input parameters.
C
MOESP = LSAME( METH, 'M' )
N4SID = LSAME( METH, 'N' )
FQRALG = LSAME( ALG, 'F' )
QRALG = LSAME( ALG, 'Q' )
CHALG = LSAME( ALG, 'C' )
ONEBCH = LSAME( BATCH, 'O' )
FIRST = LSAME( BATCH, 'F' ) .OR. ONEBCH
INTERM = LSAME( BATCH, 'I' )
LAST = LSAME( BATCH, 'L' ) .OR. ONEBCH
IF( .NOT.ONEBCH ) THEN
CONNEC = LSAME( CONCT, 'C' )
ELSE
CONNEC = .FALSE.
END IF
C
MNOBR = M*NOBR
LNOBR = L*NOBR
LMNOBR = LNOBR + MNOBR
MMNOBR = MNOBR + MNOBR
NOBRM1 = NOBR - 1
NOBR21 = NOBR + NOBRM1
NOBR2 = NOBR21 + 1
IWARN = 0
INFO = 0
IERR = 0
IF( FIRST ) THEN
ICYCLE = 1
MAXWRK = 1
NSMPSM = 0
END IF
NSMPSM = NSMPSM + NSMP
NR = LMNOBR + LMNOBR
C
C Check the scalar input parameters.
C
IF( .NOT.( MOESP .OR. N4SID ) ) THEN
INFO = -1
ELSE IF( .NOT.( FQRALG .OR. QRALG .OR. CHALG ) ) THEN
INFO = -2
ELSE IF( .NOT.( FIRST .OR. INTERM .OR. LAST ) ) THEN
INFO = -3
ELSE IF( .NOT. ONEBCH ) THEN
IF( .NOT.( CONNEC .OR. LSAME( CONCT, 'N' ) ) )
$ INFO = -4
END IF
IF( INFO.EQ.0 ) THEN
IF( NOBR.LE.0 ) THEN
INFO = -5
ELSE IF( M.LT.0 ) THEN
INFO = -6
ELSE IF( L.LE.0 ) THEN
INFO = -7
ELSE IF( NSMP.LT.NOBR2 .OR.
$ ( LAST .AND. NSMPSM.LT.NR+NOBR21 ) ) THEN
INFO = -8
ELSE IF( LDU.LT.1 .OR. ( M.GT.0 .AND. LDU.LT.NSMP ) ) THEN
INFO = -10
ELSE IF( LDY.LT.NSMP ) THEN
INFO = -12
ELSE IF( LDR.LT.NR ) THEN
INFO = -14
ELSE
C
C Compute workspace.
C (Note: Comments in the code beginning "Workspace:" describe
C the minimal amount of workspace needed at that point in the
C code, 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
NS = NSMP - NOBR21
IF ( CHALG ) THEN
IF ( .NOT.ONEBCH .AND. CONNEC ) THEN
MINWRK = 2*( NR - M - L )
ELSE
MINWRK = 1
END IF
ELSE IF ( FQRALG ) THEN
IF ( .NOT.ONEBCH .AND. CONNEC ) THEN
MINWRK = NR*( M + L + 3 )
ELSE IF ( FIRST .OR. INTERM ) THEN
MINWRK = NR*( M + L + 1 )
ELSE
MINWRK = 2*NR*( M + L + 1 ) + NR
END IF
ELSE
MINWRK = 2*NR
MAXWRK = NR + NR*ILAENV( 1, 'DGEQRF', ' ', NS, NR, -1,
$ -1 )
IF ( FIRST ) THEN
IF ( LDR.LT.NS ) THEN
MINWRK = MINWRK + NR
MAXWRK = NS*NR + MAXWRK
END IF
ELSE
IF ( CONNEC ) THEN
MINWRK = MINWRK*( NOBR + 1 )
ELSE
MINWRK = MINWRK + NR
END IF
MAXWRK = NS*NR + MAXWRK
END IF
END IF
MAXWRK = MAX( MINWRK, MAXWRK )
C
IF( LDWORK.LT.MINWRK ) THEN
INFO = -17
DWORK( 1 ) = MINWRK
END IF
END IF
END IF
C
C Return if there are illegal arguments.
C
IF( INFO.NE.0 ) THEN
CALL XERBLA( 'IB01MD', -INFO )
RETURN
END IF
C
IF ( CHALG ) THEN
C
C Compute the R factor from a Cholesky factorization of the
C input-output data correlation matrix.
C
C Set the parameters for constructing the correlations of the
C current block.
C
LDRWRK = 2*NOBR2 - 2
IF( FIRST ) THEN
UPD = ZERO
ELSE
UPD = ONE
END IF
C
IF( .NOT.FIRST .AND. CONNEC ) THEN
C
C Restore the saved (M+L)*(2*NOBR-1) "connection" elements of
C U and Y into their appropriate position in sequential
C processing. The process is performed column-wise, in
C reverse order, first for Y and then for U.
C Workspace: need (4*NOBR-2)*(M+L).
C
IREV = NR - M - L - NOBR21 + 1
ICOL = 2*( NR - M - L ) - LDRWRK + 1
C
DO 10 J = 2, M + L
DO 5 I = NOBR21 - 1, 0, -1
DWORK(ICOL+I) = DWORK(IREV+I)
5 CONTINUE
IREV = IREV - NOBR21
ICOL = ICOL - LDRWRK
10 CONTINUE
C
IF ( M.GT.0 )
$ CALL DLACPY( 'Full', NOBR21, M, U, LDU, DWORK(NOBR2),
$ LDRWRK )
CALL DLACPY( 'Full', NOBR21, L, Y, LDY,
$ DWORK(LDRWRK*M+NOBR2), LDRWRK )
END IF
C
IF ( M.GT.0 ) THEN
C
C Let Guu(i,j) = Guu0(i,j) + u_i*u_j' + u_(i+1)*u_(j+1)' +
C ... + u_(i+NS-1)*u_(j+NS-1)',
C where u_i' is the i-th row of U, j = 1 : 2s, i = 1 : j,
C NS = NSMP - 2s + 1, and Guu0(i,j) is a zero matrix for
C BATCH = 'O' or 'F', and it is the matrix Guu(i,j) computed
C till the current block for BATCH = 'I' or 'L'. The matrix
C Guu(i,j) is m-by-m, and Guu(j,j) is symmetric. The
C upper triangle of the U-U correlations, Guu, is computed
C (or updated) column-wise in the array R, that is, in the
C order Guu(1,1), Guu(1,2), Guu(2,2), ..., Guu(2s,2s).
C Only the submatrices of the first block-row are fully
C computed (or updated). The remaining ones are determined
C exploiting the block-Hankel structure, using the updating
C formula
C
C Guu(i+1,j+1) = Guu0(i+1,j+1) - Guu0(i,j) + Guu(i,j) +
C u_(i+NS)*u_(j+NS)' - u_i*u_j'.
C
IF( .NOT.FIRST ) THEN
C
C Subtract the contribution of the previous block of data
C in sequential processing. The columns must be processed
C in backward order.
C
DO 20 I = NOBR21*M, 1, -1
CALL DAXPY( I, -ONE, R(1,I), 1, R(M+1,M+I), 1 )
20 CONTINUE
C
END IF
C
C Compute/update Guu(1,1).
C
IF( .NOT.FIRST .AND. CONNEC )
$ CALL DSYRK( 'Upper', 'Transpose', M, NOBR21, ONE, DWORK,
$ LDRWRK, UPD, R, LDR )
CALL DSYRK( 'Upper', 'Transpose', M, NS, ONE, U, LDU, UPD,
$ R, LDR )
C
JD = 1
C
IF( FIRST .OR. .NOT.CONNEC ) THEN
C
DO 70 J = 2, NOBR2
JD = JD + M
ID = M + 1
C
C Compute/update Guu(1,j).
C
CALL DGEMM( 'Transpose', 'NoTranspose', M, M, NS, ONE,
$ U, LDU, U(J,1), LDU, UPD, R(1,JD), LDR )
C
C Compute/update Guu(2:j,j), exploiting the
C block-Hankel structure.
C
IF( FIRST ) THEN
C
DO 30 I = JD - M, JD - 1
CALL DCOPY( I, R(1,I), 1, R(M+1,M+I), 1 )
30 CONTINUE
C
ELSE
C
DO 40 I = JD - M, JD - 1
CALL DAXPY( I, ONE, R(1,I), 1, R(M+1,M+I), 1 )
40 CONTINUE
C
END IF
C
DO 50 I = 2, J - 1
CALL DGER( M, M, ONE, U(NS+I-1,1), LDU,
$ U(NS+J-1,1), LDU, R(ID,JD), LDR )
CALL DGER( M, M, -ONE, U(I-1,1), LDU, U(J-1,1),
$ LDU, R(ID,JD), LDR )
ID = ID + M
50 CONTINUE
C
DO 60 I = 1, M
CALL DAXPY( I, U(NS+J-1,I), U(NS+J-1,1), LDU,
$ R(JD,JD+I-1), 1 )
CALL DAXPY( I, -U(J-1,I), U(J-1,1), LDU,
$ R(JD,JD+I-1), 1 )
60 CONTINUE
C
70 CONTINUE
C
ELSE
C
DO 120 J = 2, NOBR2
JD = JD + M
ID = M + 1
C
C Compute/update Guu(1,j) for sequential processing
C with connected blocks.
C
CALL DGEMM( 'Transpose', 'NoTranspose', M, M, NOBR21,
$ ONE, DWORK, LDRWRK, DWORK(J), LDRWRK, UPD,
$ R(1,JD), LDR )
CALL DGEMM( 'Transpose', 'NoTranspose', M, M, NS, ONE,
$ U, LDU, U(J,1), LDU, ONE, R(1,JD), LDR )
C
C Compute/update Guu(2:j,j) for sequential processing
C with connected blocks, exploiting the block-Hankel
C structure.
C
IF( FIRST ) THEN
C
DO 80 I = JD - M, JD - 1
CALL DCOPY( I, R(1,I), 1, R(M+1,M+I), 1 )
80 CONTINUE
C
ELSE
C
DO 90 I = JD - M, JD - 1
CALL DAXPY( I, ONE, R(1,I), 1, R(M+1,M+I), 1 )
90 CONTINUE
C
END IF
C
DO 100 I = 2, J - 1
CALL DGER( M, M, ONE, U(NS+I-1,1), LDU,
$ U(NS+J-1,1), LDU, R(ID,JD), LDR )
CALL DGER( M, M, -ONE, DWORK(I-1), LDRWRK,
$ DWORK(J-1), LDRWRK, R(ID,JD), LDR )
ID = ID + M
100 CONTINUE
C
DO 110 I = 1, M
CALL DAXPY( I, U(NS+J-1,I), U(NS+J-1,1), LDU,
$ R(JD,JD+I-1), 1 )
CALL DAXPY( I, -DWORK((I-1)*LDRWRK+J-1),
$ DWORK(J-1), LDRWRK, R(JD,JD+I-1), 1 )
110 CONTINUE
C
120 CONTINUE
C
END IF
C
IF ( LAST .AND. MOESP ) THEN
C
C Interchange past and future parts for MOESP algorithm.
C (Only the upper triangular parts are interchanged, and
C the (1,2) part is transposed in-situ.)
C
TEMP = R(1,1)
R(1,1) = R(MNOBR+1,MNOBR+1)
R(MNOBR+1,MNOBR+1) = TEMP
C
DO 130 J = 2, MNOBR
CALL DSWAP( J, R(1,J), 1, R(MNOBR+1,MNOBR+J), 1 )
CALL DSWAP( J-1, R(1,MNOBR+J), 1, R(J,MNOBR+1), LDR )
130 CONTINUE
C
END IF
C
C Let Guy(i,j) = Guy0(i,j) + u_i*y_j' + u_(i+1)*y_(j+1)' +
C ... + u_(i+NS-1)*y_(j+NS-1)',
C where u_i' is the i-th row of U, y_j' is the j-th row
C of Y, j = 1 : 2s, i = 1 : 2s, NS = NSMP - 2s + 1, and
C Guy0(i,j) is a zero matrix for BATCH = 'O' or 'F', and it
C is the matrix Guy(i,j) computed till the current block for
C BATCH = 'I' or 'L'. Guy(i,j) is m-by-L. The U-Y
C correlations, Guy, are computed (or updated) column-wise
C in the array R. Only the submatrices of the first block-
C column and block-row are fully computed (or updated). The
C remaining ones are determined exploiting the block-Hankel
C structure, using the updating formula
C
C Guy(i+1,j+1) = Guy0(i+1,j+1) - Guy0(i,j) + Guy(i,j) +
C u_(i+NS)*y(j+NS)' - u_i*y_j'.
C
II = MMNOBR - M
IF( .NOT.FIRST ) THEN
C
C Subtract the contribution of the previous block of data
C in sequential processing. The columns must be processed
C in backward order.
C
DO 140 I = NR - L, MMNOBR + 1, -1
CALL DAXPY( II, -ONE, R(1,I), 1, R(M+1,L+I), 1 )
140 CONTINUE
C
END IF
C
C Compute/update the first block-column of Guy, Guy(i,1).
C
IF( FIRST .OR. .NOT.CONNEC ) THEN
C
DO 150 I = 1, NOBR2
CALL DGEMM( 'Transpose', 'NoTranspose', M, L, NS, ONE,
$ U(I,1), LDU, Y, LDY, UPD,
$ R((I-1)*M+1,MMNOBR+1), LDR )
150 CONTINUE
C
ELSE
C
DO 160 I = 1, NOBR2
CALL DGEMM( 'Transpose', 'NoTranspose', M, L, NOBR21,
$ ONE, DWORK(I), LDRWRK, DWORK(LDRWRK*M+1),
$ LDRWRK, UPD, R((I-1)*M+1,MMNOBR+1), LDR )
CALL DGEMM( 'Transpose', 'NoTranspose', M, L, NS, ONE,
$ U(I,1), LDU, Y, LDY, ONE,
$ R((I-1)*M+1,MMNOBR+1), LDR )
160 CONTINUE
C
END IF
C
JD = MMNOBR + 1
C
IF( FIRST .OR. .NOT.CONNEC ) THEN
C
DO 200 J = 2, NOBR2
JD = JD + L
ID = M + 1
C
C Compute/update Guy(1,j).
C
CALL DGEMM( 'Transpose', 'NoTranspose', M, L, NS, ONE,
$ U, LDU, Y(J,1), LDY, UPD, R(1,JD), LDR )
C
C Compute/update Guy(2:2*s,j), exploiting the
C block-Hankel structure.
C
IF( FIRST ) THEN
C
DO 170 I = JD - L, JD - 1
CALL DCOPY( II, R(1,I), 1, R(M+1,L+I), 1 )
170 CONTINUE
C
ELSE
C
DO 180 I = JD - L, JD - 1
CALL DAXPY( II, ONE, R(1,I), 1, R(M+1,L+I), 1 )
180 CONTINUE
C
END IF
C
DO 190 I = 2, NOBR2
CALL DGER( M, L, ONE, U(NS+I-1,1), LDU,
$ Y(NS+J-1,1), LDY, R(ID,JD), LDR )
CALL DGER( M, L, -ONE, U(I-1,1), LDU, Y(J-1,1),
$ LDY, R(ID,JD), LDR )
ID = ID + M
190 CONTINUE
C
200 CONTINUE
C
ELSE
C
DO 240 J = 2, NOBR2
JD = JD + L
ID = M + 1
C
C Compute/update Guy(1,j) for sequential processing
C with connected blocks.
C
CALL DGEMM( 'Transpose', 'NoTranspose', M, L, NOBR21,
$ ONE, DWORK, LDRWRK, DWORK(LDRWRK*M+J),
$ LDRWRK, UPD, R(1,JD), LDR )
CALL DGEMM( 'Transpose', 'NoTranspose', M, L, NS, ONE,
$ U, LDU, Y(J,1), LDY, ONE, R(1,JD), LDR )
C
C Compute/update Guy(2:2*s,j) for sequential
C processing with connected blocks, exploiting the
C block-Hankel structure.
C
IF( FIRST ) THEN
C
DO 210 I = JD - L, JD - 1
CALL DCOPY( II, R(1,I), 1, R(M+1,L+I), 1 )
210 CONTINUE
C
ELSE
C
DO 220 I = JD - L, JD - 1
CALL DAXPY( II, ONE, R(1,I), 1, R(M+1,L+I), 1 )
220 CONTINUE
C
END IF
C
DO 230 I = 2, NOBR2
CALL DGER( M, L, ONE, U(NS+I-1,1), LDU,
$ Y(NS+J-1,1), LDY, R(ID,JD), LDR )
CALL DGER( M, L, -ONE, DWORK(I-1), LDRWRK,
$ DWORK(LDRWRK*M+J-1), LDRWRK, R(ID,JD),
$ LDR )
ID = ID + M
230 CONTINUE
C
240 CONTINUE
C
END IF
C
IF ( LAST .AND. MOESP ) THEN
C
C Interchange past and future parts of U-Y correlations
C for MOESP algorithm.
C
DO 250 J = MMNOBR + 1, NR
CALL DSWAP( MNOBR, R(1,J), 1, R(MNOBR+1,J), 1 )
250 CONTINUE
C
END IF
END IF
C
C Let Gyy(i,j) = Gyy0(i,j) + y_i*y_i' + y_(i+1)*y_(i+1)' + ... +
C y_(i+NS-1)*y_(i+NS-1)',
C where y_i' is the i-th row of Y, j = 1 : 2s, i = 1 : j,
C NS = NSMP - 2s + 1, and Gyy0(i,j) is a zero matrix for
C BATCH = 'O' or 'F', and it is the matrix Gyy(i,j) computed till
C the current block for BATCH = 'I' or 'L'. Gyy(i,j) is L-by-L,
C and Gyy(j,j) is symmetric. The upper triangle of the Y-Y
C correlations, Gyy, is computed (or updated) column-wise in
C the corresponding part of the array R, that is, in the order
C Gyy(1,1), Gyy(1,2), Gyy(2,2), ..., Gyy(2s,2s). Only the
C submatrices of the first block-row are fully computed (or
C updated). The remaining ones are determined exploiting the
C block-Hankel structure, using the updating formula
C
C Gyy(i+1,j+1) = Gyy0(i+1,j+1) - Gyy0(i,j) + Gyy(i,j) +
C y_(i+NS)*y_(j+NS)' - y_i*y_j'.
C
JD = MMNOBR + 1
C
IF( .NOT.FIRST ) THEN
C
C Subtract the contribution of the previous block of data
C in sequential processing. The columns must be processed in
C backward order.
C
DO 260 I = NR - L, MMNOBR + 1, -1
CALL DAXPY( I-MMNOBR, -ONE, R(JD,I), 1, R(JD+L,L+I), 1 )
260 CONTINUE
C
END IF
C
C Compute/update Gyy(1,1).
C
IF( .NOT.FIRST .AND. CONNEC )
$ CALL DSYRK( 'Upper', 'Transpose', L, NOBR21, ONE,
$ DWORK(LDRWRK*M+1), LDRWRK, UPD, R(JD,JD), LDR )
CALL DSYRK( 'Upper', 'Transpose', L, NS, ONE, Y, LDY, UPD,
$ R(JD,JD), LDR )
C
IF( FIRST .OR. .NOT.CONNEC ) THEN
C
DO 310 J = 2, NOBR2
JD = JD + L
ID = MMNOBR + L + 1
C
C Compute/update Gyy(1,j).
C
CALL DGEMM( 'Transpose', 'NoTranspose', L, L, NS, ONE, Y,
$ LDY, Y(J,1), LDY, UPD, R(MMNOBR+1,JD), LDR )
C
C Compute/update Gyy(2:j,j), exploiting the block-Hankel
C structure.
C
IF( FIRST ) THEN
C
DO 270 I = JD - L, JD - 1
CALL DCOPY( I-MMNOBR, R(MMNOBR+1,I), 1,
$ R(MMNOBR+L+1,L+I), 1 )
270 CONTINUE
C
ELSE
C
DO 280 I = JD - L, JD - 1
CALL DAXPY( I-MMNOBR, ONE, R(MMNOBR+1,I), 1,
$ R(MMNOBR+L+1,L+I), 1 )
280 CONTINUE
C
END IF
C
DO 290 I = 2, J - 1
CALL DGER( L, L, ONE, Y(NS+I-1,1), LDY, Y(NS+J-1,1),
$ LDY, R(ID,JD), LDR )
CALL DGER( L, L, -ONE, Y(I-1,1), LDY, Y(J-1,1), LDY,
$ R(ID,JD), LDR )
ID = ID + L
290 CONTINUE
C
DO 300 I = 1, L
CALL DAXPY( I, Y(NS+J-1,I), Y(NS+J-1,1), LDY,
$ R(JD,JD+I-1), 1 )
CALL DAXPY( I, -Y(J-1,I), Y(J-1,1), LDY, R(JD,JD+I-1),
$ 1 )
300 CONTINUE
C
310 CONTINUE
C
ELSE
C
DO 360 J = 2, NOBR2
JD = JD + L
ID = MMNOBR + L + 1
C
C Compute/update Gyy(1,j) for sequential processing with
C connected blocks.
C
CALL DGEMM( 'Transpose', 'NoTranspose', L, L, NOBR21,
$ ONE, DWORK(LDRWRK*M+1), LDRWRK,
$ DWORK(LDRWRK*M+J), LDRWRK, UPD,
$ R(MMNOBR+1,JD), LDR )
CALL DGEMM( 'Transpose', 'NoTranspose', L, L, NS, ONE, Y,
$ LDY, Y(J,1), LDY, ONE, R(MMNOBR+1,JD), LDR )
C
C Compute/update Gyy(2:j,j) for sequential processing
C with connected blocks, exploiting the block-Hankel
C structure.
C
IF( FIRST ) THEN
C
DO 320 I = JD - L, JD - 1
CALL DCOPY( I-MMNOBR, R(MMNOBR+1,I), 1,
$ R(MMNOBR+L+1,L+I), 1 )
320 CONTINUE
C
ELSE
C
DO 330 I = JD - L, JD - 1
CALL DAXPY( I-MMNOBR, ONE, R(MMNOBR+1,I), 1,
$ R(MMNOBR+L+1,L+I), 1 )
330 CONTINUE
C
END IF
C
DO 340 I = 2, J - 1
CALL DGER( L, L, ONE, Y(NS+I-1,1), LDY, Y(NS+J-1,1),
$ LDY, R(ID,JD), LDR )
CALL DGER( L, L, -ONE, DWORK(LDRWRK*M+I-1), LDRWRK,
$ DWORK(LDRWRK*M+J-1), LDRWRK, R(ID,JD),
$ LDR )
ID = ID + L
340 CONTINUE
C
DO 350 I = 1, L
CALL DAXPY( I, Y(NS+J-1,I), Y(NS+J-1,1), LDY,
$ R(JD,JD+I-1), 1 )
CALL DAXPY( I, -DWORK(LDRWRK*(M+I-1)+J-1),
$ DWORK(LDRWRK*M+J-1), LDRWRK, R(JD,JD+I-1),
$ 1 )
350 CONTINUE
C
360 CONTINUE
C
END IF
C
IF ( .NOT.LAST ) THEN
IF ( CONNEC ) THEN
C
C For sequential processing with connected data blocks,
C save the remaining ("connection") elements of U and Y
C in the first (M+L)*(2*NOBR-1) locations of DWORK.
C
IF ( M.GT.0 )
$ CALL DLACPY( 'Full', NOBR21, M, U(NS+1,1), LDU, DWORK,
$ NOBR21 )
CALL DLACPY( 'Full', NOBR21, L, Y(NS+1,1), LDY,
$ DWORK(MMNOBR-M+1), NOBR21 )
END IF
C
C Return to get new data.
C
ICYCLE = ICYCLE + 1
IF ( ICYCLE.GT.MAXCYC )
$ IWARN = 1
RETURN
C
ELSE
C
C Try to compute the Cholesky factor of the correlation
C matrix.
C
CALL DPOTRF( 'Upper', NR, R, LDR, IERR )
GO TO 370
END IF
ELSE IF ( FQRALG ) THEN
C
C Compute the R factor from a fast QR factorization of the
C input-output data correlation matrix.
C
CALL IB01MY( METH, BATCH, CONCT, NOBR, M, L, NSMP, U, LDU,
$ Y, LDY, R, LDR, IWORK, DWORK, LDWORK, IWARN,
$ IERR )
IF( .NOT.LAST )
$ RETURN
MAXWRK = MAX( MAXWRK, INT( DWORK(1) ) )
END IF
C
370 CONTINUE
C
IF( IERR.NE.0 ) THEN
C
C Error return from a fast factorization algorithm of the
C input-output data correlation matrix.
C
IF( ONEBCH ) THEN
QRALG = .TRUE.
IWARN = 2
MINWRK = 2*NR
MAXWRK = NR + NR*ILAENV( 1, 'DGEQRF', ' ', NS, NR, -1,
$ -1 )
IF ( LDR.LT.NS ) THEN
MINWRK = MINWRK + NR
MAXWRK = NS*NR + MAXWRK
END IF
MAXWRK = MAX( MINWRK, MAXWRK )
C
IF( LDWORK.LT.MINWRK ) THEN
INFO = -17
C
C Return: Not enough workspace.
C
DWORK( 1 ) = MINWRK
CALL XERBLA( 'IB01MD', -INFO )
RETURN
END IF
ELSE
INFO = 1
RETURN
END IF
END IF
C
IF ( QRALG ) THEN
C
C Compute the R factor from a QR factorization of the matrix H
C of concatenated block Hankel matrices.
C
C Construct the matrix H.
C
C Set the parameters for constructing the current segment of the
C Hankel matrix, taking the available memory space into account.
C INITI+1 points to the beginning rows of U and Y from which
C data are taken when NCYCLE > 1 inner cycles are needed,
C or for sequential processing with connected blocks.
C LDRWMX is the number of rows that can fit in the working space.
C LDRWRK is the actual number of rows processed in this space.
C NSLAST is the number of samples to be processed at the last
C inner cycle.
C
INITI = 0
LDRWMX = LDWORK / NR - 2
NCYCLE = 1
NSLAST = NSMP
LINR = .FALSE.
IF ( FIRST ) THEN
LINR = LDR.GE.NS
LDRWRK = NS
ELSE IF ( CONNEC ) THEN
LDRWRK = NSMP
ELSE
LDRWRK = NS
END IF
INICYC = 1
C
IF ( .NOT.LINR ) THEN
IF ( LDRWMX.LT.LDRWRK ) THEN
C
C Not enough working space for doing a single inner cycle.
C NCYCLE inner cycles are to be performed for the current
C data block using the working space.
C
NCYCLE = LDRWRK / LDRWMX
NSLAST = MOD( LDRWRK, LDRWMX )
IF ( NSLAST.NE.0 ) THEN
NCYCLE = NCYCLE + 1
ELSE
NSLAST = LDRWMX
END IF
LDRWRK = LDRWMX
NS = LDRWRK
IF ( FIRST ) INICYC = 2
END IF
MLDRW = M*LDRWRK
LLDRW = L*LDRWRK
INU = MLDRW*NOBR + 1
INY = MLDRW*NOBR2 + 1
END IF
C
C Process the data given at the current call.
C
IF ( .NOT.FIRST .AND. CONNEC ) THEN
C
C Restore the saved (M+L)*(2*NOBR-1) "connection" elements of
C U and Y into their appropriate position in sequential
C processing. The process is performed column-wise, in
C reverse order, first for Y and then for U.
C
IREV = NR - M - L - NOBR21 + 1
ICOL = INY + LLDRW - LDRWRK
C
DO 380 J = 1, L
DO 375 I = NOBR21 - 1, 0, -1
DWORK(ICOL+I) = DWORK(IREV+I)
375 CONTINUE
IREV = IREV - NOBR21
ICOL = ICOL - LDRWRK
380 CONTINUE
C
IF( MOESP ) THEN
ICOL = INU + MLDRW - LDRWRK
ELSE
ICOL = MLDRW - LDRWRK + 1
END IF
C
DO 390 J = 1, M
DO 385 I = NOBR21 - 1, 0, -1
DWORK(ICOL+I) = DWORK(IREV+I)
385 CONTINUE
IREV = IREV - NOBR21
ICOL = ICOL - LDRWRK
390 CONTINUE
C
IF( MOESP )
$ CALL DLACPY( 'Full', NOBRM1, M, DWORK(INU+NOBR), LDRWRK,
$ DWORK, LDRWRK )
END IF
C
C Data compression using QR factorization.
C
IF ( FIRST ) THEN
C
C Non-sequential data processing or first block in
C sequential data processing:
C Use the general QR factorization algorithm.
C
IF ( LINR ) THEN
C
C Put the input-output data in the array R.
C
IF( M.GT.0 ) THEN
IF( MOESP ) THEN
C
DO 400 I = 1, NOBR
CALL DLACPY( 'Full', NS, M, U(NOBR+I,1), LDU,
$ R(1,M*(I-1)+1), LDR )
400 CONTINUE
C
DO 410 I = 1, NOBR
CALL DLACPY( 'Full', NS, M, U(I,1), LDU,
$ R(1,MNOBR+M*(I-1)+1), LDR )
410 CONTINUE
C
ELSE
C
DO 420 I = 1, NOBR2
CALL DLACPY( 'Full', NS, M, U(I,1), LDU,
$ R(1,M*(I-1)+1), LDR )
420 CONTINUE
C
END IF
END IF
C
DO 430 I = 1, NOBR2
CALL DLACPY( 'Full', NS, L, Y(I,1), LDY,
$ R(1,MMNOBR+L*(I-1)+1), LDR )
430 CONTINUE
C
C Workspace: need 4*(M+L)*NOBR,
C prefer 2*(M+L)*NOBR+2*(M+L)*NOBR*NB.
C
ITAU = 1
JWORK = ITAU + NR
CALL DGEQRF( NS, NR, R, LDR, DWORK(ITAU), DWORK(JWORK),
$ LDWORK-JWORK+1, IERR )
ELSE
C
C Put the input-output data in the array DWORK.
C
IF( M.GT.0 ) THEN
ISHFTU = 1
IF( MOESP ) THEN
ISHFT2 = INU
C
DO 440 I = 1, NOBR
CALL DLACPY( 'Full', NS, M, U(NOBR+I,1), LDU,
$ DWORK(ISHFTU), LDRWRK )
ISHFTU = ISHFTU + MLDRW
440 CONTINUE
C
DO 450 I = 1, NOBR
CALL DLACPY( 'Full', NS, M, U(I,1), LDU,
$ DWORK(ISHFT2), LDRWRK )
ISHFT2 = ISHFT2 + MLDRW
450 CONTINUE
C
ELSE
C
DO 460 I = 1, NOBR2
CALL DLACPY( 'Full', NS, M, U(I,1), LDU,
$ DWORK(ISHFTU), LDRWRK )
ISHFTU = ISHFTU + MLDRW
460 CONTINUE
C
END IF
END IF
C
ISHFTY = INY
C
DO 470 I = 1, NOBR2
CALL DLACPY( 'Full', NS, L, Y(I,1), LDY,
$ DWORK(ISHFTY), LDRWRK )
ISHFTY = ISHFTY + LLDRW
470 CONTINUE
C
C Workspace: need 2*(M+L)*NOBR + 4*(M+L)*NOBR,
C prefer NS*2*(M+L)*NOBR + 2*(M+L)*NOBR
C + 2*(M+L)*NOBR*NB,
C used LDRWRK*2*(M+L)*NOBR + 4*(M+L)*NOBR,
C where NS = NSMP - 2*NOBR + 1,
C LDRWRK = min(NS, LDWORK/(2*(M+L)*NOBR)-2).
C
ITAU = LDRWRK*NR + 1
JWORK = ITAU + NR
CALL DGEQRF( NS, NR, DWORK, LDRWRK, DWORK(ITAU),
$ DWORK(JWORK), LDWORK-JWORK+1, IERR )
CALL DLACPY( 'Upper ', MIN(NS,NR), NR, DWORK, LDRWRK, R,
$ LDR )
END IF
C
IF ( NS.LT.NR )
$ CALL DLASET( 'Upper ', NR - NS, NR - NS, ZERO, ZERO,
$ R(NS+1,NS+1), LDR )
INITI = INITI + NS
END IF
C
IF ( NCYCLE.GT.1 .OR. .NOT.FIRST ) THEN
C
C Remaining segments of the first data block or
C remaining segments/blocks in sequential data processing:
C Use a structure-exploiting QR factorization algorithm.
C
NSL = LDRWRK
IF ( .NOT.CONNEC ) NSL = NS
ITAU = LDRWRK*NR + 1
JWORK = ITAU + NR
C
DO 560 NICYCL = INICYC, NCYCLE
C
C INIT denotes the beginning row where new data are put.
C
IF ( CONNEC .AND. NICYCL.EQ.1 ) THEN
INIT = NOBR2
ELSE
INIT = 1
END IF
IF ( NCYCLE.GT.1 .AND. NICYCL.EQ.NCYCLE ) THEN
C
C Last samples in the last data segment of a block.
C
NS = NSLAST
NSL = NSLAST
END IF
C
C Put the input-output data in the array DWORK.
C
NSF = NS
IF ( INIT.GT.1 .AND. NCYCLE.GT.1 ) NSF = NSF - NOBR21
IF ( M.GT.0 ) THEN
ISHFTU = INIT
C
IF( MOESP ) THEN
ISHFT2 = INIT + INU - 1
C
DO 480 I = 1, NOBR
CALL DLACPY( 'Full', NSF, M, U(INITI+NOBR+I,1),
$ LDU, DWORK(ISHFTU), LDRWRK )
ISHFTU = ISHFTU + MLDRW
480 CONTINUE
C
DO 490 I = 1, NOBR
CALL DLACPY( 'Full', NSF, M, U(INITI+I,1), LDU,
$ DWORK(ISHFT2), LDRWRK )
ISHFT2 = ISHFT2 + MLDRW
490 CONTINUE
C
ELSE
C
DO 500 I = 1, NOBR2
CALL DLACPY( 'Full', NSF, M, U(INITI+I,1), LDU,
$ DWORK(ISHFTU), LDRWRK )
ISHFTU = ISHFTU + MLDRW
500 CONTINUE
C
END IF
END IF
C
ISHFTY = INIT + INY - 1
C
DO 510 I = 1, NOBR2
CALL DLACPY( 'Full', NSF, L, Y(INITI+I,1), LDY,
$ DWORK(ISHFTY), LDRWRK )
ISHFTY = ISHFTY + LLDRW
510 CONTINUE
C
IF ( INIT.GT.1 ) THEN
C
C Prepare the connection to the previous block of data
C in sequential processing.
C
IF( MOESP .AND. M.GT.0 )
$ CALL DLACPY( 'Full', NOBR, M, U, LDU, DWORK(NOBR),
$ LDRWRK )
C
C Shift the elements from the connection to the previous
C block of data in sequential processing.
C
IF ( M.GT.0 ) THEN
ISHFTU = MLDRW + 1
C
IF( MOESP ) THEN
ISHFT2 = MLDRW + INU
C
DO 520 I = 1, NOBRM1
CALL DLACPY( 'Full', NOBR21, M,
$ DWORK(ISHFTU-MLDRW+1), LDRWRK,
$ DWORK(ISHFTU), LDRWRK )
ISHFTU = ISHFTU + MLDRW
520 CONTINUE
C
DO 530 I = 1, NOBRM1
CALL DLACPY( 'Full', NOBR21, M,
$ DWORK(ISHFT2-MLDRW+1), LDRWRK,
$ DWORK(ISHFT2), LDRWRK )
ISHFT2 = ISHFT2 + MLDRW
530 CONTINUE
C
ELSE
C
DO 540 I = 1, NOBR21
CALL DLACPY( 'Full', NOBR21, M,
$ DWORK(ISHFTU-MLDRW+1), LDRWRK,
$ DWORK(ISHFTU), LDRWRK )
ISHFTU = ISHFTU + MLDRW
540 CONTINUE
C
END IF
END IF
C
ISHFTY = LLDRW + INY
C
DO 550 I = 1, NOBR21
CALL DLACPY( 'Full', NOBR21, L,
$ DWORK(ISHFTY-LLDRW+1), LDRWRK,
$ DWORK(ISHFTY), LDRWRK )
ISHFTY = ISHFTY + LLDRW
550 CONTINUE
C
END IF
C
C Workspace: need LDRWRK*2*(M+L)*NOBR + 4*(M+L)*NOBR.
C
CALL MB04OD( 'Full', NR, 0, NSL, R, LDR, DWORK, LDRWRK,
$ DUM, NR, DUM, NR, DWORK(ITAU), DWORK(JWORK)
$ )
INITI = INITI + NSF
560 CONTINUE
C
END IF
C
IF ( .NOT.LAST ) THEN
IF ( CONNEC ) THEN
C
C For sequential processing with connected data blocks,
C save the remaining ("connection") elements of U and Y
C in the first (M+L)*(2*NOBR-1) locations of DWORK.
C
IF ( M.GT.0 )
$ CALL DLACPY( 'Full', NOBR21, M, U(INITI+1,1), LDU,
$ DWORK, NOBR21 )
CALL DLACPY( 'Full', NOBR21, L, Y(INITI+1,1), LDY,
$ DWORK(MMNOBR-M+1), NOBR21 )
END IF
C
C Return to get new data.
C
ICYCLE = ICYCLE + 1
IF ( ICYCLE.LE.MAXCYC )
$ RETURN
IWARN = 1
ICYCLE = 1
C
END IF
C
END IF
C
C Return optimal workspace in DWORK(1).
C
DWORK( 1 ) = MAXWRK
IF ( LAST ) THEN
ICYCLE = 1
MAXWRK = 1
NSMPSM = 0
END IF
RETURN
C
C *** Last line of IB01MD ***
END
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