Move LAPACK trunk into position.

1 files changed, 515 insertions, 0 deletions

diff --git a/SRC/stgsja.f b/SRC/stgsja.f
new file mode 100644
index 00000000..be29a7a4
--- /dev/null
+++ b/SRC/stgsja.f
@@ -0,0 +1,515 @@
+      SUBROUTINE STGSJA( JOBU, JOBV, JOBQ, M, P, N, K, L, A, LDA, B,
+     $                   LDB, TOLA, TOLB, ALPHA, BETA, U, LDU, V, LDV,
+     $                   Q, LDQ, WORK, NCYCLE, INFO )
+*
+*  -- LAPACK routine (version 3.1) --
+*     Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd..
+*     November 2006
+*
+*     .. Scalar Arguments ..
+      CHARACTER          JOBQ, JOBU, JOBV
+      INTEGER            INFO, K, L, LDA, LDB, LDQ, LDU, LDV, M, N,
+     $                   NCYCLE, P
+      REAL               TOLA, TOLB
+*     ..
+*     .. Array Arguments ..
+      REAL               A( LDA, * ), ALPHA( * ), B( LDB, * ),
+     $                   BETA( * ), Q( LDQ, * ), U( LDU, * ),
+     $                   V( LDV, * ), WORK( * )
+*     ..
+*
+*  Purpose
+*  =======
+*
+*  STGSJA computes the generalized singular value decomposition (GSVD)
+*  of two real upper triangular (or trapezoidal) matrices A and B.
+*
+*  On entry, it is assumed that matrices A and B have the following
+*  forms, which may be obtained by the preprocessing subroutine SGGSVP
+*  from a general M-by-N matrix A and P-by-N matrix B:
+*
+*               N-K-L  K    L
+*     A =    K ( 0    A12  A13 ) if M-K-L >= 0;
+*            L ( 0     0   A23 )
+*        M-K-L ( 0     0    0  )
+*
+*             N-K-L  K    L
+*     A =  K ( 0    A12  A13 ) if M-K-L < 0;
+*        M-K ( 0     0   A23 )
+*
+*             N-K-L  K    L
+*     B =  L ( 0     0   B13 )
+*        P-L ( 0     0    0  )
+*
+*  where the K-by-K matrix A12 and L-by-L matrix B13 are nonsingular
+*  upper triangular; A23 is L-by-L upper triangular if M-K-L >= 0,
+*  otherwise A23 is (M-K)-by-L upper trapezoidal.
+*
+*  On exit,
+*
+*              U'*A*Q = D1*( 0 R ),    V'*B*Q = D2*( 0 R ),
+*
+*  where U, V and Q are orthogonal matrices, Z' denotes the transpose
+*  of Z, R is a nonsingular upper triangular matrix, and D1 and D2 are
+*  ``diagonal'' matrices, which are of the following structures:
+*
+*  If M-K-L >= 0,
+*
+*                      K  L
+*         D1 =     K ( I  0 )
+*                  L ( 0  C )
+*              M-K-L ( 0  0 )
+*
+*                    K  L
+*         D2 = L   ( 0  S )
+*              P-L ( 0  0 )
+*
+*                 N-K-L  K    L
+*    ( 0 R ) = K (  0   R11  R12 ) K
+*              L (  0    0   R22 ) L
+*
+*  where
+*
+*    C = diag( ALPHA(K+1), ... , ALPHA(K+L) ),
+*    S = diag( BETA(K+1),  ... , BETA(K+L) ),
+*    C**2 + S**2 = I.
+*
+*    R is stored in A(1:K+L,N-K-L+1:N) on exit.
+*
+*  If M-K-L < 0,
+*
+*                 K M-K K+L-M
+*      D1 =   K ( I  0    0   )
+*           M-K ( 0  C    0   )
+*
+*                   K M-K K+L-M
+*      D2 =   M-K ( 0  S    0   )
+*           K+L-M ( 0  0    I   )
+*             P-L ( 0  0    0   )
+*
+*                 N-K-L  K   M-K  K+L-M
+* ( 0 R ) =    K ( 0    R11  R12  R13  )
+*            M-K ( 0     0   R22  R23  )
+*          K+L-M ( 0     0    0   R33  )
+*
+*  where
+*  C = diag( ALPHA(K+1), ... , ALPHA(M) ),
+*  S = diag( BETA(K+1),  ... , BETA(M) ),
+*  C**2 + S**2 = I.
+*
+*  R = ( R11 R12 R13 ) is stored in A(1:M, N-K-L+1:N) and R33 is stored
+*      (  0  R22 R23 )
+*  in B(M-K+1:L,N+M-K-L+1:N) on exit.
+*
+*  The computation of the orthogonal transformation matrices U, V or Q
+*  is optional.  These matrices may either be formed explicitly, or they
+*  may be postmultiplied into input matrices U1, V1, or Q1.
+*
+*  Arguments
+*  =========
+*
+*  JOBU    (input) CHARACTER*1
+*          = 'U':  U must contain an orthogonal matrix U1 on entry, and
+*                  the product U1*U is returned;
+*          = 'I':  U is initialized to the unit matrix, and the
+*                  orthogonal matrix U is returned;
+*          = 'N':  U is not computed.
+*
+*  JOBV    (input) CHARACTER*1
+*          = 'V':  V must contain an orthogonal matrix V1 on entry, and
+*                  the product V1*V is returned;
+*          = 'I':  V is initialized to the unit matrix, and the
+*                  orthogonal matrix V is returned;
+*          = 'N':  V is not computed.
+*
+*  JOBQ    (input) CHARACTER*1
+*          = 'Q':  Q must contain an orthogonal matrix Q1 on entry, and
+*                  the product Q1*Q is returned;
+*          = 'I':  Q is initialized to the unit matrix, and the
+*                  orthogonal matrix Q is returned;
+*          = 'N':  Q is not computed.
+*
+*  M       (input) INTEGER
+*          The number of rows of the matrix A.  M >= 0.
+*
+*  P       (input) INTEGER
+*          The number of rows of the matrix B.  P >= 0.
+*
+*  N       (input) INTEGER
+*          The number of columns of the matrices A and B.  N >= 0.
+*
+*  K       (input) INTEGER
+*  L       (input) INTEGER
+*          K and L specify the subblocks in the input matrices A and B:
+*          A23 = A(K+1:MIN(K+L,M),N-L+1:N) and B13 = B(1:L,N-L+1:N)
+*          of A and B, whose GSVD is going to be computed by STGSJA.
+*          See Further details.
+*
+*  A       (input/output) REAL array, dimension (LDA,N)
+*          On entry, the M-by-N matrix A.
+*          On exit, A(N-K+1:N,1:MIN(K+L,M) ) contains the triangular
+*          matrix R or part of R.  See Purpose for details.
+*
+*  LDA     (input) INTEGER
+*          The leading dimension of the array A. LDA >= max(1,M).
+*
+*  B       (input/output) REAL array, dimension (LDB,N)
+*          On entry, the P-by-N matrix B.
+*          On exit, if necessary, B(M-K+1:L,N+M-K-L+1:N) contains
+*          a part of R.  See Purpose for details.
+*
+*  LDB     (input) INTEGER
+*          The leading dimension of the array B. LDB >= max(1,P).
+*
+*  TOLA    (input) REAL
+*  TOLB    (input) REAL
+*          TOLA and TOLB are the convergence criteria for the Jacobi-
+*          Kogbetliantz iteration procedure. Generally, they are the
+*          same as used in the preprocessing step, say
+*              TOLA = max(M,N)*norm(A)*MACHEPS,
+*              TOLB = max(P,N)*norm(B)*MACHEPS.
+*
+*  ALPHA   (output) REAL array, dimension (N)
+*  BETA    (output) REAL array, dimension (N)
+*          On exit, ALPHA and BETA contain the generalized singular
+*          value pairs of A and B;
+*            ALPHA(1:K) = 1,
+*            BETA(1:K)  = 0,
+*          and if M-K-L >= 0,
+*            ALPHA(K+1:K+L) = diag(C),
+*            BETA(K+1:K+L)  = diag(S),
+*          or if M-K-L < 0,
+*            ALPHA(K+1:M)= C, ALPHA(M+1:K+L)= 0
+*            BETA(K+1:M) = S, BETA(M+1:K+L) = 1.
+*          Furthermore, if K+L < N,
+*            ALPHA(K+L+1:N) = 0 and
+*            BETA(K+L+1:N)  = 0.
+*
+*  U       (input/output) REAL array, dimension (LDU,M)
+*          On entry, if JOBU = 'U', U must contain a matrix U1 (usually
+*          the orthogonal matrix returned by SGGSVP).
+*          On exit,
+*          if JOBU = 'I', U contains the orthogonal matrix U;
+*          if JOBU = 'U', U contains the product U1*U.
+*          If JOBU = 'N', U is not referenced.
+*
+*  LDU     (input) INTEGER
+*          The leading dimension of the array U. LDU >= max(1,M) if
+*          JOBU = 'U'; LDU >= 1 otherwise.
+*
+*  V       (input/output) REAL array, dimension (LDV,P)
+*          On entry, if JOBV = 'V', V must contain a matrix V1 (usually
+*          the orthogonal matrix returned by SGGSVP).
+*          On exit,
+*          if JOBV = 'I', V contains the orthogonal matrix V;
+*          if JOBV = 'V', V contains the product V1*V.
+*          If JOBV = 'N', V is not referenced.
+*
+*  LDV     (input) INTEGER
+*          The leading dimension of the array V. LDV >= max(1,P) if
+*          JOBV = 'V'; LDV >= 1 otherwise.
+*
+*  Q       (input/output) REAL array, dimension (LDQ,N)
+*          On entry, if JOBQ = 'Q', Q must contain a matrix Q1 (usually
+*          the orthogonal matrix returned by SGGSVP).
+*          On exit,
+*          if JOBQ = 'I', Q contains the orthogonal matrix Q;
+*          if JOBQ = 'Q', Q contains the product Q1*Q.
+*          If JOBQ = 'N', Q is not referenced.
+*
+*  LDQ     (input) INTEGER
+*          The leading dimension of the array Q. LDQ >= max(1,N) if
+*          JOBQ = 'Q'; LDQ >= 1 otherwise.
+*
+*  WORK    (workspace) REAL array, dimension (2*N)
+*
+*  NCYCLE  (output) INTEGER
+*          The number of cycles required for convergence.
+*
+*  INFO    (output) INTEGER
+*          = 0:  successful exit
+*          < 0:  if INFO = -i, the i-th argument had an illegal value.
+*          = 1:  the procedure does not converge after MAXIT cycles.
+*
+*  Internal Parameters
+*  ===================
+*
+*  MAXIT   INTEGER
+*          MAXIT specifies the total loops that the iterative procedure
+*          may take. If after MAXIT cycles, the routine fails to
+*          converge, we return INFO = 1.
+*
+*  Further Details
+*  ===============
+*
+*  STGSJA essentially uses a variant of Kogbetliantz algorithm to reduce
+*  min(L,M-K)-by-L triangular (or trapezoidal) matrix A23 and L-by-L
+*  matrix B13 to the form:
+*
+*           U1'*A13*Q1 = C1*R1; V1'*B13*Q1 = S1*R1,
+*
+*  where U1, V1 and Q1 are orthogonal matrix, and Z' is the transpose
+*  of Z.  C1 and S1 are diagonal matrices satisfying
+*
+*                C1**2 + S1**2 = I,
+*
+*  and R1 is an L-by-L nonsingular upper triangular matrix.
+*
+*  =====================================================================
+*
+*     .. Parameters ..
+      INTEGER            MAXIT
+      PARAMETER          ( MAXIT = 40 )
+      REAL               ZERO, ONE
+      PARAMETER          ( ZERO = 0.0E+0, ONE = 1.0E+0 )
+*     ..
+*     .. Local Scalars ..
+*
+      LOGICAL            INITQ, INITU, INITV, UPPER, WANTQ, WANTU, WANTV
+      INTEGER            I, J, KCYCLE
+      REAL               A1, A2, A3, B1, B2, B3, CSQ, CSU, CSV, ERROR,
+     $                   GAMMA, RWK, SNQ, SNU, SNV, SSMIN
+*     ..
+*     .. External Functions ..
+      LOGICAL            LSAME
+      EXTERNAL           LSAME
+*     ..
+*     .. External Subroutines ..
+      EXTERNAL           SCOPY, SLAGS2, SLAPLL, SLARTG, SLASET, SROT,
+     $                   SSCAL, XERBLA
+*     ..
+*     .. Intrinsic Functions ..
+      INTRINSIC          ABS, MAX, MIN
+*     ..
+*     .. Executable Statements ..
+*
+*     Decode and test the input parameters
+*
+      INITU = LSAME( JOBU, 'I' )
+      WANTU = INITU .OR. LSAME( JOBU, 'U' )
+*
+      INITV = LSAME( JOBV, 'I' )
+      WANTV = INITV .OR. LSAME( JOBV, 'V' )
+*
+      INITQ = LSAME( JOBQ, 'I' )
+      WANTQ = INITQ .OR. LSAME( JOBQ, 'Q' )
+*
+      INFO = 0
+      IF( .NOT.( INITU .OR. WANTU .OR. LSAME( JOBU, 'N' ) ) ) THEN
+         INFO = -1
+      ELSE IF( .NOT.( INITV .OR. WANTV .OR. LSAME( JOBV, 'N' ) ) ) THEN
+         INFO = -2
+      ELSE IF( .NOT.( INITQ .OR. WANTQ .OR. LSAME( JOBQ, 'N' ) ) ) THEN
+         INFO = -3
+      ELSE IF( M.LT.0 ) THEN
+         INFO = -4
+      ELSE IF( P.LT.0 ) THEN
+         INFO = -5
+      ELSE IF( N.LT.0 ) THEN
+         INFO = -6
+      ELSE IF( LDA.LT.MAX( 1, M ) ) THEN
+         INFO = -10
+      ELSE IF( LDB.LT.MAX( 1, P ) ) THEN
+         INFO = -12
+      ELSE IF( LDU.LT.1 .OR. ( WANTU .AND. LDU.LT.M ) ) THEN
+         INFO = -18
+      ELSE IF( LDV.LT.1 .OR. ( WANTV .AND. LDV.LT.P ) ) THEN
+         INFO = -20
+      ELSE IF( LDQ.LT.1 .OR. ( WANTQ .AND. LDQ.LT.N ) ) THEN
+         INFO = -22
+      END IF
+      IF( INFO.NE.0 ) THEN
+         CALL XERBLA( 'STGSJA', -INFO )
+         RETURN
+      END IF
+*
+*     Initialize U, V and Q, if necessary
+*
+      IF( INITU )
+     $   CALL SLASET( 'Full', M, M, ZERO, ONE, U, LDU )
+      IF( INITV )
+     $   CALL SLASET( 'Full', P, P, ZERO, ONE, V, LDV )
+      IF( INITQ )
+     $   CALL SLASET( 'Full', N, N, ZERO, ONE, Q, LDQ )
+*
+*     Loop until convergence
+*
+      UPPER = .FALSE.
+      DO 40 KCYCLE = 1, MAXIT
+*
+         UPPER = .NOT.UPPER
+*
+         DO 20 I = 1, L - 1
+            DO 10 J = I + 1, L
+*
+               A1 = ZERO
+               A2 = ZERO
+               A3 = ZERO
+               IF( K+I.LE.M )
+     $            A1 = A( K+I, N-L+I )
+               IF( K+J.LE.M )
+     $            A3 = A( K+J, N-L+J )
+*
+               B1 = B( I, N-L+I )
+               B3 = B( J, N-L+J )
+*
+               IF( UPPER ) THEN
+                  IF( K+I.LE.M )
+     $               A2 = A( K+I, N-L+J )
+                  B2 = B( I, N-L+J )
+               ELSE
+                  IF( K+J.LE.M )
+     $               A2 = A( K+J, N-L+I )
+                  B2 = B( J, N-L+I )
+               END IF
+*
+               CALL SLAGS2( UPPER, A1, A2, A3, B1, B2, B3, CSU, SNU,
+     $                      CSV, SNV, CSQ, SNQ )
+*
+*              Update (K+I)-th and (K+J)-th rows of matrix A: U'*A
+*
+               IF( K+J.LE.M )
+     $            CALL SROT( L, A( K+J, N-L+1 ), LDA, A( K+I, N-L+1 ),
+     $                       LDA, CSU, SNU )
+*
+*              Update I-th and J-th rows of matrix B: V'*B
+*
+               CALL SROT( L, B( J, N-L+1 ), LDB, B( I, N-L+1 ), LDB,
+     $                    CSV, SNV )
+*
+*              Update (N-L+I)-th and (N-L+J)-th columns of matrices
+*              A and B: A*Q and B*Q
+*
+               CALL SROT( MIN( K+L, M ), A( 1, N-L+J ), 1,
+     $                    A( 1, N-L+I ), 1, CSQ, SNQ )
+*
+               CALL SROT( L, B( 1, N-L+J ), 1, B( 1, N-L+I ), 1, CSQ,
+     $                    SNQ )
+*
+               IF( UPPER ) THEN
+                  IF( K+I.LE.M )
+     $               A( K+I, N-L+J ) = ZERO
+                  B( I, N-L+J ) = ZERO
+               ELSE
+                  IF( K+J.LE.M )
+     $               A( K+J, N-L+I ) = ZERO
+                  B( J, N-L+I ) = ZERO
+               END IF
+*
+*              Update orthogonal matrices U, V, Q, if desired.
+*
+               IF( WANTU .AND. K+J.LE.M )
+     $            CALL SROT( M, U( 1, K+J ), 1, U( 1, K+I ), 1, CSU,
+     $                       SNU )
+*
+               IF( WANTV )
+     $            CALL SROT( P, V( 1, J ), 1, V( 1, I ), 1, CSV, SNV )
+*
+               IF( WANTQ )
+     $            CALL SROT( N, Q( 1, N-L+J ), 1, Q( 1, N-L+I ), 1, CSQ,
+     $                       SNQ )
+*
+   10       CONTINUE
+   20    CONTINUE
+*
+         IF( .NOT.UPPER ) THEN
+*
+*           The matrices A13 and B13 were lower triangular at the start
+*           of the cycle, and are now upper triangular.
+*
+*           Convergence test: test the parallelism of the corresponding
+*           rows of A and B.
+*
+            ERROR = ZERO
+            DO 30 I = 1, MIN( L, M-K )
+               CALL SCOPY( L-I+1, A( K+I, N-L+I ), LDA, WORK, 1 )
+               CALL SCOPY( L-I+1, B( I, N-L+I ), LDB, WORK( L+1 ), 1 )
+               CALL SLAPLL( L-I+1, WORK, 1, WORK( L+1 ), 1, SSMIN )
+               ERROR = MAX( ERROR, SSMIN )
+   30       CONTINUE
+*
+            IF( ABS( ERROR ).LE.MIN( TOLA, TOLB ) )
+     $         GO TO 50
+         END IF
+*
+*        End of cycle loop
+*
+   40 CONTINUE
+*
+*     The algorithm has not converged after MAXIT cycles.
+*
+      INFO = 1
+      GO TO 100
+*
+   50 CONTINUE
+*
+*     If ERROR <= MIN(TOLA,TOLB), then the algorithm has converged.
+*     Compute the generalized singular value pairs (ALPHA, BETA), and
+*     set the triangular matrix R to array A.
+*
+      DO 60 I = 1, K
+         ALPHA( I ) = ONE
+         BETA( I ) = ZERO
+   60 CONTINUE
+*
+      DO 70 I = 1, MIN( L, M-K )
+*
+         A1 = A( K+I, N-L+I )
+         B1 = B( I, N-L+I )
+*
+         IF( A1.NE.ZERO ) THEN
+            GAMMA = B1 / A1
+*
+*           change sign if necessary
+*
+            IF( GAMMA.LT.ZERO ) THEN
+               CALL SSCAL( L-I+1, -ONE, B( I, N-L+I ), LDB )
+               IF( WANTV )
+     $            CALL SSCAL( P, -ONE, V( 1, I ), 1 )
+            END IF
+*
+            CALL SLARTG( ABS( GAMMA ), ONE, BETA( K+I ), ALPHA( K+I ),
+     $                   RWK )
+*
+            IF( ALPHA( K+I ).GE.BETA( K+I ) ) THEN
+               CALL SSCAL( L-I+1, ONE / ALPHA( K+I ), A( K+I, N-L+I ),
+     $                     LDA )
+            ELSE
+               CALL SSCAL( L-I+1, ONE / BETA( K+I ), B( I, N-L+I ),
+     $                     LDB )
+               CALL SCOPY( L-I+1, B( I, N-L+I ), LDB, A( K+I, N-L+I ),
+     $                     LDA )
+            END IF
+*
+         ELSE
+*
+            ALPHA( K+I ) = ZERO
+            BETA( K+I ) = ONE
+            CALL SCOPY( L-I+1, B( I, N-L+I ), LDB, A( K+I, N-L+I ),
+     $                  LDA )
+*
+         END IF
+*
+   70 CONTINUE
+*
+*     Post-assignment
+*
+      DO 80 I = M + 1, K + L
+         ALPHA( I ) = ZERO
+         BETA( I ) = ONE
+   80 CONTINUE
+*
+      IF( K+L.LT.N ) THEN
+         DO 90 I = K + L + 1, N
+            ALPHA( I ) = ZERO
+            BETA( I ) = ZERO
+   90    CONTINUE
+      END IF
+*
+  100 CONTINUE
+      NCYCLE = KCYCLE
+      RETURN
+*
+*     End of STGSJA
+*
+      END