numeric-linalg
Educational material on the SciPy implementation of numerical linear algebra algorithms
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lapack/SRC/zsteqr.f | 15886B | -rw-r--r-- |
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*> \brief \b ZSTEQR * * =========== DOCUMENTATION =========== * * Online html documentation available at * http://www.netlib.org/lapack/explore-html/ * *> \htmlonly *> Download ZSTEQR + dependencies *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/zsteqr.f"> *> [TGZ]</a> *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/zsteqr.f"> *> [ZIP]</a> *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/zsteqr.f"> *> [TXT]</a> *> \endhtmlonly * * Definition: * =========== * * SUBROUTINE ZSTEQR( COMPZ, N, D, E, Z, LDZ, WORK, INFO ) * * .. Scalar Arguments .. * CHARACTER COMPZ * INTEGER INFO, LDZ, N * .. * .. Array Arguments .. * DOUBLE PRECISION D( * ), E( * ), WORK( * ) * COMPLEX*16 Z( LDZ, * ) * .. * * *> \par Purpose: * ============= *> *> \verbatim *> *> ZSTEQR computes all eigenvalues and, optionally, eigenvectors of a *> symmetric tridiagonal matrix using the implicit QL or QR method. *> The eigenvectors of a full or band complex Hermitian matrix can also *> be found if ZHETRD or ZHPTRD or ZHBTRD has been used to reduce this *> matrix to tridiagonal form. *> \endverbatim * * Arguments: * ========== * *> \param[in] COMPZ *> \verbatim *> COMPZ is CHARACTER*1 *> = 'N': Compute eigenvalues only. *> = 'V': Compute eigenvalues and eigenvectors of the original *> Hermitian matrix. On entry, Z must contain the *> unitary matrix used to reduce the original matrix *> to tridiagonal form. *> = 'I': Compute eigenvalues and eigenvectors of the *> tridiagonal matrix. Z is initialized to the identity *> matrix. *> \endverbatim *> *> \param[in] N *> \verbatim *> N is INTEGER *> The order of the matrix. N >= 0. *> \endverbatim *> *> \param[in,out] D *> \verbatim *> D is DOUBLE PRECISION array, dimension (N) *> On entry, the diagonal elements of the tridiagonal matrix. *> On exit, if INFO = 0, the eigenvalues in ascending order. *> \endverbatim *> *> \param[in,out] E *> \verbatim *> E is DOUBLE PRECISION array, dimension (N-1) *> On entry, the (n-1) subdiagonal elements of the tridiagonal *> matrix. *> On exit, E has been destroyed. *> \endverbatim *> *> \param[in,out] Z *> \verbatim *> Z is COMPLEX*16 array, dimension (LDZ, N) *> On entry, if COMPZ = 'V', then Z contains the unitary *> matrix used in the reduction to tridiagonal form. *> On exit, if INFO = 0, then if COMPZ = 'V', Z contains the *> orthonormal eigenvectors of the original Hermitian matrix, *> and if COMPZ = 'I', Z contains the orthonormal eigenvectors *> of the symmetric tridiagonal matrix. *> If COMPZ = 'N', then Z is not referenced. *> \endverbatim *> *> \param[in] LDZ *> \verbatim *> LDZ is INTEGER *> The leading dimension of the array Z. LDZ >= 1, and if *> eigenvectors are desired, then LDZ >= max(1,N). *> \endverbatim *> *> \param[out] WORK *> \verbatim *> WORK is DOUBLE PRECISION array, dimension (max(1,2*N-2)) *> If COMPZ = 'N', then WORK is not referenced. *> \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 algorithm has failed to find all the eigenvalues in *> a total of 30*N iterations; if INFO = i, then i *> elements of E have not converged to zero; on exit, D *> and E contain the elements of a symmetric tridiagonal *> matrix which is unitarily similar to the original *> matrix. *> \endverbatim * * Authors: * ======== * *> \author Univ. of Tennessee *> \author Univ. of California Berkeley *> \author Univ. of Colorado Denver *> \author NAG Ltd. * *> \ingroup steqr * * ===================================================================== SUBROUTINE ZSTEQR( COMPZ, N, D, E, Z, LDZ, 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 COMPZ INTEGER INFO, LDZ, N * .. * .. Array Arguments .. DOUBLE PRECISION D( * ), E( * ), WORK( * ) COMPLEX*16 Z( LDZ, * ) * .. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE, TWO, THREE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0, TWO = 2.0D0, $ THREE = 3.0D0 ) COMPLEX*16 CZERO, CONE PARAMETER ( CZERO = ( 0.0D0, 0.0D0 ), $ CONE = ( 1.0D0, 0.0D0 ) ) INTEGER MAXIT PARAMETER ( MAXIT = 30 ) * .. * .. Local Scalars .. INTEGER I, ICOMPZ, II, ISCALE, J, JTOT, K, L, L1, LEND, $ LENDM1, LENDP1, LENDSV, LM1, LSV, M, MM, MM1, $ NM1, NMAXIT DOUBLE PRECISION ANORM, B, C, EPS, EPS2, F, G, P, R, RT1, RT2, $ S, SAFMAX, SAFMIN, SSFMAX, SSFMIN, TST * .. * .. External Functions .. LOGICAL LSAME DOUBLE PRECISION DLAMCH, DLANST, DLAPY2 EXTERNAL LSAME, DLAMCH, DLANST, DLAPY2 * .. * .. External Subroutines .. EXTERNAL DLAE2, DLAEV2, DLARTG, DLASCL, DLASRT, $ XERBLA, $ ZLASET, ZLASR, ZSWAP * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, SIGN, SQRT * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 * IF( LSAME( COMPZ, 'N' ) ) THEN ICOMPZ = 0 ELSE IF( LSAME( COMPZ, 'V' ) ) THEN ICOMPZ = 1 ELSE IF( LSAME( COMPZ, 'I' ) ) THEN ICOMPZ = 2 ELSE ICOMPZ = -1 END IF IF( ICOMPZ.LT.0 ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 ELSE IF( ( LDZ.LT.1 ) .OR. ( ICOMPZ.GT.0 .AND. LDZ.LT.MAX( 1, $ N ) ) ) THEN INFO = -6 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'ZSTEQR', -INFO ) RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * IF( N.EQ.1 ) THEN IF( ICOMPZ.EQ.2 ) $ Z( 1, 1 ) = CONE RETURN END IF * * Determine the unit roundoff and over/underflow thresholds. * EPS = DLAMCH( 'E' ) EPS2 = EPS**2 SAFMIN = DLAMCH( 'S' ) SAFMAX = ONE / SAFMIN SSFMAX = SQRT( SAFMAX ) / THREE SSFMIN = SQRT( SAFMIN ) / EPS2 * * Compute the eigenvalues and eigenvectors of the tridiagonal * matrix. * IF( ICOMPZ.EQ.2 ) $ CALL ZLASET( 'Full', N, N, CZERO, CONE, Z, LDZ ) * NMAXIT = N*MAXIT JTOT = 0 * * Determine where the matrix splits and choose QL or QR iteration * for each block, according to whether top or bottom diagonal * element is smaller. * L1 = 1 NM1 = N - 1 * 10 CONTINUE IF( L1.GT.N ) $ GO TO 160 IF( L1.GT.1 ) $ E( L1-1 ) = ZERO IF( L1.LE.NM1 ) THEN DO 20 M = L1, NM1 TST = ABS( E( M ) ) IF( TST.EQ.ZERO ) $ GO TO 30 IF( TST.LE.( SQRT( ABS( D( M ) ) )*SQRT( ABS( D( M+ $ 1 ) ) ) )*EPS ) THEN E( M ) = ZERO GO TO 30 END IF 20 CONTINUE END IF M = N * 30 CONTINUE L = L1 LSV = L LEND = M LENDSV = LEND L1 = M + 1 IF( LEND.EQ.L ) $ GO TO 10 * * Scale submatrix in rows and columns L to LEND * ANORM = DLANST( 'I', LEND-L+1, D( L ), E( L ) ) ISCALE = 0 IF( ANORM.EQ.ZERO ) $ GO TO 10 IF( ANORM.GT.SSFMAX ) THEN ISCALE = 1 CALL DLASCL( 'G', 0, 0, ANORM, SSFMAX, LEND-L+1, 1, D( L ), $ N, $ INFO ) CALL DLASCL( 'G', 0, 0, ANORM, SSFMAX, LEND-L, 1, E( L ), N, $ INFO ) ELSE IF( ANORM.LT.SSFMIN ) THEN ISCALE = 2 CALL DLASCL( 'G', 0, 0, ANORM, SSFMIN, LEND-L+1, 1, D( L ), $ N, $ INFO ) CALL DLASCL( 'G', 0, 0, ANORM, SSFMIN, LEND-L, 1, E( L ), N, $ INFO ) END IF * * Choose between QL and QR iteration * IF( ABS( D( LEND ) ).LT.ABS( D( L ) ) ) THEN LEND = LSV L = LENDSV END IF * IF( LEND.GT.L ) THEN * * QL Iteration * * Look for small subdiagonal element. * 40 CONTINUE IF( L.NE.LEND ) THEN LENDM1 = LEND - 1 DO 50 M = L, LENDM1 TST = ABS( E( M ) )**2 IF( TST.LE.( EPS2*ABS( D( M ) ) )*ABS( D( M+1 ) )+ $ SAFMIN )GO TO 60 50 CONTINUE END IF * M = LEND * 60 CONTINUE IF( M.LT.LEND ) $ E( M ) = ZERO P = D( L ) IF( M.EQ.L ) $ GO TO 80 * * If remaining matrix is 2-by-2, use DLAE2 or SLAEV2 * to compute its eigensystem. * IF( M.EQ.L+1 ) THEN IF( ICOMPZ.GT.0 ) THEN CALL DLAEV2( D( L ), E( L ), D( L+1 ), RT1, RT2, C, $ S ) WORK( L ) = C WORK( N-1+L ) = S CALL ZLASR( 'R', 'V', 'B', N, 2, WORK( L ), $ WORK( N-1+L ), Z( 1, L ), LDZ ) ELSE CALL DLAE2( D( L ), E( L ), D( L+1 ), RT1, RT2 ) END IF D( L ) = RT1 D( L+1 ) = RT2 E( L ) = ZERO L = L + 2 IF( L.LE.LEND ) $ GO TO 40 GO TO 140 END IF * IF( JTOT.EQ.NMAXIT ) $ GO TO 140 JTOT = JTOT + 1 * * Form shift. * G = ( D( L+1 )-P ) / ( TWO*E( L ) ) R = DLAPY2( G, ONE ) G = D( M ) - P + ( E( L ) / ( G+SIGN( R, G ) ) ) * S = ONE C = ONE P = ZERO * * Inner loop * MM1 = M - 1 DO 70 I = MM1, L, -1 F = S*E( I ) B = C*E( I ) CALL DLARTG( G, F, C, S, R ) IF( I.NE.M-1 ) $ E( I+1 ) = R G = D( I+1 ) - P R = ( D( I )-G )*S + TWO*C*B P = S*R D( I+1 ) = G + P G = C*R - B * * If eigenvectors are desired, then save rotations. * IF( ICOMPZ.GT.0 ) THEN WORK( I ) = C WORK( N-1+I ) = -S END IF * 70 CONTINUE * * If eigenvectors are desired, then apply saved rotations. * IF( ICOMPZ.GT.0 ) THEN MM = M - L + 1 CALL ZLASR( 'R', 'V', 'B', N, MM, WORK( L ), $ WORK( N-1+L ), $ Z( 1, L ), LDZ ) END IF * D( L ) = D( L ) - P E( L ) = G GO TO 40 * * Eigenvalue found. * 80 CONTINUE D( L ) = P * L = L + 1 IF( L.LE.LEND ) $ GO TO 40 GO TO 140 * ELSE * * QR Iteration * * Look for small superdiagonal element. * 90 CONTINUE IF( L.NE.LEND ) THEN LENDP1 = LEND + 1 DO 100 M = L, LENDP1, -1 TST = ABS( E( M-1 ) )**2 IF( TST.LE.( EPS2*ABS( D( M ) ) )*ABS( D( M-1 ) )+ $ SAFMIN )GO TO 110 100 CONTINUE END IF * M = LEND * 110 CONTINUE IF( M.GT.LEND ) $ E( M-1 ) = ZERO P = D( L ) IF( M.EQ.L ) $ GO TO 130 * * If remaining matrix is 2-by-2, use DLAE2 or SLAEV2 * to compute its eigensystem. * IF( M.EQ.L-1 ) THEN IF( ICOMPZ.GT.0 ) THEN CALL DLAEV2( D( L-1 ), E( L-1 ), D( L ), RT1, RT2, C, $ S ) WORK( M ) = C WORK( N-1+M ) = S CALL ZLASR( 'R', 'V', 'F', N, 2, WORK( M ), $ WORK( N-1+M ), Z( 1, L-1 ), LDZ ) ELSE CALL DLAE2( D( L-1 ), E( L-1 ), D( L ), RT1, RT2 ) END IF D( L-1 ) = RT1 D( L ) = RT2 E( L-1 ) = ZERO L = L - 2 IF( L.GE.LEND ) $ GO TO 90 GO TO 140 END IF * IF( JTOT.EQ.NMAXIT ) $ GO TO 140 JTOT = JTOT + 1 * * Form shift. * G = ( D( L-1 )-P ) / ( TWO*E( L-1 ) ) R = DLAPY2( G, ONE ) G = D( M ) - P + ( E( L-1 ) / ( G+SIGN( R, G ) ) ) * S = ONE C = ONE P = ZERO * * Inner loop * LM1 = L - 1 DO 120 I = M, LM1 F = S*E( I ) B = C*E( I ) CALL DLARTG( G, F, C, S, R ) IF( I.NE.M ) $ E( I-1 ) = R G = D( I ) - P R = ( D( I+1 )-G )*S + TWO*C*B P = S*R D( I ) = G + P G = C*R - B * * If eigenvectors are desired, then save rotations. * IF( ICOMPZ.GT.0 ) THEN WORK( I ) = C WORK( N-1+I ) = S END IF * 120 CONTINUE * * If eigenvectors are desired, then apply saved rotations. * IF( ICOMPZ.GT.0 ) THEN MM = L - M + 1 CALL ZLASR( 'R', 'V', 'F', N, MM, WORK( M ), $ WORK( N-1+M ), $ Z( 1, M ), LDZ ) END IF * D( L ) = D( L ) - P E( LM1 ) = G GO TO 90 * * Eigenvalue found. * 130 CONTINUE D( L ) = P * L = L - 1 IF( L.GE.LEND ) $ GO TO 90 GO TO 140 * END IF * * Undo scaling if necessary * 140 CONTINUE IF( ISCALE.EQ.1 ) THEN CALL DLASCL( 'G', 0, 0, SSFMAX, ANORM, LENDSV-LSV+1, 1, $ D( LSV ), N, INFO ) CALL DLASCL( 'G', 0, 0, SSFMAX, ANORM, LENDSV-LSV, 1, $ E( LSV ), $ N, INFO ) ELSE IF( ISCALE.EQ.2 ) THEN CALL DLASCL( 'G', 0, 0, SSFMIN, ANORM, LENDSV-LSV+1, 1, $ D( LSV ), N, INFO ) CALL DLASCL( 'G', 0, 0, SSFMIN, ANORM, LENDSV-LSV, 1, $ E( LSV ), $ N, INFO ) END IF * * Check for no convergence to an eigenvalue after a total * of N*MAXIT iterations. * IF( JTOT.EQ.NMAXIT ) THEN DO 150 I = 1, N - 1 IF( E( I ).NE.ZERO ) $ INFO = INFO + 1 150 CONTINUE RETURN END IF GO TO 10 * * Order eigenvalues and eigenvectors. * 160 CONTINUE IF( ICOMPZ.EQ.0 ) THEN * * Use Quick Sort * CALL DLASRT( 'I', N, D, INFO ) * ELSE * * Use Selection Sort to minimize swaps of eigenvectors * DO 180 II = 2, N I = II - 1 K = I P = D( I ) DO 170 J = II, N IF( D( J ).LT.P ) THEN K = J P = D( J ) END IF 170 CONTINUE IF( K.NE.I ) THEN D( K ) = D( I ) D( I ) = P CALL ZSWAP( N, Z( 1, I ), 1, Z( 1, K ), 1 ) END IF 180 CONTINUE END IF RETURN * * End of ZSTEQR * END