numeric-linalg
Educational material on the SciPy implementation of numerical linear algebra algorithms
| Name | Size | Mode | |
| .. | |||
| lapack/SRC/stgevc.f | 41255B | -rw-r--r-- |
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*> \brief \b STGEVC * * =========== DOCUMENTATION =========== * * Online html documentation available at * http://www.netlib.org/lapack/explore-html/ * *> \htmlonly *> Download STGEVC + dependencies *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/stgevc.f"> *> [TGZ]</a> *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/stgevc.f"> *> [ZIP]</a> *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/stgevc.f"> *> [TXT]</a> *> \endhtmlonly * * Definition: * =========== * * SUBROUTINE STGEVC( SIDE, HOWMNY, SELECT, N, S, LDS, P, LDP, VL, * LDVL, VR, LDVR, MM, M, WORK, INFO ) * * .. Scalar Arguments .. * CHARACTER HOWMNY, SIDE * INTEGER INFO, LDP, LDS, LDVL, LDVR, M, MM, N * .. * .. Array Arguments .. * LOGICAL SELECT( * ) * REAL P( LDP, * ), S( LDS, * ), VL( LDVL, * ), * $ VR( LDVR, * ), WORK( * ) * .. * * * *> \par Purpose: * ============= *> *> \verbatim *> *> STGEVC computes some or all of the right and/or left eigenvectors of *> a pair of real matrices (S,P), where S is a quasi-triangular matrix *> and P is upper triangular. Matrix pairs of this type are produced by *> the generalized Schur factorization of a matrix pair (A,B): *> *> A = Q*S*Z**T, B = Q*P*Z**T *> *> as computed by SGGHRD + SHGEQZ. *> *> The right eigenvector x and the left eigenvector y of (S,P) *> corresponding to an eigenvalue w are defined by: *> *> S*x = w*P*x, (y**H)*S = w*(y**H)*P, *> *> where y**H denotes the conjugate transpose of y. *> The eigenvalues are not input to this routine, but are computed *> directly from the diagonal blocks of S and P. *> *> This routine returns the matrices X and/or Y of right and left *> eigenvectors of (S,P), or the products Z*X and/or Q*Y, *> where Z and Q are input matrices. *> If Q and Z are the orthogonal factors from the generalized Schur *> factorization of a matrix pair (A,B), then Z*X and Q*Y *> are the matrices of right and left eigenvectors of (A,B). *> *> \endverbatim * * Arguments: * ========== * *> \param[in] SIDE *> \verbatim *> SIDE is CHARACTER*1 *> = 'R': compute right eigenvectors only; *> = 'L': compute left eigenvectors only; *> = 'B': compute both right and left eigenvectors. *> \endverbatim *> *> \param[in] HOWMNY *> \verbatim *> HOWMNY is CHARACTER*1 *> = 'A': compute all right and/or left eigenvectors; *> = 'B': compute all right and/or left eigenvectors, *> backtransformed by the matrices in VR and/or VL; *> = 'S': compute selected right and/or left eigenvectors, *> specified by the logical array SELECT. *> \endverbatim *> *> \param[in] SELECT *> \verbatim *> SELECT is LOGICAL array, dimension (N) *> If HOWMNY='S', SELECT specifies the eigenvectors to be *> computed. If w(j) is a real eigenvalue, the corresponding *> real eigenvector is computed if SELECT(j) is .TRUE.. *> If w(j) and w(j+1) are the real and imaginary parts of a *> complex eigenvalue, the corresponding complex eigenvector *> is computed if either SELECT(j) or SELECT(j+1) is .TRUE., *> and on exit SELECT(j) is set to .TRUE. and SELECT(j+1) is *> set to .FALSE.. *> Not referenced if HOWMNY = 'A' or 'B'. *> \endverbatim *> *> \param[in] N *> \verbatim *> N is INTEGER *> The order of the matrices S and P. N >= 0. *> \endverbatim *> *> \param[in] S *> \verbatim *> S is REAL array, dimension (LDS,N) *> The upper quasi-triangular matrix S from a generalized Schur *> factorization, as computed by SHGEQZ. *> \endverbatim *> *> \param[in] LDS *> \verbatim *> LDS is INTEGER *> The leading dimension of array S. LDS >= max(1,N). *> \endverbatim *> *> \param[in] P *> \verbatim *> P is REAL array, dimension (LDP,N) *> The upper triangular matrix P from a generalized Schur *> factorization, as computed by SHGEQZ. *> 2-by-2 diagonal blocks of P corresponding to 2-by-2 blocks *> of S must be in positive diagonal form. *> \endverbatim *> *> \param[in] LDP *> \verbatim *> LDP is INTEGER *> The leading dimension of array P. LDP >= max(1,N). *> \endverbatim *> *> \param[in,out] VL *> \verbatim *> VL is REAL array, dimension (LDVL,MM) *> On entry, if SIDE = 'L' or 'B' and HOWMNY = 'B', VL must *> contain an N-by-N matrix Q (usually the orthogonal matrix Q *> of left Schur vectors returned by SHGEQZ). *> On exit, if SIDE = 'L' or 'B', VL contains: *> if HOWMNY = 'A', the matrix Y of left eigenvectors of (S,P); *> if HOWMNY = 'B', the matrix Q*Y; *> if HOWMNY = 'S', the left eigenvectors of (S,P) specified by *> SELECT, stored consecutively in the columns of *> VL, in the same order as their eigenvalues. *> *> A complex eigenvector corresponding to a complex eigenvalue *> is stored in two consecutive columns, the first holding the *> real part, and the second the imaginary part. *> *> Not referenced if SIDE = 'R'. *> \endverbatim *> *> \param[in] LDVL *> \verbatim *> LDVL is INTEGER *> The leading dimension of array VL. LDVL >= 1, and if *> SIDE = 'L' or 'B', LDVL >= N. *> \endverbatim *> *> \param[in,out] VR *> \verbatim *> VR is REAL array, dimension (LDVR,MM) *> On entry, if SIDE = 'R' or 'B' and HOWMNY = 'B', VR must *> contain an N-by-N matrix Z (usually the orthogonal matrix Z *> of right Schur vectors returned by SHGEQZ). *> *> On exit, if SIDE = 'R' or 'B', VR contains: *> if HOWMNY = 'A', the matrix X of right eigenvectors of (S,P); *> if HOWMNY = 'B' or 'b', the matrix Z*X; *> if HOWMNY = 'S' or 's', the right eigenvectors of (S,P) *> specified by SELECT, stored consecutively in the *> columns of VR, in the same order as their *> eigenvalues. *> *> A complex eigenvector corresponding to a complex eigenvalue *> is stored in two consecutive columns, the first holding the *> real part and the second the imaginary part. *> *> Not referenced if SIDE = 'L'. *> \endverbatim *> *> \param[in] LDVR *> \verbatim *> LDVR is INTEGER *> The leading dimension of the array VR. LDVR >= 1, and if *> SIDE = 'R' or 'B', LDVR >= N. *> \endverbatim *> *> \param[in] MM *> \verbatim *> MM is INTEGER *> The number of columns in the arrays VL and/or VR. MM >= M. *> \endverbatim *> *> \param[out] M *> \verbatim *> M is INTEGER *> The number of columns in the arrays VL and/or VR actually *> used to store the eigenvectors. If HOWMNY = 'A' or 'B', M *> is set to N. Each selected real eigenvector occupies one *> column and each selected complex eigenvector occupies two *> columns. *> \endverbatim *> *> \param[out] WORK *> \verbatim *> WORK is REAL array, dimension (6*N) *> \endverbatim *> *> \param[out] INFO *> \verbatim *> INFO is INTEGER *> = 0: successful exit. *> < 0: if INFO = -i, the i-th argument had an illegal value. *> > 0: the 2-by-2 block (INFO:INFO+1) does not have a complex *> eigenvalue. *> \endverbatim * * Authors: * ======== * *> \author Univ. of Tennessee *> \author Univ. of California Berkeley *> \author Univ. of Colorado Denver *> \author NAG Ltd. * *> \ingroup tgevc * *> \par Further Details: * ===================== *> *> \verbatim *> *> Allocation of workspace: *> ---------- -- --------- *> *> WORK( j ) = 1-norm of j-th column of A, above the diagonal *> WORK( N+j ) = 1-norm of j-th column of B, above the diagonal *> WORK( 2*N+1:3*N ) = real part of eigenvector *> WORK( 3*N+1:4*N ) = imaginary part of eigenvector *> WORK( 4*N+1:5*N ) = real part of back-transformed eigenvector *> WORK( 5*N+1:6*N ) = imaginary part of back-transformed eigenvector *> *> Rowwise vs. columnwise solution methods: *> ------- -- ---------- -------- ------- *> *> Finding a generalized eigenvector consists basically of solving the *> singular triangular system *> *> (A - w B) x = 0 (for right) or: (A - w B)**H y = 0 (for left) *> *> Consider finding the i-th right eigenvector (assume all eigenvalues *> are real). The equation to be solved is: *> n i *> 0 = sum C(j,k) v(k) = sum C(j,k) v(k) for j = i,. . .,1 *> k=j k=j *> *> where C = (A - w B) (The components v(i+1:n) are 0.) *> *> The "rowwise" method is: *> *> (1) v(i) := 1 *> for j = i-1,. . .,1: *> i *> (2) compute s = - sum C(j,k) v(k) and *> k=j+1 *> *> (3) v(j) := s / C(j,j) *> *> Step 2 is sometimes called the "dot product" step, since it is an *> inner product between the j-th row and the portion of the eigenvector *> that has been computed so far. *> *> The "columnwise" method consists basically in doing the sums *> for all the rows in parallel. As each v(j) is computed, the *> contribution of v(j) times the j-th column of C is added to the *> partial sums. Since FORTRAN arrays are stored columnwise, this has *> the advantage that at each step, the elements of C that are accessed *> are adjacent to one another, whereas with the rowwise method, the *> elements accessed at a step are spaced LDS (and LDP) words apart. *> *> When finding left eigenvectors, the matrix in question is the *> transpose of the one in storage, so the rowwise method then *> actually accesses columns of A and B at each step, and so is the *> preferred method. *> \endverbatim *> * ===================================================================== SUBROUTINE STGEVC( SIDE, HOWMNY, SELECT, N, S, LDS, P, LDP, VL, $ LDVL, VR, LDVR, MM, M, WORK, INFO ) * * -- LAPACK computational routine -- * -- LAPACK is a software package provided by Univ. of Tennessee, -- * -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- * * .. Scalar Arguments .. CHARACTER HOWMNY, SIDE INTEGER INFO, LDP, LDS, LDVL, LDVR, M, MM, N * .. * .. Array Arguments .. LOGICAL SELECT( * ) REAL P( LDP, * ), S( LDS, * ), VL( LDVL, * ), $ VR( LDVR, * ), WORK( * ) * .. * * * ===================================================================== * * .. Parameters .. REAL ZERO, ONE, SAFETY PARAMETER ( ZERO = 0.0E+0, ONE = 1.0E+0, $ SAFETY = 1.0E+2 ) * .. * .. Local Scalars .. LOGICAL COMPL, COMPR, IL2BY2, ILABAD, ILALL, ILBACK, $ ILBBAD, ILCOMP, ILCPLX, LSA, LSB INTEGER I, IBEG, IEIG, IEND, IHWMNY, IINFO, IM, ISIDE, $ J, JA, JC, JE, JR, JW, NA, NW REAL ACOEF, ACOEFA, ANORM, ASCALE, BCOEFA, BCOEFI, $ BCOEFR, BIG, BIGNUM, BNORM, BSCALE, CIM2A, $ CIM2B, CIMAGA, CIMAGB, CRE2A, CRE2B, CREALA, $ CREALB, DMIN, SAFMIN, SALFAR, SBETA, SCALE, $ SMALL, TEMP, TEMP2, TEMP2I, TEMP2R, ULP, XMAX, $ XSCALE * .. * .. Local Arrays .. REAL BDIAG( 2 ), SUM( 2, 2 ), SUMS( 2, 2 ), $ SUMP( 2, 2 ) * .. * .. External Functions .. LOGICAL LSAME REAL SLAMCH EXTERNAL LSAME, SLAMCH * .. * .. External Subroutines .. EXTERNAL SGEMV, SLACPY, SLAG2, SLALN2, $ XERBLA * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, MIN * .. * .. Executable Statements .. * * Decode and Test the input parameters * IF( LSAME( HOWMNY, 'A' ) ) THEN IHWMNY = 1 ILALL = .TRUE. ILBACK = .FALSE. ELSE IF( LSAME( HOWMNY, 'S' ) ) THEN IHWMNY = 2 ILALL = .FALSE. ILBACK = .FALSE. ELSE IF( LSAME( HOWMNY, 'B' ) ) THEN IHWMNY = 3 ILALL = .TRUE. ILBACK = .TRUE. ELSE IHWMNY = -1 ILALL = .TRUE. END IF * IF( LSAME( SIDE, 'R' ) ) THEN ISIDE = 1 COMPL = .FALSE. COMPR = .TRUE. ELSE IF( LSAME( SIDE, 'L' ) ) THEN ISIDE = 2 COMPL = .TRUE. COMPR = .FALSE. ELSE IF( LSAME( SIDE, 'B' ) ) THEN ISIDE = 3 COMPL = .TRUE. COMPR = .TRUE. ELSE ISIDE = -1 END IF * INFO = 0 IF( ISIDE.LT.0 ) THEN INFO = -1 ELSE IF( IHWMNY.LT.0 ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -4 ELSE IF( LDS.LT.MAX( 1, N ) ) THEN INFO = -6 ELSE IF( LDP.LT.MAX( 1, N ) ) THEN INFO = -8 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'STGEVC', -INFO ) RETURN END IF * * Count the number of eigenvectors to be computed * IF( .NOT.ILALL ) THEN IM = 0 ILCPLX = .FALSE. DO 10 J = 1, N IF( ILCPLX ) THEN ILCPLX = .FALSE. GO TO 10 END IF IF( J.LT.N ) THEN IF( S( J+1, J ).NE.ZERO ) $ ILCPLX = .TRUE. END IF IF( ILCPLX ) THEN IF( SELECT( J ) .OR. SELECT( J+1 ) ) $ IM = IM + 2 ELSE IF( SELECT( J ) ) $ IM = IM + 1 END IF 10 CONTINUE ELSE IM = N END IF * * Check 2-by-2 diagonal blocks of A, B * ILABAD = .FALSE. ILBBAD = .FALSE. DO 20 J = 1, N - 1 IF( S( J+1, J ).NE.ZERO ) THEN IF( P( J, J ).EQ.ZERO .OR. P( J+1, J+1 ).EQ.ZERO .OR. $ P( J, J+1 ).NE.ZERO )ILBBAD = .TRUE. IF( J.LT.N-1 ) THEN IF( S( J+2, J+1 ).NE.ZERO ) $ ILABAD = .TRUE. END IF END IF 20 CONTINUE * IF( ILABAD ) THEN INFO = -5 ELSE IF( ILBBAD ) THEN INFO = -7 ELSE IF( COMPL .AND. LDVL.LT.N .OR. LDVL.LT.1 ) THEN INFO = -10 ELSE IF( COMPR .AND. LDVR.LT.N .OR. LDVR.LT.1 ) THEN INFO = -12 ELSE IF( MM.LT.IM ) THEN INFO = -13 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'STGEVC', -INFO ) RETURN END IF * * Quick return if possible * M = IM IF( N.EQ.0 ) $ RETURN * * Machine Constants * SAFMIN = SLAMCH( 'Safe minimum' ) BIG = ONE / SAFMIN ULP = SLAMCH( 'Epsilon' )*SLAMCH( 'Base' ) SMALL = SAFMIN*REAL( N ) / ULP BIG = ONE / SMALL BIGNUM = ONE / ( SAFMIN*REAL( N ) ) * * Compute the 1-norm of each column of the strictly upper triangular * part (i.e., excluding all elements belonging to the diagonal * blocks) of A and B to check for possible overflow in the * triangular solver. * ANORM = ABS( S( 1, 1 ) ) IF( N.GT.1 ) $ ANORM = ANORM + ABS( S( 2, 1 ) ) BNORM = ABS( P( 1, 1 ) ) WORK( 1 ) = ZERO WORK( N+1 ) = ZERO * DO 50 J = 2, N TEMP = ZERO TEMP2 = ZERO IF( S( J, J-1 ).EQ.ZERO ) THEN IEND = J - 1 ELSE IEND = J - 2 END IF DO 30 I = 1, IEND TEMP = TEMP + ABS( S( I, J ) ) TEMP2 = TEMP2 + ABS( P( I, J ) ) 30 CONTINUE WORK( J ) = TEMP WORK( N+J ) = TEMP2 DO 40 I = IEND + 1, MIN( J+1, N ) TEMP = TEMP + ABS( S( I, J ) ) TEMP2 = TEMP2 + ABS( P( I, J ) ) 40 CONTINUE ANORM = MAX( ANORM, TEMP ) BNORM = MAX( BNORM, TEMP2 ) 50 CONTINUE * ASCALE = ONE / MAX( ANORM, SAFMIN ) BSCALE = ONE / MAX( BNORM, SAFMIN ) * * Left eigenvectors * IF( COMPL ) THEN IEIG = 0 * * Main loop over eigenvalues * ILCPLX = .FALSE. DO 220 JE = 1, N * * Skip this iteration if (a) HOWMNY='S' and SELECT=.FALSE., or * (b) this would be the second of a complex pair. * Check for complex eigenvalue, so as to be sure of which * entry(-ies) of SELECT to look at. * IF( ILCPLX ) THEN ILCPLX = .FALSE. GO TO 220 END IF NW = 1 IF( JE.LT.N ) THEN IF( S( JE+1, JE ).NE.ZERO ) THEN ILCPLX = .TRUE. NW = 2 END IF END IF IF( ILALL ) THEN ILCOMP = .TRUE. ELSE IF( ILCPLX ) THEN ILCOMP = SELECT( JE ) .OR. SELECT( JE+1 ) ELSE ILCOMP = SELECT( JE ) END IF IF( .NOT.ILCOMP ) $ GO TO 220 * * Decide if (a) singular pencil, (b) real eigenvalue, or * (c) complex eigenvalue. * IF( .NOT.ILCPLX ) THEN IF( ABS( S( JE, JE ) ).LE.SAFMIN .AND. $ ABS( P( JE, JE ) ).LE.SAFMIN ) THEN * * Singular matrix pencil -- return unit eigenvector * IEIG = IEIG + 1 DO 60 JR = 1, N VL( JR, IEIG ) = ZERO 60 CONTINUE VL( IEIG, IEIG ) = ONE GO TO 220 END IF END IF * * Clear vector * DO 70 JR = 1, NW*N WORK( 2*N+JR ) = ZERO 70 CONTINUE * T * Compute coefficients in ( a A - b B ) y = 0 * a is ACOEF * b is BCOEFR + i*BCOEFI * IF( .NOT.ILCPLX ) THEN * * Real eigenvalue * TEMP = ONE / MAX( ABS( S( JE, JE ) )*ASCALE, $ ABS( P( JE, JE ) )*BSCALE, SAFMIN ) SALFAR = ( TEMP*S( JE, JE ) )*ASCALE SBETA = ( TEMP*P( JE, JE ) )*BSCALE ACOEF = SBETA*ASCALE BCOEFR = SALFAR*BSCALE BCOEFI = ZERO * * Scale to avoid underflow * SCALE = ONE LSA = ABS( SBETA ).GE.SAFMIN .AND. ABS( ACOEF ).LT.SMALL LSB = ABS( SALFAR ).GE.SAFMIN .AND. ABS( BCOEFR ).LT. $ SMALL IF( LSA ) $ SCALE = ( SMALL / ABS( SBETA ) )*MIN( ANORM, BIG ) IF( LSB ) $ SCALE = MAX( SCALE, ( SMALL / ABS( SALFAR ) )* $ MIN( BNORM, BIG ) ) IF( LSA .OR. LSB ) THEN SCALE = MIN( SCALE, ONE / $ ( SAFMIN*MAX( ONE, ABS( ACOEF ), $ ABS( BCOEFR ) ) ) ) IF( LSA ) THEN ACOEF = ASCALE*( SCALE*SBETA ) ELSE ACOEF = SCALE*ACOEF END IF IF( LSB ) THEN BCOEFR = BSCALE*( SCALE*SALFAR ) ELSE BCOEFR = SCALE*BCOEFR END IF END IF ACOEFA = ABS( ACOEF ) BCOEFA = ABS( BCOEFR ) * * First component is 1 * WORK( 2*N+JE ) = ONE XMAX = ONE ELSE * * Complex eigenvalue * CALL SLAG2( S( JE, JE ), LDS, P( JE, JE ), LDP, $ SAFMIN*SAFETY, ACOEF, TEMP, BCOEFR, TEMP2, $ BCOEFI ) BCOEFI = -BCOEFI IF( BCOEFI.EQ.ZERO ) THEN INFO = JE RETURN END IF * * Scale to avoid over/underflow * ACOEFA = ABS( ACOEF ) BCOEFA = ABS( BCOEFR ) + ABS( BCOEFI ) SCALE = ONE IF( ACOEFA*ULP.LT.SAFMIN .AND. ACOEFA.GE.SAFMIN ) $ SCALE = ( SAFMIN / ULP ) / ACOEFA IF( BCOEFA*ULP.LT.SAFMIN .AND. BCOEFA.GE.SAFMIN ) $ SCALE = MAX( SCALE, ( SAFMIN / ULP ) / BCOEFA ) IF( SAFMIN*ACOEFA.GT.ASCALE ) $ SCALE = ASCALE / ( SAFMIN*ACOEFA ) IF( SAFMIN*BCOEFA.GT.BSCALE ) $ SCALE = MIN( SCALE, BSCALE / ( SAFMIN*BCOEFA ) ) IF( SCALE.NE.ONE ) THEN ACOEF = SCALE*ACOEF ACOEFA = ABS( ACOEF ) BCOEFR = SCALE*BCOEFR BCOEFI = SCALE*BCOEFI BCOEFA = ABS( BCOEFR ) + ABS( BCOEFI ) END IF * * Compute first two components of eigenvector * TEMP = ACOEF*S( JE+1, JE ) TEMP2R = ACOEF*S( JE, JE ) - BCOEFR*P( JE, JE ) TEMP2I = -BCOEFI*P( JE, JE ) IF( ABS( TEMP ).GT.ABS( TEMP2R )+ABS( TEMP2I ) ) THEN WORK( 2*N+JE ) = ONE WORK( 3*N+JE ) = ZERO WORK( 2*N+JE+1 ) = -TEMP2R / TEMP WORK( 3*N+JE+1 ) = -TEMP2I / TEMP ELSE WORK( 2*N+JE+1 ) = ONE WORK( 3*N+JE+1 ) = ZERO TEMP = ACOEF*S( JE, JE+1 ) WORK( 2*N+JE ) = ( BCOEFR*P( JE+1, JE+1 )-ACOEF* $ S( JE+1, JE+1 ) ) / TEMP WORK( 3*N+JE ) = BCOEFI*P( JE+1, JE+1 ) / TEMP END IF XMAX = MAX( ABS( WORK( 2*N+JE ) )+ABS( WORK( 3*N+JE ) ), $ ABS( WORK( 2*N+JE+1 ) )+ABS( WORK( 3*N+JE+1 ) ) ) END IF * DMIN = MAX( ULP*ACOEFA*ANORM, ULP*BCOEFA*BNORM, SAFMIN ) * * T * Triangular solve of (a A - b B) y = 0 * * T * (rowwise in (a A - b B) , or columnwise in (a A - b B) ) * IL2BY2 = .FALSE. * DO 160 J = JE + NW, N IF( IL2BY2 ) THEN IL2BY2 = .FALSE. GO TO 160 END IF * NA = 1 BDIAG( 1 ) = P( J, J ) IF( J.LT.N ) THEN IF( S( J+1, J ).NE.ZERO ) THEN IL2BY2 = .TRUE. BDIAG( 2 ) = P( J+1, J+1 ) NA = 2 END IF END IF * * Check whether scaling is necessary for dot products * XSCALE = ONE / MAX( ONE, XMAX ) TEMP = MAX( WORK( J ), WORK( N+J ), $ ACOEFA*WORK( J )+BCOEFA*WORK( N+J ) ) IF( IL2BY2 ) $ TEMP = MAX( TEMP, WORK( J+1 ), WORK( N+J+1 ), $ ACOEFA*WORK( J+1 )+BCOEFA*WORK( N+J+1 ) ) IF( TEMP.GT.BIGNUM*XSCALE ) THEN DO 90 JW = 0, NW - 1 DO 80 JR = JE, J - 1 WORK( ( JW+2 )*N+JR ) = XSCALE* $ WORK( ( JW+2 )*N+JR ) 80 CONTINUE 90 CONTINUE XMAX = XMAX*XSCALE END IF * * Compute dot products * * j-1 * SUM = sum conjg( a*S(k,j) - b*P(k,j) )*x(k) * k=je * * To reduce the op count, this is done as * * _ j-1 _ j-1 * a*conjg( sum S(k,j)*x(k) ) - b*conjg( sum P(k,j)*x(k) ) * k=je k=je * * which may cause underflow problems if A or B are close * to underflow. (E.g., less than SMALL.) * * DO 120 JW = 1, NW DO 110 JA = 1, NA SUMS( JA, JW ) = ZERO SUMP( JA, JW ) = ZERO * DO 100 JR = JE, J - 1 SUMS( JA, JW ) = SUMS( JA, JW ) + $ S( JR, J+JA-1 )* $ WORK( ( JW+1 )*N+JR ) SUMP( JA, JW ) = SUMP( JA, JW ) + $ P( JR, J+JA-1 )* $ WORK( ( JW+1 )*N+JR ) 100 CONTINUE 110 CONTINUE 120 CONTINUE * DO 130 JA = 1, NA IF( ILCPLX ) THEN SUM( JA, 1 ) = -ACOEF*SUMS( JA, 1 ) + $ BCOEFR*SUMP( JA, 1 ) - $ BCOEFI*SUMP( JA, 2 ) SUM( JA, 2 ) = -ACOEF*SUMS( JA, 2 ) + $ BCOEFR*SUMP( JA, 2 ) + $ BCOEFI*SUMP( JA, 1 ) ELSE SUM( JA, 1 ) = -ACOEF*SUMS( JA, 1 ) + $ BCOEFR*SUMP( JA, 1 ) END IF 130 CONTINUE * * T * Solve ( a A - b B ) y = SUM(,) * with scaling and perturbation of the denominator * CALL SLALN2( .TRUE., NA, NW, DMIN, ACOEF, S( J, J ), $ LDS, $ BDIAG( 1 ), BDIAG( 2 ), SUM, 2, BCOEFR, $ BCOEFI, WORK( 2*N+J ), N, SCALE, TEMP, $ IINFO ) IF( SCALE.LT.ONE ) THEN DO 150 JW = 0, NW - 1 DO 140 JR = JE, J - 1 WORK( ( JW+2 )*N+JR ) = SCALE* $ WORK( ( JW+2 )*N+JR ) 140 CONTINUE 150 CONTINUE XMAX = SCALE*XMAX END IF XMAX = MAX( XMAX, TEMP ) 160 CONTINUE * * Copy eigenvector to VL, back transforming if * HOWMNY='B'. * IEIG = IEIG + 1 IF( ILBACK ) THEN DO 170 JW = 0, NW - 1 CALL SGEMV( 'N', N, N+1-JE, ONE, VL( 1, JE ), LDVL, $ WORK( ( JW+2 )*N+JE ), 1, ZERO, $ WORK( ( JW+4 )*N+1 ), 1 ) 170 CONTINUE CALL SLACPY( ' ', N, NW, WORK( 4*N+1 ), N, VL( 1, $ JE ), $ LDVL ) IBEG = 1 ELSE CALL SLACPY( ' ', N, NW, WORK( 2*N+1 ), N, VL( 1, $ IEIG ), $ LDVL ) IBEG = JE END IF * * Scale eigenvector * XMAX = ZERO IF( ILCPLX ) THEN DO 180 J = IBEG, N XMAX = MAX( XMAX, ABS( VL( J, IEIG ) )+ $ ABS( VL( J, IEIG+1 ) ) ) 180 CONTINUE ELSE DO 190 J = IBEG, N XMAX = MAX( XMAX, ABS( VL( J, IEIG ) ) ) 190 CONTINUE END IF * IF( XMAX.GT.SAFMIN ) THEN XSCALE = ONE / XMAX * DO 210 JW = 0, NW - 1 DO 200 JR = IBEG, N VL( JR, IEIG+JW ) = XSCALE*VL( JR, IEIG+JW ) 200 CONTINUE 210 CONTINUE END IF IEIG = IEIG + NW - 1 * 220 CONTINUE END IF * * Right eigenvectors * IF( COMPR ) THEN IEIG = IM + 1 * * Main loop over eigenvalues * ILCPLX = .FALSE. DO 500 JE = N, 1, -1 * * Skip this iteration if (a) HOWMNY='S' and SELECT=.FALSE., or * (b) this would be the second of a complex pair. * Check for complex eigenvalue, so as to be sure of which * entry(-ies) of SELECT to look at -- if complex, SELECT(JE) * or SELECT(JE-1). * If this is a complex pair, the 2-by-2 diagonal block * corresponding to the eigenvalue is in rows/columns JE-1:JE * IF( ILCPLX ) THEN ILCPLX = .FALSE. GO TO 500 END IF NW = 1 IF( JE.GT.1 ) THEN IF( S( JE, JE-1 ).NE.ZERO ) THEN ILCPLX = .TRUE. NW = 2 END IF END IF IF( ILALL ) THEN ILCOMP = .TRUE. ELSE IF( ILCPLX ) THEN ILCOMP = SELECT( JE ) .OR. SELECT( JE-1 ) ELSE ILCOMP = SELECT( JE ) END IF IF( .NOT.ILCOMP ) $ GO TO 500 * * Decide if (a) singular pencil, (b) real eigenvalue, or * (c) complex eigenvalue. * IF( .NOT.ILCPLX ) THEN IF( ABS( S( JE, JE ) ).LE.SAFMIN .AND. $ ABS( P( JE, JE ) ).LE.SAFMIN ) THEN * * Singular matrix pencil -- unit eigenvector * IEIG = IEIG - 1 DO 230 JR = 1, N VR( JR, IEIG ) = ZERO 230 CONTINUE VR( IEIG, IEIG ) = ONE GO TO 500 END IF END IF * * Clear vector * DO 250 JW = 0, NW - 1 DO 240 JR = 1, N WORK( ( JW+2 )*N+JR ) = ZERO 240 CONTINUE 250 CONTINUE * * Compute coefficients in ( a A - b B ) x = 0 * a is ACOEF * b is BCOEFR + i*BCOEFI * IF( .NOT.ILCPLX ) THEN * * Real eigenvalue * TEMP = ONE / MAX( ABS( S( JE, JE ) )*ASCALE, $ ABS( P( JE, JE ) )*BSCALE, SAFMIN ) SALFAR = ( TEMP*S( JE, JE ) )*ASCALE SBETA = ( TEMP*P( JE, JE ) )*BSCALE ACOEF = SBETA*ASCALE BCOEFR = SALFAR*BSCALE BCOEFI = ZERO * * Scale to avoid underflow * SCALE = ONE LSA = ABS( SBETA ).GE.SAFMIN .AND. ABS( ACOEF ).LT.SMALL LSB = ABS( SALFAR ).GE.SAFMIN .AND. ABS( BCOEFR ).LT. $ SMALL IF( LSA ) $ SCALE = ( SMALL / ABS( SBETA ) )*MIN( ANORM, BIG ) IF( LSB ) $ SCALE = MAX( SCALE, ( SMALL / ABS( SALFAR ) )* $ MIN( BNORM, BIG ) ) IF( LSA .OR. LSB ) THEN SCALE = MIN( SCALE, ONE / $ ( SAFMIN*MAX( ONE, ABS( ACOEF ), $ ABS( BCOEFR ) ) ) ) IF( LSA ) THEN ACOEF = ASCALE*( SCALE*SBETA ) ELSE ACOEF = SCALE*ACOEF END IF IF( LSB ) THEN BCOEFR = BSCALE*( SCALE*SALFAR ) ELSE BCOEFR = SCALE*BCOEFR END IF END IF ACOEFA = ABS( ACOEF ) BCOEFA = ABS( BCOEFR ) * * First component is 1 * WORK( 2*N+JE ) = ONE XMAX = ONE * * Compute contribution from column JE of A and B to sum * (See "Further Details", above.) * DO 260 JR = 1, JE - 1 WORK( 2*N+JR ) = BCOEFR*P( JR, JE ) - $ ACOEF*S( JR, JE ) 260 CONTINUE ELSE * * Complex eigenvalue * CALL SLAG2( S( JE-1, JE-1 ), LDS, P( JE-1, JE-1 ), $ LDP, $ SAFMIN*SAFETY, ACOEF, TEMP, BCOEFR, TEMP2, $ BCOEFI ) IF( BCOEFI.EQ.ZERO ) THEN INFO = JE - 1 RETURN END IF * * Scale to avoid over/underflow * ACOEFA = ABS( ACOEF ) BCOEFA = ABS( BCOEFR ) + ABS( BCOEFI ) SCALE = ONE IF( ACOEFA*ULP.LT.SAFMIN .AND. ACOEFA.GE.SAFMIN ) $ SCALE = ( SAFMIN / ULP ) / ACOEFA IF( BCOEFA*ULP.LT.SAFMIN .AND. BCOEFA.GE.SAFMIN ) $ SCALE = MAX( SCALE, ( SAFMIN / ULP ) / BCOEFA ) IF( SAFMIN*ACOEFA.GT.ASCALE ) $ SCALE = ASCALE / ( SAFMIN*ACOEFA ) IF( SAFMIN*BCOEFA.GT.BSCALE ) $ SCALE = MIN( SCALE, BSCALE / ( SAFMIN*BCOEFA ) ) IF( SCALE.NE.ONE ) THEN ACOEF = SCALE*ACOEF ACOEFA = ABS( ACOEF ) BCOEFR = SCALE*BCOEFR BCOEFI = SCALE*BCOEFI BCOEFA = ABS( BCOEFR ) + ABS( BCOEFI ) END IF * * Compute first two components of eigenvector * and contribution to sums * TEMP = ACOEF*S( JE, JE-1 ) TEMP2R = ACOEF*S( JE, JE ) - BCOEFR*P( JE, JE ) TEMP2I = -BCOEFI*P( JE, JE ) IF( ABS( TEMP ).GE.ABS( TEMP2R )+ABS( TEMP2I ) ) THEN WORK( 2*N+JE ) = ONE WORK( 3*N+JE ) = ZERO WORK( 2*N+JE-1 ) = -TEMP2R / TEMP WORK( 3*N+JE-1 ) = -TEMP2I / TEMP ELSE WORK( 2*N+JE-1 ) = ONE WORK( 3*N+JE-1 ) = ZERO TEMP = ACOEF*S( JE-1, JE ) WORK( 2*N+JE ) = ( BCOEFR*P( JE-1, JE-1 )-ACOEF* $ S( JE-1, JE-1 ) ) / TEMP WORK( 3*N+JE ) = BCOEFI*P( JE-1, JE-1 ) / TEMP END IF * XMAX = MAX( ABS( WORK( 2*N+JE ) )+ABS( WORK( 3*N+JE ) ), $ ABS( WORK( 2*N+JE-1 ) )+ABS( WORK( 3*N+JE-1 ) ) ) * * Compute contribution from columns JE and JE-1 * of A and B to the sums. * CREALA = ACOEF*WORK( 2*N+JE-1 ) CIMAGA = ACOEF*WORK( 3*N+JE-1 ) CREALB = BCOEFR*WORK( 2*N+JE-1 ) - $ BCOEFI*WORK( 3*N+JE-1 ) CIMAGB = BCOEFI*WORK( 2*N+JE-1 ) + $ BCOEFR*WORK( 3*N+JE-1 ) CRE2A = ACOEF*WORK( 2*N+JE ) CIM2A = ACOEF*WORK( 3*N+JE ) CRE2B = BCOEFR*WORK( 2*N+JE ) - BCOEFI*WORK( 3*N+JE ) CIM2B = BCOEFI*WORK( 2*N+JE ) + BCOEFR*WORK( 3*N+JE ) DO 270 JR = 1, JE - 2 WORK( 2*N+JR ) = -CREALA*S( JR, JE-1 ) + $ CREALB*P( JR, JE-1 ) - $ CRE2A*S( JR, JE ) + CRE2B*P( JR, JE ) WORK( 3*N+JR ) = -CIMAGA*S( JR, JE-1 ) + $ CIMAGB*P( JR, JE-1 ) - $ CIM2A*S( JR, JE ) + CIM2B*P( JR, JE ) 270 CONTINUE END IF * DMIN = MAX( ULP*ACOEFA*ANORM, ULP*BCOEFA*BNORM, SAFMIN ) * * Columnwise triangular solve of (a A - b B) x = 0 * IL2BY2 = .FALSE. DO 370 J = JE - NW, 1, -1 * * If a 2-by-2 block, is in position j-1:j, wait until * next iteration to process it (when it will be j:j+1) * IF( .NOT.IL2BY2 .AND. J.GT.1 ) THEN IF( S( J, J-1 ).NE.ZERO ) THEN IL2BY2 = .TRUE. GO TO 370 END IF END IF BDIAG( 1 ) = P( J, J ) IF( IL2BY2 ) THEN NA = 2 BDIAG( 2 ) = P( J+1, J+1 ) ELSE NA = 1 END IF * * Compute x(j) (and x(j+1), if 2-by-2 block) * CALL SLALN2( .FALSE., NA, NW, DMIN, ACOEF, S( J, J ), $ LDS, BDIAG( 1 ), BDIAG( 2 ), WORK( 2*N+J ), $ N, BCOEFR, BCOEFI, SUM, 2, SCALE, TEMP, $ IINFO ) IF( SCALE.LT.ONE ) THEN * DO 290 JW = 0, NW - 1 DO 280 JR = 1, JE WORK( ( JW+2 )*N+JR ) = SCALE* $ WORK( ( JW+2 )*N+JR ) 280 CONTINUE 290 CONTINUE END IF XMAX = MAX( SCALE*XMAX, TEMP ) * DO 310 JW = 1, NW DO 300 JA = 1, NA WORK( ( JW+1 )*N+J+JA-1 ) = SUM( JA, JW ) 300 CONTINUE 310 CONTINUE * * w = w + x(j)*(a S(*,j) - b P(*,j) ) with scaling * IF( J.GT.1 ) THEN * * Check whether scaling is necessary for sum. * XSCALE = ONE / MAX( ONE, XMAX ) TEMP = ACOEFA*WORK( J ) + BCOEFA*WORK( N+J ) IF( IL2BY2 ) $ TEMP = MAX( TEMP, ACOEFA*WORK( J+1 )+BCOEFA* $ WORK( N+J+1 ) ) TEMP = MAX( TEMP, ACOEFA, BCOEFA ) IF( TEMP.GT.BIGNUM*XSCALE ) THEN * DO 330 JW = 0, NW - 1 DO 320 JR = 1, JE WORK( ( JW+2 )*N+JR ) = XSCALE* $ WORK( ( JW+2 )*N+JR ) 320 CONTINUE 330 CONTINUE XMAX = XMAX*XSCALE END IF * * Compute the contributions of the off-diagonals of * column j (and j+1, if 2-by-2 block) of A and B to the * sums. * * DO 360 JA = 1, NA IF( ILCPLX ) THEN CREALA = ACOEF*WORK( 2*N+J+JA-1 ) CIMAGA = ACOEF*WORK( 3*N+J+JA-1 ) CREALB = BCOEFR*WORK( 2*N+J+JA-1 ) - $ BCOEFI*WORK( 3*N+J+JA-1 ) CIMAGB = BCOEFI*WORK( 2*N+J+JA-1 ) + $ BCOEFR*WORK( 3*N+J+JA-1 ) DO 340 JR = 1, J - 1 WORK( 2*N+JR ) = WORK( 2*N+JR ) - $ CREALA*S( JR, J+JA-1 ) + $ CREALB*P( JR, J+JA-1 ) WORK( 3*N+JR ) = WORK( 3*N+JR ) - $ CIMAGA*S( JR, J+JA-1 ) + $ CIMAGB*P( JR, J+JA-1 ) 340 CONTINUE ELSE CREALA = ACOEF*WORK( 2*N+J+JA-1 ) CREALB = BCOEFR*WORK( 2*N+J+JA-1 ) DO 350 JR = 1, J - 1 WORK( 2*N+JR ) = WORK( 2*N+JR ) - $ CREALA*S( JR, J+JA-1 ) + $ CREALB*P( JR, J+JA-1 ) 350 CONTINUE END IF 360 CONTINUE END IF * IL2BY2 = .FALSE. 370 CONTINUE * * Copy eigenvector to VR, back transforming if * HOWMNY='B'. * IEIG = IEIG - NW IF( ILBACK ) THEN * DO 410 JW = 0, NW - 1 DO 380 JR = 1, N WORK( ( JW+4 )*N+JR ) = WORK( ( JW+2 )*N+1 )* $ VR( JR, 1 ) 380 CONTINUE * * A series of compiler directives to defeat * vectorization for the next loop * * DO 400 JC = 2, JE DO 390 JR = 1, N WORK( ( JW+4 )*N+JR ) = WORK( ( JW+4 )*N+JR ) + $ WORK( ( JW+2 )*N+JC )*VR( JR, JC ) 390 CONTINUE 400 CONTINUE 410 CONTINUE * DO 430 JW = 0, NW - 1 DO 420 JR = 1, N VR( JR, IEIG+JW ) = WORK( ( JW+4 )*N+JR ) 420 CONTINUE 430 CONTINUE * IEND = N ELSE DO 450 JW = 0, NW - 1 DO 440 JR = 1, N VR( JR, IEIG+JW ) = WORK( ( JW+2 )*N+JR ) 440 CONTINUE 450 CONTINUE * IEND = JE END IF * * Scale eigenvector * XMAX = ZERO IF( ILCPLX ) THEN DO 460 J = 1, IEND XMAX = MAX( XMAX, ABS( VR( J, IEIG ) )+ $ ABS( VR( J, IEIG+1 ) ) ) 460 CONTINUE ELSE DO 470 J = 1, IEND XMAX = MAX( XMAX, ABS( VR( J, IEIG ) ) ) 470 CONTINUE END IF * IF( XMAX.GT.SAFMIN ) THEN XSCALE = ONE / XMAX DO 490 JW = 0, NW - 1 DO 480 JR = 1, IEND VR( JR, IEIG+JW ) = XSCALE*VR( JR, IEIG+JW ) 480 CONTINUE 490 CONTINUE END IF 500 CONTINUE END IF * RETURN * * End of STGEVC * END