SUBROUTINE DGBSV( N, KL, KU, NRHS, AB, LDAB, IPIV, B, LDB, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * March 31, 1993 * * .. Scalar Arguments .. INTEGER INFO, KL, KU, LDAB, LDB, N, NRHS * .. * .. Array Arguments .. INTEGER IPIV( * ) DOUBLE PRECISION AB( LDAB, * ), B( LDB, * ) * .. * * Purpose * ======= * * DGBSV computes the solution to a real system of linear equations * A * X = B, where A is a band matrix of order N with KL subdiagonals * and KU superdiagonals, and X and B are N-by-NRHS matrices. * * The LU decomposition with partial pivoting and row interchanges is * used to factor A as A = L * U, where L is a product of permutation * and unit lower triangular matrices with KL subdiagonals, and U is * upper triangular with KL+KU superdiagonals. The factored form of A * is then used to solve the system of equations A * X = B. * * Arguments * ========= * * N (input) INTEGER * The number of linear equations, i.e., the order of the * matrix A. N >= 0. * * KL (input) INTEGER * The number of subdiagonals within the band of A. KL >= 0. * * KU (input) INTEGER * The number of superdiagonals within the band of A. KU >= 0. * * NRHS (input) INTEGER * The number of right hand sides, i.e., the number of columns * of the matrix B. NRHS >= 0. * * AB (input/output) DOUBLE PRECISION array, dimension (LDAB,N) * On entry, the matrix A in band storage, in rows KL+1 to * 2*KL+KU+1; rows 1 to KL of the array need not be set. * The j-th column of A is stored in the j-th column of the * array AB as follows: * AB(KL+KU+1+i-j,j) = A(i,j) for max(1,j-KU)<=i<=min(N,j+KL) * On exit, details of the factorization: U is stored as an * upper triangular band matrix with KL+KU superdiagonals in * rows 1 to KL+KU+1, and the multipliers used during the * factorization are stored in rows KL+KU+2 to 2*KL+KU+1. * See below for further details. * * LDAB (input) INTEGER * The leading dimension of the array AB. LDAB >= 2*KL+KU+1. * * IPIV (output) INTEGER array, dimension (N) * The pivot indices that define the permutation matrix P; * row i of the matrix was interchanged with row IPIV(i). * * B (input/output) DOUBLE PRECISION array, dimension (LDB,NRHS) * On entry, the N-by-NRHS right hand side matrix B. * On exit, if INFO = 0, the N-by-NRHS solution matrix X. * * LDB (input) INTEGER * The leading dimension of the array B. LDB >= max(1,N). * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = i, U(i,i) is exactly zero. The factorization * has been completed, but the factor U is exactly * singular, and the solution has not been computed. * * Further Details * =============== * * The band storage scheme is illustrated by the following example, when * M = N = 6, KL = 2, KU = 1: * * On entry: On exit: * * * * * + + + * * * u14 u25 u36 * * * + + + + * * u13 u24 u35 u46 * * a12 a23 a34 a45 a56 * u12 u23 u34 u45 u56 * a11 a22 a33 a44 a55 a66 u11 u22 u33 u44 u55 u66 * a21 a32 a43 a54 a65 * m21 m32 m43 m54 m65 * * a31 a42 a53 a64 * * m31 m42 m53 m64 * * * * Array elements marked * are not used by the routine; elements marked * + need not be set on entry, but are required by the routine to store * elements of U because of fill-in resulting from the row interchanges. * * ===================================================================== * * .. External Subroutines .. EXTERNAL DGBTRF, DGBTRS, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 IF( N.LT.0 ) THEN INFO = -1 ELSE IF( KL.LT.0 ) THEN INFO = -2 ELSE IF( KU.LT.0 ) THEN INFO = -3 ELSE IF( NRHS.LT.0 ) THEN INFO = -4 ELSE IF( LDAB.LT.2*KL+KU+1 ) THEN INFO = -6 ELSE IF( LDB.LT.MAX( N, 1 ) ) THEN INFO = -9 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGBSV ', -INFO ) RETURN END IF * * Compute the LU factorization of the band matrix A. * CALL DGBTRF( N, N, KL, KU, AB, LDAB, IPIV, INFO ) IF( INFO.EQ.0 ) THEN * * Solve the system A*X = B, overwriting B with X. * CALL DGBTRS( 'No transpose', N, KL, KU, NRHS, AB, LDAB, IPIV, $ B, LDB, INFO ) END IF RETURN * * End of DGBSV * END SUBROUTINE DGBSVX( FACT, TRANS, N, KL, KU, NRHS, AB, LDAB, AFB, $ LDAFB, IPIV, EQUED, R, C, B, LDB, X, LDX, $ RCOND, FERR, BERR, WORK, IWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER EQUED, FACT, TRANS INTEGER INFO, KL, KU, LDAB, LDAFB, LDB, LDX, N, NRHS DOUBLE PRECISION RCOND * .. * .. Array Arguments .. INTEGER IPIV( * ), IWORK( * ) DOUBLE PRECISION AB( LDAB, * ), AFB( LDAFB, * ), B( LDB, * ), $ BERR( * ), C( * ), FERR( * ), R( * ), $ WORK( * ), X( LDX, * ) * .. * * Purpose * ======= * * DGBSVX uses the LU factorization to compute the solution to a real * system of linear equations A * X = B, A**T * X = B, or A**H * X = B, * where A is a band matrix of order N with KL subdiagonals and KU * superdiagonals, and X and B are N-by-NRHS matrices. * * Error bounds on the solution and a condition estimate are also * provided. * * Description * =========== * * The following steps are performed by this subroutine: * * 1. If FACT = 'E', real scaling factors are computed to equilibrate * the system: * TRANS = 'N': diag(R)*A*diag(C) *inv(diag(C))*X = diag(R)*B * TRANS = 'T': (diag(R)*A*diag(C))**T *inv(diag(R))*X = diag(C)*B * TRANS = 'C': (diag(R)*A*diag(C))**H *inv(diag(R))*X = diag(C)*B * Whether or not the system will be equilibrated depends on the * scaling of the matrix A, but if equilibration is used, A is * overwritten by diag(R)*A*diag(C) and B by diag(R)*B (if TRANS='N') * or diag(C)*B (if TRANS = 'T' or 'C'). * * 2. If FACT = 'N' or 'E', the LU decomposition is used to factor the * matrix A (after equilibration if FACT = 'E') as * A = L * U, * where L is a product of permutation and unit lower triangular * matrices with KL subdiagonals, and U is upper triangular with * KL+KU superdiagonals. * * 3. If some U(i,i)=0, so that U is exactly singular, then the routine * returns with INFO = i. Otherwise, the factored form of A is used * to estimate the condition number of the matrix A. If the * reciprocal of the condition number is less than machine precision, * INFO = N+1 is returned as a warning, but the routine still goes on * to solve for X and compute error bounds as described below. * * 4. The system of equations is solved for X using the factored form * of A. * * 5. Iterative refinement is applied to improve the computed solution * matrix and calculate error bounds and backward error estimates * for it. * * 6. If equilibration was used, the matrix X is premultiplied by * diag(C) (if TRANS = 'N') or diag(R) (if TRANS = 'T' or 'C') so * that it solves the original system before equilibration. * * Arguments * ========= * * FACT (input) CHARACTER*1 * Specifies whether or not the factored form of the matrix A is * supplied on entry, and if not, whether the matrix A should be * equilibrated before it is factored. * = 'F': On entry, AFB and IPIV contain the factored form of * A. If EQUED is not 'N', the matrix A has been * equilibrated with scaling factors given by R and C. * AB, AFB, and IPIV are not modified. * = 'N': The matrix A will be copied to AFB and factored. * = 'E': The matrix A will be equilibrated if necessary, then * copied to AFB and factored. * * TRANS (input) CHARACTER*1 * Specifies the form of the system of equations. * = 'N': A * X = B (No transpose) * = 'T': A**T * X = B (Transpose) * = 'C': A**H * X = B (Transpose) * * N (input) INTEGER * The number of linear equations, i.e., the order of the * matrix A. N >= 0. * * KL (input) INTEGER * The number of subdiagonals within the band of A. KL >= 0. * * KU (input) INTEGER * The number of superdiagonals within the band of A. KU >= 0. * * NRHS (input) INTEGER * The number of right hand sides, i.e., the number of columns * of the matrices B and X. NRHS >= 0. * * AB (input/output) DOUBLE PRECISION array, dimension (LDAB,N) * On entry, the matrix A in band storage, in rows 1 to KL+KU+1. * The j-th column of A is stored in the j-th column of the * array AB as follows: * AB(KU+1+i-j,j) = A(i,j) for max(1,j-KU)<=i<=min(N,j+kl) * * If FACT = 'F' and EQUED is not 'N', then A must have been * equilibrated by the scaling factors in R and/or C. AB is not * modified if FACT = 'F' or 'N', or if FACT = 'E' and * EQUED = 'N' on exit. * * On exit, if EQUED .ne. 'N', A is scaled as follows: * EQUED = 'R': A := diag(R) * A * EQUED = 'C': A := A * diag(C) * EQUED = 'B': A := diag(R) * A * diag(C). * * LDAB (input) INTEGER * The leading dimension of the array AB. LDAB >= KL+KU+1. * * AFB (input or output) DOUBLE PRECISION array, dimension (LDAFB,N) * If FACT = 'F', then AFB is an input argument and on entry * contains details of the LU factorization of the band matrix * A, as computed by DGBTRF. U is stored as an upper triangular * band matrix with KL+KU superdiagonals in rows 1 to KL+KU+1, * and the multipliers used during the factorization are stored * in rows KL+KU+2 to 2*KL+KU+1. If EQUED .ne. 'N', then AFB is * the factored form of the equilibrated matrix A. * * If FACT = 'N', then AFB is an output argument and on exit * returns details of the LU factorization of A. * * If FACT = 'E', then AFB is an output argument and on exit * returns details of the LU factorization of the equilibrated * matrix A (see the description of AB for the form of the * equilibrated matrix). * * LDAFB (input) INTEGER * The leading dimension of the array AFB. LDAFB >= 2*KL+KU+1. * * IPIV (input or output) INTEGER array, dimension (N) * If FACT = 'F', then IPIV is an input argument and on entry * contains the pivot indices from the factorization A = L*U * as computed by DGBTRF; row i of the matrix was interchanged * with row IPIV(i). * * If FACT = 'N', then IPIV is an output argument and on exit * contains the pivot indices from the factorization A = L*U * of the original matrix A. * * If FACT = 'E', then IPIV is an output argument and on exit * contains the pivot indices from the factorization A = L*U * of the equilibrated matrix A. * * EQUED (input or output) CHARACTER*1 * Specifies the form of equilibration that was done. * = 'N': No equilibration (always true if FACT = 'N'). * = 'R': Row equilibration, i.e., A has been premultiplied by * diag(R). * = 'C': Column equilibration, i.e., A has been postmultiplied * by diag(C). * = 'B': Both row and column equilibration, i.e., A has been * replaced by diag(R) * A * diag(C). * EQUED is an input argument if FACT = 'F'; otherwise, it is an * output argument. * * R (input or output) DOUBLE PRECISION array, dimension (N) * The row scale factors for A. If EQUED = 'R' or 'B', A is * multiplied on the left by diag(R); if EQUED = 'N' or 'C', R * is not accessed. R is an input argument if FACT = 'F'; * otherwise, R is an output argument. If FACT = 'F' and * EQUED = 'R' or 'B', each element of R must be positive. * * C (input or output) DOUBLE PRECISION array, dimension (N) * The column scale factors for A. If EQUED = 'C' or 'B', A is * multiplied on the right by diag(C); if EQUED = 'N' or 'R', C * is not accessed. C is an input argument if FACT = 'F'; * otherwise, C is an output argument. If FACT = 'F' and * EQUED = 'C' or 'B', each element of C must be positive. * * B (input/output) DOUBLE PRECISION array, dimension (LDB,NRHS) * On entry, the right hand side matrix B. * On exit, * if EQUED = 'N', B is not modified; * if TRANS = 'N' and EQUED = 'R' or 'B', B is overwritten by * diag(R)*B; * if TRANS = 'T' or 'C' and EQUED = 'C' or 'B', B is * overwritten by diag(C)*B. * * LDB (input) INTEGER * The leading dimension of the array B. LDB >= max(1,N). * * X (output) DOUBLE PRECISION array, dimension (LDX,NRHS) * If INFO = 0 or INFO = N+1, the N-by-NRHS solution matrix X * to the original system of equations. Note that A and B are * modified on exit if EQUED .ne. 'N', and the solution to the * equilibrated system is inv(diag(C))*X if TRANS = 'N' and * EQUED = 'C' or 'B', or inv(diag(R))*X if TRANS = 'T' or 'C' * and EQUED = 'R' or 'B'. * * LDX (input) INTEGER * The leading dimension of the array X. LDX >= max(1,N). * * RCOND (output) DOUBLE PRECISION * The estimate of the reciprocal condition number of the matrix * A after equilibration (if done). If RCOND is less than the * machine precision (in particular, if RCOND = 0), the matrix * is singular to working precision. This condition is * indicated by a return code of INFO > 0. * * FERR (output) DOUBLE PRECISION array, dimension (NRHS) * The estimated forward error bound for each solution vector * X(j) (the j-th column of the solution matrix X). * If XTRUE is the true solution corresponding to X(j), FERR(j) * is an estimated upper bound for the magnitude of the largest * element in (X(j) - XTRUE) divided by the magnitude of the * largest element in X(j). The estimate is as reliable as * the estimate for RCOND, and is almost always a slight * overestimate of the true error. * * BERR (output) DOUBLE PRECISION array, dimension (NRHS) * The componentwise relative backward error of each solution * vector X(j) (i.e., the smallest relative change in * any element of A or B that makes X(j) an exact solution). * * WORK (workspace/output) DOUBLE PRECISION array, dimension (3*N) * On exit, WORK(1) contains the reciprocal pivot growth * factor norm(A)/norm(U). The "max absolute element" norm is * used. If WORK(1) is much less than 1, then the stability * of the LU factorization of the (equilibrated) matrix A * could be poor. This also means that the solution X, condition * estimator RCOND, and forward error bound FERR could be * unreliable. If factorization fails with 0 0: if INFO = i, and i is * <= N: U(i,i) is exactly zero. The factorization * has been completed, but the factor U is exactly * singular, so the solution and error bounds * could not be computed. RCOND = 0 is returned. * = N+1: U is nonsingular, but RCOND is less than machine * precision, meaning that the matrix is singular * to working precision. Nevertheless, the * solution and error bounds are computed because * there are a number of situations where the * computed solution can be more accurate than the * value of RCOND would suggest. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL COLEQU, EQUIL, NOFACT, NOTRAN, ROWEQU CHARACTER NORM INTEGER I, INFEQU, J, J1, J2 DOUBLE PRECISION AMAX, ANORM, BIGNUM, COLCND, RCMAX, RCMIN, $ ROWCND, RPVGRW, SMLNUM * .. * .. External Functions .. LOGICAL LSAME DOUBLE PRECISION DLAMCH, DLANGB, DLANTB EXTERNAL LSAME, DLAMCH, DLANGB, DLANTB * .. * .. External Subroutines .. EXTERNAL DCOPY, DGBCON, DGBEQU, DGBRFS, DGBTRF, DGBTRS, $ DLACPY, DLAQGB, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, MIN * .. * .. Executable Statements .. * INFO = 0 NOFACT = LSAME( FACT, 'N' ) EQUIL = LSAME( FACT, 'E' ) NOTRAN = LSAME( TRANS, 'N' ) IF( NOFACT .OR. EQUIL ) THEN EQUED = 'N' ROWEQU = .FALSE. COLEQU = .FALSE. ELSE ROWEQU = LSAME( EQUED, 'R' ) .OR. LSAME( EQUED, 'B' ) COLEQU = LSAME( EQUED, 'C' ) .OR. LSAME( EQUED, 'B' ) SMLNUM = DLAMCH( 'Safe minimum' ) BIGNUM = ONE / SMLNUM END IF * * Test the input parameters. * IF( .NOT.NOFACT .AND. .NOT.EQUIL .AND. .NOT.LSAME( FACT, 'F' ) ) $ THEN INFO = -1 ELSE IF( .NOT.NOTRAN .AND. .NOT.LSAME( TRANS, 'T' ) .AND. .NOT. $ LSAME( TRANS, 'C' ) ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( KL.LT.0 ) THEN INFO = -4 ELSE IF( KU.LT.0 ) THEN INFO = -5 ELSE IF( NRHS.LT.0 ) THEN INFO = -6 ELSE IF( LDAB.LT.KL+KU+1 ) THEN INFO = -8 ELSE IF( LDAFB.LT.2*KL+KU+1 ) THEN INFO = -10 ELSE IF( LSAME( FACT, 'F' ) .AND. .NOT. $ ( ROWEQU .OR. COLEQU .OR. LSAME( EQUED, 'N' ) ) ) THEN INFO = -12 ELSE IF( ROWEQU ) THEN RCMIN = BIGNUM RCMAX = ZERO DO 10 J = 1, N RCMIN = MIN( RCMIN, R( J ) ) RCMAX = MAX( RCMAX, R( J ) ) 10 CONTINUE IF( RCMIN.LE.ZERO ) THEN INFO = -13 ELSE IF( N.GT.0 ) THEN ROWCND = MAX( RCMIN, SMLNUM ) / MIN( RCMAX, BIGNUM ) ELSE ROWCND = ONE END IF END IF IF( COLEQU .AND. INFO.EQ.0 ) THEN RCMIN = BIGNUM RCMAX = ZERO DO 20 J = 1, N RCMIN = MIN( RCMIN, C( J ) ) RCMAX = MAX( RCMAX, C( J ) ) 20 CONTINUE IF( RCMIN.LE.ZERO ) THEN INFO = -14 ELSE IF( N.GT.0 ) THEN COLCND = MAX( RCMIN, SMLNUM ) / MIN( RCMAX, BIGNUM ) ELSE COLCND = ONE END IF END IF IF( INFO.EQ.0 ) THEN IF( LDB.LT.MAX( 1, N ) ) THEN INFO = -16 ELSE IF( LDX.LT.MAX( 1, N ) ) THEN INFO = -18 END IF END IF END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGBSVX', -INFO ) RETURN END IF * IF( EQUIL ) THEN * * Compute row and column scalings to equilibrate the matrix A. * CALL DGBEQU( N, N, KL, KU, AB, LDAB, R, C, ROWCND, COLCND, $ AMAX, INFEQU ) IF( INFEQU.EQ.0 ) THEN * * Equilibrate the matrix. * CALL DLAQGB( N, N, KL, KU, AB, LDAB, R, C, ROWCND, COLCND, $ AMAX, EQUED ) ROWEQU = LSAME( EQUED, 'R' ) .OR. LSAME( EQUED, 'B' ) COLEQU = LSAME( EQUED, 'C' ) .OR. LSAME( EQUED, 'B' ) END IF END IF * * Scale the right hand side. * IF( NOTRAN ) THEN IF( ROWEQU ) THEN DO 40 J = 1, NRHS DO 30 I = 1, N B( I, J ) = R( I )*B( I, J ) 30 CONTINUE 40 CONTINUE END IF ELSE IF( COLEQU ) THEN DO 60 J = 1, NRHS DO 50 I = 1, N B( I, J ) = C( I )*B( I, J ) 50 CONTINUE 60 CONTINUE END IF * IF( NOFACT .OR. EQUIL ) THEN * * Compute the LU factorization of the band matrix A. * DO 70 J = 1, N J1 = MAX( J-KU, 1 ) J2 = MIN( J+KL, N ) CALL DCOPY( J2-J1+1, AB( KU+1-J+J1, J ), 1, $ AFB( KL+KU+1-J+J1, J ), 1 ) 70 CONTINUE * CALL DGBTRF( N, N, KL, KU, AFB, LDAFB, IPIV, INFO ) * * Return if INFO is non-zero. * IF( INFO.NE.0 ) THEN IF( INFO.GT.0 ) THEN * * Compute the reciprocal pivot growth factor of the * leading rank-deficient INFO columns of A. * ANORM = ZERO DO 90 J = 1, INFO DO 80 I = MAX( KU+2-J, 1 ), $ MIN( N+KU+1-J, KL+KU+1 ) ANORM = MAX( ANORM, ABS( AB( I, J ) ) ) 80 CONTINUE 90 CONTINUE RPVGRW = DLANTB( 'M', 'U', 'N', INFO, $ MIN( INFO-1, KL+KU ), AFB( MAX( 1, $ KL+KU+2-INFO ), 1 ), LDAFB, WORK ) IF( RPVGRW.EQ.ZERO ) THEN RPVGRW = ONE ELSE RPVGRW = ANORM / RPVGRW END IF WORK( 1 ) = RPVGRW RCOND = ZERO END IF RETURN END IF END IF * * Compute the norm of the matrix A and the * reciprocal pivot growth factor RPVGRW. * IF( NOTRAN ) THEN NORM = '1' ELSE NORM = 'I' END IF ANORM = DLANGB( NORM, N, KL, KU, AB, LDAB, WORK ) RPVGRW = DLANTB( 'M', 'U', 'N', N, KL+KU, AFB, LDAFB, WORK ) IF( RPVGRW.EQ.ZERO ) THEN RPVGRW = ONE ELSE RPVGRW = DLANGB( 'M', N, KL, KU, AB, LDAB, WORK ) / RPVGRW END IF * * Compute the reciprocal of the condition number of A. * CALL DGBCON( NORM, N, KL, KU, AFB, LDAFB, IPIV, ANORM, RCOND, $ WORK, IWORK, INFO ) * * Set INFO = N+1 if the matrix is singular to working precision. * IF( RCOND.LT.DLAMCH( 'Epsilon' ) ) $ INFO = N + 1 * * Compute the solution matrix X. * CALL DLACPY( 'Full', N, NRHS, B, LDB, X, LDX ) CALL DGBTRS( TRANS, N, KL, KU, NRHS, AFB, LDAFB, IPIV, X, LDX, $ INFO ) * * Use iterative refinement to improve the computed solution and * compute error bounds and backward error estimates for it. * CALL DGBRFS( TRANS, N, KL, KU, NRHS, AB, LDAB, AFB, LDAFB, IPIV, $ B, LDB, X, LDX, FERR, BERR, WORK, IWORK, INFO ) * * Transform the solution matrix X to a solution of the original * system. * IF( NOTRAN ) THEN IF( COLEQU ) THEN DO 110 J = 1, NRHS DO 100 I = 1, N X( I, J ) = C( I )*X( I, J ) 100 CONTINUE 110 CONTINUE DO 120 J = 1, NRHS FERR( J ) = FERR( J ) / COLCND 120 CONTINUE END IF ELSE IF( ROWEQU ) THEN DO 140 J = 1, NRHS DO 130 I = 1, N X( I, J ) = R( I )*X( I, J ) 130 CONTINUE 140 CONTINUE DO 150 J = 1, NRHS FERR( J ) = FERR( J ) / ROWCND 150 CONTINUE END IF * WORK( 1 ) = RPVGRW RETURN * * End of DGBSVX * END SUBROUTINE DGEES( JOBVS, SORT, SELECT, N, A, LDA, SDIM, WR, WI, $ VS, LDVS, WORK, LWORK, BWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBVS, SORT INTEGER INFO, LDA, LDVS, LWORK, N, SDIM * .. * .. Array Arguments .. LOGICAL BWORK( * ) DOUBLE PRECISION A( LDA, * ), VS( LDVS, * ), WI( * ), WORK( * ), $ WR( * ) * .. * .. Function Arguments .. LOGICAL SELECT EXTERNAL SELECT * .. * * Purpose * ======= * * DGEES computes for an N-by-N real nonsymmetric matrix A, the * eigenvalues, the real Schur form T, and, optionally, the matrix of * Schur vectors Z. This gives the Schur factorization A = Z*T*(Z**T). * * Optionally, it also orders the eigenvalues on the diagonal of the * real Schur form so that selected eigenvalues are at the top left. * The leading columns of Z then form an orthonormal basis for the * invariant subspace corresponding to the selected eigenvalues. * * A matrix is in real Schur form if it is upper quasi-triangular with * 1-by-1 and 2-by-2 blocks. 2-by-2 blocks will be standardized in the * form * [ a b ] * [ c a ] * * where b*c < 0. The eigenvalues of such a block are a +- sqrt(bc). * * Arguments * ========= * * JOBVS (input) CHARACTER*1 * = 'N': Schur vectors are not computed; * = 'V': Schur vectors are computed. * * SORT (input) CHARACTER*1 * Specifies whether or not to order the eigenvalues on the * diagonal of the Schur form. * = 'N': Eigenvalues are not ordered; * = 'S': Eigenvalues are ordered (see SELECT). * * SELECT (input) LOGICAL FUNCTION of two DOUBLE PRECISION arguments * SELECT must be declared EXTERNAL in the calling subroutine. * If SORT = 'S', SELECT is used to select eigenvalues to sort * to the top left of the Schur form. * If SORT = 'N', SELECT is not referenced. * An eigenvalue WR(j)+sqrt(-1)*WI(j) is selected if * SELECT(WR(j),WI(j)) is true; i.e., if either one of a complex * conjugate pair of eigenvalues is selected, then both complex * eigenvalues are selected. * Note that a selected complex eigenvalue may no longer * satisfy SELECT(WR(j),WI(j)) = .TRUE. after ordering, since * ordering may change the value of complex eigenvalues * (especially if the eigenvalue is ill-conditioned); in this * case INFO is set to N+2 (see INFO below). * * N (input) INTEGER * The order of the matrix A. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the N-by-N matrix A. * On exit, A has been overwritten by its real Schur form T. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * SDIM (output) INTEGER * If SORT = 'N', SDIM = 0. * If SORT = 'S', SDIM = number of eigenvalues (after sorting) * for which SELECT is true. (Complex conjugate * pairs for which SELECT is true for either * eigenvalue count as 2.) * * WR (output) DOUBLE PRECISION array, dimension (N) * WI (output) DOUBLE PRECISION array, dimension (N) * WR and WI contain the real and imaginary parts, * respectively, of the computed eigenvalues in the same order * that they appear on the diagonal of the output Schur form T. * Complex conjugate pairs of eigenvalues will appear * consecutively with the eigenvalue having the positive * imaginary part first. * * VS (output) DOUBLE PRECISION array, dimension (LDVS,N) * If JOBVS = 'V', VS contains the orthogonal matrix Z of Schur * vectors. * If JOBVS = 'N', VS is not referenced. * * LDVS (input) INTEGER * The leading dimension of the array VS. LDVS >= 1; if * JOBVS = 'V', LDVS >= N. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) contains the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= max(1,3*N). * For good performance, LWORK must generally be larger. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * BWORK (workspace) LOGICAL array, dimension (N) * Not referenced if SORT = 'N'. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: if INFO = i, and i is * <= N: the QR algorithm failed to compute all the * eigenvalues; elements 1:ILO-1 and i+1:N of WR and WI * contain those eigenvalues which have converged; if * JOBVS = 'V', VS contains the matrix which reduces A * to its partially converged Schur form. * = N+1: the eigenvalues could not be reordered because some * eigenvalues were too close to separate (the problem * is very ill-conditioned); * = N+2: after reordering, roundoff changed values of some * complex eigenvalues so that leading eigenvalues in * the Schur form no longer satisfy SELECT=.TRUE. This * could also be caused by underflow due to scaling. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. LOGICAL CURSL, LASTSL, LQUERY, LST2SL, SCALEA, WANTST, $ WANTVS INTEGER HSWORK, I, I1, I2, IBAL, ICOND, IERR, IEVAL, $ IHI, ILO, INXT, IP, ITAU, IWRK, K, MAXB, $ MAXWRK, MINWRK DOUBLE PRECISION ANRM, BIGNUM, CSCALE, EPS, S, SEP, SMLNUM * .. * .. Local Arrays .. INTEGER IDUM( 1 ) DOUBLE PRECISION DUM( 1 ) * .. * .. External Subroutines .. EXTERNAL DCOPY, DGEBAK, DGEBAL, DGEHRD, DHSEQR, DLACPY, $ DLASCL, DORGHR, DSWAP, DTRSEN, XERBLA * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANGE EXTERNAL LSAME, ILAENV, DLAMCH, DLANGE * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN, SQRT * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 LQUERY = ( LWORK.EQ.-1 ) WANTVS = LSAME( JOBVS, 'V' ) WANTST = LSAME( SORT, 'S' ) IF( ( .NOT.WANTVS ) .AND. ( .NOT.LSAME( JOBVS, 'N' ) ) ) THEN INFO = -1 ELSE IF( ( .NOT.WANTST ) .AND. ( .NOT.LSAME( SORT, 'N' ) ) ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -4 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -6 ELSE IF( LDVS.LT.1 .OR. ( WANTVS .AND. LDVS.LT.N ) ) THEN INFO = -11 END IF * * Compute workspace * (Note: Comments in the code beginning "Workspace:" describe the * minimal amount of workspace needed at that point in the code, * as well as the preferred amount for good performance. * NB refers to the optimal block size for the immediately * following subroutine, as returned by ILAENV. * HSWORK refers to the workspace preferred by DHSEQR, as * calculated below. HSWORK is computed assuming ILO=1 and IHI=N, * the worst case.) * MINWRK = 1 IF( INFO.EQ.0 .AND. ( LWORK.GE.1 .OR. LQUERY ) ) THEN MAXWRK = 2*N + N*ILAENV( 1, 'DGEHRD', ' ', N, 1, N, 0 ) MINWRK = MAX( 1, 3*N ) IF( .NOT.WANTVS ) THEN MAXB = MAX( ILAENV( 8, 'DHSEQR', 'SN', N, 1, N, -1 ), 2 ) K = MIN( MAXB, N, MAX( 2, ILAENV( 4, 'DHSEQR', 'SN', N, 1, $ N, -1 ) ) ) HSWORK = MAX( K*( K+2 ), 2*N ) MAXWRK = MAX( MAXWRK, N+HSWORK, 1 ) ELSE MAXWRK = MAX( MAXWRK, 2*N+( N-1 )* $ ILAENV( 1, 'DORGHR', ' ', N, 1, N, -1 ) ) MAXB = MAX( ILAENV( 8, 'DHSEQR', 'EN', N, 1, N, -1 ), 2 ) K = MIN( MAXB, N, MAX( 2, ILAENV( 4, 'DHSEQR', 'EN', N, 1, $ N, -1 ) ) ) HSWORK = MAX( K*( K+2 ), 2*N ) MAXWRK = MAX( MAXWRK, N+HSWORK, 1 ) END IF WORK( 1 ) = MAXWRK END IF IF( LWORK.LT.MINWRK .AND. .NOT.LQUERY ) THEN INFO = -13 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGEES ', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) THEN SDIM = 0 RETURN END IF * * Get machine constants * EPS = DLAMCH( 'P' ) SMLNUM = DLAMCH( 'S' ) BIGNUM = ONE / SMLNUM CALL DLABAD( SMLNUM, BIGNUM ) SMLNUM = SQRT( SMLNUM ) / EPS BIGNUM = ONE / SMLNUM * * Scale A if max element outside range [SMLNUM,BIGNUM] * ANRM = DLANGE( 'M', N, N, A, LDA, DUM ) SCALEA = .FALSE. IF( ANRM.GT.ZERO .AND. ANRM.LT.SMLNUM ) THEN SCALEA = .TRUE. CSCALE = SMLNUM ELSE IF( ANRM.GT.BIGNUM ) THEN SCALEA = .TRUE. CSCALE = BIGNUM END IF IF( SCALEA ) $ CALL DLASCL( 'G', 0, 0, ANRM, CSCALE, N, N, A, LDA, IERR ) * * Permute the matrix to make it more nearly triangular * (Workspace: need N) * IBAL = 1 CALL DGEBAL( 'P', N, A, LDA, ILO, IHI, WORK( IBAL ), IERR ) * * Reduce to upper Hessenberg form * (Workspace: need 3*N, prefer 2*N+N*NB) * ITAU = N + IBAL IWRK = N + ITAU CALL DGEHRD( N, ILO, IHI, A, LDA, WORK( ITAU ), WORK( IWRK ), $ LWORK-IWRK+1, IERR ) * IF( WANTVS ) THEN * * Copy Householder vectors to VS * CALL DLACPY( 'L', N, N, A, LDA, VS, LDVS ) * * Generate orthogonal matrix in VS * (Workspace: need 3*N-1, prefer 2*N+(N-1)*NB) * CALL DORGHR( N, ILO, IHI, VS, LDVS, WORK( ITAU ), WORK( IWRK ), $ LWORK-IWRK+1, IERR ) END IF * SDIM = 0 * * Perform QR iteration, accumulating Schur vectors in VS if desired * (Workspace: need N+1, prefer N+HSWORK (see comments) ) * IWRK = ITAU CALL DHSEQR( 'S', JOBVS, N, ILO, IHI, A, LDA, WR, WI, VS, LDVS, $ WORK( IWRK ), LWORK-IWRK+1, IEVAL ) IF( IEVAL.GT.0 ) $ INFO = IEVAL * * Sort eigenvalues if desired * IF( WANTST .AND. INFO.EQ.0 ) THEN IF( SCALEA ) THEN CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, N, 1, WR, N, IERR ) CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, N, 1, WI, N, IERR ) END IF DO 10 I = 1, N BWORK( I ) = SELECT( WR( I ), WI( I ) ) 10 CONTINUE * * Reorder eigenvalues and transform Schur vectors * (Workspace: none needed) * CALL DTRSEN( 'N', JOBVS, BWORK, N, A, LDA, VS, LDVS, WR, WI, $ SDIM, S, SEP, WORK( IWRK ), LWORK-IWRK+1, IDUM, 1, $ ICOND ) IF( ICOND.GT.0 ) $ INFO = N + ICOND END IF * IF( WANTVS ) THEN * * Undo balancing * (Workspace: need N) * CALL DGEBAK( 'P', 'R', N, ILO, IHI, WORK( IBAL ), N, VS, LDVS, $ IERR ) END IF * IF( SCALEA ) THEN * * Undo scaling for the Schur form of A * CALL DLASCL( 'H', 0, 0, CSCALE, ANRM, N, N, A, LDA, IERR ) CALL DCOPY( N, A, LDA+1, WR, 1 ) IF( CSCALE.EQ.SMLNUM ) THEN * * If scaling back towards underflow, adjust WI if an * offdiagonal element of a 2-by-2 block in the Schur form * underflows. * IF( IEVAL.GT.0 ) THEN I1 = IEVAL + 1 I2 = IHI - 1 CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, ILO-1, 1, WI, $ MAX( ILO-1, 1 ), IERR ) ELSE IF( WANTST ) THEN I1 = 1 I2 = N - 1 ELSE I1 = ILO I2 = IHI - 1 END IF INXT = I1 - 1 DO 20 I = I1, I2 IF( I.LT.INXT ) $ GO TO 20 IF( WI( I ).EQ.ZERO ) THEN INXT = I + 1 ELSE IF( A( I+1, I ).EQ.ZERO ) THEN WI( I ) = ZERO WI( I+1 ) = ZERO ELSE IF( A( I+1, I ).NE.ZERO .AND. A( I, I+1 ).EQ. $ ZERO ) THEN WI( I ) = ZERO WI( I+1 ) = ZERO IF( I.GT.1 ) $ CALL DSWAP( I-1, A( 1, I ), 1, A( 1, I+1 ), 1 ) IF( N.GT.I+1 ) $ CALL DSWAP( N-I-1, A( I, I+2 ), LDA, $ A( I+1, I+2 ), LDA ) CALL DSWAP( N, VS( 1, I ), 1, VS( 1, I+1 ), 1 ) A( I, I+1 ) = A( I+1, I ) A( I+1, I ) = ZERO END IF INXT = I + 2 END IF 20 CONTINUE END IF * * Undo scaling for the imaginary part of the eigenvalues * CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, N-IEVAL, 1, $ WI( IEVAL+1 ), MAX( N-IEVAL, 1 ), IERR ) END IF * IF( WANTST .AND. INFO.EQ.0 ) THEN * * Check if reordering successful * LASTSL = .TRUE. LST2SL = .TRUE. SDIM = 0 IP = 0 DO 30 I = 1, N CURSL = SELECT( WR( I ), WI( I ) ) IF( WI( I ).EQ.ZERO ) THEN IF( CURSL ) $ SDIM = SDIM + 1 IP = 0 IF( CURSL .AND. .NOT.LASTSL ) $ INFO = N + 2 ELSE IF( IP.EQ.1 ) THEN * * Last eigenvalue of conjugate pair * CURSL = CURSL .OR. LASTSL LASTSL = CURSL IF( CURSL ) $ SDIM = SDIM + 2 IP = -1 IF( CURSL .AND. .NOT.LST2SL ) $ INFO = N + 2 ELSE * * First eigenvalue of conjugate pair * IP = 1 END IF END IF LST2SL = LASTSL LASTSL = CURSL 30 CONTINUE END IF * WORK( 1 ) = MAXWRK RETURN * * End of DGEES * END SUBROUTINE DGEESX( JOBVS, SORT, SELECT, SENSE, N, A, LDA, SDIM, $ WR, WI, VS, LDVS, RCONDE, RCONDV, WORK, LWORK, $ IWORK, LIWORK, BWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBVS, SENSE, SORT INTEGER INFO, LDA, LDVS, LIWORK, LWORK, N, SDIM DOUBLE PRECISION RCONDE, RCONDV * .. * .. Array Arguments .. LOGICAL BWORK( * ) INTEGER IWORK( * ) DOUBLE PRECISION A( LDA, * ), VS( LDVS, * ), WI( * ), WORK( * ), $ WR( * ) * .. * .. Function Arguments .. LOGICAL SELECT EXTERNAL SELECT * .. * * Purpose * ======= * * DGEESX computes for an N-by-N real nonsymmetric matrix A, the * eigenvalues, the real Schur form T, and, optionally, the matrix of * Schur vectors Z. This gives the Schur factorization A = Z*T*(Z**T). * * Optionally, it also orders the eigenvalues on the diagonal of the * real Schur form so that selected eigenvalues are at the top left; * computes a reciprocal condition number for the average of the * selected eigenvalues (RCONDE); and computes a reciprocal condition * number for the right invariant subspace corresponding to the * selected eigenvalues (RCONDV). The leading columns of Z form an * orthonormal basis for this invariant subspace. * * For further explanation of the reciprocal condition numbers RCONDE * and RCONDV, see Section 4.10 of the LAPACK Users' Guide (where * these quantities are called s and sep respectively). * * A real matrix is in real Schur form if it is upper quasi-triangular * with 1-by-1 and 2-by-2 blocks. 2-by-2 blocks will be standardized in * the form * [ a b ] * [ c a ] * * where b*c < 0. The eigenvalues of such a block are a +- sqrt(bc). * * Arguments * ========= * * JOBVS (input) CHARACTER*1 * = 'N': Schur vectors are not computed; * = 'V': Schur vectors are computed. * * SORT (input) CHARACTER*1 * Specifies whether or not to order the eigenvalues on the * diagonal of the Schur form. * = 'N': Eigenvalues are not ordered; * = 'S': Eigenvalues are ordered (see SELECT). * * SELECT (input) LOGICAL FUNCTION of two DOUBLE PRECISION arguments * SELECT must be declared EXTERNAL in the calling subroutine. * If SORT = 'S', SELECT is used to select eigenvalues to sort * to the top left of the Schur form. * If SORT = 'N', SELECT is not referenced. * An eigenvalue WR(j)+sqrt(-1)*WI(j) is selected if * SELECT(WR(j),WI(j)) is true; i.e., if either one of a * complex conjugate pair of eigenvalues is selected, then both * are. Note that a selected complex eigenvalue may no longer * satisfy SELECT(WR(j),WI(j)) = .TRUE. after ordering, since * ordering may change the value of complex eigenvalues * (especially if the eigenvalue is ill-conditioned); in this * case INFO may be set to N+3 (see INFO below). * * SENSE (input) CHARACTER*1 * Determines which reciprocal condition numbers are computed. * = 'N': None are computed; * = 'E': Computed for average of selected eigenvalues only; * = 'V': Computed for selected right invariant subspace only; * = 'B': Computed for both. * If SENSE = 'E', 'V' or 'B', SORT must equal 'S'. * * N (input) INTEGER * The order of the matrix A. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA, N) * On entry, the N-by-N matrix A. * On exit, A is overwritten by its real Schur form T. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * SDIM (output) INTEGER * If SORT = 'N', SDIM = 0. * If SORT = 'S', SDIM = number of eigenvalues (after sorting) * for which SELECT is true. (Complex conjugate * pairs for which SELECT is true for either * eigenvalue count as 2.) * * WR (output) DOUBLE PRECISION array, dimension (N) * WI (output) DOUBLE PRECISION array, dimension (N) * WR and WI contain the real and imaginary parts, respectively, * of the computed eigenvalues, in the same order that they * appear on the diagonal of the output Schur form T. Complex * conjugate pairs of eigenvalues appear consecutively with the * eigenvalue having the positive imaginary part first. * * VS (output) DOUBLE PRECISION array, dimension (LDVS,N) * If JOBVS = 'V', VS contains the orthogonal matrix Z of Schur * vectors. * If JOBVS = 'N', VS is not referenced. * * LDVS (input) INTEGER * The leading dimension of the array VS. LDVS >= 1, and if * JOBVS = 'V', LDVS >= N. * * RCONDE (output) DOUBLE PRECISION * If SENSE = 'E' or 'B', RCONDE contains the reciprocal * condition number for the average of the selected eigenvalues. * Not referenced if SENSE = 'N' or 'V'. * * RCONDV (output) DOUBLE PRECISION * If SENSE = 'V' or 'B', RCONDV contains the reciprocal * condition number for the selected right invariant subspace. * Not referenced if SENSE = 'N' or 'E'. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= max(1,3*N). * Also, if SENSE = 'E' or 'V' or 'B', * LWORK >= N+2*SDIM*(N-SDIM), where SDIM is the number of * selected eigenvalues computed by this routine. Note that * N+2*SDIM*(N-SDIM) <= N+N*N/2. * For good performance, LWORK must generally be larger. * * IWORK (workspace/output) INTEGER array, dimension (LIWORK) * Not referenced if SENSE = 'N' or 'E'. * On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK. * * LIWORK (input) INTEGER * The dimension of the array IWORK. * LIWORK >= 1; if SENSE = 'V' or 'B', LIWORK >= SDIM*(N-SDIM). * * BWORK (workspace) LOGICAL array, dimension (N) * Not referenced if SORT = 'N'. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: if INFO = i, and i is * <= N: the QR algorithm failed to compute all the * eigenvalues; elements 1:ILO-1 and i+1:N of WR and WI * contain those eigenvalues which have converged; if * JOBVS = 'V', VS contains the transformation which * reduces A to its partially converged Schur form. * = N+1: the eigenvalues could not be reordered because some * eigenvalues were too close to separate (the problem * is very ill-conditioned); * = N+2: after reordering, roundoff changed values of some * complex eigenvalues so that leading eigenvalues in * the Schur form no longer satisfy SELECT=.TRUE. This * could also be caused by underflow due to scaling. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. LOGICAL CURSL, LASTSL, LST2SL, SCALEA, WANTSB, WANTSE, $ WANTSN, WANTST, WANTSV, WANTVS INTEGER HSWORK, I, I1, I2, IBAL, ICOND, IERR, IEVAL, $ IHI, ILO, INXT, IP, ITAU, IWRK, K, MAXB, $ MAXWRK, MINWRK DOUBLE PRECISION ANRM, BIGNUM, CSCALE, EPS, SMLNUM * .. * .. Local Arrays .. DOUBLE PRECISION DUM( 1 ) * .. * .. External Subroutines .. EXTERNAL DCOPY, DGEBAK, DGEBAL, DGEHRD, DHSEQR, DLACPY, $ DLASCL, DORGHR, DSWAP, DTRSEN, XERBLA * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANGE EXTERNAL LSAME, ILAENV, DLAMCH, DLANGE * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN, SQRT * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 WANTVS = LSAME( JOBVS, 'V' ) WANTST = LSAME( SORT, 'S' ) WANTSN = LSAME( SENSE, 'N' ) WANTSE = LSAME( SENSE, 'E' ) WANTSV = LSAME( SENSE, 'V' ) WANTSB = LSAME( SENSE, 'B' ) IF( ( .NOT.WANTVS ) .AND. ( .NOT.LSAME( JOBVS, 'N' ) ) ) THEN INFO = -1 ELSE IF( ( .NOT.WANTST ) .AND. ( .NOT.LSAME( SORT, 'N' ) ) ) THEN INFO = -2 ELSE IF( .NOT.( WANTSN .OR. WANTSE .OR. WANTSV .OR. WANTSB ) .OR. $ ( .NOT.WANTST .AND. .NOT.WANTSN ) ) THEN INFO = -4 ELSE IF( N.LT.0 ) THEN INFO = -5 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -7 ELSE IF( LDVS.LT.1 .OR. ( WANTVS .AND. LDVS.LT.N ) ) THEN INFO = -12 END IF * * Compute workspace * (Note: Comments in the code beginning "RWorkspace:" describe the * minimal amount of real workspace needed at that point in the * code, as well as the preferred amount for good performance. * IWorkspace refers to integer workspace. * NB refers to the optimal block size for the immediately * following subroutine, as returned by ILAENV. * HSWORK refers to the workspace preferred by DHSEQR, as * calculated below. HSWORK is computed assuming ILO=1 and IHI=N, * the worst case. * If SENSE = 'E', 'V' or 'B', then the amount of workspace needed * depends on SDIM, which is computed by the routine DTRSEN later * in the code.) * MINWRK = 1 IF( INFO.EQ.0 .AND. LWORK.GE.1 ) THEN MAXWRK = 2*N + N*ILAENV( 1, 'DGEHRD', ' ', N, 1, N, 0 ) MINWRK = MAX( 1, 3*N ) IF( .NOT.WANTVS ) THEN MAXB = MAX( ILAENV( 8, 'DHSEQR', 'SN', N, 1, N, -1 ), 2 ) K = MIN( MAXB, N, MAX( 2, ILAENV( 4, 'DHSEQR', 'SN', N, 1, $ N, -1 ) ) ) HSWORK = MAX( K*( K+2 ), 2*N ) MAXWRK = MAX( MAXWRK, N+HSWORK, 1 ) ELSE MAXWRK = MAX( MAXWRK, 2*N+( N-1 )* $ ILAENV( 1, 'DORGHR', ' ', N, 1, N, -1 ) ) MAXB = MAX( ILAENV( 8, 'DHSEQR', 'SV', N, 1, N, -1 ), 2 ) K = MIN( MAXB, N, MAX( 2, ILAENV( 4, 'DHSEQR', 'SV', N, 1, $ N, -1 ) ) ) HSWORK = MAX( K*( K+2 ), 2*N ) MAXWRK = MAX( MAXWRK, N+HSWORK, 1 ) END IF WORK( 1 ) = MAXWRK END IF IF( LWORK.LT.MINWRK ) THEN INFO = -16 END IF IF( LIWORK.LT.1 ) THEN INFO = -18 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGEESX', -INFO ) RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) THEN SDIM = 0 RETURN END IF * * Get machine constants * EPS = DLAMCH( 'P' ) SMLNUM = DLAMCH( 'S' ) BIGNUM = ONE / SMLNUM CALL DLABAD( SMLNUM, BIGNUM ) SMLNUM = SQRT( SMLNUM ) / EPS BIGNUM = ONE / SMLNUM * * Scale A if max element outside range [SMLNUM,BIGNUM] * ANRM = DLANGE( 'M', N, N, A, LDA, DUM ) SCALEA = .FALSE. IF( ANRM.GT.ZERO .AND. ANRM.LT.SMLNUM ) THEN SCALEA = .TRUE. CSCALE = SMLNUM ELSE IF( ANRM.GT.BIGNUM ) THEN SCALEA = .TRUE. CSCALE = BIGNUM END IF IF( SCALEA ) $ CALL DLASCL( 'G', 0, 0, ANRM, CSCALE, N, N, A, LDA, IERR ) * * Permute the matrix to make it more nearly triangular * (RWorkspace: need N) * IBAL = 1 CALL DGEBAL( 'P', N, A, LDA, ILO, IHI, WORK( IBAL ), IERR ) * * Reduce to upper Hessenberg form * (RWorkspace: need 3*N, prefer 2*N+N*NB) * ITAU = N + IBAL IWRK = N + ITAU CALL DGEHRD( N, ILO, IHI, A, LDA, WORK( ITAU ), WORK( IWRK ), $ LWORK-IWRK+1, IERR ) * IF( WANTVS ) THEN * * Copy Householder vectors to VS * CALL DLACPY( 'L', N, N, A, LDA, VS, LDVS ) * * Generate orthogonal matrix in VS * (RWorkspace: need 3*N-1, prefer 2*N+(N-1)*NB) * CALL DORGHR( N, ILO, IHI, VS, LDVS, WORK( ITAU ), WORK( IWRK ), $ LWORK-IWRK+1, IERR ) END IF * SDIM = 0 * * Perform QR iteration, accumulating Schur vectors in VS if desired * (RWorkspace: need N+1, prefer N+HSWORK (see comments) ) * IWRK = ITAU CALL DHSEQR( 'S', JOBVS, N, ILO, IHI, A, LDA, WR, WI, VS, LDVS, $ WORK( IWRK ), LWORK-IWRK+1, IEVAL ) IF( IEVAL.GT.0 ) $ INFO = IEVAL * * Sort eigenvalues if desired * IF( WANTST .AND. INFO.EQ.0 ) THEN IF( SCALEA ) THEN CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, N, 1, WR, N, IERR ) CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, N, 1, WI, N, IERR ) END IF DO 10 I = 1, N BWORK( I ) = SELECT( WR( I ), WI( I ) ) 10 CONTINUE * * Reorder eigenvalues, transform Schur vectors, and compute * reciprocal condition numbers * (RWorkspace: if SENSE is not 'N', need N+2*SDIM*(N-SDIM) * otherwise, need N ) * (IWorkspace: if SENSE is 'V' or 'B', need SDIM*(N-SDIM) * otherwise, need 0 ) * CALL DTRSEN( SENSE, JOBVS, BWORK, N, A, LDA, VS, LDVS, WR, WI, $ SDIM, RCONDE, RCONDV, WORK( IWRK ), LWORK-IWRK+1, $ IWORK, LIWORK, ICOND ) IF( .NOT.WANTSN ) $ MAXWRK = MAX( MAXWRK, N+2*SDIM*( N-SDIM ) ) IF( ICOND.EQ.-15 ) THEN * * Not enough real workspace * INFO = -16 ELSE IF( ICOND.EQ.-17 ) THEN * * Not enough integer workspace * INFO = -18 ELSE IF( ICOND.GT.0 ) THEN * * DTRSEN failed to reorder or to restore standard Schur form * INFO = ICOND + N END IF END IF * IF( WANTVS ) THEN * * Undo balancing * (RWorkspace: need N) * CALL DGEBAK( 'P', 'R', N, ILO, IHI, WORK( IBAL ), N, VS, LDVS, $ IERR ) END IF * IF( SCALEA ) THEN * * Undo scaling for the Schur form of A * CALL DLASCL( 'H', 0, 0, CSCALE, ANRM, N, N, A, LDA, IERR ) CALL DCOPY( N, A, LDA+1, WR, 1 ) IF( ( WANTSV .OR. WANTSB ) .AND. INFO.EQ.0 ) THEN DUM( 1 ) = RCONDV CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, 1, 1, DUM, 1, IERR ) RCONDV = DUM( 1 ) END IF IF( CSCALE.EQ.SMLNUM ) THEN * * If scaling back towards underflow, adjust WI if an * offdiagonal element of a 2-by-2 block in the Schur form * underflows. * IF( IEVAL.GT.0 ) THEN I1 = IEVAL + 1 I2 = IHI - 1 CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, ILO-1, 1, WI, N, $ IERR ) ELSE IF( WANTST ) THEN I1 = 1 I2 = N - 1 ELSE I1 = ILO I2 = IHI - 1 END IF INXT = I1 - 1 DO 20 I = I1, I2 IF( I.LT.INXT ) $ GO TO 20 IF( WI( I ).EQ.ZERO ) THEN INXT = I + 1 ELSE IF( A( I+1, I ).EQ.ZERO ) THEN WI( I ) = ZERO WI( I+1 ) = ZERO ELSE IF( A( I+1, I ).NE.ZERO .AND. A( I, I+1 ).EQ. $ ZERO ) THEN WI( I ) = ZERO WI( I+1 ) = ZERO IF( I.GT.1 ) $ CALL DSWAP( I-1, A( 1, I ), 1, A( 1, I+1 ), 1 ) IF( N.GT.I+1 ) $ CALL DSWAP( N-I-1, A( I, I+2 ), LDA, $ A( I+1, I+2 ), LDA ) CALL DSWAP( N, VS( 1, I ), 1, VS( 1, I+1 ), 1 ) A( I, I+1 ) = A( I+1, I ) A( I+1, I ) = ZERO END IF INXT = I + 2 END IF 20 CONTINUE END IF CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, N-IEVAL, 1, $ WI( IEVAL+1 ), MAX( N-IEVAL, 1 ), IERR ) END IF * IF( WANTST .AND. INFO.EQ.0 ) THEN * * Check if reordering successful * LASTSL = .TRUE. LST2SL = .TRUE. SDIM = 0 IP = 0 DO 30 I = 1, N CURSL = SELECT( WR( I ), WI( I ) ) IF( WI( I ).EQ.ZERO ) THEN IF( CURSL ) $ SDIM = SDIM + 1 IP = 0 IF( CURSL .AND. .NOT.LASTSL ) $ INFO = N + 2 ELSE IF( IP.EQ.1 ) THEN * * Last eigenvalue of conjugate pair * CURSL = CURSL .OR. LASTSL LASTSL = CURSL IF( CURSL ) $ SDIM = SDIM + 2 IP = -1 IF( CURSL .AND. .NOT.LST2SL ) $ INFO = N + 2 ELSE * * First eigenvalue of conjugate pair * IP = 1 END IF END IF LST2SL = LASTSL LASTSL = CURSL 30 CONTINUE END IF * WORK( 1 ) = MAXWRK IF( WANTSV .OR. WANTSB ) THEN IWORK( 1 ) = SDIM*( N-SDIM ) ELSE IWORK( 1 ) = 1 END IF * RETURN * * End of DGEESX * END SUBROUTINE DGEEV( JOBVL, JOBVR, N, A, LDA, WR, WI, VL, LDVL, VR, $ LDVR, WORK, LWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * December 8, 1999 * * .. Scalar Arguments .. CHARACTER JOBVL, JOBVR INTEGER INFO, LDA, LDVL, LDVR, LWORK, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), VL( LDVL, * ), VR( LDVR, * ), $ WI( * ), WORK( * ), WR( * ) * .. * * Purpose * ======= * * DGEEV computes for an N-by-N real nonsymmetric matrix A, the * eigenvalues and, optionally, the left and/or right eigenvectors. * * The right eigenvector v(j) of A satisfies * A * v(j) = lambda(j) * v(j) * where lambda(j) is its eigenvalue. * The left eigenvector u(j) of A satisfies * u(j)**H * A = lambda(j) * u(j)**H * where u(j)**H denotes the conjugate transpose of u(j). * * The computed eigenvectors are normalized to have Euclidean norm * equal to 1 and largest component real. * * Arguments * ========= * * JOBVL (input) CHARACTER*1 * = 'N': left eigenvectors of A are not computed; * = 'V': left eigenvectors of A are computed. * * JOBVR (input) CHARACTER*1 * = 'N': right eigenvectors of A are not computed; * = 'V': right eigenvectors of A are computed. * * N (input) INTEGER * The order of the matrix A. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the N-by-N matrix A. * On exit, A has been overwritten. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * WR (output) DOUBLE PRECISION array, dimension (N) * WI (output) DOUBLE PRECISION array, dimension (N) * WR and WI contain the real and imaginary parts, * respectively, of the computed eigenvalues. Complex * conjugate pairs of eigenvalues appear consecutively * with the eigenvalue having the positive imaginary part * first. * * VL (output) DOUBLE PRECISION array, dimension (LDVL,N) * If JOBVL = 'V', the left eigenvectors u(j) are stored one * after another in the columns of VL, in the same order * as their eigenvalues. * If JOBVL = 'N', VL is not referenced. * If the j-th eigenvalue is real, then u(j) = VL(:,j), * the j-th column of VL. * If the j-th and (j+1)-st eigenvalues form a complex * conjugate pair, then u(j) = VL(:,j) + i*VL(:,j+1) and * u(j+1) = VL(:,j) - i*VL(:,j+1). * * LDVL (input) INTEGER * The leading dimension of the array VL. LDVL >= 1; if * JOBVL = 'V', LDVL >= N. * * VR (output) DOUBLE PRECISION array, dimension (LDVR,N) * If JOBVR = 'V', the right eigenvectors v(j) are stored one * after another in the columns of VR, in the same order * as their eigenvalues. * If JOBVR = 'N', VR is not referenced. * If the j-th eigenvalue is real, then v(j) = VR(:,j), * the j-th column of VR. * If the j-th and (j+1)-st eigenvalues form a complex * conjugate pair, then v(j) = VR(:,j) + i*VR(:,j+1) and * v(j+1) = VR(:,j) - i*VR(:,j+1). * * LDVR (input) INTEGER * The leading dimension of the array VR. LDVR >= 1; if * JOBVR = 'V', LDVR >= N. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= max(1,3*N), and * if JOBVL = 'V' or JOBVR = 'V', LWORK >= 4*N. For good * performance, LWORK must generally be larger. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: if INFO = i, the QR algorithm failed to compute all the * eigenvalues, and no eigenvectors have been computed; * elements i+1:N of WR and WI contain eigenvalues which * have converged. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. LOGICAL LQUERY, SCALEA, WANTVL, WANTVR CHARACTER SIDE INTEGER HSWORK, I, IBAL, IERR, IHI, ILO, ITAU, IWRK, K, $ MAXB, MAXWRK, MINWRK, NOUT DOUBLE PRECISION ANRM, BIGNUM, CS, CSCALE, EPS, R, SCL, SMLNUM, $ SN * .. * .. Local Arrays .. LOGICAL SELECT( 1 ) DOUBLE PRECISION DUM( 1 ) * .. * .. External Subroutines .. EXTERNAL DGEBAK, DGEBAL, DGEHRD, DHSEQR, DLACPY, DLARTG, $ DLASCL, DORGHR, DROT, DSCAL, DTREVC, XERBLA * .. * .. External Functions .. LOGICAL LSAME INTEGER IDAMAX, ILAENV DOUBLE PRECISION DLAMCH, DLANGE, DLAPY2, DNRM2 EXTERNAL LSAME, IDAMAX, ILAENV, DLAMCH, DLANGE, DLAPY2, $ DNRM2 * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN, SQRT * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 LQUERY = ( LWORK.EQ.-1 ) WANTVL = LSAME( JOBVL, 'V' ) WANTVR = LSAME( JOBVR, 'V' ) IF( ( .NOT.WANTVL ) .AND. ( .NOT.LSAME( JOBVL, 'N' ) ) ) THEN INFO = -1 ELSE IF( ( .NOT.WANTVR ) .AND. ( .NOT.LSAME( JOBVR, 'N' ) ) ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -5 ELSE IF( LDVL.LT.1 .OR. ( WANTVL .AND. LDVL.LT.N ) ) THEN INFO = -9 ELSE IF( LDVR.LT.1 .OR. ( WANTVR .AND. LDVR.LT.N ) ) THEN INFO = -11 END IF * * Compute workspace * (Note: Comments in the code beginning "Workspace:" describe the * minimal amount of workspace needed at that point in the code, * as well as the preferred amount for good performance. * NB refers to the optimal block size for the immediately * following subroutine, as returned by ILAENV. * HSWORK refers to the workspace preferred by DHSEQR, as * calculated below. HSWORK is computed assuming ILO=1 and IHI=N, * the worst case.) * MINWRK = 1 IF( INFO.EQ.0 .AND. ( LWORK.GE.1 .OR. LQUERY ) ) THEN MAXWRK = 2*N + N*ILAENV( 1, 'DGEHRD', ' ', N, 1, N, 0 ) IF( ( .NOT.WANTVL ) .AND. ( .NOT.WANTVR ) ) THEN MINWRK = MAX( 1, 3*N ) MAXB = MAX( ILAENV( 8, 'DHSEQR', 'EN', N, 1, N, -1 ), 2 ) K = MIN( MAXB, N, MAX( 2, ILAENV( 4, 'DHSEQR', 'EN', N, 1, $ N, -1 ) ) ) HSWORK = MAX( K*( K+2 ), 2*N ) MAXWRK = MAX( MAXWRK, N+1, N+HSWORK ) ELSE MINWRK = MAX( 1, 4*N ) MAXWRK = MAX( MAXWRK, 2*N+( N-1 )* $ ILAENV( 1, 'DORGHR', ' ', N, 1, N, -1 ) ) MAXB = MAX( ILAENV( 8, 'DHSEQR', 'SV', N, 1, N, -1 ), 2 ) K = MIN( MAXB, N, MAX( 2, ILAENV( 4, 'DHSEQR', 'SV', N, 1, $ N, -1 ) ) ) HSWORK = MAX( K*( K+2 ), 2*N ) MAXWRK = MAX( MAXWRK, N+1, N+HSWORK ) MAXWRK = MAX( MAXWRK, 4*N ) END IF WORK( 1 ) = MAXWRK END IF IF( LWORK.LT.MINWRK .AND. .NOT.LQUERY ) THEN INFO = -13 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGEEV ', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * * Get machine constants * EPS = DLAMCH( 'P' ) SMLNUM = DLAMCH( 'S' ) BIGNUM = ONE / SMLNUM CALL DLABAD( SMLNUM, BIGNUM ) SMLNUM = SQRT( SMLNUM ) / EPS BIGNUM = ONE / SMLNUM * * Scale A if max element outside range [SMLNUM,BIGNUM] * ANRM = DLANGE( 'M', N, N, A, LDA, DUM ) SCALEA = .FALSE. IF( ANRM.GT.ZERO .AND. ANRM.LT.SMLNUM ) THEN SCALEA = .TRUE. CSCALE = SMLNUM ELSE IF( ANRM.GT.BIGNUM ) THEN SCALEA = .TRUE. CSCALE = BIGNUM END IF IF( SCALEA ) $ CALL DLASCL( 'G', 0, 0, ANRM, CSCALE, N, N, A, LDA, IERR ) * * Balance the matrix * (Workspace: need N) * IBAL = 1 CALL DGEBAL( 'B', N, A, LDA, ILO, IHI, WORK( IBAL ), IERR ) * * Reduce to upper Hessenberg form * (Workspace: need 3*N, prefer 2*N+N*NB) * ITAU = IBAL + N IWRK = ITAU + N CALL DGEHRD( N, ILO, IHI, A, LDA, WORK( ITAU ), WORK( IWRK ), $ LWORK-IWRK+1, IERR ) * IF( WANTVL ) THEN * * Want left eigenvectors * Copy Householder vectors to VL * SIDE = 'L' CALL DLACPY( 'L', N, N, A, LDA, VL, LDVL ) * * Generate orthogonal matrix in VL * (Workspace: need 3*N-1, prefer 2*N+(N-1)*NB) * CALL DORGHR( N, ILO, IHI, VL, LDVL, WORK( ITAU ), WORK( IWRK ), $ LWORK-IWRK+1, IERR ) * * Perform QR iteration, accumulating Schur vectors in VL * (Workspace: need N+1, prefer N+HSWORK (see comments) ) * IWRK = ITAU CALL DHSEQR( 'S', 'V', N, ILO, IHI, A, LDA, WR, WI, VL, LDVL, $ WORK( IWRK ), LWORK-IWRK+1, INFO ) * IF( WANTVR ) THEN * * Want left and right eigenvectors * Copy Schur vectors to VR * SIDE = 'B' CALL DLACPY( 'F', N, N, VL, LDVL, VR, LDVR ) END IF * ELSE IF( WANTVR ) THEN * * Want right eigenvectors * Copy Householder vectors to VR * SIDE = 'R' CALL DLACPY( 'L', N, N, A, LDA, VR, LDVR ) * * Generate orthogonal matrix in VR * (Workspace: need 3*N-1, prefer 2*N+(N-1)*NB) * CALL DORGHR( N, ILO, IHI, VR, LDVR, WORK( ITAU ), WORK( IWRK ), $ LWORK-IWRK+1, IERR ) * * Perform QR iteration, accumulating Schur vectors in VR * (Workspace: need N+1, prefer N+HSWORK (see comments) ) * IWRK = ITAU CALL DHSEQR( 'S', 'V', N, ILO, IHI, A, LDA, WR, WI, VR, LDVR, $ WORK( IWRK ), LWORK-IWRK+1, INFO ) * ELSE * * Compute eigenvalues only * (Workspace: need N+1, prefer N+HSWORK (see comments) ) * IWRK = ITAU CALL DHSEQR( 'E', 'N', N, ILO, IHI, A, LDA, WR, WI, VR, LDVR, $ WORK( IWRK ), LWORK-IWRK+1, INFO ) END IF * * If INFO > 0 from DHSEQR, then quit * IF( INFO.GT.0 ) $ GO TO 50 * IF( WANTVL .OR. WANTVR ) THEN * * Compute left and/or right eigenvectors * (Workspace: need 4*N) * CALL DTREVC( SIDE, 'B', SELECT, N, A, LDA, VL, LDVL, VR, LDVR, $ N, NOUT, WORK( IWRK ), IERR ) END IF * IF( WANTVL ) THEN * * Undo balancing of left eigenvectors * (Workspace: need N) * CALL DGEBAK( 'B', 'L', N, ILO, IHI, WORK( IBAL ), N, VL, LDVL, $ IERR ) * * Normalize left eigenvectors and make largest component real * DO 20 I = 1, N IF( WI( I ).EQ.ZERO ) THEN SCL = ONE / DNRM2( N, VL( 1, I ), 1 ) CALL DSCAL( N, SCL, VL( 1, I ), 1 ) ELSE IF( WI( I ).GT.ZERO ) THEN SCL = ONE / DLAPY2( DNRM2( N, VL( 1, I ), 1 ), $ DNRM2( N, VL( 1, I+1 ), 1 ) ) CALL DSCAL( N, SCL, VL( 1, I ), 1 ) CALL DSCAL( N, SCL, VL( 1, I+1 ), 1 ) DO 10 K = 1, N WORK( IWRK+K-1 ) = VL( K, I )**2 + VL( K, I+1 )**2 10 CONTINUE K = IDAMAX( N, WORK( IWRK ), 1 ) CALL DLARTG( VL( K, I ), VL( K, I+1 ), CS, SN, R ) CALL DROT( N, VL( 1, I ), 1, VL( 1, I+1 ), 1, CS, SN ) VL( K, I+1 ) = ZERO END IF 20 CONTINUE END IF * IF( WANTVR ) THEN * * Undo balancing of right eigenvectors * (Workspace: need N) * CALL DGEBAK( 'B', 'R', N, ILO, IHI, WORK( IBAL ), N, VR, LDVR, $ IERR ) * * Normalize right eigenvectors and make largest component real * DO 40 I = 1, N IF( WI( I ).EQ.ZERO ) THEN SCL = ONE / DNRM2( N, VR( 1, I ), 1 ) CALL DSCAL( N, SCL, VR( 1, I ), 1 ) ELSE IF( WI( I ).GT.ZERO ) THEN SCL = ONE / DLAPY2( DNRM2( N, VR( 1, I ), 1 ), $ DNRM2( N, VR( 1, I+1 ), 1 ) ) CALL DSCAL( N, SCL, VR( 1, I ), 1 ) CALL DSCAL( N, SCL, VR( 1, I+1 ), 1 ) DO 30 K = 1, N WORK( IWRK+K-1 ) = VR( K, I )**2 + VR( K, I+1 )**2 30 CONTINUE K = IDAMAX( N, WORK( IWRK ), 1 ) CALL DLARTG( VR( K, I ), VR( K, I+1 ), CS, SN, R ) CALL DROT( N, VR( 1, I ), 1, VR( 1, I+1 ), 1, CS, SN ) VR( K, I+1 ) = ZERO END IF 40 CONTINUE END IF * * Undo scaling if necessary * 50 CONTINUE IF( SCALEA ) THEN CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, N-INFO, 1, WR( INFO+1 ), $ MAX( N-INFO, 1 ), IERR ) CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, N-INFO, 1, WI( INFO+1 ), $ MAX( N-INFO, 1 ), IERR ) IF( INFO.GT.0 ) THEN CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, ILO-1, 1, WR, N, $ IERR ) CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, ILO-1, 1, WI, N, $ IERR ) END IF END IF * WORK( 1 ) = MAXWRK RETURN * * End of DGEEV * END SUBROUTINE DGEEVX( BALANC, JOBVL, JOBVR, SENSE, N, A, LDA, WR, WI, $ VL, LDVL, VR, LDVR, ILO, IHI, SCALE, ABNRM, $ RCONDE, RCONDV, WORK, LWORK, IWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER BALANC, JOBVL, JOBVR, SENSE INTEGER IHI, ILO, INFO, LDA, LDVL, LDVR, LWORK, N DOUBLE PRECISION ABNRM * .. * .. Array Arguments .. INTEGER IWORK( * ) DOUBLE PRECISION A( LDA, * ), RCONDE( * ), RCONDV( * ), $ SCALE( * ), VL( LDVL, * ), VR( LDVR, * ), $ WI( * ), WORK( * ), WR( * ) * .. * * Purpose * ======= * * DGEEVX computes for an N-by-N real nonsymmetric matrix A, the * eigenvalues and, optionally, the left and/or right eigenvectors. * * Optionally also, it computes a balancing transformation to improve * the conditioning of the eigenvalues and eigenvectors (ILO, IHI, * SCALE, and ABNRM), reciprocal condition numbers for the eigenvalues * (RCONDE), and reciprocal condition numbers for the right * eigenvectors (RCONDV). * * The right eigenvector v(j) of A satisfies * A * v(j) = lambda(j) * v(j) * where lambda(j) is its eigenvalue. * The left eigenvector u(j) of A satisfies * u(j)**H * A = lambda(j) * u(j)**H * where u(j)**H denotes the conjugate transpose of u(j). * * The computed eigenvectors are normalized to have Euclidean norm * equal to 1 and largest component real. * * Balancing a matrix means permuting the rows and columns to make it * more nearly upper triangular, and applying a diagonal similarity * transformation D * A * D**(-1), where D is a diagonal matrix, to * make its rows and columns closer in norm and the condition numbers * of its eigenvalues and eigenvectors smaller. The computed * reciprocal condition numbers correspond to the balanced matrix. * Permuting rows and columns will not change the condition numbers * (in exact arithmetic) but diagonal scaling will. For further * explanation of balancing, see section 4.10.2 of the LAPACK * Users' Guide. * * Arguments * ========= * * BALANC (input) CHARACTER*1 * Indicates how the input matrix should be diagonally scaled * and/or permuted to improve the conditioning of its * eigenvalues. * = 'N': Do not diagonally scale or permute; * = 'P': Perform permutations to make the matrix more nearly * upper triangular. Do not diagonally scale; * = 'S': Diagonally scale the matrix, i.e. replace A by * D*A*D**(-1), where D is a diagonal matrix chosen * to make the rows and columns of A more equal in * norm. Do not permute; * = 'B': Both diagonally scale and permute A. * * Computed reciprocal condition numbers will be for the matrix * after balancing and/or permuting. Permuting does not change * condition numbers (in exact arithmetic), but balancing does. * * JOBVL (input) CHARACTER*1 * = 'N': left eigenvectors of A are not computed; * = 'V': left eigenvectors of A are computed. * If SENSE = 'E' or 'B', JOBVL must = 'V'. * * JOBVR (input) CHARACTER*1 * = 'N': right eigenvectors of A are not computed; * = 'V': right eigenvectors of A are computed. * If SENSE = 'E' or 'B', JOBVR must = 'V'. * * SENSE (input) CHARACTER*1 * Determines which reciprocal condition numbers are computed. * = 'N': None are computed; * = 'E': Computed for eigenvalues only; * = 'V': Computed for right eigenvectors only; * = 'B': Computed for eigenvalues and right eigenvectors. * * If SENSE = 'E' or 'B', both left and right eigenvectors * must also be computed (JOBVL = 'V' and JOBVR = 'V'). * * N (input) INTEGER * The order of the matrix A. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the N-by-N matrix A. * On exit, A has been overwritten. If JOBVL = 'V' or * JOBVR = 'V', A contains the real Schur form of the balanced * version of the input matrix A. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * WR (output) DOUBLE PRECISION array, dimension (N) * WI (output) DOUBLE PRECISION array, dimension (N) * WR and WI contain the real and imaginary parts, * respectively, of the computed eigenvalues. Complex * conjugate pairs of eigenvalues will appear consecutively * with the eigenvalue having the positive imaginary part * first. * * VL (output) DOUBLE PRECISION array, dimension (LDVL,N) * If JOBVL = 'V', the left eigenvectors u(j) are stored one * after another in the columns of VL, in the same order * as their eigenvalues. * If JOBVL = 'N', VL is not referenced. * If the j-th eigenvalue is real, then u(j) = VL(:,j), * the j-th column of VL. * If the j-th and (j+1)-st eigenvalues form a complex * conjugate pair, then u(j) = VL(:,j) + i*VL(:,j+1) and * u(j+1) = VL(:,j) - i*VL(:,j+1). * * LDVL (input) INTEGER * The leading dimension of the array VL. LDVL >= 1; if * JOBVL = 'V', LDVL >= N. * * VR (output) DOUBLE PRECISION array, dimension (LDVR,N) * If JOBVR = 'V', the right eigenvectors v(j) are stored one * after another in the columns of VR, in the same order * as their eigenvalues. * If JOBVR = 'N', VR is not referenced. * If the j-th eigenvalue is real, then v(j) = VR(:,j), * the j-th column of VR. * If the j-th and (j+1)-st eigenvalues form a complex * conjugate pair, then v(j) = VR(:,j) + i*VR(:,j+1) and * v(j+1) = VR(:,j) - i*VR(:,j+1). * * LDVR (input) INTEGER * The leading dimension of the array VR. LDVR >= 1, and if * JOBVR = 'V', LDVR >= N. * * ILO,IHI (output) INTEGER * ILO and IHI are integer values determined when A was * balanced. The balanced A(i,j) = 0 if I > J and * J = 1,...,ILO-1 or I = IHI+1,...,N. * * SCALE (output) DOUBLE PRECISION array, dimension (N) * Details of the permutations and scaling factors applied * when balancing A. If P(j) is the index of the row and column * interchanged with row and column j, and D(j) is the scaling * factor applied to row and column j, then * SCALE(J) = P(J), for J = 1,...,ILO-1 * = D(J), for J = ILO,...,IHI * = P(J) for J = IHI+1,...,N. * The order in which the interchanges are made is N to IHI+1, * then 1 to ILO-1. * * ABNRM (output) DOUBLE PRECISION * The one-norm of the balanced matrix (the maximum * of the sum of absolute values of elements of any column). * * RCONDE (output) DOUBLE PRECISION array, dimension (N) * RCONDE(j) is the reciprocal condition number of the j-th * eigenvalue. * * RCONDV (output) DOUBLE PRECISION array, dimension (N) * RCONDV(j) is the reciprocal condition number of the j-th * right eigenvector. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. If SENSE = 'N' or 'E', * LWORK >= max(1,2*N), and if JOBVL = 'V' or JOBVR = 'V', * LWORK >= 3*N. If SENSE = 'V' or 'B', LWORK >= N*(N+6). * For good performance, LWORK must generally be larger. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * IWORK (workspace) INTEGER array, dimension (2*N-2) * If SENSE = 'N' or 'E', not referenced. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: if INFO = i, the QR algorithm failed to compute all the * eigenvalues, and no eigenvectors or condition numbers * have been computed; elements 1:ILO-1 and i+1:N of WR * and WI contain eigenvalues which have converged. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. LOGICAL LQUERY, SCALEA, WANTVL, WANTVR, WNTSNB, WNTSNE, $ WNTSNN, WNTSNV CHARACTER JOB, SIDE INTEGER HSWORK, I, ICOND, IERR, ITAU, IWRK, K, MAXB, $ MAXWRK, MINWRK, NOUT DOUBLE PRECISION ANRM, BIGNUM, CS, CSCALE, EPS, R, SCL, SMLNUM, $ SN * .. * .. Local Arrays .. LOGICAL SELECT( 1 ) DOUBLE PRECISION DUM( 1 ) * .. * .. External Subroutines .. EXTERNAL DGEBAK, DGEBAL, DGEHRD, DHSEQR, DLACPY, DLARTG, $ DLASCL, DORGHR, DROT, DSCAL, DTREVC, DTRSNA, $ XERBLA * .. * .. External Functions .. LOGICAL LSAME INTEGER IDAMAX, ILAENV DOUBLE PRECISION DLAMCH, DLANGE, DLAPY2, DNRM2 EXTERNAL LSAME, IDAMAX, ILAENV, DLAMCH, DLANGE, DLAPY2, $ DNRM2 * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN, SQRT * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 LQUERY = ( LWORK.EQ.-1 ) WANTVL = LSAME( JOBVL, 'V' ) WANTVR = LSAME( JOBVR, 'V' ) WNTSNN = LSAME( SENSE, 'N' ) WNTSNE = LSAME( SENSE, 'E' ) WNTSNV = LSAME( SENSE, 'V' ) WNTSNB = LSAME( SENSE, 'B' ) IF( .NOT.( LSAME( BALANC, 'N' ) .OR. LSAME( BALANC, $ 'S' ) .OR. LSAME( BALANC, 'P' ) .OR. LSAME( BALANC, 'B' ) ) ) $ THEN INFO = -1 ELSE IF( ( .NOT.WANTVL ) .AND. ( .NOT.LSAME( JOBVL, 'N' ) ) ) THEN INFO = -2 ELSE IF( ( .NOT.WANTVR ) .AND. ( .NOT.LSAME( JOBVR, 'N' ) ) ) THEN INFO = -3 ELSE IF( .NOT.( WNTSNN .OR. WNTSNE .OR. WNTSNB .OR. WNTSNV ) .OR. $ ( ( WNTSNE .OR. WNTSNB ) .AND. .NOT.( WANTVL .AND. $ WANTVR ) ) ) THEN INFO = -4 ELSE IF( N.LT.0 ) THEN INFO = -5 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -7 ELSE IF( LDVL.LT.1 .OR. ( WANTVL .AND. LDVL.LT.N ) ) THEN INFO = -11 ELSE IF( LDVR.LT.1 .OR. ( WANTVR .AND. LDVR.LT.N ) ) THEN INFO = -13 END IF * * Compute workspace * (Note: Comments in the code beginning "Workspace:" describe the * minimal amount of workspace needed at that point in the code, * as well as the preferred amount for good performance. * NB refers to the optimal block size for the immediately * following subroutine, as returned by ILAENV. * HSWORK refers to the workspace preferred by DHSEQR, as * calculated below. HSWORK is computed assuming ILO=1 and IHI=N, * the worst case.) * MINWRK = 1 IF( INFO.EQ.0 .AND. ( LWORK.GE.1 .OR. LQUERY ) ) THEN MAXWRK = N + N*ILAENV( 1, 'DGEHRD', ' ', N, 1, N, 0 ) IF( ( .NOT.WANTVL ) .AND. ( .NOT.WANTVR ) ) THEN MINWRK = MAX( 1, 2*N ) IF( .NOT.WNTSNN ) $ MINWRK = MAX( MINWRK, N*N+6*N ) MAXB = MAX( ILAENV( 8, 'DHSEQR', 'SN', N, 1, N, -1 ), 2 ) IF( WNTSNN ) THEN K = MIN( MAXB, N, MAX( 2, ILAENV( 4, 'DHSEQR', 'EN', N, $ 1, N, -1 ) ) ) ELSE K = MIN( MAXB, N, MAX( 2, ILAENV( 4, 'DHSEQR', 'SN', N, $ 1, N, -1 ) ) ) END IF HSWORK = MAX( K*( K+2 ), 2*N ) MAXWRK = MAX( MAXWRK, 1, HSWORK ) IF( .NOT.WNTSNN ) $ MAXWRK = MAX( MAXWRK, N*N+6*N ) ELSE MINWRK = MAX( 1, 3*N ) IF( ( .NOT.WNTSNN ) .AND. ( .NOT.WNTSNE ) ) $ MINWRK = MAX( MINWRK, N*N+6*N ) MAXB = MAX( ILAENV( 8, 'DHSEQR', 'SN', N, 1, N, -1 ), 2 ) K = MIN( MAXB, N, MAX( 2, ILAENV( 4, 'DHSEQR', 'EN', N, 1, $ N, -1 ) ) ) HSWORK = MAX( K*( K+2 ), 2*N ) MAXWRK = MAX( MAXWRK, 1, HSWORK ) MAXWRK = MAX( MAXWRK, N+( N-1 )* $ ILAENV( 1, 'DORGHR', ' ', N, 1, N, -1 ) ) IF( ( .NOT.WNTSNN ) .AND. ( .NOT.WNTSNE ) ) $ MAXWRK = MAX( MAXWRK, N*N+6*N ) MAXWRK = MAX( MAXWRK, 3*N, 1 ) END IF WORK( 1 ) = MAXWRK END IF IF( LWORK.LT.MINWRK .AND. .NOT.LQUERY ) THEN INFO = -21 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGEEVX', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * * Get machine constants * EPS = DLAMCH( 'P' ) SMLNUM = DLAMCH( 'S' ) BIGNUM = ONE / SMLNUM CALL DLABAD( SMLNUM, BIGNUM ) SMLNUM = SQRT( SMLNUM ) / EPS BIGNUM = ONE / SMLNUM * * Scale A if max element outside range [SMLNUM,BIGNUM] * ICOND = 0 ANRM = DLANGE( 'M', N, N, A, LDA, DUM ) SCALEA = .FALSE. IF( ANRM.GT.ZERO .AND. ANRM.LT.SMLNUM ) THEN SCALEA = .TRUE. CSCALE = SMLNUM ELSE IF( ANRM.GT.BIGNUM ) THEN SCALEA = .TRUE. CSCALE = BIGNUM END IF IF( SCALEA ) $ CALL DLASCL( 'G', 0, 0, ANRM, CSCALE, N, N, A, LDA, IERR ) * * Balance the matrix and compute ABNRM * CALL DGEBAL( BALANC, N, A, LDA, ILO, IHI, SCALE, IERR ) ABNRM = DLANGE( '1', N, N, A, LDA, DUM ) IF( SCALEA ) THEN DUM( 1 ) = ABNRM CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, 1, 1, DUM, 1, IERR ) ABNRM = DUM( 1 ) END IF * * Reduce to upper Hessenberg form * (Workspace: need 2*N, prefer N+N*NB) * ITAU = 1 IWRK = ITAU + N CALL DGEHRD( N, ILO, IHI, A, LDA, WORK( ITAU ), WORK( IWRK ), $ LWORK-IWRK+1, IERR ) * IF( WANTVL ) THEN * * Want left eigenvectors * Copy Householder vectors to VL * SIDE = 'L' CALL DLACPY( 'L', N, N, A, LDA, VL, LDVL ) * * Generate orthogonal matrix in VL * (Workspace: need 2*N-1, prefer N+(N-1)*NB) * CALL DORGHR( N, ILO, IHI, VL, LDVL, WORK( ITAU ), WORK( IWRK ), $ LWORK-IWRK+1, IERR ) * * Perform QR iteration, accumulating Schur vectors in VL * (Workspace: need 1, prefer HSWORK (see comments) ) * IWRK = ITAU CALL DHSEQR( 'S', 'V', N, ILO, IHI, A, LDA, WR, WI, VL, LDVL, $ WORK( IWRK ), LWORK-IWRK+1, INFO ) * IF( WANTVR ) THEN * * Want left and right eigenvectors * Copy Schur vectors to VR * SIDE = 'B' CALL DLACPY( 'F', N, N, VL, LDVL, VR, LDVR ) END IF * ELSE IF( WANTVR ) THEN * * Want right eigenvectors * Copy Householder vectors to VR * SIDE = 'R' CALL DLACPY( 'L', N, N, A, LDA, VR, LDVR ) * * Generate orthogonal matrix in VR * (Workspace: need 2*N-1, prefer N+(N-1)*NB) * CALL DORGHR( N, ILO, IHI, VR, LDVR, WORK( ITAU ), WORK( IWRK ), $ LWORK-IWRK+1, IERR ) * * Perform QR iteration, accumulating Schur vectors in VR * (Workspace: need 1, prefer HSWORK (see comments) ) * IWRK = ITAU CALL DHSEQR( 'S', 'V', N, ILO, IHI, A, LDA, WR, WI, VR, LDVR, $ WORK( IWRK ), LWORK-IWRK+1, INFO ) * ELSE * * Compute eigenvalues only * If condition numbers desired, compute Schur form * IF( WNTSNN ) THEN JOB = 'E' ELSE JOB = 'S' END IF * * (Workspace: need 1, prefer HSWORK (see comments) ) * IWRK = ITAU CALL DHSEQR( JOB, 'N', N, ILO, IHI, A, LDA, WR, WI, VR, LDVR, $ WORK( IWRK ), LWORK-IWRK+1, INFO ) END IF * * If INFO > 0 from DHSEQR, then quit * IF( INFO.GT.0 ) $ GO TO 50 * IF( WANTVL .OR. WANTVR ) THEN * * Compute left and/or right eigenvectors * (Workspace: need 3*N) * CALL DTREVC( SIDE, 'B', SELECT, N, A, LDA, VL, LDVL, VR, LDVR, $ N, NOUT, WORK( IWRK ), IERR ) END IF * * Compute condition numbers if desired * (Workspace: need N*N+6*N unless SENSE = 'E') * IF( .NOT.WNTSNN ) THEN CALL DTRSNA( SENSE, 'A', SELECT, N, A, LDA, VL, LDVL, VR, LDVR, $ RCONDE, RCONDV, N, NOUT, WORK( IWRK ), N, IWORK, $ ICOND ) END IF * IF( WANTVL ) THEN * * Undo balancing of left eigenvectors * CALL DGEBAK( BALANC, 'L', N, ILO, IHI, SCALE, N, VL, LDVL, $ IERR ) * * Normalize left eigenvectors and make largest component real * DO 20 I = 1, N IF( WI( I ).EQ.ZERO ) THEN SCL = ONE / DNRM2( N, VL( 1, I ), 1 ) CALL DSCAL( N, SCL, VL( 1, I ), 1 ) ELSE IF( WI( I ).GT.ZERO ) THEN SCL = ONE / DLAPY2( DNRM2( N, VL( 1, I ), 1 ), $ DNRM2( N, VL( 1, I+1 ), 1 ) ) CALL DSCAL( N, SCL, VL( 1, I ), 1 ) CALL DSCAL( N, SCL, VL( 1, I+1 ), 1 ) DO 10 K = 1, N WORK( K ) = VL( K, I )**2 + VL( K, I+1 )**2 10 CONTINUE K = IDAMAX( N, WORK, 1 ) CALL DLARTG( VL( K, I ), VL( K, I+1 ), CS, SN, R ) CALL DROT( N, VL( 1, I ), 1, VL( 1, I+1 ), 1, CS, SN ) VL( K, I+1 ) = ZERO END IF 20 CONTINUE END IF * IF( WANTVR ) THEN * * Undo balancing of right eigenvectors * CALL DGEBAK( BALANC, 'R', N, ILO, IHI, SCALE, N, VR, LDVR, $ IERR ) * * Normalize right eigenvectors and make largest component real * DO 40 I = 1, N IF( WI( I ).EQ.ZERO ) THEN SCL = ONE / DNRM2( N, VR( 1, I ), 1 ) CALL DSCAL( N, SCL, VR( 1, I ), 1 ) ELSE IF( WI( I ).GT.ZERO ) THEN SCL = ONE / DLAPY2( DNRM2( N, VR( 1, I ), 1 ), $ DNRM2( N, VR( 1, I+1 ), 1 ) ) CALL DSCAL( N, SCL, VR( 1, I ), 1 ) CALL DSCAL( N, SCL, VR( 1, I+1 ), 1 ) DO 30 K = 1, N WORK( K ) = VR( K, I )**2 + VR( K, I+1 )**2 30 CONTINUE K = IDAMAX( N, WORK, 1 ) CALL DLARTG( VR( K, I ), VR( K, I+1 ), CS, SN, R ) CALL DROT( N, VR( 1, I ), 1, VR( 1, I+1 ), 1, CS, SN ) VR( K, I+1 ) = ZERO END IF 40 CONTINUE END IF * * Undo scaling if necessary * 50 CONTINUE IF( SCALEA ) THEN CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, N-INFO, 1, WR( INFO+1 ), $ MAX( N-INFO, 1 ), IERR ) CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, N-INFO, 1, WI( INFO+1 ), $ MAX( N-INFO, 1 ), IERR ) IF( INFO.EQ.0 ) THEN IF( ( WNTSNV .OR. WNTSNB ) .AND. ICOND.EQ.0 ) $ CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, N, 1, RCONDV, N, $ IERR ) ELSE CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, ILO-1, 1, WR, N, $ IERR ) CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, ILO-1, 1, WI, N, $ IERR ) END IF END IF * WORK( 1 ) = MAXWRK RETURN * * End of DGEEVX * END SUBROUTINE DGEGS( JOBVSL, JOBVSR, N, A, LDA, B, LDB, ALPHAR, $ ALPHAI, BETA, VSL, LDVSL, VSR, LDVSR, WORK, $ LWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBVSL, JOBVSR INTEGER INFO, LDA, LDB, LDVSL, LDVSR, LWORK, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), ALPHAI( * ), ALPHAR( * ), $ B( LDB, * ), BETA( * ), VSL( LDVSL, * ), $ VSR( LDVSR, * ), WORK( * ) * .. * * Purpose * ======= * * This routine is deprecated and has been replaced by routine DGGES. * * DGEGS computes for a pair of N-by-N real nonsymmetric matrices A, B: * the generalized eigenvalues (alphar +/- alphai*i, beta), the real * Schur form (A, B), and optionally left and/or right Schur vectors * (VSL and VSR). * * (If only the generalized eigenvalues are needed, use the driver DGEGV * instead.) * * A generalized eigenvalue for a pair of matrices (A,B) is, roughly * speaking, a scalar w or a ratio alpha/beta = w, such that A - w*B * is singular. It is usually represented as the pair (alpha,beta), * as there is a reasonable interpretation for beta=0, and even for * both being zero. A good beginning reference is the book, "Matrix * Computations", by G. Golub & C. van Loan (Johns Hopkins U. Press) * * The (generalized) Schur form of a pair of matrices is the result of * multiplying both matrices on the left by one orthogonal matrix and * both on the right by another orthogonal matrix, these two orthogonal * matrices being chosen so as to bring the pair of matrices into * (real) Schur form. * * A pair of matrices A, B is in generalized real Schur form if B is * upper triangular with non-negative diagonal and A is block upper * triangular with 1-by-1 and 2-by-2 blocks. 1-by-1 blocks correspond * to real generalized eigenvalues, while 2-by-2 blocks of A will be * "standardized" by making the corresponding elements of B have the * form: * [ a 0 ] * [ 0 b ] * * and the pair of corresponding 2-by-2 blocks in A and B will * have a complex conjugate pair of generalized eigenvalues. * * The left and right Schur vectors are the columns of VSL and VSR, * respectively, where VSL and VSR are the orthogonal matrices * which reduce A and B to Schur form: * * Schur form of (A,B) = ( (VSL)**T A (VSR), (VSL)**T B (VSR) ) * * Arguments * ========= * * JOBVSL (input) CHARACTER*1 * = 'N': do not compute the left Schur vectors; * = 'V': compute the left Schur vectors. * * JOBVSR (input) CHARACTER*1 * = 'N': do not compute the right Schur vectors; * = 'V': compute the right Schur vectors. * * N (input) INTEGER * The order of the matrices A, B, VSL, and VSR. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA, N) * On entry, the first of the pair of matrices whose generalized * eigenvalues and (optionally) Schur vectors are to be * computed. * On exit, the generalized Schur form of A. * Note: to avoid overflow, the Frobenius norm of the matrix * A should be less than the overflow threshold. * * LDA (input) INTEGER * The leading dimension of A. LDA >= max(1,N). * * B (input/output) DOUBLE PRECISION array, dimension (LDB, N) * On entry, the second of the pair of matrices whose * generalized eigenvalues and (optionally) Schur vectors are * to be computed. * On exit, the generalized Schur form of B. * Note: to avoid overflow, the Frobenius norm of the matrix * B should be less than the overflow threshold. * * LDB (input) INTEGER * The leading dimension of B. LDB >= max(1,N). * * ALPHAR (output) DOUBLE PRECISION array, dimension (N) * ALPHAI (output) DOUBLE PRECISION array, dimension (N) * BETA (output) DOUBLE PRECISION array, dimension (N) * On exit, (ALPHAR(j) + ALPHAI(j)*i)/BETA(j), j=1,...,N, will * be the generalized eigenvalues. ALPHAR(j) + ALPHAI(j)*i, * j=1,...,N and BETA(j),j=1,...,N are the diagonals of the * complex Schur form (A,B) that would result if the 2-by-2 * diagonal blocks of the real Schur form of (A,B) were further * reduced to triangular form using 2-by-2 complex unitary * transformations. If ALPHAI(j) is zero, then the j-th * eigenvalue is real; if positive, then the j-th and (j+1)-st * eigenvalues are a complex conjugate pair, with ALPHAI(j+1) * negative. * * Note: the quotients ALPHAR(j)/BETA(j) and ALPHAI(j)/BETA(j) * may easily over- or underflow, and BETA(j) may even be zero. * Thus, the user should avoid naively computing the ratio * alpha/beta. However, ALPHAR and ALPHAI will be always less * than and usually comparable with norm(A) in magnitude, and * BETA always less than and usually comparable with norm(B). * * VSL (output) DOUBLE PRECISION array, dimension (LDVSL,N) * If JOBVSL = 'V', VSL will contain the left Schur vectors. * (See "Purpose", above.) * Not referenced if JOBVSL = 'N'. * * LDVSL (input) INTEGER * The leading dimension of the matrix VSL. LDVSL >=1, and * if JOBVSL = 'V', LDVSL >= N. * * VSR (output) DOUBLE PRECISION array, dimension (LDVSR,N) * If JOBVSR = 'V', VSR will contain the right Schur vectors. * (See "Purpose", above.) * Not referenced if JOBVSR = 'N'. * * LDVSR (input) INTEGER * The leading dimension of the matrix VSR. LDVSR >= 1, and * if JOBVSR = 'V', LDVSR >= N. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= max(1,4*N). * For good performance, LWORK must generally be larger. * To compute the optimal value of LWORK, call ILAENV to get * blocksizes (for DGEQRF, DORMQR, and DORGQR.) Then compute: * NB -- MAX of the blocksizes for DGEQRF, DORMQR, and DORGQR * The optimal LWORK is 2*N + N*(NB+1). * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value. * = 1,...,N: * The QZ iteration failed. (A,B) are not in Schur * form, but ALPHAR(j), ALPHAI(j), and BETA(j) should * be correct for j=INFO+1,...,N. * > N: errors that usually indicate LAPACK problems: * =N+1: error return from DGGBAL * =N+2: error return from DGEQRF * =N+3: error return from DORMQR * =N+4: error return from DORGQR * =N+5: error return from DGGHRD * =N+6: error return from DHGEQZ (other than failed * iteration) * =N+7: error return from DGGBAK (computing VSL) * =N+8: error return from DGGBAK (computing VSR) * =N+9: error return from DLASCL (various places) * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. LOGICAL ILASCL, ILBSCL, ILVSL, ILVSR, LQUERY INTEGER ICOLS, IHI, IINFO, IJOBVL, IJOBVR, ILEFT, ILO, $ IRIGHT, IROWS, ITAU, IWORK, LOPT, LWKMIN, $ LWKOPT, NB, NB1, NB2, NB3 DOUBLE PRECISION ANRM, ANRMTO, BIGNUM, BNRM, BNRMTO, EPS, $ SAFMIN, SMLNUM * .. * .. External Subroutines .. EXTERNAL DGEQRF, DGGBAK, DGGBAL, DGGHRD, DHGEQZ, DLACPY, $ DLASCL, DLASET, DORGQR, DORMQR, XERBLA * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANGE EXTERNAL LSAME, ILAENV, DLAMCH, DLANGE * .. * .. Intrinsic Functions .. INTRINSIC INT, MAX * .. * .. Executable Statements .. * * Decode the input arguments * IF( LSAME( JOBVSL, 'N' ) ) THEN IJOBVL = 1 ILVSL = .FALSE. ELSE IF( LSAME( JOBVSL, 'V' ) ) THEN IJOBVL = 2 ILVSL = .TRUE. ELSE IJOBVL = -1 ILVSL = .FALSE. END IF * IF( LSAME( JOBVSR, 'N' ) ) THEN IJOBVR = 1 ILVSR = .FALSE. ELSE IF( LSAME( JOBVSR, 'V' ) ) THEN IJOBVR = 2 ILVSR = .TRUE. ELSE IJOBVR = -1 ILVSR = .FALSE. END IF * * Test the input arguments * LWKMIN = MAX( 4*N, 1 ) LWKOPT = LWKMIN WORK( 1 ) = LWKOPT LQUERY = ( LWORK.EQ.-1 ) INFO = 0 IF( IJOBVL.LE.0 ) THEN INFO = -1 ELSE IF( IJOBVR.LE.0 ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -5 ELSE IF( LDB.LT.MAX( 1, N ) ) THEN INFO = -7 ELSE IF( LDVSL.LT.1 .OR. ( ILVSL .AND. LDVSL.LT.N ) ) THEN INFO = -12 ELSE IF( LDVSR.LT.1 .OR. ( ILVSR .AND. LDVSR.LT.N ) ) THEN INFO = -14 ELSE IF( LWORK.LT.LWKMIN .AND. .NOT.LQUERY ) THEN INFO = -16 END IF * IF( INFO.EQ.0 ) THEN NB1 = ILAENV( 1, 'DGEQRF', ' ', N, N, -1, -1 ) NB2 = ILAENV( 1, 'DORMQR', ' ', N, N, N, -1 ) NB3 = ILAENV( 1, 'DORGQR', ' ', N, N, N, -1 ) NB = MAX( NB1, NB2, NB3 ) LOPT = 2*N + N*( NB+1 ) WORK( 1 ) = LOPT END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGEGS ', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * * Get machine constants * EPS = DLAMCH( 'E' )*DLAMCH( 'B' ) SAFMIN = DLAMCH( 'S' ) SMLNUM = N*SAFMIN / EPS BIGNUM = ONE / SMLNUM * * Scale A if max element outside range [SMLNUM,BIGNUM] * ANRM = DLANGE( 'M', N, N, A, LDA, WORK ) ILASCL = .FALSE. IF( ANRM.GT.ZERO .AND. ANRM.LT.SMLNUM ) THEN ANRMTO = SMLNUM ILASCL = .TRUE. ELSE IF( ANRM.GT.BIGNUM ) THEN ANRMTO = BIGNUM ILASCL = .TRUE. END IF * IF( ILASCL ) THEN CALL DLASCL( 'G', -1, -1, ANRM, ANRMTO, N, N, A, LDA, IINFO ) IF( IINFO.NE.0 ) THEN INFO = N + 9 RETURN END IF END IF * * Scale B if max element outside range [SMLNUM,BIGNUM] * BNRM = DLANGE( 'M', N, N, B, LDB, WORK ) ILBSCL = .FALSE. IF( BNRM.GT.ZERO .AND. BNRM.LT.SMLNUM ) THEN BNRMTO = SMLNUM ILBSCL = .TRUE. ELSE IF( BNRM.GT.BIGNUM ) THEN BNRMTO = BIGNUM ILBSCL = .TRUE. END IF * IF( ILBSCL ) THEN CALL DLASCL( 'G', -1, -1, BNRM, BNRMTO, N, N, B, LDB, IINFO ) IF( IINFO.NE.0 ) THEN INFO = N + 9 RETURN END IF END IF * * Permute the matrix to make it more nearly triangular * Workspace layout: (2*N words -- "work..." not actually used) * left_permutation, right_permutation, work... * ILEFT = 1 IRIGHT = N + 1 IWORK = IRIGHT + N CALL DGGBAL( 'P', N, A, LDA, B, LDB, ILO, IHI, WORK( ILEFT ), $ WORK( IRIGHT ), WORK( IWORK ), IINFO ) IF( IINFO.NE.0 ) THEN INFO = N + 1 GO TO 10 END IF * * Reduce B to triangular form, and initialize VSL and/or VSR * Workspace layout: ("work..." must have at least N words) * left_permutation, right_permutation, tau, work... * IROWS = IHI + 1 - ILO ICOLS = N + 1 - ILO ITAU = IWORK IWORK = ITAU + IROWS CALL DGEQRF( IROWS, ICOLS, B( ILO, ILO ), LDB, WORK( ITAU ), $ WORK( IWORK ), LWORK+1-IWORK, IINFO ) IF( IINFO.GE.0 ) $ LWKOPT = MAX( LWKOPT, INT( WORK( IWORK ) )+IWORK-1 ) IF( IINFO.NE.0 ) THEN INFO = N + 2 GO TO 10 END IF * CALL DORMQR( 'L', 'T', IROWS, ICOLS, IROWS, B( ILO, ILO ), LDB, $ WORK( ITAU ), A( ILO, ILO ), LDA, WORK( IWORK ), $ LWORK+1-IWORK, IINFO ) IF( IINFO.GE.0 ) $ LWKOPT = MAX( LWKOPT, INT( WORK( IWORK ) )+IWORK-1 ) IF( IINFO.NE.0 ) THEN INFO = N + 3 GO TO 10 END IF * IF( ILVSL ) THEN CALL DLASET( 'Full', N, N, ZERO, ONE, VSL, LDVSL ) CALL DLACPY( 'L', IROWS-1, IROWS-1, B( ILO+1, ILO ), LDB, $ VSL( ILO+1, ILO ), LDVSL ) CALL DORGQR( IROWS, IROWS, IROWS, VSL( ILO, ILO ), LDVSL, $ WORK( ITAU ), WORK( IWORK ), LWORK+1-IWORK, $ IINFO ) IF( IINFO.GE.0 ) $ LWKOPT = MAX( LWKOPT, INT( WORK( IWORK ) )+IWORK-1 ) IF( IINFO.NE.0 ) THEN INFO = N + 4 GO TO 10 END IF END IF * IF( ILVSR ) $ CALL DLASET( 'Full', N, N, ZERO, ONE, VSR, LDVSR ) * * Reduce to generalized Hessenberg form * CALL DGGHRD( JOBVSL, JOBVSR, N, ILO, IHI, A, LDA, B, LDB, VSL, $ LDVSL, VSR, LDVSR, IINFO ) IF( IINFO.NE.0 ) THEN INFO = N + 5 GO TO 10 END IF * * Perform QZ algorithm, computing Schur vectors if desired * Workspace layout: ("work..." must have at least 1 word) * left_permutation, right_permutation, work... * IWORK = ITAU CALL DHGEQZ( 'S', JOBVSL, JOBVSR, N, ILO, IHI, A, LDA, B, LDB, $ ALPHAR, ALPHAI, BETA, VSL, LDVSL, VSR, LDVSR, $ WORK( IWORK ), LWORK+1-IWORK, IINFO ) IF( IINFO.GE.0 ) $ LWKOPT = MAX( LWKOPT, INT( WORK( IWORK ) )+IWORK-1 ) IF( IINFO.NE.0 ) THEN IF( IINFO.GT.0 .AND. IINFO.LE.N ) THEN INFO = IINFO ELSE IF( IINFO.GT.N .AND. IINFO.LE.2*N ) THEN INFO = IINFO - N ELSE INFO = N + 6 END IF GO TO 10 END IF * * Apply permutation to VSL and VSR * IF( ILVSL ) THEN CALL DGGBAK( 'P', 'L', N, ILO, IHI, WORK( ILEFT ), $ WORK( IRIGHT ), N, VSL, LDVSL, IINFO ) IF( IINFO.NE.0 ) THEN INFO = N + 7 GO TO 10 END IF END IF IF( ILVSR ) THEN CALL DGGBAK( 'P', 'R', N, ILO, IHI, WORK( ILEFT ), $ WORK( IRIGHT ), N, VSR, LDVSR, IINFO ) IF( IINFO.NE.0 ) THEN INFO = N + 8 GO TO 10 END IF END IF * * Undo scaling * IF( ILASCL ) THEN CALL DLASCL( 'H', -1, -1, ANRMTO, ANRM, N, N, A, LDA, IINFO ) IF( IINFO.NE.0 ) THEN INFO = N + 9 RETURN END IF CALL DLASCL( 'G', -1, -1, ANRMTO, ANRM, N, 1, ALPHAR, N, $ IINFO ) IF( IINFO.NE.0 ) THEN INFO = N + 9 RETURN END IF CALL DLASCL( 'G', -1, -1, ANRMTO, ANRM, N, 1, ALPHAI, N, $ IINFO ) IF( IINFO.NE.0 ) THEN INFO = N + 9 RETURN END IF END IF * IF( ILBSCL ) THEN CALL DLASCL( 'U', -1, -1, BNRMTO, BNRM, N, N, B, LDB, IINFO ) IF( IINFO.NE.0 ) THEN INFO = N + 9 RETURN END IF CALL DLASCL( 'G', -1, -1, BNRMTO, BNRM, N, 1, BETA, N, IINFO ) IF( IINFO.NE.0 ) THEN INFO = N + 9 RETURN END IF END IF * 10 CONTINUE WORK( 1 ) = LWKOPT * RETURN * * End of DGEGS * END SUBROUTINE DGEGV( JOBVL, JOBVR, N, A, LDA, B, LDB, ALPHAR, ALPHAI, $ BETA, VL, LDVL, VR, LDVR, WORK, LWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBVL, JOBVR INTEGER INFO, LDA, LDB, LDVL, LDVR, LWORK, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), ALPHAI( * ), ALPHAR( * ), $ B( LDB, * ), BETA( * ), VL( LDVL, * ), $ VR( LDVR, * ), WORK( * ) * .. * * Purpose * ======= * * This routine is deprecated and has been replaced by routine DGGEV. * * DGEGV computes for a pair of n-by-n real nonsymmetric matrices A and * B, the generalized eigenvalues (alphar +/- alphai*i, beta), and * optionally, the left and/or right generalized eigenvectors (VL and * VR). * * A generalized eigenvalue for a pair of matrices (A,B) is, roughly * speaking, a scalar w or a ratio alpha/beta = w, such that A - w*B * is singular. It is usually represented as the pair (alpha,beta), * as there is a reasonable interpretation for beta=0, and even for * both being zero. A good beginning reference is the book, "Matrix * Computations", by G. Golub & C. van Loan (Johns Hopkins U. Press) * * A right generalized eigenvector corresponding to a generalized * eigenvalue w for a pair of matrices (A,B) is a vector r such * that (A - w B) r = 0 . A left generalized eigenvector is a vector * l such that l**H * (A - w B) = 0, where l**H is the * conjugate-transpose of l. * * Note: this routine performs "full balancing" on A and B -- see * "Further Details", below. * * Arguments * ========= * * JOBVL (input) CHARACTER*1 * = 'N': do not compute the left generalized eigenvectors; * = 'V': compute the left generalized eigenvectors. * * JOBVR (input) CHARACTER*1 * = 'N': do not compute the right generalized eigenvectors; * = 'V': compute the right generalized eigenvectors. * * N (input) INTEGER * The order of the matrices A, B, VL, and VR. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA, N) * On entry, the first of the pair of matrices whose * generalized eigenvalues and (optionally) generalized * eigenvectors are to be computed. * On exit, the contents will have been destroyed. (For a * description of the contents of A on exit, see "Further * Details", below.) * * LDA (input) INTEGER * The leading dimension of A. LDA >= max(1,N). * * B (input/output) DOUBLE PRECISION array, dimension (LDB, N) * On entry, the second of the pair of matrices whose * generalized eigenvalues and (optionally) generalized * eigenvectors are to be computed. * On exit, the contents will have been destroyed. (For a * description of the contents of B on exit, see "Further * Details", below.) * * LDB (input) INTEGER * The leading dimension of B. LDB >= max(1,N). * * ALPHAR (output) DOUBLE PRECISION array, dimension (N) * ALPHAI (output) DOUBLE PRECISION array, dimension (N) * BETA (output) DOUBLE PRECISION array, dimension (N) * On exit, (ALPHAR(j) + ALPHAI(j)*i)/BETA(j), j=1,...,N, will * be the generalized eigenvalues. If ALPHAI(j) is zero, then * the j-th eigenvalue is real; if positive, then the j-th and * (j+1)-st eigenvalues are a complex conjugate pair, with * ALPHAI(j+1) negative. * * Note: the quotients ALPHAR(j)/BETA(j) and ALPHAI(j)/BETA(j) * may easily over- or underflow, and BETA(j) may even be zero. * Thus, the user should avoid naively computing the ratio * alpha/beta. However, ALPHAR and ALPHAI will be always less * than and usually comparable with norm(A) in magnitude, and * BETA always less than and usually comparable with norm(B). * * VL (output) DOUBLE PRECISION array, dimension (LDVL,N) * If JOBVL = 'V', the left generalized eigenvectors. (See * "Purpose", above.) Real eigenvectors take one column, * complex take two columns, the first for the real part and * the second for the imaginary part. Complex eigenvectors * correspond to an eigenvalue with positive imaginary part. * Each eigenvector will be scaled so the largest component * will have abs(real part) + abs(imag. part) = 1, *except* * that for eigenvalues with alpha=beta=0, a zero vector will * be returned as the corresponding eigenvector. * Not referenced if JOBVL = 'N'. * * LDVL (input) INTEGER * The leading dimension of the matrix VL. LDVL >= 1, and * if JOBVL = 'V', LDVL >= N. * * VR (output) DOUBLE PRECISION array, dimension (LDVR,N) * If JOBVR = 'V', the right generalized eigenvectors. (See * "Purpose", above.) Real eigenvectors take one column, * complex take two columns, the first for the real part and * the second for the imaginary part. Complex eigenvectors * correspond to an eigenvalue with positive imaginary part. * Each eigenvector will be scaled so the largest component * will have abs(real part) + abs(imag. part) = 1, *except* * that for eigenvalues with alpha=beta=0, a zero vector will * be returned as the corresponding eigenvector. * Not referenced if JOBVR = 'N'. * * LDVR (input) INTEGER * The leading dimension of the matrix VR. LDVR >= 1, and * if JOBVR = 'V', LDVR >= N. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= max(1,8*N). * For good performance, LWORK must generally be larger. * To compute the optimal value of LWORK, call ILAENV to get * blocksizes (for DGEQRF, DORMQR, and DORGQR.) Then compute: * NB -- MAX of the blocksizes for DGEQRF, DORMQR, and DORGQR; * The optimal LWORK is: * 2*N + MAX( 6*N, N*(NB+1) ). * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value. * = 1,...,N: * The QZ iteration failed. No eigenvectors have been * calculated, but ALPHAR(j), ALPHAI(j), and BETA(j) * should be correct for j=INFO+1,...,N. * > N: errors that usually indicate LAPACK problems: * =N+1: error return from DGGBAL * =N+2: error return from DGEQRF * =N+3: error return from DORMQR * =N+4: error return from DORGQR * =N+5: error return from DGGHRD * =N+6: error return from DHGEQZ (other than failed * iteration) * =N+7: error return from DTGEVC * =N+8: error return from DGGBAK (computing VL) * =N+9: error return from DGGBAK (computing VR) * =N+10: error return from DLASCL (various calls) * * Further Details * =============== * * Balancing * --------- * * This driver calls DGGBAL to both permute and scale rows and columns * of A and B. The permutations PL and PR are chosen so that PL*A*PR * and PL*B*R will be upper triangular except for the diagonal blocks * A(i:j,i:j) and B(i:j,i:j), with i and j as close together as * possible. The diagonal scaling matrices DL and DR are chosen so * that the pair DL*PL*A*PR*DR, DL*PL*B*PR*DR have elements close to * one (except for the elements that start out zero.) * * After the eigenvalues and eigenvectors of the balanced matrices * have been computed, DGGBAK transforms the eigenvectors back to what * they would have been (in perfect arithmetic) if they had not been * balanced. * * Contents of A and B on Exit * -------- -- - --- - -- ---- * * If any eigenvectors are computed (either JOBVL='V' or JOBVR='V' or * both), then on exit the arrays A and B will contain the real Schur * form[*] of the "balanced" versions of A and B. If no eigenvectors * are computed, then only the diagonal blocks will be correct. * * [*] See DHGEQZ, DGEGS, or read the book "Matrix Computations", * by Golub & van Loan, pub. by Johns Hopkins U. Press. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. LOGICAL ILIMIT, ILV, ILVL, ILVR, LQUERY CHARACTER CHTEMP INTEGER ICOLS, IHI, IINFO, IJOBVL, IJOBVR, ILEFT, ILO, $ IN, IRIGHT, IROWS, ITAU, IWORK, JC, JR, LOPT, $ LWKMIN, LWKOPT, NB, NB1, NB2, NB3 DOUBLE PRECISION ABSAI, ABSAR, ABSB, ANRM, ANRM1, ANRM2, BNRM, $ BNRM1, BNRM2, EPS, ONEPLS, SAFMAX, SAFMIN, $ SALFAI, SALFAR, SBETA, SCALE, TEMP * .. * .. Local Arrays .. LOGICAL LDUMMA( 1 ) * .. * .. External Subroutines .. EXTERNAL DGEQRF, DGGBAK, DGGBAL, DGGHRD, DHGEQZ, DLACPY, $ DLASCL, DLASET, DORGQR, DORMQR, DTGEVC, XERBLA * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANGE EXTERNAL LSAME, ILAENV, DLAMCH, DLANGE * .. * .. Intrinsic Functions .. INTRINSIC ABS, INT, MAX * .. * .. Executable Statements .. * * Decode the input arguments * IF( LSAME( JOBVL, 'N' ) ) THEN IJOBVL = 1 ILVL = .FALSE. ELSE IF( LSAME( JOBVL, 'V' ) ) THEN IJOBVL = 2 ILVL = .TRUE. ELSE IJOBVL = -1 ILVL = .FALSE. END IF * IF( LSAME( JOBVR, 'N' ) ) THEN IJOBVR = 1 ILVR = .FALSE. ELSE IF( LSAME( JOBVR, 'V' ) ) THEN IJOBVR = 2 ILVR = .TRUE. ELSE IJOBVR = -1 ILVR = .FALSE. END IF ILV = ILVL .OR. ILVR * * Test the input arguments * LWKMIN = MAX( 8*N, 1 ) LWKOPT = LWKMIN WORK( 1 ) = LWKOPT LQUERY = ( LWORK.EQ.-1 ) INFO = 0 IF( IJOBVL.LE.0 ) THEN INFO = -1 ELSE IF( IJOBVR.LE.0 ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -5 ELSE IF( LDB.LT.MAX( 1, N ) ) THEN INFO = -7 ELSE IF( LDVL.LT.1 .OR. ( ILVL .AND. LDVL.LT.N ) ) THEN INFO = -12 ELSE IF( LDVR.LT.1 .OR. ( ILVR .AND. LDVR.LT.N ) ) THEN INFO = -14 ELSE IF( LWORK.LT.LWKMIN .AND. .NOT.LQUERY ) THEN INFO = -16 END IF * IF( INFO.EQ.0 ) THEN NB1 = ILAENV( 1, 'DGEQRF', ' ', N, N, -1, -1 ) NB2 = ILAENV( 1, 'DORMQR', ' ', N, N, N, -1 ) NB3 = ILAENV( 1, 'DORGQR', ' ', N, N, N, -1 ) NB = MAX( NB1, NB2, NB3 ) LOPT = 2*N + MAX( 6*N, N*( NB+1 ) ) WORK( 1 ) = LOPT END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGEGV ', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * * Get machine constants * EPS = DLAMCH( 'E' )*DLAMCH( 'B' ) SAFMIN = DLAMCH( 'S' ) SAFMIN = SAFMIN + SAFMIN SAFMAX = ONE / SAFMIN ONEPLS = ONE + ( 4*EPS ) * * Scale A * ANRM = DLANGE( 'M', N, N, A, LDA, WORK ) ANRM1 = ANRM ANRM2 = ONE IF( ANRM.LT.ONE ) THEN IF( SAFMAX*ANRM.LT.ONE ) THEN ANRM1 = SAFMIN ANRM2 = SAFMAX*ANRM END IF END IF * IF( ANRM.GT.ZERO ) THEN CALL DLASCL( 'G', -1, -1, ANRM, ONE, N, N, A, LDA, IINFO ) IF( IINFO.NE.0 ) THEN INFO = N + 10 RETURN END IF END IF * * Scale B * BNRM = DLANGE( 'M', N, N, B, LDB, WORK ) BNRM1 = BNRM BNRM2 = ONE IF( BNRM.LT.ONE ) THEN IF( SAFMAX*BNRM.LT.ONE ) THEN BNRM1 = SAFMIN BNRM2 = SAFMAX*BNRM END IF END IF * IF( BNRM.GT.ZERO ) THEN CALL DLASCL( 'G', -1, -1, BNRM, ONE, N, N, B, LDB, IINFO ) IF( IINFO.NE.0 ) THEN INFO = N + 10 RETURN END IF END IF * * Permute the matrix to make it more nearly triangular * Workspace layout: (8*N words -- "work" requires 6*N words) * left_permutation, right_permutation, work... * ILEFT = 1 IRIGHT = N + 1 IWORK = IRIGHT + N CALL DGGBAL( 'P', N, A, LDA, B, LDB, ILO, IHI, WORK( ILEFT ), $ WORK( IRIGHT ), WORK( IWORK ), IINFO ) IF( IINFO.NE.0 ) THEN INFO = N + 1 GO TO 120 END IF * * Reduce B to triangular form, and initialize VL and/or VR * Workspace layout: ("work..." must have at least N words) * left_permutation, right_permutation, tau, work... * IROWS = IHI + 1 - ILO IF( ILV ) THEN ICOLS = N + 1 - ILO ELSE ICOLS = IROWS END IF ITAU = IWORK IWORK = ITAU + IROWS CALL DGEQRF( IROWS, ICOLS, B( ILO, ILO ), LDB, WORK( ITAU ), $ WORK( IWORK ), LWORK+1-IWORK, IINFO ) IF( IINFO.GE.0 ) $ LWKOPT = MAX( LWKOPT, INT( WORK( IWORK ) )+IWORK-1 ) IF( IINFO.NE.0 ) THEN INFO = N + 2 GO TO 120 END IF * CALL DORMQR( 'L', 'T', IROWS, ICOLS, IROWS, B( ILO, ILO ), LDB, $ WORK( ITAU ), A( ILO, ILO ), LDA, WORK( IWORK ), $ LWORK+1-IWORK, IINFO ) IF( IINFO.GE.0 ) $ LWKOPT = MAX( LWKOPT, INT( WORK( IWORK ) )+IWORK-1 ) IF( IINFO.NE.0 ) THEN INFO = N + 3 GO TO 120 END IF * IF( ILVL ) THEN CALL DLASET( 'Full', N, N, ZERO, ONE, VL, LDVL ) CALL DLACPY( 'L', IROWS-1, IROWS-1, B( ILO+1, ILO ), LDB, $ VL( ILO+1, ILO ), LDVL ) CALL DORGQR( IROWS, IROWS, IROWS, VL( ILO, ILO ), LDVL, $ WORK( ITAU ), WORK( IWORK ), LWORK+1-IWORK, $ IINFO ) IF( IINFO.GE.0 ) $ LWKOPT = MAX( LWKOPT, INT( WORK( IWORK ) )+IWORK-1 ) IF( IINFO.NE.0 ) THEN INFO = N + 4 GO TO 120 END IF END IF * IF( ILVR ) $ CALL DLASET( 'Full', N, N, ZERO, ONE, VR, LDVR ) * * Reduce to generalized Hessenberg form * IF( ILV ) THEN * * Eigenvectors requested -- work on whole matrix. * CALL DGGHRD( JOBVL, JOBVR, N, ILO, IHI, A, LDA, B, LDB, VL, $ LDVL, VR, LDVR, IINFO ) ELSE CALL DGGHRD( 'N', 'N', IROWS, 1, IROWS, A( ILO, ILO ), LDA, $ B( ILO, ILO ), LDB, VL, LDVL, VR, LDVR, IINFO ) END IF IF( IINFO.NE.0 ) THEN INFO = N + 5 GO TO 120 END IF * * Perform QZ algorithm * Workspace layout: ("work..." must have at least 1 word) * left_permutation, right_permutation, work... * IWORK = ITAU IF( ILV ) THEN CHTEMP = 'S' ELSE CHTEMP = 'E' END IF CALL DHGEQZ( CHTEMP, JOBVL, JOBVR, N, ILO, IHI, A, LDA, B, LDB, $ ALPHAR, ALPHAI, BETA, VL, LDVL, VR, LDVR, $ WORK( IWORK ), LWORK+1-IWORK, IINFO ) IF( IINFO.GE.0 ) $ LWKOPT = MAX( LWKOPT, INT( WORK( IWORK ) )+IWORK-1 ) IF( IINFO.NE.0 ) THEN IF( IINFO.GT.0 .AND. IINFO.LE.N ) THEN INFO = IINFO ELSE IF( IINFO.GT.N .AND. IINFO.LE.2*N ) THEN INFO = IINFO - N ELSE INFO = N + 6 END IF GO TO 120 END IF * IF( ILV ) THEN * * Compute Eigenvectors (DTGEVC requires 6*N words of workspace) * IF( ILVL ) THEN IF( ILVR ) THEN CHTEMP = 'B' ELSE CHTEMP = 'L' END IF ELSE CHTEMP = 'R' END IF * CALL DTGEVC( CHTEMP, 'B', LDUMMA, N, A, LDA, B, LDB, VL, LDVL, $ VR, LDVR, N, IN, WORK( IWORK ), IINFO ) IF( IINFO.NE.0 ) THEN INFO = N + 7 GO TO 120 END IF * * Undo balancing on VL and VR, rescale * IF( ILVL ) THEN CALL DGGBAK( 'P', 'L', N, ILO, IHI, WORK( ILEFT ), $ WORK( IRIGHT ), N, VL, LDVL, IINFO ) IF( IINFO.NE.0 ) THEN INFO = N + 8 GO TO 120 END IF DO 50 JC = 1, N IF( ALPHAI( JC ).LT.ZERO ) $ GO TO 50 TEMP = ZERO IF( ALPHAI( JC ).EQ.ZERO ) THEN DO 10 JR = 1, N TEMP = MAX( TEMP, ABS( VL( JR, JC ) ) ) 10 CONTINUE ELSE DO 20 JR = 1, N TEMP = MAX( TEMP, ABS( VL( JR, JC ) )+ $ ABS( VL( JR, JC+1 ) ) ) 20 CONTINUE END IF IF( TEMP.LT.SAFMIN ) $ GO TO 50 TEMP = ONE / TEMP IF( ALPHAI( JC ).EQ.ZERO ) THEN DO 30 JR = 1, N VL( JR, JC ) = VL( JR, JC )*TEMP 30 CONTINUE ELSE DO 40 JR = 1, N VL( JR, JC ) = VL( JR, JC )*TEMP VL( JR, JC+1 ) = VL( JR, JC+1 )*TEMP 40 CONTINUE END IF 50 CONTINUE END IF IF( ILVR ) THEN CALL DGGBAK( 'P', 'R', N, ILO, IHI, WORK( ILEFT ), $ WORK( IRIGHT ), N, VR, LDVR, IINFO ) IF( IINFO.NE.0 ) THEN INFO = N + 9 GO TO 120 END IF DO 100 JC = 1, N IF( ALPHAI( JC ).LT.ZERO ) $ GO TO 100 TEMP = ZERO IF( ALPHAI( JC ).EQ.ZERO ) THEN DO 60 JR = 1, N TEMP = MAX( TEMP, ABS( VR( JR, JC ) ) ) 60 CONTINUE ELSE DO 70 JR = 1, N TEMP = MAX( TEMP, ABS( VR( JR, JC ) )+ $ ABS( VR( JR, JC+1 ) ) ) 70 CONTINUE END IF IF( TEMP.LT.SAFMIN ) $ GO TO 100 TEMP = ONE / TEMP IF( ALPHAI( JC ).EQ.ZERO ) THEN DO 80 JR = 1, N VR( JR, JC ) = VR( JR, JC )*TEMP 80 CONTINUE ELSE DO 90 JR = 1, N VR( JR, JC ) = VR( JR, JC )*TEMP VR( JR, JC+1 ) = VR( JR, JC+1 )*TEMP 90 CONTINUE END IF 100 CONTINUE END IF * * End of eigenvector calculation * END IF * * Undo scaling in alpha, beta * * Note: this does not give the alpha and beta for the unscaled * problem. * * Un-scaling is limited to avoid underflow in alpha and beta * if they are significant. * DO 110 JC = 1, N ABSAR = ABS( ALPHAR( JC ) ) ABSAI = ABS( ALPHAI( JC ) ) ABSB = ABS( BETA( JC ) ) SALFAR = ANRM*ALPHAR( JC ) SALFAI = ANRM*ALPHAI( JC ) SBETA = BNRM*BETA( JC ) ILIMIT = .FALSE. SCALE = ONE * * Check for significant underflow in ALPHAI * IF( ABS( SALFAI ).LT.SAFMIN .AND. ABSAI.GE. $ MAX( SAFMIN, EPS*ABSAR, EPS*ABSB ) ) THEN ILIMIT = .TRUE. SCALE = ( ONEPLS*SAFMIN / ANRM1 ) / $ MAX( ONEPLS*SAFMIN, ANRM2*ABSAI ) * ELSE IF( SALFAI.EQ.ZERO ) THEN * * If insignificant underflow in ALPHAI, then make the * conjugate eigenvalue real. * IF( ALPHAI( JC ).LT.ZERO .AND. JC.GT.1 ) THEN ALPHAI( JC-1 ) = ZERO ELSE IF( ALPHAI( JC ).GT.ZERO .AND. JC.LT.N ) THEN ALPHAI( JC+1 ) = ZERO END IF END IF * * Check for significant underflow in ALPHAR * IF( ABS( SALFAR ).LT.SAFMIN .AND. ABSAR.GE. $ MAX( SAFMIN, EPS*ABSAI, EPS*ABSB ) ) THEN ILIMIT = .TRUE. SCALE = MAX( SCALE, ( ONEPLS*SAFMIN / ANRM1 ) / $ MAX( ONEPLS*SAFMIN, ANRM2*ABSAR ) ) END IF * * Check for significant underflow in BETA * IF( ABS( SBETA ).LT.SAFMIN .AND. ABSB.GE. $ MAX( SAFMIN, EPS*ABSAR, EPS*ABSAI ) ) THEN ILIMIT = .TRUE. SCALE = MAX( SCALE, ( ONEPLS*SAFMIN / BNRM1 ) / $ MAX( ONEPLS*SAFMIN, BNRM2*ABSB ) ) END IF * * Check for possible overflow when limiting scaling * IF( ILIMIT ) THEN TEMP = ( SCALE*SAFMIN )*MAX( ABS( SALFAR ), ABS( SALFAI ), $ ABS( SBETA ) ) IF( TEMP.GT.ONE ) $ SCALE = SCALE / TEMP IF( SCALE.LT.ONE ) $ ILIMIT = .FALSE. END IF * * Recompute un-scaled ALPHAR, ALPHAI, BETA if necessary. * IF( ILIMIT ) THEN SALFAR = ( SCALE*ALPHAR( JC ) )*ANRM SALFAI = ( SCALE*ALPHAI( JC ) )*ANRM SBETA = ( SCALE*BETA( JC ) )*BNRM END IF ALPHAR( JC ) = SALFAR ALPHAI( JC ) = SALFAI BETA( JC ) = SBETA 110 CONTINUE * 120 CONTINUE WORK( 1 ) = LWKOPT * RETURN * * End of DGEGV * END SUBROUTINE DGELS( TRANS, M, N, NRHS, A, LDA, B, LDB, WORK, LWORK, $ INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER TRANS INTEGER INFO, LDA, LDB, LWORK, M, N, NRHS * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), B( LDB, * ), WORK( * ) * .. * * Purpose * ======= * * DGELS solves overdetermined or underdetermined real linear systems * involving an M-by-N matrix A, or its transpose, using a QR or LQ * factorization of A. It is assumed that A has full rank. * * The following options are provided: * * 1. If TRANS = 'N' and m >= n: find the least squares solution of * an overdetermined system, i.e., solve the least squares problem * minimize || B - A*X ||. * * 2. If TRANS = 'N' and m < n: find the minimum norm solution of * an underdetermined system A * X = B. * * 3. If TRANS = 'T' and m >= n: find the minimum norm solution of * an undetermined system A**T * X = B. * * 4. If TRANS = 'T' and m < n: find the least squares solution of * an overdetermined system, i.e., solve the least squares problem * minimize || B - A**T * X ||. * * Several right hand side vectors b and solution vectors x can be * handled in a single call; they are stored as the columns of the * M-by-NRHS right hand side matrix B and the N-by-NRHS solution * matrix X. * * Arguments * ========= * * TRANS (input) CHARACTER * = 'N': the linear system involves A; * = 'T': the linear system involves A**T. * * M (input) INTEGER * The number of rows of the matrix A. M >= 0. * * N (input) INTEGER * The number of columns of the matrix A. N >= 0. * * NRHS (input) INTEGER * The number of right hand sides, i.e., the number of * columns of the matrices B and X. NRHS >=0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the M-by-N matrix A. * On exit, * if M >= N, A is overwritten by details of its QR * factorization as returned by DGEQRF; * if M < N, A is overwritten by details of its LQ * factorization as returned by DGELQF. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,M). * * B (input/output) DOUBLE PRECISION array, dimension (LDB,NRHS) * On entry, the matrix B of right hand side vectors, stored * columnwise; B is M-by-NRHS if TRANS = 'N', or N-by-NRHS * if TRANS = 'T'. * On exit, B is overwritten by the solution vectors, stored * columnwise: * if TRANS = 'N' and m >= n, rows 1 to n of B contain the least * squares solution vectors; the residual sum of squares for the * solution in each column is given by the sum of squares of * elements N+1 to M in that column; * if TRANS = 'N' and m < n, rows 1 to N of B contain the * minimum norm solution vectors; * if TRANS = 'T' and m >= n, rows 1 to M of B contain the * minimum norm solution vectors; * if TRANS = 'T' and m < n, rows 1 to M of B contain the * least squares solution vectors; the residual sum of squares * for the solution in each column is given by the sum of * squares of elements M+1 to N in that column. * * LDB (input) INTEGER * The leading dimension of the array B. LDB >= MAX(1,M,N). * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. * LWORK >= max( 1, MN + max( MN, NRHS ) ). * For optimal performance, * LWORK >= max( 1, MN + max( MN, NRHS )*NB ). * where MN = min(M,N) and NB is the optimum block size. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. LOGICAL LQUERY, TPSD INTEGER BROW, I, IASCL, IBSCL, J, MN, NB, SCLLEN, WSIZE DOUBLE PRECISION ANRM, BIGNUM, BNRM, SMLNUM * .. * .. Local Arrays .. DOUBLE PRECISION RWORK( 1 ) * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANGE EXTERNAL LSAME, ILAENV, DLAMCH, DLANGE * .. * .. External Subroutines .. EXTERNAL DGELQF, DGEQRF, DLASCL, DLASET, DORMLQ, DORMQR, $ DTRSM, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC DBLE, MAX, MIN * .. * .. Executable Statements .. * * Test the input arguments. * INFO = 0 MN = MIN( M, N ) LQUERY = ( LWORK.EQ.-1 ) IF( .NOT.( LSAME( TRANS, 'N' ) .OR. LSAME( TRANS, 'T' ) ) ) THEN INFO = -1 ELSE IF( M.LT.0 ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( NRHS.LT.0 ) THEN INFO = -4 ELSE IF( LDA.LT.MAX( 1, M ) ) THEN INFO = -6 ELSE IF( LDB.LT.MAX( 1, M, N ) ) THEN INFO = -8 ELSE IF( LWORK.LT.MAX( 1, MN+MAX( MN, NRHS ) ) .AND. .NOT.LQUERY ) $ THEN INFO = -10 END IF * * Figure out optimal block size * IF( INFO.EQ.0 .OR. INFO.EQ.-10 ) THEN * TPSD = .TRUE. IF( LSAME( TRANS, 'N' ) ) $ TPSD = .FALSE. * IF( M.GE.N ) THEN NB = ILAENV( 1, 'DGEQRF', ' ', M, N, -1, -1 ) IF( TPSD ) THEN NB = MAX( NB, ILAENV( 1, 'DORMQR', 'LN', M, NRHS, N, $ -1 ) ) ELSE NB = MAX( NB, ILAENV( 1, 'DORMQR', 'LT', M, NRHS, N, $ -1 ) ) END IF ELSE NB = ILAENV( 1, 'DGELQF', ' ', M, N, -1, -1 ) IF( TPSD ) THEN NB = MAX( NB, ILAENV( 1, 'DORMLQ', 'LT', N, NRHS, M, $ -1 ) ) ELSE NB = MAX( NB, ILAENV( 1, 'DORMLQ', 'LN', N, NRHS, M, $ -1 ) ) END IF END IF * WSIZE = MAX( 1, MN+MAX( MN, NRHS )*NB ) WORK( 1 ) = DBLE( WSIZE ) * END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGELS ', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( MIN( M, N, NRHS ).EQ.0 ) THEN CALL DLASET( 'Full', MAX( M, N ), NRHS, ZERO, ZERO, B, LDB ) RETURN END IF * * Get machine parameters * SMLNUM = DLAMCH( 'S' ) / DLAMCH( 'P' ) BIGNUM = ONE / SMLNUM CALL DLABAD( SMLNUM, BIGNUM ) * * Scale A, B if max element outside range [SMLNUM,BIGNUM] * ANRM = DLANGE( 'M', M, N, A, LDA, RWORK ) IASCL = 0 IF( ANRM.GT.ZERO .AND. ANRM.LT.SMLNUM ) THEN * * Scale matrix norm up to SMLNUM * CALL DLASCL( 'G', 0, 0, ANRM, SMLNUM, M, N, A, LDA, INFO ) IASCL = 1 ELSE IF( ANRM.GT.BIGNUM ) THEN * * Scale matrix norm down to BIGNUM * CALL DLASCL( 'G', 0, 0, ANRM, BIGNUM, M, N, A, LDA, INFO ) IASCL = 2 ELSE IF( ANRM.EQ.ZERO ) THEN * * Matrix all zero. Return zero solution. * CALL DLASET( 'F', MAX( M, N ), NRHS, ZERO, ZERO, B, LDB ) GO TO 50 END IF * BROW = M IF( TPSD ) $ BROW = N BNRM = DLANGE( 'M', BROW, NRHS, B, LDB, RWORK ) IBSCL = 0 IF( BNRM.GT.ZERO .AND. BNRM.LT.SMLNUM ) THEN * * Scale matrix norm up to SMLNUM * CALL DLASCL( 'G', 0, 0, BNRM, SMLNUM, BROW, NRHS, B, LDB, $ INFO ) IBSCL = 1 ELSE IF( BNRM.GT.BIGNUM ) THEN * * Scale matrix norm down to BIGNUM * CALL DLASCL( 'G', 0, 0, BNRM, BIGNUM, BROW, NRHS, B, LDB, $ INFO ) IBSCL = 2 END IF * IF( M.GE.N ) THEN * * compute QR factorization of A * CALL DGEQRF( M, N, A, LDA, WORK( 1 ), WORK( MN+1 ), LWORK-MN, $ INFO ) * * workspace at least N, optimally N*NB * IF( .NOT.TPSD ) THEN * * Least-Squares Problem min || A * X - B || * * B(1:M,1:NRHS) := Q' * B(1:M,1:NRHS) * CALL DORMQR( 'Left', 'Transpose', M, NRHS, N, A, LDA, $ WORK( 1 ), B, LDB, WORK( MN+1 ), LWORK-MN, $ INFO ) * * workspace at least NRHS, optimally NRHS*NB * * B(1:N,1:NRHS) := inv(R) * B(1:N,1:NRHS) * CALL DTRSM( 'Left', 'Upper', 'No transpose', 'Non-unit', N, $ NRHS, ONE, A, LDA, B, LDB ) * SCLLEN = N * ELSE * * Overdetermined system of equations A' * X = B * * B(1:N,1:NRHS) := inv(R') * B(1:N,1:NRHS) * CALL DTRSM( 'Left', 'Upper', 'Transpose', 'Non-unit', N, $ NRHS, ONE, A, LDA, B, LDB ) * * B(N+1:M,1:NRHS) = ZERO * DO 20 J = 1, NRHS DO 10 I = N + 1, M B( I, J ) = ZERO 10 CONTINUE 20 CONTINUE * * B(1:M,1:NRHS) := Q(1:N,:) * B(1:N,1:NRHS) * CALL DORMQR( 'Left', 'No transpose', M, NRHS, N, A, LDA, $ WORK( 1 ), B, LDB, WORK( MN+1 ), LWORK-MN, $ INFO ) * * workspace at least NRHS, optimally NRHS*NB * SCLLEN = M * END IF * ELSE * * Compute LQ factorization of A * CALL DGELQF( M, N, A, LDA, WORK( 1 ), WORK( MN+1 ), LWORK-MN, $ INFO ) * * workspace at least M, optimally M*NB. * IF( .NOT.TPSD ) THEN * * underdetermined system of equations A * X = B * * B(1:M,1:NRHS) := inv(L) * B(1:M,1:NRHS) * CALL DTRSM( 'Left', 'Lower', 'No transpose', 'Non-unit', M, $ NRHS, ONE, A, LDA, B, LDB ) * * B(M+1:N,1:NRHS) = 0 * DO 40 J = 1, NRHS DO 30 I = M + 1, N B( I, J ) = ZERO 30 CONTINUE 40 CONTINUE * * B(1:N,1:NRHS) := Q(1:N,:)' * B(1:M,1:NRHS) * CALL DORMLQ( 'Left', 'Transpose', N, NRHS, M, A, LDA, $ WORK( 1 ), B, LDB, WORK( MN+1 ), LWORK-MN, $ INFO ) * * workspace at least NRHS, optimally NRHS*NB * SCLLEN = N * ELSE * * overdetermined system min || A' * X - B || * * B(1:N,1:NRHS) := Q * B(1:N,1:NRHS) * CALL DORMLQ( 'Left', 'No transpose', N, NRHS, M, A, LDA, $ WORK( 1 ), B, LDB, WORK( MN+1 ), LWORK-MN, $ INFO ) * * workspace at least NRHS, optimally NRHS*NB * * B(1:M,1:NRHS) := inv(L') * B(1:M,1:NRHS) * CALL DTRSM( 'Left', 'Lower', 'Transpose', 'Non-unit', M, $ NRHS, ONE, A, LDA, B, LDB ) * SCLLEN = M * END IF * END IF * * Undo scaling * IF( IASCL.EQ.1 ) THEN CALL DLASCL( 'G', 0, 0, ANRM, SMLNUM, SCLLEN, NRHS, B, LDB, $ INFO ) ELSE IF( IASCL.EQ.2 ) THEN CALL DLASCL( 'G', 0, 0, ANRM, BIGNUM, SCLLEN, NRHS, B, LDB, $ INFO ) END IF IF( IBSCL.EQ.1 ) THEN CALL DLASCL( 'G', 0, 0, SMLNUM, BNRM, SCLLEN, NRHS, B, LDB, $ INFO ) ELSE IF( IBSCL.EQ.2 ) THEN CALL DLASCL( 'G', 0, 0, BIGNUM, BNRM, SCLLEN, NRHS, B, LDB, $ INFO ) END IF * 50 CONTINUE WORK( 1 ) = DBLE( WSIZE ) * RETURN * * End of DGELS * END SUBROUTINE DGELSD( M, N, NRHS, A, LDA, B, LDB, S, RCOND, RANK, $ WORK, LWORK, IWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1999 * * .. Scalar Arguments .. INTEGER INFO, LDA, LDB, LWORK, M, N, NRHS, RANK DOUBLE PRECISION RCOND * .. * .. Array Arguments .. INTEGER IWORK( * ) DOUBLE PRECISION A( LDA, * ), B( LDB, * ), S( * ), WORK( * ) * .. * * Purpose * ======= * * DGELSD computes the minimum-norm solution to a real linear least * squares problem: * minimize 2-norm(| b - A*x |) * using the singular value decomposition (SVD) of A. A is an M-by-N * matrix which may be rank-deficient. * * Several right hand side vectors b and solution vectors x can be * handled in a single call; they are stored as the columns of the * M-by-NRHS right hand side matrix B and the N-by-NRHS solution * matrix X. * * The problem is solved in three steps: * (1) Reduce the coefficient matrix A to bidiagonal form with * Householder transformations, reducing the original problem * into a "bidiagonal least squares problem" (BLS) * (2) Solve the BLS using a divide and conquer approach. * (3) Apply back all the Householder tranformations to solve * the original least squares problem. * * The effective rank of A is determined by treating as zero those * singular values which are less than RCOND times the largest singular * value. * * The divide and conquer algorithm makes very mild assumptions about * floating point arithmetic. It will work on machines with a guard * digit in add/subtract, or on those binary machines without guard * digits which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or * Cray-2. It could conceivably fail on hexadecimal or decimal machines * without guard digits, but we know of none. * * Arguments * ========= * * M (input) INTEGER * The number of rows of A. M >= 0. * * N (input) INTEGER * The number of columns of A. N >= 0. * * NRHS (input) INTEGER * The number of right hand sides, i.e., the number of columns * of the matrices B and X. NRHS >= 0. * * A (input) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the M-by-N matrix A. * On exit, A has been destroyed. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,M). * * B (input/output) DOUBLE PRECISION array, dimension (LDB,NRHS) * On entry, the M-by-NRHS right hand side matrix B. * On exit, B is overwritten by the N-by-NRHS solution * matrix X. If m >= n and RANK = n, the residual * sum-of-squares for the solution in the i-th column is given * by the sum of squares of elements n+1:m in that column. * * LDB (input) INTEGER * The leading dimension of the array B. LDB >= max(1,max(M,N)). * * S (output) DOUBLE PRECISION array, dimension (min(M,N)) * The singular values of A in decreasing order. * The condition number of A in the 2-norm = S(1)/S(min(m,n)). * * RCOND (input) DOUBLE PRECISION * RCOND is used to determine the effective rank of A. * Singular values S(i) <= RCOND*S(1) are treated as zero. * If RCOND < 0, machine precision is used instead. * * RANK (output) INTEGER * The effective rank of A, i.e., the number of singular values * which are greater than RCOND*S(1). * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK must be at least 1. * The exact minimum amount of workspace needed depends on M, * N and NRHS. As long as LWORK is at least * 12*N + 2*N*SMLSIZ + 8*N*NLVL + N*NRHS + (SMLSIZ+1)**2, * if M is greater than or equal to N or * 12*M + 2*M*SMLSIZ + 8*M*NLVL + M*NRHS + (SMLSIZ+1)**2, * if M is less than N, the code will execute correctly. * SMLSIZ is returned by ILAENV and is equal to the maximum * size of the subproblems at the bottom of the computation * tree (usually about 25), and * NLVL = MAX( 0, INT( LOG_2( MIN( M,N )/(SMLSIZ+1) ) ) + 1 ) * For good performance, LWORK should generally be larger. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * IWORK (workspace) INTEGER array, dimension (LIWORK) * LIWORK >= 3 * MINMN * NLVL + 11 * MINMN, * where MINMN = MIN( M,N ). * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: the algorithm for computing the SVD failed to converge; * if INFO = i, i off-diagonal elements of an intermediate * bidiagonal form did not converge to zero. * * Further Details * =============== * * Based on contributions by * Ming Gu and Ren-Cang Li, Computer Science Division, University of * California at Berkeley, USA * Osni Marques, LBNL/NERSC, USA * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE, TWO PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0, TWO = 2.0D0 ) * .. * .. Local Scalars .. LOGICAL LQUERY INTEGER IASCL, IBSCL, IE, IL, ITAU, ITAUP, ITAUQ, $ LDWORK, MAXMN, MAXWRK, MINMN, MINWRK, MM, $ MNTHR, NLVL, NWORK, SMLSIZ, WLALSD DOUBLE PRECISION ANRM, BIGNUM, BNRM, EPS, SFMIN, SMLNUM * .. * .. External Subroutines .. EXTERNAL DGEBRD, DGELQF, DGEQRF, DLABAD, DLACPY, DLALSD, $ DLASCL, DLASET, DORMBR, DORMLQ, DORMQR, XERBLA * .. * .. External Functions .. INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANGE EXTERNAL ILAENV, DLAMCH, DLANGE * .. * .. Intrinsic Functions .. INTRINSIC DBLE, INT, LOG, MAX, MIN * .. * .. Executable Statements .. * * Test the input arguments. * INFO = 0 MINMN = MIN( M, N ) MAXMN = MAX( M, N ) MNTHR = ILAENV( 6, 'DGELSD', ' ', M, N, NRHS, -1 ) LQUERY = ( LWORK.EQ.-1 ) IF( M.LT.0 ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 ELSE IF( NRHS.LT.0 ) THEN INFO = -3 ELSE IF( LDA.LT.MAX( 1, M ) ) THEN INFO = -5 ELSE IF( LDB.LT.MAX( 1, MAXMN ) ) THEN INFO = -7 END IF * SMLSIZ = ILAENV( 9, 'DGELSD', ' ', 0, 0, 0, 0 ) * * Compute workspace. * (Note: Comments in the code beginning "Workspace:" describe the * minimal amount of workspace needed at that point in the code, * as well as the preferred amount for good performance. * NB refers to the optimal block size for the immediately * following subroutine, as returned by ILAENV.) * MINWRK = 1 MINMN = MAX( 1, MINMN ) NLVL = MAX( INT( LOG( DBLE( MINMN ) / DBLE( SMLSIZ+1 ) ) / $ LOG( TWO ) ) + 1, 0 ) * IF( INFO.EQ.0 ) THEN MAXWRK = 0 MM = M IF( M.GE.N .AND. M.GE.MNTHR ) THEN * * Path 1a - overdetermined, with many more rows than columns. * MM = N MAXWRK = MAX( MAXWRK, N+N*ILAENV( 1, 'DGEQRF', ' ', M, N, $ -1, -1 ) ) MAXWRK = MAX( MAXWRK, N+NRHS* $ ILAENV( 1, 'DORMQR', 'LT', M, NRHS, N, -1 ) ) END IF IF( M.GE.N ) THEN * * Path 1 - overdetermined or exactly determined. * MAXWRK = MAX( MAXWRK, 3*N+( MM+N )* $ ILAENV( 1, 'DGEBRD', ' ', MM, N, -1, -1 ) ) MAXWRK = MAX( MAXWRK, 3*N+NRHS* $ ILAENV( 1, 'DORMBR', 'QLT', MM, NRHS, N, -1 ) ) MAXWRK = MAX( MAXWRK, 3*N+( N-1 )* $ ILAENV( 1, 'DORMBR', 'PLN', N, NRHS, N, -1 ) ) WLALSD = 9*N+2*N*SMLSIZ+8*N*NLVL+N*NRHS+(SMLSIZ+1)**2 MAXWRK = MAX( MAXWRK, 3*N+WLALSD ) MINWRK = MAX( 3*N+MM, 3*N+NRHS, 3*N+WLALSD ) END IF IF( N.GT.M ) THEN WLALSD = 9*M+2*M*SMLSIZ+8*M*NLVL+M*NRHS+(SMLSIZ+1)**2 IF( N.GE.MNTHR ) THEN * * Path 2a - underdetermined, with many more columns * than rows. * MAXWRK = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, -1 ) MAXWRK = MAX( MAXWRK, M*M+4*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) MAXWRK = MAX( MAXWRK, M*M+4*M+NRHS* $ ILAENV( 1, 'DORMBR', 'QLT', M, NRHS, M, -1 ) ) MAXWRK = MAX( MAXWRK, M*M+4*M+( M-1 )* $ ILAENV( 1, 'DORMBR', 'PLN', M, NRHS, M, -1 ) ) IF( NRHS.GT.1 ) THEN MAXWRK = MAX( MAXWRK, M*M+M+M*NRHS ) ELSE MAXWRK = MAX( MAXWRK, M*M+2*M ) END IF MAXWRK = MAX( MAXWRK, M+NRHS* $ ILAENV( 1, 'DORMLQ', 'LT', N, NRHS, M, -1 ) ) MAXWRK = MAX( MAXWRK, M*M+4*M+WLALSD ) ELSE * * Path 2 - remaining underdetermined cases. * MAXWRK = 3*M + ( N+M )*ILAENV( 1, 'DGEBRD', ' ', M, N, $ -1, -1 ) MAXWRK = MAX( MAXWRK, 3*M+NRHS* $ ILAENV( 1, 'DORMBR', 'QLT', M, NRHS, N, -1 ) ) MAXWRK = MAX( MAXWRK, 3*M+M* $ ILAENV( 1, 'DORMBR', 'PLN', N, NRHS, M, -1 ) ) MAXWRK = MAX( MAXWRK, 3*M+WLALSD ) END IF MINWRK = MAX( 3*M+NRHS, 3*M+M, 3*M+WLALSD ) END IF MINWRK = MIN( MINWRK, MAXWRK ) WORK( 1 ) = MAXWRK IF( LWORK.LT.MINWRK .AND. .NOT.LQUERY ) THEN INFO = -12 END IF END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGELSD', -INFO ) RETURN ELSE IF( LQUERY ) THEN GO TO 10 END IF * * Quick return if possible. * IF( M.EQ.0 .OR. N.EQ.0 ) THEN RANK = 0 RETURN END IF * * Get machine parameters. * EPS = DLAMCH( 'P' ) SFMIN = DLAMCH( 'S' ) SMLNUM = SFMIN / EPS BIGNUM = ONE / SMLNUM CALL DLABAD( SMLNUM, BIGNUM ) * * Scale A if max entry outside range [SMLNUM,BIGNUM]. * ANRM = DLANGE( 'M', M, N, A, LDA, WORK ) IASCL = 0 IF( ANRM.GT.ZERO .AND. ANRM.LT.SMLNUM ) THEN * * Scale matrix norm up to SMLNUM. * CALL DLASCL( 'G', 0, 0, ANRM, SMLNUM, M, N, A, LDA, INFO ) IASCL = 1 ELSE IF( ANRM.GT.BIGNUM ) THEN * * Scale matrix norm down to BIGNUM. * CALL DLASCL( 'G', 0, 0, ANRM, BIGNUM, M, N, A, LDA, INFO ) IASCL = 2 ELSE IF( ANRM.EQ.ZERO ) THEN * * Matrix all zero. Return zero solution. * CALL DLASET( 'F', MAX( M, N ), NRHS, ZERO, ZERO, B, LDB ) CALL DLASET( 'F', MINMN, 1, ZERO, ZERO, S, 1 ) RANK = 0 GO TO 10 END IF * * Scale B if max entry outside range [SMLNUM,BIGNUM]. * BNRM = DLANGE( 'M', M, NRHS, B, LDB, WORK ) IBSCL = 0 IF( BNRM.GT.ZERO .AND. BNRM.LT.SMLNUM ) THEN * * Scale matrix norm up to SMLNUM. * CALL DLASCL( 'G', 0, 0, BNRM, SMLNUM, M, NRHS, B, LDB, INFO ) IBSCL = 1 ELSE IF( BNRM.GT.BIGNUM ) THEN * * Scale matrix norm down to BIGNUM. * CALL DLASCL( 'G', 0, 0, BNRM, BIGNUM, M, NRHS, B, LDB, INFO ) IBSCL = 2 END IF * * If M < N make sure certain entries of B are zero. * IF( M.LT.N ) $ CALL DLASET( 'F', N-M, NRHS, ZERO, ZERO, B( M+1, 1 ), LDB ) * * Overdetermined case. * IF( M.GE.N ) THEN * * Path 1 - overdetermined or exactly determined. * MM = M IF( M.GE.MNTHR ) THEN * * Path 1a - overdetermined, with many more rows than columns. * MM = N ITAU = 1 NWORK = ITAU + N * * Compute A=Q*R. * (Workspace: need 2*N, prefer N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), WORK( NWORK ), $ LWORK-NWORK+1, INFO ) * * Multiply B by transpose(Q). * (Workspace: need N+NRHS, prefer N+NRHS*NB) * CALL DORMQR( 'L', 'T', M, NRHS, N, A, LDA, WORK( ITAU ), B, $ LDB, WORK( NWORK ), LWORK-NWORK+1, INFO ) * * Zero out below R. * IF( N.GT.1 ) THEN CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, A( 2, 1 ), LDA ) END IF END IF * IE = 1 ITAUQ = IE + N ITAUP = ITAUQ + N NWORK = ITAUP + N * * Bidiagonalize R in A. * (Workspace: need 3*N+MM, prefer 3*N+(MM+N)*NB) * CALL DGEBRD( MM, N, A, LDA, S, WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( NWORK ), LWORK-NWORK+1, $ INFO ) * * Multiply B by transpose of left bidiagonalizing vectors of R. * (Workspace: need 3*N+NRHS, prefer 3*N+NRHS*NB) * CALL DORMBR( 'Q', 'L', 'T', MM, NRHS, N, A, LDA, WORK( ITAUQ ), $ B, LDB, WORK( NWORK ), LWORK-NWORK+1, INFO ) * * Solve the bidiagonal least squares problem. * CALL DLALSD( 'U', SMLSIZ, N, NRHS, S, WORK( IE ), B, LDB, $ RCOND, RANK, WORK( NWORK ), IWORK, INFO ) IF( INFO.NE.0 ) THEN GO TO 10 END IF * * Multiply B by right bidiagonalizing vectors of R. * CALL DORMBR( 'P', 'L', 'N', N, NRHS, N, A, LDA, WORK( ITAUP ), $ B, LDB, WORK( NWORK ), LWORK-NWORK+1, INFO ) * ELSE IF( N.GE.MNTHR .AND. LWORK.GE.4*M+M*M+ $ MAX( M, 2*M-4, NRHS, N-3*M ) ) THEN * * Path 2a - underdetermined, with many more columns than rows * and sufficient workspace for an efficient algorithm. * LDWORK = M IF( LWORK.GE.MAX( 4*M+M*LDA+MAX( M, 2*M-4, NRHS, N-3*M ), $ M*LDA+M+M*NRHS ) )LDWORK = LDA ITAU = 1 NWORK = M + 1 * * Compute A=L*Q. * (Workspace: need 2*M, prefer M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), WORK( NWORK ), $ LWORK-NWORK+1, INFO ) IL = NWORK * * Copy L to WORK(IL), zeroing out above its diagonal. * CALL DLACPY( 'L', M, M, A, LDA, WORK( IL ), LDWORK ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, WORK( IL+LDWORK ), $ LDWORK ) IE = IL + LDWORK*M ITAUQ = IE + M ITAUP = ITAUQ + M NWORK = ITAUP + M * * Bidiagonalize L in WORK(IL). * (Workspace: need M*M+5*M, prefer M*M+4*M+2*M*NB) * CALL DGEBRD( M, M, WORK( IL ), LDWORK, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), WORK( NWORK ), $ LWORK-NWORK+1, INFO ) * * Multiply B by transpose of left bidiagonalizing vectors of L. * (Workspace: need M*M+4*M+NRHS, prefer M*M+4*M+NRHS*NB) * CALL DORMBR( 'Q', 'L', 'T', M, NRHS, M, WORK( IL ), LDWORK, $ WORK( ITAUQ ), B, LDB, WORK( NWORK ), $ LWORK-NWORK+1, INFO ) * * Solve the bidiagonal least squares problem. * CALL DLALSD( 'U', SMLSIZ, M, NRHS, S, WORK( IE ), B, LDB, $ RCOND, RANK, WORK( NWORK ), IWORK, INFO ) IF( INFO.NE.0 ) THEN GO TO 10 END IF * * Multiply B by right bidiagonalizing vectors of L. * CALL DORMBR( 'P', 'L', 'N', M, NRHS, M, WORK( IL ), LDWORK, $ WORK( ITAUP ), B, LDB, WORK( NWORK ), $ LWORK-NWORK+1, INFO ) * * Zero out below first M rows of B. * CALL DLASET( 'F', N-M, NRHS, ZERO, ZERO, B( M+1, 1 ), LDB ) NWORK = ITAU + M * * Multiply transpose(Q) by B. * (Workspace: need M+NRHS, prefer M+NRHS*NB) * CALL DORMLQ( 'L', 'T', N, NRHS, M, A, LDA, WORK( ITAU ), B, $ LDB, WORK( NWORK ), LWORK-NWORK+1, INFO ) * ELSE * * Path 2 - remaining underdetermined cases. * IE = 1 ITAUQ = IE + M ITAUP = ITAUQ + M NWORK = ITAUP + M * * Bidiagonalize A. * (Workspace: need 3*M+N, prefer 3*M+(M+N)*NB) * CALL DGEBRD( M, N, A, LDA, S, WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( NWORK ), LWORK-NWORK+1, $ INFO ) * * Multiply B by transpose of left bidiagonalizing vectors. * (Workspace: need 3*M+NRHS, prefer 3*M+NRHS*NB) * CALL DORMBR( 'Q', 'L', 'T', M, NRHS, N, A, LDA, WORK( ITAUQ ), $ B, LDB, WORK( NWORK ), LWORK-NWORK+1, INFO ) * * Solve the bidiagonal least squares problem. * CALL DLALSD( 'L', SMLSIZ, M, NRHS, S, WORK( IE ), B, LDB, $ RCOND, RANK, WORK( NWORK ), IWORK, INFO ) IF( INFO.NE.0 ) THEN GO TO 10 END IF * * Multiply B by right bidiagonalizing vectors of A. * CALL DORMBR( 'P', 'L', 'N', N, NRHS, M, A, LDA, WORK( ITAUP ), $ B, LDB, WORK( NWORK ), LWORK-NWORK+1, INFO ) * END IF * * Undo scaling. * IF( IASCL.EQ.1 ) THEN CALL DLASCL( 'G', 0, 0, ANRM, SMLNUM, N, NRHS, B, LDB, INFO ) CALL DLASCL( 'G', 0, 0, SMLNUM, ANRM, MINMN, 1, S, MINMN, $ INFO ) ELSE IF( IASCL.EQ.2 ) THEN CALL DLASCL( 'G', 0, 0, ANRM, BIGNUM, N, NRHS, B, LDB, INFO ) CALL DLASCL( 'G', 0, 0, BIGNUM, ANRM, MINMN, 1, S, MINMN, $ INFO ) END IF IF( IBSCL.EQ.1 ) THEN CALL DLASCL( 'G', 0, 0, SMLNUM, BNRM, N, NRHS, B, LDB, INFO ) ELSE IF( IBSCL.EQ.2 ) THEN CALL DLASCL( 'G', 0, 0, BIGNUM, BNRM, N, NRHS, B, LDB, INFO ) END IF * 10 CONTINUE WORK( 1 ) = MAXWRK RETURN * * End of DGELSD * END SUBROUTINE DGELSS( M, N, NRHS, A, LDA, B, LDB, S, RCOND, RANK, $ WORK, LWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1999 * * .. Scalar Arguments .. INTEGER INFO, LDA, LDB, LWORK, M, N, NRHS, RANK DOUBLE PRECISION RCOND * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), B( LDB, * ), S( * ), WORK( * ) * .. * * Purpose * ======= * * DGELSS computes the minimum norm solution to a real linear least * squares problem: * * Minimize 2-norm(| b - A*x |). * * using the singular value decomposition (SVD) of A. A is an M-by-N * matrix which may be rank-deficient. * * Several right hand side vectors b and solution vectors x can be * handled in a single call; they are stored as the columns of the * M-by-NRHS right hand side matrix B and the N-by-NRHS solution matrix * X. * * The effective rank of A is determined by treating as zero those * singular values which are less than RCOND times the largest singular * value. * * Arguments * ========= * * M (input) INTEGER * The number of rows of the matrix A. M >= 0. * * N (input) INTEGER * The number of columns of the matrix A. N >= 0. * * NRHS (input) INTEGER * The number of right hand sides, i.e., the number of columns * of the matrices B and X. NRHS >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the M-by-N matrix A. * On exit, the first min(m,n) rows of A are overwritten with * its right singular vectors, stored rowwise. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,M). * * B (input/output) DOUBLE PRECISION array, dimension (LDB,NRHS) * On entry, the M-by-NRHS right hand side matrix B. * On exit, B is overwritten by the N-by-NRHS solution * matrix X. If m >= n and RANK = n, the residual * sum-of-squares for the solution in the i-th column is given * by the sum of squares of elements n+1:m in that column. * * LDB (input) INTEGER * The leading dimension of the array B. LDB >= max(1,max(M,N)). * * S (output) DOUBLE PRECISION array, dimension (min(M,N)) * The singular values of A in decreasing order. * The condition number of A in the 2-norm = S(1)/S(min(m,n)). * * RCOND (input) DOUBLE PRECISION * RCOND is used to determine the effective rank of A. * Singular values S(i) <= RCOND*S(1) are treated as zero. * If RCOND < 0, machine precision is used instead. * * RANK (output) INTEGER * The effective rank of A, i.e., the number of singular values * which are greater than RCOND*S(1). * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= 1, and also: * LWORK >= 3*min(M,N) + max( 2*min(M,N), max(M,N), NRHS ) * For good performance, LWORK should generally be larger. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: the algorithm for computing the SVD failed to converge; * if INFO = i, i off-diagonal elements of an intermediate * bidiagonal form did not converge to zero. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL LQUERY INTEGER BDSPAC, BL, CHUNK, I, IASCL, IBSCL, IE, IL, $ ITAU, ITAUP, ITAUQ, IWORK, LDWORK, MAXMN, $ MAXWRK, MINMN, MINWRK, MM, MNTHR DOUBLE PRECISION ANRM, BIGNUM, BNRM, EPS, SFMIN, SMLNUM, THR * .. * .. Local Arrays .. DOUBLE PRECISION VDUM( 1 ) * .. * .. External Subroutines .. EXTERNAL DBDSQR, DCOPY, DGEBRD, DGELQF, DGEMM, DGEMV, $ DGEQRF, DLABAD, DLACPY, DLASCL, DLASET, DORGBR, $ DORMBR, DORMLQ, DORMQR, DRSCL, XERBLA * .. * .. External Functions .. INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANGE EXTERNAL ILAENV, DLAMCH, DLANGE * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 MINMN = MIN( M, N ) MAXMN = MAX( M, N ) MNTHR = ILAENV( 6, 'DGELSS', ' ', M, N, NRHS, -1 ) LQUERY = ( LWORK.EQ.-1 ) IF( M.LT.0 ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 ELSE IF( NRHS.LT.0 ) THEN INFO = -3 ELSE IF( LDA.LT.MAX( 1, M ) ) THEN INFO = -5 ELSE IF( LDB.LT.MAX( 1, MAXMN ) ) THEN INFO = -7 END IF * * Compute workspace * (Note: Comments in the code beginning "Workspace:" describe the * minimal amount of workspace needed at that point in the code, * as well as the preferred amount for good performance. * NB refers to the optimal block size for the immediately * following subroutine, as returned by ILAENV.) * MINWRK = 1 IF( INFO.EQ.0 .AND. ( LWORK.GE.1 .OR. LQUERY ) ) THEN MAXWRK = 0 MM = M IF( M.GE.N .AND. M.GE.MNTHR ) THEN * * Path 1a - overdetermined, with many more rows than columns * MM = N MAXWRK = MAX( MAXWRK, N+N*ILAENV( 1, 'DGEQRF', ' ', M, N, $ -1, -1 ) ) MAXWRK = MAX( MAXWRK, N+NRHS* $ ILAENV( 1, 'DORMQR', 'LT', M, NRHS, N, -1 ) ) END IF IF( M.GE.N ) THEN * * Path 1 - overdetermined or exactly determined * * Compute workspace needed for DBDSQR * BDSPAC = MAX( 1, 5*N ) MAXWRK = MAX( MAXWRK, 3*N+( MM+N )* $ ILAENV( 1, 'DGEBRD', ' ', MM, N, -1, -1 ) ) MAXWRK = MAX( MAXWRK, 3*N+NRHS* $ ILAENV( 1, 'DORMBR', 'QLT', MM, NRHS, N, -1 ) ) MAXWRK = MAX( MAXWRK, 3*N+( N-1 )* $ ILAENV( 1, 'DORGBR', 'P', N, N, N, -1 ) ) MAXWRK = MAX( MAXWRK, BDSPAC ) MAXWRK = MAX( MAXWRK, N*NRHS ) MINWRK = MAX( 3*N+MM, 3*N+NRHS, BDSPAC ) MAXWRK = MAX( MINWRK, MAXWRK ) END IF IF( N.GT.M ) THEN * * Compute workspace needed for DBDSQR * BDSPAC = MAX( 1, 5*M ) MINWRK = MAX( 3*M+NRHS, 3*M+N, BDSPAC ) IF( N.GE.MNTHR ) THEN * * Path 2a - underdetermined, with many more columns * than rows * MAXWRK = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, -1 ) MAXWRK = MAX( MAXWRK, M*M+4*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) MAXWRK = MAX( MAXWRK, M*M+4*M+NRHS* $ ILAENV( 1, 'DORMBR', 'QLT', M, NRHS, M, -1 ) ) MAXWRK = MAX( MAXWRK, M*M+4*M+( M-1 )* $ ILAENV( 1, 'DORGBR', 'P', M, M, M, -1 ) ) MAXWRK = MAX( MAXWRK, M*M+M+BDSPAC ) IF( NRHS.GT.1 ) THEN MAXWRK = MAX( MAXWRK, M*M+M+M*NRHS ) ELSE MAXWRK = MAX( MAXWRK, M*M+2*M ) END IF MAXWRK = MAX( MAXWRK, M+NRHS* $ ILAENV( 1, 'DORMLQ', 'LT', N, NRHS, M, -1 ) ) ELSE * * Path 2 - underdetermined * MAXWRK = 3*M + ( N+M )*ILAENV( 1, 'DGEBRD', ' ', M, N, $ -1, -1 ) MAXWRK = MAX( MAXWRK, 3*M+NRHS* $ ILAENV( 1, 'DORMBR', 'QLT', M, NRHS, M, -1 ) ) MAXWRK = MAX( MAXWRK, 3*M+M* $ ILAENV( 1, 'DORGBR', 'P', M, N, M, -1 ) ) MAXWRK = MAX( MAXWRK, BDSPAC ) MAXWRK = MAX( MAXWRK, N*NRHS ) END IF END IF MAXWRK = MAX( MINWRK, MAXWRK ) WORK( 1 ) = MAXWRK END IF * MINWRK = MAX( MINWRK, 1 ) IF( LWORK.LT.MINWRK .AND. .NOT.LQUERY ) $ INFO = -12 IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGELSS', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( M.EQ.0 .OR. N.EQ.0 ) THEN RANK = 0 RETURN END IF * * Get machine parameters * EPS = DLAMCH( 'P' ) SFMIN = DLAMCH( 'S' ) SMLNUM = SFMIN / EPS BIGNUM = ONE / SMLNUM CALL DLABAD( SMLNUM, BIGNUM ) * * Scale A if max element outside range [SMLNUM,BIGNUM] * ANRM = DLANGE( 'M', M, N, A, LDA, WORK ) IASCL = 0 IF( ANRM.GT.ZERO .AND. ANRM.LT.SMLNUM ) THEN * * Scale matrix norm up to SMLNUM * CALL DLASCL( 'G', 0, 0, ANRM, SMLNUM, M, N, A, LDA, INFO ) IASCL = 1 ELSE IF( ANRM.GT.BIGNUM ) THEN * * Scale matrix norm down to BIGNUM * CALL DLASCL( 'G', 0, 0, ANRM, BIGNUM, M, N, A, LDA, INFO ) IASCL = 2 ELSE IF( ANRM.EQ.ZERO ) THEN * * Matrix all zero. Return zero solution. * CALL DLASET( 'F', MAX( M, N ), NRHS, ZERO, ZERO, B, LDB ) CALL DLASET( 'F', MINMN, 1, ZERO, ZERO, S, 1 ) RANK = 0 GO TO 70 END IF * * Scale B if max element outside range [SMLNUM,BIGNUM] * BNRM = DLANGE( 'M', M, NRHS, B, LDB, WORK ) IBSCL = 0 IF( BNRM.GT.ZERO .AND. BNRM.LT.SMLNUM ) THEN * * Scale matrix norm up to SMLNUM * CALL DLASCL( 'G', 0, 0, BNRM, SMLNUM, M, NRHS, B, LDB, INFO ) IBSCL = 1 ELSE IF( BNRM.GT.BIGNUM ) THEN * * Scale matrix norm down to BIGNUM * CALL DLASCL( 'G', 0, 0, BNRM, BIGNUM, M, NRHS, B, LDB, INFO ) IBSCL = 2 END IF * * Overdetermined case * IF( M.GE.N ) THEN * * Path 1 - overdetermined or exactly determined * MM = M IF( M.GE.MNTHR ) THEN * * Path 1a - overdetermined, with many more rows than columns * MM = N ITAU = 1 IWORK = ITAU + N * * Compute A=Q*R * (Workspace: need 2*N, prefer N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), WORK( IWORK ), $ LWORK-IWORK+1, INFO ) * * Multiply B by transpose(Q) * (Workspace: need N+NRHS, prefer N+NRHS*NB) * CALL DORMQR( 'L', 'T', M, NRHS, N, A, LDA, WORK( ITAU ), B, $ LDB, WORK( IWORK ), LWORK-IWORK+1, INFO ) * * Zero out below R * IF( N.GT.1 ) $ CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, A( 2, 1 ), LDA ) END IF * IE = 1 ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize R in A * (Workspace: need 3*N+MM, prefer 3*N+(MM+N)*NB) * CALL DGEBRD( MM, N, A, LDA, S, WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), LWORK-IWORK+1, $ INFO ) * * Multiply B by transpose of left bidiagonalizing vectors of R * (Workspace: need 3*N+NRHS, prefer 3*N+NRHS*NB) * CALL DORMBR( 'Q', 'L', 'T', MM, NRHS, N, A, LDA, WORK( ITAUQ ), $ B, LDB, WORK( IWORK ), LWORK-IWORK+1, INFO ) * * Generate right bidiagonalizing vectors of R in A * (Workspace: need 4*N-1, prefer 3*N+(N-1)*NB) * CALL DORGBR( 'P', N, N, N, A, LDA, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, INFO ) IWORK = IE + N * * Perform bidiagonal QR iteration * multiply B by transpose of left singular vectors * compute right singular vectors in A * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', N, N, 0, NRHS, S, WORK( IE ), A, LDA, VDUM, $ 1, B, LDB, WORK( IWORK ), INFO ) IF( INFO.NE.0 ) $ GO TO 70 * * Multiply B by reciprocals of singular values * THR = MAX( RCOND*S( 1 ), SFMIN ) IF( RCOND.LT.ZERO ) $ THR = MAX( EPS*S( 1 ), SFMIN ) RANK = 0 DO 10 I = 1, N IF( S( I ).GT.THR ) THEN CALL DRSCL( NRHS, S( I ), B( I, 1 ), LDB ) RANK = RANK + 1 ELSE CALL DLASET( 'F', 1, NRHS, ZERO, ZERO, B( I, 1 ), LDB ) END IF 10 CONTINUE * * Multiply B by right singular vectors * (Workspace: need N, prefer N*NRHS) * IF( LWORK.GE.LDB*NRHS .AND. NRHS.GT.1 ) THEN CALL DGEMM( 'T', 'N', N, NRHS, N, ONE, A, LDA, B, LDB, ZERO, $ WORK, LDB ) CALL DLACPY( 'G', N, NRHS, WORK, LDB, B, LDB ) ELSE IF( NRHS.GT.1 ) THEN CHUNK = LWORK / N DO 20 I = 1, NRHS, CHUNK BL = MIN( NRHS-I+1, CHUNK ) CALL DGEMM( 'T', 'N', N, BL, N, ONE, A, LDA, B( 1, I ), $ LDB, ZERO, WORK, N ) CALL DLACPY( 'G', N, BL, WORK, N, B( 1, I ), LDB ) 20 CONTINUE ELSE CALL DGEMV( 'T', N, N, ONE, A, LDA, B, 1, ZERO, WORK, 1 ) CALL DCOPY( N, WORK, 1, B, 1 ) END IF * ELSE IF( N.GE.MNTHR .AND. LWORK.GE.4*M+M*M+ $ MAX( M, 2*M-4, NRHS, N-3*M ) ) THEN * * Path 2a - underdetermined, with many more columns than rows * and sufficient workspace for an efficient algorithm * LDWORK = M IF( LWORK.GE.MAX( 4*M+M*LDA+MAX( M, 2*M-4, NRHS, N-3*M ), $ M*LDA+M+M*NRHS ) )LDWORK = LDA ITAU = 1 IWORK = M + 1 * * Compute A=L*Q * (Workspace: need 2*M, prefer M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), WORK( IWORK ), $ LWORK-IWORK+1, INFO ) IL = IWORK * * Copy L to WORK(IL), zeroing out above it * CALL DLACPY( 'L', M, M, A, LDA, WORK( IL ), LDWORK ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, WORK( IL+LDWORK ), $ LDWORK ) IE = IL + LDWORK*M ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize L in WORK(IL) * (Workspace: need M*M+5*M, prefer M*M+4*M+2*M*NB) * CALL DGEBRD( M, M, WORK( IL ), LDWORK, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, INFO ) * * Multiply B by transpose of left bidiagonalizing vectors of L * (Workspace: need M*M+4*M+NRHS, prefer M*M+4*M+NRHS*NB) * CALL DORMBR( 'Q', 'L', 'T', M, NRHS, M, WORK( IL ), LDWORK, $ WORK( ITAUQ ), B, LDB, WORK( IWORK ), $ LWORK-IWORK+1, INFO ) * * Generate right bidiagonalizing vectors of R in WORK(IL) * (Workspace: need M*M+5*M-1, prefer M*M+4*M+(M-1)*NB) * CALL DORGBR( 'P', M, M, M, WORK( IL ), LDWORK, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, INFO ) IWORK = IE + M * * Perform bidiagonal QR iteration, * computing right singular vectors of L in WORK(IL) and * multiplying B by transpose of left singular vectors * (Workspace: need M*M+M+BDSPAC) * CALL DBDSQR( 'U', M, M, 0, NRHS, S, WORK( IE ), WORK( IL ), $ LDWORK, A, LDA, B, LDB, WORK( IWORK ), INFO ) IF( INFO.NE.0 ) $ GO TO 70 * * Multiply B by reciprocals of singular values * THR = MAX( RCOND*S( 1 ), SFMIN ) IF( RCOND.LT.ZERO ) $ THR = MAX( EPS*S( 1 ), SFMIN ) RANK = 0 DO 30 I = 1, M IF( S( I ).GT.THR ) THEN CALL DRSCL( NRHS, S( I ), B( I, 1 ), LDB ) RANK = RANK + 1 ELSE CALL DLASET( 'F', 1, NRHS, ZERO, ZERO, B( I, 1 ), LDB ) END IF 30 CONTINUE IWORK = IE * * Multiply B by right singular vectors of L in WORK(IL) * (Workspace: need M*M+2*M, prefer M*M+M+M*NRHS) * IF( LWORK.GE.LDB*NRHS+IWORK-1 .AND. NRHS.GT.1 ) THEN CALL DGEMM( 'T', 'N', M, NRHS, M, ONE, WORK( IL ), LDWORK, $ B, LDB, ZERO, WORK( IWORK ), LDB ) CALL DLACPY( 'G', M, NRHS, WORK( IWORK ), LDB, B, LDB ) ELSE IF( NRHS.GT.1 ) THEN CHUNK = ( LWORK-IWORK+1 ) / M DO 40 I = 1, NRHS, CHUNK BL = MIN( NRHS-I+1, CHUNK ) CALL DGEMM( 'T', 'N', M, BL, M, ONE, WORK( IL ), LDWORK, $ B( 1, I ), LDB, ZERO, WORK( IWORK ), N ) CALL DLACPY( 'G', M, BL, WORK( IWORK ), N, B( 1, I ), $ LDB ) 40 CONTINUE ELSE CALL DGEMV( 'T', M, M, ONE, WORK( IL ), LDWORK, B( 1, 1 ), $ 1, ZERO, WORK( IWORK ), 1 ) CALL DCOPY( M, WORK( IWORK ), 1, B( 1, 1 ), 1 ) END IF * * Zero out below first M rows of B * CALL DLASET( 'F', N-M, NRHS, ZERO, ZERO, B( M+1, 1 ), LDB ) IWORK = ITAU + M * * Multiply transpose(Q) by B * (Workspace: need M+NRHS, prefer M+NRHS*NB) * CALL DORMLQ( 'L', 'T', N, NRHS, M, A, LDA, WORK( ITAU ), B, $ LDB, WORK( IWORK ), LWORK-IWORK+1, INFO ) * ELSE * * Path 2 - remaining underdetermined cases * IE = 1 ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize A * (Workspace: need 3*M+N, prefer 3*M+(M+N)*NB) * CALL DGEBRD( M, N, A, LDA, S, WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), LWORK-IWORK+1, $ INFO ) * * Multiply B by transpose of left bidiagonalizing vectors * (Workspace: need 3*M+NRHS, prefer 3*M+NRHS*NB) * CALL DORMBR( 'Q', 'L', 'T', M, NRHS, N, A, LDA, WORK( ITAUQ ), $ B, LDB, WORK( IWORK ), LWORK-IWORK+1, INFO ) * * Generate right bidiagonalizing vectors in A * (Workspace: need 4*M, prefer 3*M+M*NB) * CALL DORGBR( 'P', M, N, M, A, LDA, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, INFO ) IWORK = IE + M * * Perform bidiagonal QR iteration, * computing right singular vectors of A in A and * multiplying B by transpose of left singular vectors * (Workspace: need BDSPAC) * CALL DBDSQR( 'L', M, N, 0, NRHS, S, WORK( IE ), A, LDA, VDUM, $ 1, B, LDB, WORK( IWORK ), INFO ) IF( INFO.NE.0 ) $ GO TO 70 * * Multiply B by reciprocals of singular values * THR = MAX( RCOND*S( 1 ), SFMIN ) IF( RCOND.LT.ZERO ) $ THR = MAX( EPS*S( 1 ), SFMIN ) RANK = 0 DO 50 I = 1, M IF( S( I ).GT.THR ) THEN CALL DRSCL( NRHS, S( I ), B( I, 1 ), LDB ) RANK = RANK + 1 ELSE CALL DLASET( 'F', 1, NRHS, ZERO, ZERO, B( I, 1 ), LDB ) END IF 50 CONTINUE * * Multiply B by right singular vectors of A * (Workspace: need N, prefer N*NRHS) * IF( LWORK.GE.LDB*NRHS .AND. NRHS.GT.1 ) THEN CALL DGEMM( 'T', 'N', N, NRHS, M, ONE, A, LDA, B, LDB, ZERO, $ WORK, LDB ) CALL DLACPY( 'F', N, NRHS, WORK, LDB, B, LDB ) ELSE IF( NRHS.GT.1 ) THEN CHUNK = LWORK / N DO 60 I = 1, NRHS, CHUNK BL = MIN( NRHS-I+1, CHUNK ) CALL DGEMM( 'T', 'N', N, BL, M, ONE, A, LDA, B( 1, I ), $ LDB, ZERO, WORK, N ) CALL DLACPY( 'F', N, BL, WORK, N, B( 1, I ), LDB ) 60 CONTINUE ELSE CALL DGEMV( 'T', M, N, ONE, A, LDA, B, 1, ZERO, WORK, 1 ) CALL DCOPY( N, WORK, 1, B, 1 ) END IF END IF * * Undo scaling * IF( IASCL.EQ.1 ) THEN CALL DLASCL( 'G', 0, 0, ANRM, SMLNUM, N, NRHS, B, LDB, INFO ) CALL DLASCL( 'G', 0, 0, SMLNUM, ANRM, MINMN, 1, S, MINMN, $ INFO ) ELSE IF( IASCL.EQ.2 ) THEN CALL DLASCL( 'G', 0, 0, ANRM, BIGNUM, N, NRHS, B, LDB, INFO ) CALL DLASCL( 'G', 0, 0, BIGNUM, ANRM, MINMN, 1, S, MINMN, $ INFO ) END IF IF( IBSCL.EQ.1 ) THEN CALL DLASCL( 'G', 0, 0, SMLNUM, BNRM, N, NRHS, B, LDB, INFO ) ELSE IF( IBSCL.EQ.2 ) THEN CALL DLASCL( 'G', 0, 0, BIGNUM, BNRM, N, NRHS, B, LDB, INFO ) END IF * 70 CONTINUE WORK( 1 ) = MAXWRK RETURN * * End of DGELSS * END SUBROUTINE DGELSX( M, N, NRHS, A, LDA, B, LDB, JPVT, RCOND, RANK, $ WORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * March 31, 1993 * * .. Scalar Arguments .. INTEGER INFO, LDA, LDB, M, N, NRHS, RANK DOUBLE PRECISION RCOND * .. * .. Array Arguments .. INTEGER JPVT( * ) DOUBLE PRECISION A( LDA, * ), B( LDB, * ), WORK( * ) * .. * * Purpose * ======= * * This routine is deprecated and has been replaced by routine DGELSY. * * DGELSX computes the minimum-norm solution to a real linear least * squares problem: * minimize || A * X - B || * using a complete orthogonal factorization of A. A is an M-by-N * matrix which may be rank-deficient. * * Several right hand side vectors b and solution vectors x can be * handled in a single call; they are stored as the columns of the * M-by-NRHS right hand side matrix B and the N-by-NRHS solution * matrix X. * * The routine first computes a QR factorization with column pivoting: * A * P = Q * [ R11 R12 ] * [ 0 R22 ] * with R11 defined as the largest leading submatrix whose estimated * condition number is less than 1/RCOND. The order of R11, RANK, * is the effective rank of A. * * Then, R22 is considered to be negligible, and R12 is annihilated * by orthogonal transformations from the right, arriving at the * complete orthogonal factorization: * A * P = Q * [ T11 0 ] * Z * [ 0 0 ] * The minimum-norm solution is then * X = P * Z' [ inv(T11)*Q1'*B ] * [ 0 ] * where Q1 consists of the first RANK columns of Q. * * Arguments * ========= * * M (input) INTEGER * The number of rows of the matrix A. M >= 0. * * N (input) INTEGER * The number of columns of the matrix A. N >= 0. * * NRHS (input) INTEGER * The number of right hand sides, i.e., the number of * columns of matrices B and X. NRHS >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the M-by-N matrix A. * On exit, A has been overwritten by details of its * complete orthogonal factorization. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,M). * * B (input/output) DOUBLE PRECISION array, dimension (LDB,NRHS) * On entry, the M-by-NRHS right hand side matrix B. * On exit, the N-by-NRHS solution matrix X. * If m >= n and RANK = n, the residual sum-of-squares for * the solution in the i-th column is given by the sum of * squares of elements N+1:M in that column. * * LDB (input) INTEGER * The leading dimension of the array B. LDB >= max(1,M,N). * * JPVT (input/output) INTEGER array, dimension (N) * On entry, if JPVT(i) .ne. 0, the i-th column of A is an * initial column, otherwise it is a free column. Before * the QR factorization of A, all initial columns are * permuted to the leading positions; only the remaining * free columns are moved as a result of column pivoting * during the factorization. * On exit, if JPVT(i) = k, then the i-th column of A*P * was the k-th column of A. * * RCOND (input) DOUBLE PRECISION * RCOND is used to determine the effective rank of A, which * is defined as the order of the largest leading triangular * submatrix R11 in the QR factorization with pivoting of A, * whose estimated condition number < 1/RCOND. * * RANK (output) INTEGER * The effective rank of A, i.e., the order of the submatrix * R11. This is the same as the order of the submatrix T11 * in the complete orthogonal factorization of A. * * WORK (workspace) DOUBLE PRECISION array, dimension * (max( min(M,N)+3*N, 2*min(M,N)+NRHS )), * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * * ===================================================================== * * .. Parameters .. INTEGER IMAX, IMIN PARAMETER ( IMAX = 1, IMIN = 2 ) DOUBLE PRECISION ZERO, ONE, DONE, NTDONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0, DONE = ZERO, $ NTDONE = ONE ) * .. * .. Local Scalars .. INTEGER I, IASCL, IBSCL, ISMAX, ISMIN, J, K, MN DOUBLE PRECISION ANRM, BIGNUM, BNRM, C1, C2, S1, S2, SMAX, $ SMAXPR, SMIN, SMINPR, SMLNUM, T1, T2 * .. * .. External Functions .. DOUBLE PRECISION DLAMCH, DLANGE EXTERNAL DLAMCH, DLANGE * .. * .. External Subroutines .. EXTERNAL DGEQPF, DLAIC1, DLASCL, DLASET, DLATZM, DORM2R, $ DTRSM, DTZRQF, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, MIN * .. * .. Executable Statements .. * MN = MIN( M, N ) ISMIN = MN + 1 ISMAX = 2*MN + 1 * * Test the input arguments. * INFO = 0 IF( M.LT.0 ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 ELSE IF( NRHS.LT.0 ) THEN INFO = -3 ELSE IF( LDA.LT.MAX( 1, M ) ) THEN INFO = -5 ELSE IF( LDB.LT.MAX( 1, M, N ) ) THEN INFO = -7 END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGELSX', -INFO ) RETURN END IF * * Quick return if possible * IF( MIN( M, N, NRHS ).EQ.0 ) THEN RANK = 0 RETURN END IF * * Get machine parameters * SMLNUM = DLAMCH( 'S' ) / DLAMCH( 'P' ) BIGNUM = ONE / SMLNUM CALL DLABAD( SMLNUM, BIGNUM ) * * Scale A, B if max elements outside range [SMLNUM,BIGNUM] * ANRM = DLANGE( 'M', M, N, A, LDA, WORK ) IASCL = 0 IF( ANRM.GT.ZERO .AND. ANRM.LT.SMLNUM ) THEN * * Scale matrix norm up to SMLNUM * CALL DLASCL( 'G', 0, 0, ANRM, SMLNUM, M, N, A, LDA, INFO ) IASCL = 1 ELSE IF( ANRM.GT.BIGNUM ) THEN * * Scale matrix norm down to BIGNUM * CALL DLASCL( 'G', 0, 0, ANRM, BIGNUM, M, N, A, LDA, INFO ) IASCL = 2 ELSE IF( ANRM.EQ.ZERO ) THEN * * Matrix all zero. Return zero solution. * CALL DLASET( 'F', MAX( M, N ), NRHS, ZERO, ZERO, B, LDB ) RANK = 0 GO TO 100 END IF * BNRM = DLANGE( 'M', M, NRHS, B, LDB, WORK ) IBSCL = 0 IF( BNRM.GT.ZERO .AND. BNRM.LT.SMLNUM ) THEN * * Scale matrix norm up to SMLNUM * CALL DLASCL( 'G', 0, 0, BNRM, SMLNUM, M, NRHS, B, LDB, INFO ) IBSCL = 1 ELSE IF( BNRM.GT.BIGNUM ) THEN * * Scale matrix norm down to BIGNUM * CALL DLASCL( 'G', 0, 0, BNRM, BIGNUM, M, NRHS, B, LDB, INFO ) IBSCL = 2 END IF * * Compute QR factorization with column pivoting of A: * A * P = Q * R * CALL DGEQPF( M, N, A, LDA, JPVT, WORK( 1 ), WORK( MN+1 ), INFO ) * * workspace 3*N. Details of Householder rotations stored * in WORK(1:MN). * * Determine RANK using incremental condition estimation * WORK( ISMIN ) = ONE WORK( ISMAX ) = ONE SMAX = ABS( A( 1, 1 ) ) SMIN = SMAX IF( ABS( A( 1, 1 ) ).EQ.ZERO ) THEN RANK = 0 CALL DLASET( 'F', MAX( M, N ), NRHS, ZERO, ZERO, B, LDB ) GO TO 100 ELSE RANK = 1 END IF * 10 CONTINUE IF( RANK.LT.MN ) THEN I = RANK + 1 CALL DLAIC1( IMIN, RANK, WORK( ISMIN ), SMIN, A( 1, I ), $ A( I, I ), SMINPR, S1, C1 ) CALL DLAIC1( IMAX, RANK, WORK( ISMAX ), SMAX, A( 1, I ), $ A( I, I ), SMAXPR, S2, C2 ) * IF( SMAXPR*RCOND.LE.SMINPR ) THEN DO 20 I = 1, RANK WORK( ISMIN+I-1 ) = S1*WORK( ISMIN+I-1 ) WORK( ISMAX+I-1 ) = S2*WORK( ISMAX+I-1 ) 20 CONTINUE WORK( ISMIN+RANK ) = C1 WORK( ISMAX+RANK ) = C2 SMIN = SMINPR SMAX = SMAXPR RANK = RANK + 1 GO TO 10 END IF END IF * * Logically partition R = [ R11 R12 ] * [ 0 R22 ] * where R11 = R(1:RANK,1:RANK) * * [R11,R12] = [ T11, 0 ] * Y * IF( RANK.LT.N ) $ CALL DTZRQF( RANK, N, A, LDA, WORK( MN+1 ), INFO ) * * Details of Householder rotations stored in WORK(MN+1:2*MN) * * B(1:M,1:NRHS) := Q' * B(1:M,1:NRHS) * CALL DORM2R( 'Left', 'Transpose', M, NRHS, MN, A, LDA, WORK( 1 ), $ B, LDB, WORK( 2*MN+1 ), INFO ) * * workspace NRHS * * B(1:RANK,1:NRHS) := inv(T11) * B(1:RANK,1:NRHS) * CALL DTRSM( 'Left', 'Upper', 'No transpose', 'Non-unit', RANK, $ NRHS, ONE, A, LDA, B, LDB ) * DO 40 I = RANK + 1, N DO 30 J = 1, NRHS B( I, J ) = ZERO 30 CONTINUE 40 CONTINUE * * B(1:N,1:NRHS) := Y' * B(1:N,1:NRHS) * IF( RANK.LT.N ) THEN DO 50 I = 1, RANK CALL DLATZM( 'Left', N-RANK+1, NRHS, A( I, RANK+1 ), LDA, $ WORK( MN+I ), B( I, 1 ), B( RANK+1, 1 ), LDB, $ WORK( 2*MN+1 ) ) 50 CONTINUE END IF * * workspace NRHS * * B(1:N,1:NRHS) := P * B(1:N,1:NRHS) * DO 90 J = 1, NRHS DO 60 I = 1, N WORK( 2*MN+I ) = NTDONE 60 CONTINUE DO 80 I = 1, N IF( WORK( 2*MN+I ).EQ.NTDONE ) THEN IF( JPVT( I ).NE.I ) THEN K = I T1 = B( K, J ) T2 = B( JPVT( K ), J ) 70 CONTINUE B( JPVT( K ), J ) = T1 WORK( 2*MN+K ) = DONE T1 = T2 K = JPVT( K ) T2 = B( JPVT( K ), J ) IF( JPVT( K ).NE.I ) $ GO TO 70 B( I, J ) = T1 WORK( 2*MN+K ) = DONE END IF END IF 80 CONTINUE 90 CONTINUE * * Undo scaling * IF( IASCL.EQ.1 ) THEN CALL DLASCL( 'G', 0, 0, ANRM, SMLNUM, N, NRHS, B, LDB, INFO ) CALL DLASCL( 'U', 0, 0, SMLNUM, ANRM, RANK, RANK, A, LDA, $ INFO ) ELSE IF( IASCL.EQ.2 ) THEN CALL DLASCL( 'G', 0, 0, ANRM, BIGNUM, N, NRHS, B, LDB, INFO ) CALL DLASCL( 'U', 0, 0, BIGNUM, ANRM, RANK, RANK, A, LDA, $ INFO ) END IF IF( IBSCL.EQ.1 ) THEN CALL DLASCL( 'G', 0, 0, SMLNUM, BNRM, N, NRHS, B, LDB, INFO ) ELSE IF( IBSCL.EQ.2 ) THEN CALL DLASCL( 'G', 0, 0, BIGNUM, BNRM, N, NRHS, B, LDB, INFO ) END IF * 100 CONTINUE * RETURN * * End of DGELSX * END SUBROUTINE DGELSY( M, N, NRHS, A, LDA, B, LDB, JPVT, RCOND, RANK, $ WORK, LWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER INFO, LDA, LDB, LWORK, M, N, NRHS, RANK DOUBLE PRECISION RCOND * .. * .. Array Arguments .. INTEGER JPVT( * ) DOUBLE PRECISION A( LDA, * ), B( LDB, * ), WORK( * ) * .. * * Purpose * ======= * * DGELSY computes the minimum-norm solution to a real linear least * squares problem: * minimize || A * X - B || * using a complete orthogonal factorization of A. A is an M-by-N * matrix which may be rank-deficient. * * Several right hand side vectors b and solution vectors x can be * handled in a single call; they are stored as the columns of the * M-by-NRHS right hand side matrix B and the N-by-NRHS solution * matrix X. * * The routine first computes a QR factorization with column pivoting: * A * P = Q * [ R11 R12 ] * [ 0 R22 ] * with R11 defined as the largest leading submatrix whose estimated * condition number is less than 1/RCOND. The order of R11, RANK, * is the effective rank of A. * * Then, R22 is considered to be negligible, and R12 is annihilated * by orthogonal transformations from the right, arriving at the * complete orthogonal factorization: * A * P = Q * [ T11 0 ] * Z * [ 0 0 ] * The minimum-norm solution is then * X = P * Z' [ inv(T11)*Q1'*B ] * [ 0 ] * where Q1 consists of the first RANK columns of Q. * * This routine is basically identical to the original xGELSX except * three differences: * o The call to the subroutine xGEQPF has been substituted by the * the call to the subroutine xGEQP3. This subroutine is a Blas-3 * version of the QR factorization with column pivoting. * o Matrix B (the right hand side) is updated with Blas-3. * o The permutation of matrix B (the right hand side) is faster and * more simple. * * Arguments * ========= * * M (input) INTEGER * The number of rows of the matrix A. M >= 0. * * N (input) INTEGER * The number of columns of the matrix A. N >= 0. * * NRHS (input) INTEGER * The number of right hand sides, i.e., the number of * columns of matrices B and X. NRHS >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the M-by-N matrix A. * On exit, A has been overwritten by details of its * complete orthogonal factorization. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,M). * * B (input/output) DOUBLE PRECISION array, dimension (LDB,NRHS) * On entry, the M-by-NRHS right hand side matrix B. * On exit, the N-by-NRHS solution matrix X. * * LDB (input) INTEGER * The leading dimension of the array B. LDB >= max(1,M,N). * * JPVT (input/output) INTEGER array, dimension (N) * On entry, if JPVT(i) .ne. 0, the i-th column of A is permuted * to the front of AP, otherwise column i is a free column. * On exit, if JPVT(i) = k, then the i-th column of AP * was the k-th column of A. * * RCOND (input) DOUBLE PRECISION * RCOND is used to determine the effective rank of A, which * is defined as the order of the largest leading triangular * submatrix R11 in the QR factorization with pivoting of A, * whose estimated condition number < 1/RCOND. * * RANK (output) INTEGER * The effective rank of A, i.e., the order of the submatrix * R11. This is the same as the order of the submatrix T11 * in the complete orthogonal factorization of A. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. * The unblocked strategy requires that: * LWORK >= MAX( MN+3*N+1, 2*MN+NRHS ), * where MN = min( M, N ). * The block algorithm requires that: * LWORK >= MAX( MN+2*N+NB*(N+1), 2*MN+NB*NRHS ), * where NB is an upper bound on the blocksize returned * by ILAENV for the routines DGEQP3, DTZRZF, STZRQF, DORMQR, * and DORMRZ. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: If INFO = -i, the i-th argument had an illegal value. * * Further Details * =============== * * Based on contributions by * A. Petitet, Computer Science Dept., Univ. of Tenn., Knoxville, USA * E. Quintana-Orti, Depto. de Informatica, Universidad Jaime I, Spain * G. Quintana-Orti, Depto. de Informatica, Universidad Jaime I, Spain * * ===================================================================== * * .. Parameters .. INTEGER IMAX, IMIN PARAMETER ( IMAX = 1, IMIN = 2 ) DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL LQUERY INTEGER I, IASCL, IBSCL, ISMAX, ISMIN, J, LWKOPT, MN, $ NB, NB1, NB2, NB3, NB4 DOUBLE PRECISION ANRM, BIGNUM, BNRM, C1, C2, S1, S2, SMAX, $ SMAXPR, SMIN, SMINPR, SMLNUM, WSIZE * .. * .. External Functions .. INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANGE EXTERNAL ILAENV, DLAMCH, DLANGE * .. * .. External Subroutines .. EXTERNAL DCOPY, DGEQP3, DLABAD, DLAIC1, DLASCL, DLASET, $ DORMQR, DORMRZ, DTRSM, DTZRZF, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC ABS, DBLE, MAX, MIN * .. * .. Executable Statements .. * MN = MIN( M, N ) ISMIN = MN + 1 ISMAX = 2*MN + 1 * * Test the input arguments. * INFO = 0 NB1 = ILAENV( 1, 'DGEQRF', ' ', M, N, -1, -1 ) NB2 = ILAENV( 1, 'DGERQF', ' ', M, N, -1, -1 ) NB3 = ILAENV( 1, 'DORMQR', ' ', M, N, NRHS, -1 ) NB4 = ILAENV( 1, 'DORMRQ', ' ', M, N, NRHS, -1 ) NB = MAX( NB1, NB2, NB3, NB4 ) LWKOPT = MAX( 1, MN+2*N+NB*( N+1 ), 2*MN+NB*NRHS ) WORK( 1 ) = DBLE( LWKOPT ) LQUERY = ( LWORK.EQ.-1 ) IF( M.LT.0 ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 ELSE IF( NRHS.LT.0 ) THEN INFO = -3 ELSE IF( LDA.LT.MAX( 1, M ) ) THEN INFO = -5 ELSE IF( LDB.LT.MAX( 1, M, N ) ) THEN INFO = -7 ELSE IF( LWORK.LT.MAX( 1, MN+3*N+1, 2*MN+NRHS ) .AND. .NOT. $ LQUERY ) THEN INFO = -12 END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGELSY', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( MIN( M, N, NRHS ).EQ.0 ) THEN RANK = 0 RETURN END IF * * Get machine parameters * SMLNUM = DLAMCH( 'S' ) / DLAMCH( 'P' ) BIGNUM = ONE / SMLNUM CALL DLABAD( SMLNUM, BIGNUM ) * * Scale A, B if max entries outside range [SMLNUM,BIGNUM] * ANRM = DLANGE( 'M', M, N, A, LDA, WORK ) IASCL = 0 IF( ANRM.GT.ZERO .AND. ANRM.LT.SMLNUM ) THEN * * Scale matrix norm up to SMLNUM * CALL DLASCL( 'G', 0, 0, ANRM, SMLNUM, M, N, A, LDA, INFO ) IASCL = 1 ELSE IF( ANRM.GT.BIGNUM ) THEN * * Scale matrix norm down to BIGNUM * CALL DLASCL( 'G', 0, 0, ANRM, BIGNUM, M, N, A, LDA, INFO ) IASCL = 2 ELSE IF( ANRM.EQ.ZERO ) THEN * * Matrix all zero. Return zero solution. * CALL DLASET( 'F', MAX( M, N ), NRHS, ZERO, ZERO, B, LDB ) RANK = 0 GO TO 70 END IF * BNRM = DLANGE( 'M', M, NRHS, B, LDB, WORK ) IBSCL = 0 IF( BNRM.GT.ZERO .AND. BNRM.LT.SMLNUM ) THEN * * Scale matrix norm up to SMLNUM * CALL DLASCL( 'G', 0, 0, BNRM, SMLNUM, M, NRHS, B, LDB, INFO ) IBSCL = 1 ELSE IF( BNRM.GT.BIGNUM ) THEN * * Scale matrix norm down to BIGNUM * CALL DLASCL( 'G', 0, 0, BNRM, BIGNUM, M, NRHS, B, LDB, INFO ) IBSCL = 2 END IF * * Compute QR factorization with column pivoting of A: * A * P = Q * R * CALL DGEQP3( M, N, A, LDA, JPVT, WORK( 1 ), WORK( MN+1 ), $ LWORK-MN, INFO ) WSIZE = MN + WORK( MN+1 ) * * workspace: MN+2*N+NB*(N+1). * Details of Householder rotations stored in WORK(1:MN). * * Determine RANK using incremental condition estimation * WORK( ISMIN ) = ONE WORK( ISMAX ) = ONE SMAX = ABS( A( 1, 1 ) ) SMIN = SMAX IF( ABS( A( 1, 1 ) ).EQ.ZERO ) THEN RANK = 0 CALL DLASET( 'F', MAX( M, N ), NRHS, ZERO, ZERO, B, LDB ) GO TO 70 ELSE RANK = 1 END IF * 10 CONTINUE IF( RANK.LT.MN ) THEN I = RANK + 1 CALL DLAIC1( IMIN, RANK, WORK( ISMIN ), SMIN, A( 1, I ), $ A( I, I ), SMINPR, S1, C1 ) CALL DLAIC1( IMAX, RANK, WORK( ISMAX ), SMAX, A( 1, I ), $ A( I, I ), SMAXPR, S2, C2 ) * IF( SMAXPR*RCOND.LE.SMINPR ) THEN DO 20 I = 1, RANK WORK( ISMIN+I-1 ) = S1*WORK( ISMIN+I-1 ) WORK( ISMAX+I-1 ) = S2*WORK( ISMAX+I-1 ) 20 CONTINUE WORK( ISMIN+RANK ) = C1 WORK( ISMAX+RANK ) = C2 SMIN = SMINPR SMAX = SMAXPR RANK = RANK + 1 GO TO 10 END IF END IF * * workspace: 3*MN. * * Logically partition R = [ R11 R12 ] * [ 0 R22 ] * where R11 = R(1:RANK,1:RANK) * * [R11,R12] = [ T11, 0 ] * Y * IF( RANK.LT.N ) $ CALL DTZRZF( RANK, N, A, LDA, WORK( MN+1 ), WORK( 2*MN+1 ), $ LWORK-2*MN, INFO ) * * workspace: 2*MN. * Details of Householder rotations stored in WORK(MN+1:2*MN) * * B(1:M,1:NRHS) := Q' * B(1:M,1:NRHS) * CALL DORMQR( 'Left', 'Transpose', M, NRHS, MN, A, LDA, WORK( 1 ), $ B, LDB, WORK( 2*MN+1 ), LWORK-2*MN, INFO ) WSIZE = MAX( WSIZE, 2*MN+WORK( 2*MN+1 ) ) * * workspace: 2*MN+NB*NRHS. * * B(1:RANK,1:NRHS) := inv(T11) * B(1:RANK,1:NRHS) * CALL DTRSM( 'Left', 'Upper', 'No transpose', 'Non-unit', RANK, $ NRHS, ONE, A, LDA, B, LDB ) * DO 40 J = 1, NRHS DO 30 I = RANK + 1, N B( I, J ) = ZERO 30 CONTINUE 40 CONTINUE * * B(1:N,1:NRHS) := Y' * B(1:N,1:NRHS) * IF( RANK.LT.N ) THEN CALL DORMRZ( 'Left', 'Transpose', N, NRHS, RANK, N-RANK, A, $ LDA, WORK( MN+1 ), B, LDB, WORK( 2*MN+1 ), $ LWORK-2*MN, INFO ) END IF * * workspace: 2*MN+NRHS. * * B(1:N,1:NRHS) := P * B(1:N,1:NRHS) * DO 60 J = 1, NRHS DO 50 I = 1, N WORK( JPVT( I ) ) = B( I, J ) 50 CONTINUE CALL DCOPY( N, WORK( 1 ), 1, B( 1, J ), 1 ) 60 CONTINUE * * workspace: N. * * Undo scaling * IF( IASCL.EQ.1 ) THEN CALL DLASCL( 'G', 0, 0, ANRM, SMLNUM, N, NRHS, B, LDB, INFO ) CALL DLASCL( 'U', 0, 0, SMLNUM, ANRM, RANK, RANK, A, LDA, $ INFO ) ELSE IF( IASCL.EQ.2 ) THEN CALL DLASCL( 'G', 0, 0, ANRM, BIGNUM, N, NRHS, B, LDB, INFO ) CALL DLASCL( 'U', 0, 0, BIGNUM, ANRM, RANK, RANK, A, LDA, $ INFO ) END IF IF( IBSCL.EQ.1 ) THEN CALL DLASCL( 'G', 0, 0, SMLNUM, BNRM, N, NRHS, B, LDB, INFO ) ELSE IF( IBSCL.EQ.2 ) THEN CALL DLASCL( 'G', 0, 0, BIGNUM, BNRM, N, NRHS, B, LDB, INFO ) END IF * 70 CONTINUE WORK( 1 ) = DBLE( LWKOPT ) * RETURN * * End of DGELSY * END SUBROUTINE DGESDD( JOBZ, M, N, A, LDA, S, U, LDU, VT, LDVT, WORK, $ LWORK, IWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1999 * * .. Scalar Arguments .. CHARACTER JOBZ INTEGER INFO, LDA, LDU, LDVT, LWORK, M, N * .. * .. Array Arguments .. INTEGER IWORK( * ) DOUBLE PRECISION A( LDA, * ), S( * ), U( LDU, * ), $ VT( LDVT, * ), WORK( * ) * .. * * Purpose * ======= * * DGESDD computes the singular value decomposition (SVD) of a real * M-by-N matrix A, optionally computing the left and right singular * vectors. If singular vectors are desired, it uses a * divide-and-conquer algorithm. * * The SVD is written * * A = U * SIGMA * transpose(V) * * where SIGMA is an M-by-N matrix which is zero except for its * min(m,n) diagonal elements, U is an M-by-M orthogonal matrix, and * V is an N-by-N orthogonal matrix. The diagonal elements of SIGMA * are the singular values of A; they are real and non-negative, and * are returned in descending order. The first min(m,n) columns of * U and V are the left and right singular vectors of A. * * Note that the routine returns VT = V**T, not V. * * The divide and conquer algorithm makes very mild assumptions about * floating point arithmetic. It will work on machines with a guard * digit in add/subtract, or on those binary machines without guard * digits which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or * Cray-2. It could conceivably fail on hexadecimal or decimal machines * without guard digits, but we know of none. * * Arguments * ========= * * JOBZ (input) CHARACTER*1 * Specifies options for computing all or part of the matrix U: * = 'A': all M columns of U and all N rows of V**T are * returned in the arrays U and VT; * = 'S': the first min(M,N) columns of U and the first * min(M,N) rows of V**T are returned in the arrays U * and VT; * = 'O': If M >= N, the first N columns of U are overwritten * on the array A and all rows of V**T are returned in * the array VT; * otherwise, all columns of U are returned in the * array U and the first M rows of V**T are overwritten * in the array VT; * = 'N': no columns of U or rows of V**T are computed. * * M (input) INTEGER * The number of rows of the input matrix A. M >= 0. * * N (input) INTEGER * The number of columns of the input matrix A. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the M-by-N matrix A. * On exit, * if JOBZ = 'O', A is overwritten with the first N columns * of U (the left singular vectors, stored * columnwise) if M >= N; * A is overwritten with the first M rows * of V**T (the right singular vectors, stored * rowwise) otherwise. * if JOBZ .ne. 'O', the contents of A are destroyed. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,M). * * S (output) DOUBLE PRECISION array, dimension (min(M,N)) * The singular values of A, sorted so that S(i) >= S(i+1). * * U (output) DOUBLE PRECISION array, dimension (LDU,UCOL) * UCOL = M if JOBZ = 'A' or JOBZ = 'O' and M < N; * UCOL = min(M,N) if JOBZ = 'S'. * If JOBZ = 'A' or JOBZ = 'O' and M < N, U contains the M-by-M * orthogonal matrix U; * if JOBZ = 'S', U contains the first min(M,N) columns of U * (the left singular vectors, stored columnwise); * if JOBZ = 'O' and M >= N, or JOBZ = 'N', U is not referenced. * * LDU (input) INTEGER * The leading dimension of the array U. LDU >= 1; if * JOBZ = 'S' or 'A' or JOBZ = 'O' and M < N, LDU >= M. * * VT (output) DOUBLE PRECISION array, dimension (LDVT,N) * If JOBZ = 'A' or JOBZ = 'O' and M >= N, VT contains the * N-by-N orthogonal matrix V**T; * if JOBZ = 'S', VT contains the first min(M,N) rows of * V**T (the right singular vectors, stored rowwise); * if JOBZ = 'O' and M < N, or JOBZ = 'N', VT is not referenced. * * LDVT (input) INTEGER * The leading dimension of the array VT. LDVT >= 1; if * JOBZ = 'A' or JOBZ = 'O' and M >= N, LDVT >= N; * if JOBZ = 'S', LDVT >= min(M,N). * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK; * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= 1. * If JOBZ = 'N', * LWORK >= 3*min(M,N) + max(max(M,N),6*min(M,N)). * If JOBZ = 'O', * LWORK >= 3*min(M,N)*min(M,N) + * max(max(M,N),5*min(M,N)*min(M,N)+4*min(M,N)). * If JOBZ = 'S' or 'A' * LWORK >= 3*min(M,N)*min(M,N) + * max(max(M,N),4*min(M,N)*min(M,N)+4*min(M,N)). * For good performance, LWORK should generally be larger. * If LWORK < 0 but other input arguments are legal, WORK(1) * returns the optimal LWORK. * * IWORK (workspace) INTEGER array, dimension (8*min(M,N)) * * INFO (output) INTEGER * = 0: successful exit. * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: DBDSDC did not converge, updating process failed. * * Further Details * =============== * * Based on contributions by * Ming Gu and Huan Ren, Computer Science Division, University of * California at Berkeley, USA * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. LOGICAL LQUERY, WNTQA, WNTQAS, WNTQN, WNTQO, WNTQS INTEGER BDSPAC, BLK, CHUNK, I, IE, IERR, IL, $ IR, ISCL, ITAU, ITAUP, ITAUQ, IU, IVT, LDWKVT, $ LDWRKL, LDWRKR, LDWRKU, MAXWRK, MINMN, MINWRK, $ MNTHR, NWORK, WRKBL DOUBLE PRECISION ANRM, BIGNUM, EPS, SMLNUM * .. * .. Local Arrays .. INTEGER IDUM( 1 ) DOUBLE PRECISION DUM( 1 ) * .. * .. External Subroutines .. EXTERNAL DBDSDC, DGEBRD, DGELQF, DGEMM, DGEQRF, DLACPY, $ DLASCL, DLASET, DORGBR, DORGLQ, DORGQR, DORMBR, $ XERBLA * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANGE EXTERNAL DLAMCH, DLANGE, ILAENV, LSAME * .. * .. Intrinsic Functions .. INTRINSIC DBLE, INT, MAX, MIN, SQRT * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 MINMN = MIN( M, N ) MNTHR = INT( MINMN*11.0D0 / 6.0D0 ) WNTQA = LSAME( JOBZ, 'A' ) WNTQS = LSAME( JOBZ, 'S' ) WNTQAS = WNTQA .OR. WNTQS WNTQO = LSAME( JOBZ, 'O' ) WNTQN = LSAME( JOBZ, 'N' ) MINWRK = 1 MAXWRK = 1 LQUERY = ( LWORK.EQ.-1 ) * IF( .NOT.( WNTQA .OR. WNTQS .OR. WNTQO .OR. WNTQN ) ) THEN INFO = -1 ELSE IF( M.LT.0 ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( LDA.LT.MAX( 1, M ) ) THEN INFO = -5 ELSE IF( LDU.LT.1 .OR. ( WNTQAS .AND. LDU.LT.M ) .OR. $ ( WNTQO .AND. M.LT.N .AND. LDU.LT.M ) ) THEN INFO = -8 ELSE IF( LDVT.LT.1 .OR. ( WNTQA .AND. LDVT.LT.N ) .OR. $ ( WNTQS .AND. LDVT.LT.MINMN ) .OR. $ ( WNTQO .AND. M.GE.N .AND. LDVT.LT.N ) ) THEN INFO = -10 END IF * * Compute workspace * (Note: Comments in the code beginning "Workspace:" describe the * minimal amount of workspace needed at that point in the code, * as well as the preferred amount for good performance. * NB refers to the optimal block size for the immediately * following subroutine, as returned by ILAENV.) * IF( INFO.EQ.0 .AND. M.GT.0 .AND. N.GT.0 ) THEN IF( M.GE.N ) THEN * * Compute space needed for DBDSDC * IF( WNTQN ) THEN BDSPAC = 7*N ELSE BDSPAC = 3*N*N + 4*N END IF IF( M.GE.MNTHR ) THEN IF( WNTQN ) THEN * * Path 1 (M much larger than N, JOBZ='N') * WRKBL = N + N*ILAENV( 1, 'DGEQRF', ' ', M, N, -1, $ -1 ) WRKBL = MAX( WRKBL, 3*N+2*N* $ ILAENV( 1, 'DGEBRD', ' ', N, N, -1, -1 ) ) MAXWRK = MAX( WRKBL, BDSPAC+N ) MINWRK = BDSPAC + N ELSE IF( WNTQO ) THEN * * Path 2 (M much larger than N, JOBZ='O') * WRKBL = N + N*ILAENV( 1, 'DGEQRF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, N+N*ILAENV( 1, 'DORGQR', ' ', M, $ N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+2*N* $ ILAENV( 1, 'DGEBRD', ' ', N, N, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORMBR', 'QLN', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORMBR', 'PRT', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC+3*N ) MAXWRK = WRKBL + 2*N*N MINWRK = BDSPAC + 2*N*N + 3*N ELSE IF( WNTQS ) THEN * * Path 3 (M much larger than N, JOBZ='S') * WRKBL = N + N*ILAENV( 1, 'DGEQRF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, N+N*ILAENV( 1, 'DORGQR', ' ', M, $ N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+2*N* $ ILAENV( 1, 'DGEBRD', ' ', N, N, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORMBR', 'QLN', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORMBR', 'PRT', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC+3*N ) MAXWRK = WRKBL + N*N MINWRK = BDSPAC + N*N + 3*N ELSE IF( WNTQA ) THEN * * Path 4 (M much larger than N, JOBZ='A') * WRKBL = N + N*ILAENV( 1, 'DGEQRF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, N+M*ILAENV( 1, 'DORGQR', ' ', M, $ M, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+2*N* $ ILAENV( 1, 'DGEBRD', ' ', N, N, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORMBR', 'QLN', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORMBR', 'PRT', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC+3*N ) MAXWRK = WRKBL + N*N MINWRK = BDSPAC + N*N + 3*N END IF ELSE * * Path 5 (M at least N, but not much larger) * WRKBL = 3*N + ( M+N )*ILAENV( 1, 'DGEBRD', ' ', M, N, -1, $ -1 ) IF( WNTQN ) THEN MAXWRK = MAX( WRKBL, BDSPAC+3*N ) MINWRK = 3*N + MAX( M, BDSPAC ) ELSE IF( WNTQO ) THEN WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORMBR', 'QLN', M, N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORMBR', 'PRT', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC+3*N ) MAXWRK = WRKBL + M*N MINWRK = 3*N + MAX( M, N*N+BDSPAC ) ELSE IF( WNTQS ) THEN WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORMBR', 'QLN', M, N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORMBR', 'PRT', N, N, N, -1 ) ) MAXWRK = MAX( WRKBL, BDSPAC+3*N ) MINWRK = 3*N + MAX( M, BDSPAC ) ELSE IF( WNTQA ) THEN WRKBL = MAX( WRKBL, 3*N+M* $ ILAENV( 1, 'DORMBR', 'QLN', M, M, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORMBR', 'PRT', N, N, N, -1 ) ) MAXWRK = MAX( MAXWRK, BDSPAC+3*N ) MINWRK = 3*N + MAX( M, BDSPAC ) END IF END IF ELSE * * Compute space needed for DBDSDC * IF( WNTQN ) THEN BDSPAC = 7*M ELSE BDSPAC = 3*M*M + 4*M END IF IF( N.GE.MNTHR ) THEN IF( WNTQN ) THEN * * Path 1t (N much larger than M, JOBZ='N') * WRKBL = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, $ -1 ) WRKBL = MAX( WRKBL, 3*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) MAXWRK = MAX( WRKBL, BDSPAC+M ) MINWRK = BDSPAC + M ELSE IF( WNTQO ) THEN * * Path 2t (N much larger than M, JOBZ='O') * WRKBL = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, M+M*ILAENV( 1, 'DORGLQ', ' ', M, $ N, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORMBR', 'QLN', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORMBR', 'PRT', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC+3*M ) MAXWRK = WRKBL + 2*M*M MINWRK = BDSPAC + 2*M*M + 3*M ELSE IF( WNTQS ) THEN * * Path 3t (N much larger than M, JOBZ='S') * WRKBL = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, M+M*ILAENV( 1, 'DORGLQ', ' ', M, $ N, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORMBR', 'QLN', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORMBR', 'PRT', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC+3*M ) MAXWRK = WRKBL + M*M MINWRK = BDSPAC + M*M + 3*M ELSE IF( WNTQA ) THEN * * Path 4t (N much larger than M, JOBZ='A') * WRKBL = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, M+N*ILAENV( 1, 'DORGLQ', ' ', N, $ N, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORMBR', 'QLN', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORMBR', 'PRT', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC+3*M ) MAXWRK = WRKBL + M*M MINWRK = BDSPAC + M*M + 3*M END IF ELSE * * Path 5t (N greater than M, but not much larger) * WRKBL = 3*M + ( M+N )*ILAENV( 1, 'DGEBRD', ' ', M, N, -1, $ -1 ) IF( WNTQN ) THEN MAXWRK = MAX( WRKBL, BDSPAC+3*M ) MINWRK = 3*M + MAX( N, BDSPAC ) ELSE IF( WNTQO ) THEN WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORMBR', 'QLN', M, M, N, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORMBR', 'PRT', M, N, M, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC+3*M ) MAXWRK = WRKBL + M*N MINWRK = 3*M + MAX( N, M*M+BDSPAC ) ELSE IF( WNTQS ) THEN WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORMBR', 'QLN', M, M, N, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORMBR', 'PRT', M, N, M, -1 ) ) MAXWRK = MAX( WRKBL, BDSPAC+3*M ) MINWRK = 3*M + MAX( N, BDSPAC ) ELSE IF( WNTQA ) THEN WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORMBR', 'QLN', M, M, N, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORMBR', 'PRT', N, N, M, -1 ) ) MAXWRK = MAX( WRKBL, BDSPAC+3*M ) MINWRK = 3*M + MAX( N, BDSPAC ) END IF END IF END IF WORK( 1 ) = MAXWRK END IF * IF( LWORK.LT.MINWRK .AND. .NOT.LQUERY ) THEN INFO = -12 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGESDD', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( M.EQ.0 .OR. N.EQ.0 ) THEN IF( LWORK.GE.1 ) $ WORK( 1 ) = ONE RETURN END IF * * Get machine constants * EPS = DLAMCH( 'P' ) SMLNUM = SQRT( DLAMCH( 'S' ) ) / EPS BIGNUM = ONE / SMLNUM * * Scale A if max element outside range [SMLNUM,BIGNUM] * ANRM = DLANGE( 'M', M, N, A, LDA, DUM ) ISCL = 0 IF( ANRM.GT.ZERO .AND. ANRM.LT.SMLNUM ) THEN ISCL = 1 CALL DLASCL( 'G', 0, 0, ANRM, SMLNUM, M, N, A, LDA, IERR ) ELSE IF( ANRM.GT.BIGNUM ) THEN ISCL = 1 CALL DLASCL( 'G', 0, 0, ANRM, BIGNUM, M, N, A, LDA, IERR ) END IF * IF( M.GE.N ) THEN * * A has at least as many rows as columns. If A has sufficiently * more rows than columns, first reduce using the QR * decomposition (if sufficient workspace available) * IF( M.GE.MNTHR ) THEN * IF( WNTQN ) THEN * * Path 1 (M much larger than N, JOBZ='N') * No singular vectors to be computed * ITAU = 1 NWORK = ITAU + N * * Compute A=Q*R * (Workspace: need 2*N, prefer N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * Zero out below R * CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, A( 2, 1 ), LDA ) IE = 1 ITAUQ = IE + N ITAUP = ITAUQ + N NWORK = ITAUP + N * * Bidiagonalize R in A * (Workspace: need 4*N, prefer 3*N+2*N*NB) * CALL DGEBRD( N, N, A, LDA, S, WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( NWORK ), LWORK-NWORK+1, $ IERR ) NWORK = IE + N * * Perform bidiagonal SVD, computing singular values only * (Workspace: need N+BDSPAC) * CALL DBDSDC( 'U', 'N', N, S, WORK( IE ), DUM, 1, DUM, 1, $ DUM, IDUM, WORK( NWORK ), IWORK, INFO ) * ELSE IF( WNTQO ) THEN * * Path 2 (M much larger than N, JOBZ = 'O') * N left singular vectors to be overwritten on A and * N right singular vectors to be computed in VT * IR = 1 * * WORK(IR) is LDWRKR by N * IF( LWORK.GE.LDA*N+N*N+3*N+BDSPAC ) THEN LDWRKR = LDA ELSE LDWRKR = ( LWORK-N*N-3*N-BDSPAC ) / N END IF ITAU = IR + LDWRKR*N NWORK = ITAU + N * * Compute A=Q*R * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * Copy R to WORK(IR), zeroing out below it * CALL DLACPY( 'U', N, N, A, LDA, WORK( IR ), LDWRKR ) CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, WORK( IR+1 ), $ LDWRKR ) * * Generate Q in A * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DORGQR( M, N, N, A, LDA, WORK( ITAU ), $ WORK( NWORK ), LWORK-NWORK+1, IERR ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N NWORK = ITAUP + N * * Bidiagonalize R in VT, copying result to WORK(IR) * (Workspace: need N*N+4*N, prefer N*N+3*N+2*N*NB) * CALL DGEBRD( N, N, WORK( IR ), LDWRKR, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * WORK(IU) is N by N * IU = NWORK NWORK = IU + N*N * * Perform bidiagonal SVD, computing left singular vectors * of bidiagonal matrix in WORK(IU) and computing right * singular vectors of bidiagonal matrix in VT * (Workspace: need N+N*N+BDSPAC) * CALL DBDSDC( 'U', 'I', N, S, WORK( IE ), WORK( IU ), N, $ VT, LDVT, DUM, IDUM, WORK( NWORK ), IWORK, $ INFO ) * * Overwrite WORK(IU) by left singular vectors of R * and VT by right singular vectors of R * (Workspace: need 2*N*N+3*N, prefer 2*N*N+2*N+N*NB) * CALL DORMBR( 'Q', 'L', 'N', N, N, N, WORK( IR ), LDWRKR, $ WORK( ITAUQ ), WORK( IU ), N, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) CALL DORMBR( 'P', 'R', 'T', N, N, N, WORK( IR ), LDWRKR, $ WORK( ITAUP ), VT, LDVT, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * Multiply Q in A by left singular vectors of R in * WORK(IU), storing result in WORK(IR) and copying to A * (Workspace: need 2*N*N, prefer N*N+M*N) * DO 10 I = 1, M, LDWRKR CHUNK = MIN( M-I+1, LDWRKR ) CALL DGEMM( 'N', 'N', CHUNK, N, N, ONE, A( I, 1 ), $ LDA, WORK( IU ), N, ZERO, WORK( IR ), $ LDWRKR ) CALL DLACPY( 'F', CHUNK, N, WORK( IR ), LDWRKR, $ A( I, 1 ), LDA ) 10 CONTINUE * ELSE IF( WNTQS ) THEN * * Path 3 (M much larger than N, JOBZ='S') * N left singular vectors to be computed in U and * N right singular vectors to be computed in VT * IR = 1 * * WORK(IR) is N by N * LDWRKR = N ITAU = IR + LDWRKR*N NWORK = ITAU + N * * Compute A=Q*R * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * Copy R to WORK(IR), zeroing out below it * CALL DLACPY( 'U', N, N, A, LDA, WORK( IR ), LDWRKR ) CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, WORK( IR+1 ), $ LDWRKR ) * * Generate Q in A * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DORGQR( M, N, N, A, LDA, WORK( ITAU ), $ WORK( NWORK ), LWORK-NWORK+1, IERR ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N NWORK = ITAUP + N * * Bidiagonalize R in WORK(IR) * (Workspace: need N*N+4*N, prefer N*N+3*N+2*N*NB) * CALL DGEBRD( N, N, WORK( IR ), LDWRKR, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * Perform bidiagonal SVD, computing left singular vectors * of bidiagoal matrix in U and computing right singular * vectors of bidiagonal matrix in VT * (Workspace: need N+BDSPAC) * CALL DBDSDC( 'U', 'I', N, S, WORK( IE ), U, LDU, VT, $ LDVT, DUM, IDUM, WORK( NWORK ), IWORK, $ INFO ) * * Overwrite U by left singular vectors of R and VT * by right singular vectors of R * (Workspace: need N*N+3*N, prefer N*N+2*N+N*NB) * CALL DORMBR( 'Q', 'L', 'N', N, N, N, WORK( IR ), LDWRKR, $ WORK( ITAUQ ), U, LDU, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * CALL DORMBR( 'P', 'R', 'T', N, N, N, WORK( IR ), LDWRKR, $ WORK( ITAUP ), VT, LDVT, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * Multiply Q in A by left singular vectors of R in * WORK(IR), storing result in U * (Workspace: need N*N) * CALL DLACPY( 'F', N, N, U, LDU, WORK( IR ), LDWRKR ) CALL DGEMM( 'N', 'N', M, N, N, ONE, A, LDA, WORK( IR ), $ LDWRKR, ZERO, U, LDU ) * ELSE IF( WNTQA ) THEN * * Path 4 (M much larger than N, JOBZ='A') * M left singular vectors to be computed in U and * N right singular vectors to be computed in VT * IU = 1 * * WORK(IU) is N by N * LDWRKU = N ITAU = IU + LDWRKU*N NWORK = ITAU + N * * Compute A=Q*R, copying result to U * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), WORK( NWORK ), $ LWORK-NWORK+1, IERR ) CALL DLACPY( 'L', M, N, A, LDA, U, LDU ) * * Generate Q in U * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) CALL DORGQR( M, M, N, U, LDU, WORK( ITAU ), $ WORK( NWORK ), LWORK-NWORK+1, IERR ) * * Produce R in A, zeroing out other entries * CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, A( 2, 1 ), LDA ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N NWORK = ITAUP + N * * Bidiagonalize R in A * (Workspace: need N*N+4*N, prefer N*N+3*N+2*N*NB) * CALL DGEBRD( N, N, A, LDA, S, WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( NWORK ), LWORK-NWORK+1, $ IERR ) * * Perform bidiagonal SVD, computing left singular vectors * of bidiagonal matrix in WORK(IU) and computing right * singular vectors of bidiagonal matrix in VT * (Workspace: need N+N*N+BDSPAC) * CALL DBDSDC( 'U', 'I', N, S, WORK( IE ), WORK( IU ), N, $ VT, LDVT, DUM, IDUM, WORK( NWORK ), IWORK, $ INFO ) * * Overwrite WORK(IU) by left singular vectors of R and VT * by right singular vectors of R * (Workspace: need N*N+3*N, prefer N*N+2*N+N*NB) * CALL DORMBR( 'Q', 'L', 'N', N, N, N, A, LDA, $ WORK( ITAUQ ), WORK( IU ), LDWRKU, $ WORK( NWORK ), LWORK-NWORK+1, IERR ) CALL DORMBR( 'P', 'R', 'T', N, N, N, A, LDA, $ WORK( ITAUP ), VT, LDVT, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * Multiply Q in U by left singular vectors of R in * WORK(IU), storing result in A * (Workspace: need N*N) * CALL DGEMM( 'N', 'N', M, N, N, ONE, U, LDU, WORK( IU ), $ LDWRKU, ZERO, A, LDA ) * * Copy left singular vectors of A from A to U * CALL DLACPY( 'F', M, N, A, LDA, U, LDU ) * END IF * ELSE * * M .LT. MNTHR * * Path 5 (M at least N, but not much larger) * Reduce to bidiagonal form without QR decomposition * IE = 1 ITAUQ = IE + N ITAUP = ITAUQ + N NWORK = ITAUP + N * * Bidiagonalize A * (Workspace: need 3*N+M, prefer 3*N+(M+N)*NB) * CALL DGEBRD( M, N, A, LDA, S, WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( NWORK ), LWORK-NWORK+1, $ IERR ) IF( WNTQN ) THEN * * Perform bidiagonal SVD, only computing singular values * (Workspace: need N+BDSPAC) * CALL DBDSDC( 'U', 'N', N, S, WORK( IE ), DUM, 1, DUM, 1, $ DUM, IDUM, WORK( NWORK ), IWORK, INFO ) ELSE IF( WNTQO ) THEN IU = NWORK IF( LWORK.GE.M*N+3*N+BDSPAC ) THEN * * WORK( IU ) is M by N * LDWRKU = M NWORK = IU + LDWRKU*N CALL DLASET( 'F', M, N, ZERO, ZERO, WORK( IU ), $ LDWRKU ) ELSE * * WORK( IU ) is N by N * LDWRKU = N NWORK = IU + LDWRKU*N * * WORK(IR) is LDWRKR by N * IR = NWORK LDWRKR = ( LWORK-N*N-3*N ) / N END IF NWORK = IU + LDWRKU*N * * Perform bidiagonal SVD, computing left singular vectors * of bidiagonal matrix in WORK(IU) and computing right * singular vectors of bidiagonal matrix in VT * (Workspace: need N+N*N+BDSPAC) * CALL DBDSDC( 'U', 'I', N, S, WORK( IE ), WORK( IU ), $ LDWRKU, VT, LDVT, DUM, IDUM, WORK( NWORK ), $ IWORK, INFO ) * * Overwrite VT by right singular vectors of A * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DORMBR( 'P', 'R', 'T', N, N, N, A, LDA, $ WORK( ITAUP ), VT, LDVT, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * IF( LWORK.GE.M*N+3*N+BDSPAC ) THEN * * Overwrite WORK(IU) by left singular vectors of A * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DORMBR( 'Q', 'L', 'N', M, N, N, A, LDA, $ WORK( ITAUQ ), WORK( IU ), LDWRKU, $ WORK( NWORK ), LWORK-NWORK+1, IERR ) * * Copy left singular vectors of A from WORK(IU) to A * CALL DLACPY( 'F', M, N, WORK( IU ), LDWRKU, A, LDA ) ELSE * * Generate Q in A * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DORGBR( 'Q', M, N, N, A, LDA, WORK( ITAUQ ), $ WORK( NWORK ), LWORK-NWORK+1, IERR ) * * Multiply Q in A by left singular vectors of * bidiagonal matrix in WORK(IU), storing result in * WORK(IR) and copying to A * (Workspace: need 2*N*N, prefer N*N+M*N) * DO 20 I = 1, M, LDWRKR CHUNK = MIN( M-I+1, LDWRKR ) CALL DGEMM( 'N', 'N', CHUNK, N, N, ONE, A( I, 1 ), $ LDA, WORK( IU ), LDWRKU, ZERO, $ WORK( IR ), LDWRKR ) CALL DLACPY( 'F', CHUNK, N, WORK( IR ), LDWRKR, $ A( I, 1 ), LDA ) 20 CONTINUE END IF * ELSE IF( WNTQS ) THEN * * Perform bidiagonal SVD, computing left singular vectors * of bidiagonal matrix in U and computing right singular * vectors of bidiagonal matrix in VT * (Workspace: need N+BDSPAC) * CALL DLASET( 'F', M, N, ZERO, ZERO, U, LDU ) CALL DBDSDC( 'U', 'I', N, S, WORK( IE ), U, LDU, VT, $ LDVT, DUM, IDUM, WORK( NWORK ), IWORK, $ INFO ) * * Overwrite U by left singular vectors of A and VT * by right singular vectors of A * (Workspace: need 3*N, prefer 2*N+N*NB) * CALL DORMBR( 'Q', 'L', 'N', M, N, N, A, LDA, $ WORK( ITAUQ ), U, LDU, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) CALL DORMBR( 'P', 'R', 'T', N, N, N, A, LDA, $ WORK( ITAUP ), VT, LDVT, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) ELSE IF( WNTQA ) THEN * * Perform bidiagonal SVD, computing left singular vectors * of bidiagonal matrix in U and computing right singular * vectors of bidiagonal matrix in VT * (Workspace: need N+BDSPAC) * CALL DLASET( 'F', M, M, ZERO, ZERO, U, LDU ) CALL DBDSDC( 'U', 'I', N, S, WORK( IE ), U, LDU, VT, $ LDVT, DUM, IDUM, WORK( NWORK ), IWORK, $ INFO ) * * Set the right corner of U to identity matrix * CALL DLASET( 'F', M-N, M-N, ZERO, ONE, U( N+1, N+1 ), $ LDU ) * * Overwrite U by left singular vectors of A and VT * by right singular vectors of A * (Workspace: need N*N+2*N+M, prefer N*N+2*N+M*NB) * CALL DORMBR( 'Q', 'L', 'N', M, M, N, A, LDA, $ WORK( ITAUQ ), U, LDU, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) CALL DORMBR( 'P', 'R', 'T', N, N, M, A, LDA, $ WORK( ITAUP ), VT, LDVT, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) END IF * END IF * ELSE * * A has more columns than rows. If A has sufficiently more * columns than rows, first reduce using the LQ decomposition (if * sufficient workspace available) * IF( N.GE.MNTHR ) THEN * IF( WNTQN ) THEN * * Path 1t (N much larger than M, JOBZ='N') * No singular vectors to be computed * ITAU = 1 NWORK = ITAU + M * * Compute A=L*Q * (Workspace: need 2*M, prefer M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * Zero out above L * CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, A( 1, 2 ), LDA ) IE = 1 ITAUQ = IE + M ITAUP = ITAUQ + M NWORK = ITAUP + M * * Bidiagonalize L in A * (Workspace: need 4*M, prefer 3*M+2*M*NB) * CALL DGEBRD( M, M, A, LDA, S, WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( NWORK ), LWORK-NWORK+1, $ IERR ) NWORK = IE + M * * Perform bidiagonal SVD, computing singular values only * (Workspace: need M+BDSPAC) * CALL DBDSDC( 'U', 'N', M, S, WORK( IE ), DUM, 1, DUM, 1, $ DUM, IDUM, WORK( NWORK ), IWORK, INFO ) * ELSE IF( WNTQO ) THEN * * Path 2t (N much larger than M, JOBZ='O') * M right singular vectors to be overwritten on A and * M left singular vectors to be computed in U * IVT = 1 * * IVT is M by M * IL = IVT + M*M IF( LWORK.GE.M*N+M*M+3*M+BDSPAC ) THEN * * WORK(IL) is M by N * LDWRKL = M CHUNK = N ELSE LDWRKL = M CHUNK = ( LWORK-M*M ) / M END IF ITAU = IL + LDWRKL*M NWORK = ITAU + M * * Compute A=L*Q * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * Copy L to WORK(IL), zeroing about above it * CALL DLACPY( 'L', M, M, A, LDA, WORK( IL ), LDWRKL ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, $ WORK( IL+LDWRKL ), LDWRKL ) * * Generate Q in A * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DORGLQ( M, N, M, A, LDA, WORK( ITAU ), $ WORK( NWORK ), LWORK-NWORK+1, IERR ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M NWORK = ITAUP + M * * Bidiagonalize L in WORK(IL) * (Workspace: need M*M+4*M, prefer M*M+3*M+2*M*NB) * CALL DGEBRD( M, M, WORK( IL ), LDWRKL, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * Perform bidiagonal SVD, computing left singular vectors * of bidiagonal matrix in U, and computing right singular * vectors of bidiagonal matrix in WORK(IVT) * (Workspace: need M+M*M+BDSPAC) * CALL DBDSDC( 'U', 'I', M, S, WORK( IE ), U, LDU, $ WORK( IVT ), M, DUM, IDUM, WORK( NWORK ), $ IWORK, INFO ) * * Overwrite U by left singular vectors of L and WORK(IVT) * by right singular vectors of L * (Workspace: need 2*M*M+3*M, prefer 2*M*M+2*M+M*NB) * CALL DORMBR( 'Q', 'L', 'N', M, M, M, WORK( IL ), LDWRKL, $ WORK( ITAUQ ), U, LDU, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) CALL DORMBR( 'P', 'R', 'T', M, M, M, WORK( IL ), LDWRKL, $ WORK( ITAUP ), WORK( IVT ), M, $ WORK( NWORK ), LWORK-NWORK+1, IERR ) * * Multiply right singular vectors of L in WORK(IVT) by Q * in A, storing result in WORK(IL) and copying to A * (Workspace: need 2*M*M, prefer M*M+M*N) * DO 30 I = 1, N, CHUNK BLK = MIN( N-I+1, CHUNK ) CALL DGEMM( 'N', 'N', M, BLK, M, ONE, WORK( IVT ), M, $ A( 1, I ), LDA, ZERO, WORK( IL ), LDWRKL ) CALL DLACPY( 'F', M, BLK, WORK( IL ), LDWRKL, $ A( 1, I ), LDA ) 30 CONTINUE * ELSE IF( WNTQS ) THEN * * Path 3t (N much larger than M, JOBZ='S') * M right singular vectors to be computed in VT and * M left singular vectors to be computed in U * IL = 1 * * WORK(IL) is M by M * LDWRKL = M ITAU = IL + LDWRKL*M NWORK = ITAU + M * * Compute A=L*Q * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * Copy L to WORK(IL), zeroing out above it * CALL DLACPY( 'L', M, M, A, LDA, WORK( IL ), LDWRKL ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, $ WORK( IL+LDWRKL ), LDWRKL ) * * Generate Q in A * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DORGLQ( M, N, M, A, LDA, WORK( ITAU ), $ WORK( NWORK ), LWORK-NWORK+1, IERR ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M NWORK = ITAUP + M * * Bidiagonalize L in WORK(IU), copying result to U * (Workspace: need M*M+4*M, prefer M*M+3*M+2*M*NB) * CALL DGEBRD( M, M, WORK( IL ), LDWRKL, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * Perform bidiagonal SVD, computing left singular vectors * of bidiagonal matrix in U and computing right singular * vectors of bidiagonal matrix in VT * (Workspace: need M+BDSPAC) * CALL DBDSDC( 'U', 'I', M, S, WORK( IE ), U, LDU, VT, $ LDVT, DUM, IDUM, WORK( NWORK ), IWORK, $ INFO ) * * Overwrite U by left singular vectors of L and VT * by right singular vectors of L * (Workspace: need M*M+3*M, prefer M*M+2*M+M*NB) * CALL DORMBR( 'Q', 'L', 'N', M, M, M, WORK( IL ), LDWRKL, $ WORK( ITAUQ ), U, LDU, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) CALL DORMBR( 'P', 'R', 'T', M, M, M, WORK( IL ), LDWRKL, $ WORK( ITAUP ), VT, LDVT, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * Multiply right singular vectors of L in WORK(IL) by * Q in A, storing result in VT * (Workspace: need M*M) * CALL DLACPY( 'F', M, M, VT, LDVT, WORK( IL ), LDWRKL ) CALL DGEMM( 'N', 'N', M, N, M, ONE, WORK( IL ), LDWRKL, $ A, LDA, ZERO, VT, LDVT ) * ELSE IF( WNTQA ) THEN * * Path 4t (N much larger than M, JOBZ='A') * N right singular vectors to be computed in VT and * M left singular vectors to be computed in U * IVT = 1 * * WORK(IVT) is M by M * LDWKVT = M ITAU = IVT + LDWKVT*M NWORK = ITAU + M * * Compute A=L*Q, copying result to VT * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), WORK( NWORK ), $ LWORK-NWORK+1, IERR ) CALL DLACPY( 'U', M, N, A, LDA, VT, LDVT ) * * Generate Q in VT * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DORGLQ( N, N, M, VT, LDVT, WORK( ITAU ), $ WORK( NWORK ), LWORK-NWORK+1, IERR ) * * Produce L in A, zeroing out other entries * CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, A( 1, 2 ), LDA ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M NWORK = ITAUP + M * * Bidiagonalize L in A * (Workspace: need M*M+4*M, prefer M*M+3*M+2*M*NB) * CALL DGEBRD( M, M, A, LDA, S, WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( NWORK ), LWORK-NWORK+1, $ IERR ) * * Perform bidiagonal SVD, computing left singular vectors * of bidiagonal matrix in U and computing right singular * vectors of bidiagonal matrix in WORK(IVT) * (Workspace: need M+M*M+BDSPAC) * CALL DBDSDC( 'U', 'I', M, S, WORK( IE ), U, LDU, $ WORK( IVT ), LDWKVT, DUM, IDUM, $ WORK( NWORK ), IWORK, INFO ) * * Overwrite U by left singular vectors of L and WORK(IVT) * by right singular vectors of L * (Workspace: need M*M+3*M, prefer M*M+2*M+M*NB) * CALL DORMBR( 'Q', 'L', 'N', M, M, M, A, LDA, $ WORK( ITAUQ ), U, LDU, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) CALL DORMBR( 'P', 'R', 'T', M, M, M, A, LDA, $ WORK( ITAUP ), WORK( IVT ), LDWKVT, $ WORK( NWORK ), LWORK-NWORK+1, IERR ) * * Multiply right singular vectors of L in WORK(IVT) by * Q in VT, storing result in A * (Workspace: need M*M) * CALL DGEMM( 'N', 'N', M, N, M, ONE, WORK( IVT ), LDWKVT, $ VT, LDVT, ZERO, A, LDA ) * * Copy right singular vectors of A from A to VT * CALL DLACPY( 'F', M, N, A, LDA, VT, LDVT ) * END IF * ELSE * * N .LT. MNTHR * * Path 5t (N greater than M, but not much larger) * Reduce to bidiagonal form without LQ decomposition * IE = 1 ITAUQ = IE + M ITAUP = ITAUQ + M NWORK = ITAUP + M * * Bidiagonalize A * (Workspace: need 3*M+N, prefer 3*M+(M+N)*NB) * CALL DGEBRD( M, N, A, LDA, S, WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( NWORK ), LWORK-NWORK+1, $ IERR ) IF( WNTQN ) THEN * * Perform bidiagonal SVD, only computing singular values * (Workspace: need M+BDSPAC) * CALL DBDSDC( 'L', 'N', M, S, WORK( IE ), DUM, 1, DUM, 1, $ DUM, IDUM, WORK( NWORK ), IWORK, INFO ) ELSE IF( WNTQO ) THEN LDWKVT = M IVT = NWORK IF( LWORK.GE.M*N+3*M+BDSPAC ) THEN * * WORK( IVT ) is M by N * CALL DLASET( 'F', M, N, ZERO, ZERO, WORK( IVT ), $ LDWKVT ) NWORK = IVT + LDWKVT*N ELSE * * WORK( IVT ) is M by M * NWORK = IVT + LDWKVT*M IL = NWORK * * WORK(IL) is M by CHUNK * CHUNK = ( LWORK-M*M-3*M ) / M END IF * * Perform bidiagonal SVD, computing left singular vectors * of bidiagonal matrix in U and computing right singular * vectors of bidiagonal matrix in WORK(IVT) * (Workspace: need M*M+BDSPAC) * CALL DBDSDC( 'L', 'I', M, S, WORK( IE ), U, LDU, $ WORK( IVT ), LDWKVT, DUM, IDUM, $ WORK( NWORK ), IWORK, INFO ) * * Overwrite U by left singular vectors of A * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DORMBR( 'Q', 'L', 'N', M, M, N, A, LDA, $ WORK( ITAUQ ), U, LDU, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * IF( LWORK.GE.M*N+3*M+BDSPAC ) THEN * * Overwrite WORK(IVT) by left singular vectors of A * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DORMBR( 'P', 'R', 'T', M, N, M, A, LDA, $ WORK( ITAUP ), WORK( IVT ), LDWKVT, $ WORK( NWORK ), LWORK-NWORK+1, IERR ) * * Copy right singular vectors of A from WORK(IVT) to A * CALL DLACPY( 'F', M, N, WORK( IVT ), LDWKVT, A, LDA ) ELSE * * Generate P**T in A * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DORGBR( 'P', M, N, M, A, LDA, WORK( ITAUP ), $ WORK( NWORK ), LWORK-NWORK+1, IERR ) * * Multiply Q in A by right singular vectors of * bidiagonal matrix in WORK(IVT), storing result in * WORK(IL) and copying to A * (Workspace: need 2*M*M, prefer M*M+M*N) * DO 40 I = 1, N, CHUNK BLK = MIN( N-I+1, CHUNK ) CALL DGEMM( 'N', 'N', M, BLK, M, ONE, WORK( IVT ), $ LDWKVT, A( 1, I ), LDA, ZERO, $ WORK( IL ), M ) CALL DLACPY( 'F', M, BLK, WORK( IL ), M, A( 1, I ), $ LDA ) 40 CONTINUE END IF ELSE IF( WNTQS ) THEN * * Perform bidiagonal SVD, computing left singular vectors * of bidiagonal matrix in U and computing right singular * vectors of bidiagonal matrix in VT * (Workspace: need M+BDSPAC) * CALL DLASET( 'F', M, N, ZERO, ZERO, VT, LDVT ) CALL DBDSDC( 'L', 'I', M, S, WORK( IE ), U, LDU, VT, $ LDVT, DUM, IDUM, WORK( NWORK ), IWORK, $ INFO ) * * Overwrite U by left singular vectors of A and VT * by right singular vectors of A * (Workspace: need 3*M, prefer 2*M+M*NB) * CALL DORMBR( 'Q', 'L', 'N', M, M, N, A, LDA, $ WORK( ITAUQ ), U, LDU, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) CALL DORMBR( 'P', 'R', 'T', M, N, M, A, LDA, $ WORK( ITAUP ), VT, LDVT, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) ELSE IF( WNTQA ) THEN * * Perform bidiagonal SVD, computing left singular vectors * of bidiagonal matrix in U and computing right singular * vectors of bidiagonal matrix in VT * (Workspace: need M+BDSPAC) * CALL DLASET( 'F', N, N, ZERO, ZERO, VT, LDVT ) CALL DBDSDC( 'L', 'I', M, S, WORK( IE ), U, LDU, VT, $ LDVT, DUM, IDUM, WORK( NWORK ), IWORK, $ INFO ) * * Set the right corner of VT to identity matrix * CALL DLASET( 'F', N-M, N-M, ZERO, ONE, VT( M+1, M+1 ), $ LDVT ) * * Overwrite U by left singular vectors of A and VT * by right singular vectors of A * (Workspace: need 2*M+N, prefer 2*M+N*NB) * CALL DORMBR( 'Q', 'L', 'N', M, M, N, A, LDA, $ WORK( ITAUQ ), U, LDU, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) CALL DORMBR( 'P', 'R', 'T', N, N, M, A, LDA, $ WORK( ITAUP ), VT, LDVT, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) END IF * END IF * END IF * * Undo scaling if necessary * IF( ISCL.EQ.1 ) THEN IF( ANRM.GT.BIGNUM ) $ CALL DLASCL( 'G', 0, 0, BIGNUM, ANRM, MINMN, 1, S, MINMN, $ IERR ) IF( ANRM.LT.SMLNUM ) $ CALL DLASCL( 'G', 0, 0, SMLNUM, ANRM, MINMN, 1, S, MINMN, $ IERR ) END IF * * Return optimal workspace in WORK(1) * WORK( 1 ) = DBLE( MAXWRK ) * RETURN * * End of DGESDD * END SUBROUTINE DGESV( N, NRHS, A, LDA, IPIV, B, LDB, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * March 31, 1993 * * .. Scalar Arguments .. INTEGER INFO, LDA, LDB, N, NRHS * .. * .. Array Arguments .. INTEGER IPIV( * ) DOUBLE PRECISION A( LDA, * ), B( LDB, * ) * .. * * Purpose * ======= * * DGESV computes the solution to a real system of linear equations * A * X = B, * where A is an N-by-N matrix and X and B are N-by-NRHS matrices. * * The LU decomposition with partial pivoting and row interchanges is * used to factor A as * A = P * L * U, * where P is a permutation matrix, L is unit lower triangular, and U is * upper triangular. The factored form of A is then used to solve the * system of equations A * X = B. * * Arguments * ========= * * N (input) INTEGER * The number of linear equations, i.e., the order of the * matrix A. N >= 0. * * NRHS (input) INTEGER * The number of right hand sides, i.e., the number of columns * of the matrix B. NRHS >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the N-by-N coefficient matrix A. * On exit, the factors L and U from the factorization * A = P*L*U; the unit diagonal elements of L are not stored. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * IPIV (output) INTEGER array, dimension (N) * The pivot indices that define the permutation matrix P; * row i of the matrix was interchanged with row IPIV(i). * * B (input/output) DOUBLE PRECISION array, dimension (LDB,NRHS) * On entry, the N-by-NRHS matrix of right hand side matrix B. * On exit, if INFO = 0, the N-by-NRHS solution matrix X. * * LDB (input) INTEGER * The leading dimension of the array B. LDB >= max(1,N). * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = i, U(i,i) is exactly zero. The factorization * has been completed, but the factor U is exactly * singular, so the solution could not be computed. * * ===================================================================== * * .. External Subroutines .. EXTERNAL DGETRF, DGETRS, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 IF( N.LT.0 ) THEN INFO = -1 ELSE IF( NRHS.LT.0 ) THEN INFO = -2 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -4 ELSE IF( LDB.LT.MAX( 1, N ) ) THEN INFO = -7 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGESV ', -INFO ) RETURN END IF * * Compute the LU factorization of A. * CALL DGETRF( N, N, A, LDA, IPIV, INFO ) IF( INFO.EQ.0 ) THEN * * Solve the system A*X = B, overwriting B with X. * CALL DGETRS( 'No transpose', N, NRHS, A, LDA, IPIV, B, LDB, $ INFO ) END IF RETURN * * End of DGESV * END SUBROUTINE DGESVD( JOBU, JOBVT, M, N, A, LDA, S, U, LDU, VT, LDVT, $ WORK, LWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1999 * * .. Scalar Arguments .. CHARACTER JOBU, JOBVT INTEGER INFO, LDA, LDU, LDVT, LWORK, M, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), S( * ), U( LDU, * ), $ VT( LDVT, * ), WORK( * ) * .. * * Purpose * ======= * * DGESVD computes the singular value decomposition (SVD) of a real * M-by-N matrix A, optionally computing the left and/or right singular * vectors. The SVD is written * * A = U * SIGMA * transpose(V) * * where SIGMA is an M-by-N matrix which is zero except for its * min(m,n) diagonal elements, U is an M-by-M orthogonal matrix, and * V is an N-by-N orthogonal matrix. The diagonal elements of SIGMA * are the singular values of A; they are real and non-negative, and * are returned in descending order. The first min(m,n) columns of * U and V are the left and right singular vectors of A. * * Note that the routine returns V**T, not V. * * Arguments * ========= * * JOBU (input) CHARACTER*1 * Specifies options for computing all or part of the matrix U: * = 'A': all M columns of U are returned in array U: * = 'S': the first min(m,n) columns of U (the left singular * vectors) are returned in the array U; * = 'O': the first min(m,n) columns of U (the left singular * vectors) are overwritten on the array A; * = 'N': no columns of U (no left singular vectors) are * computed. * * JOBVT (input) CHARACTER*1 * Specifies options for computing all or part of the matrix * V**T: * = 'A': all N rows of V**T are returned in the array VT; * = 'S': the first min(m,n) rows of V**T (the right singular * vectors) are returned in the array VT; * = 'O': the first min(m,n) rows of V**T (the right singular * vectors) are overwritten on the array A; * = 'N': no rows of V**T (no right singular vectors) are * computed. * * JOBVT and JOBU cannot both be 'O'. * * M (input) INTEGER * The number of rows of the input matrix A. M >= 0. * * N (input) INTEGER * The number of columns of the input matrix A. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the M-by-N matrix A. * On exit, * if JOBU = 'O', A is overwritten with the first min(m,n) * columns of U (the left singular vectors, * stored columnwise); * if JOBVT = 'O', A is overwritten with the first min(m,n) * rows of V**T (the right singular vectors, * stored rowwise); * if JOBU .ne. 'O' and JOBVT .ne. 'O', the contents of A * are destroyed. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,M). * * S (output) DOUBLE PRECISION array, dimension (min(M,N)) * The singular values of A, sorted so that S(i) >= S(i+1). * * U (output) DOUBLE PRECISION array, dimension (LDU,UCOL) * (LDU,M) if JOBU = 'A' or (LDU,min(M,N)) if JOBU = 'S'. * If JOBU = 'A', U contains the M-by-M orthogonal matrix U; * if JOBU = 'S', U contains the first min(m,n) columns of U * (the left singular vectors, stored columnwise); * if JOBU = 'N' or 'O', U is not referenced. * * LDU (input) INTEGER * The leading dimension of the array U. LDU >= 1; if * JOBU = 'S' or 'A', LDU >= M. * * VT (output) DOUBLE PRECISION array, dimension (LDVT,N) * If JOBVT = 'A', VT contains the N-by-N orthogonal matrix * V**T; * if JOBVT = 'S', VT contains the first min(m,n) rows of * V**T (the right singular vectors, stored rowwise); * if JOBVT = 'N' or 'O', VT is not referenced. * * LDVT (input) INTEGER * The leading dimension of the array VT. LDVT >= 1; if * JOBVT = 'A', LDVT >= N; if JOBVT = 'S', LDVT >= min(M,N). * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK; * if INFO > 0, WORK(2:MIN(M,N)) contains the unconverged * superdiagonal elements of an upper bidiagonal matrix B * whose diagonal is in S (not necessarily sorted). B * satisfies A = U * B * VT, so it has the same singular values * as A, and singular vectors related by U and VT. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= 1. * LWORK >= MAX(3*MIN(M,N)+MAX(M,N),5*MIN(M,N)). * For good performance, LWORK should generally be larger. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit. * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: if DBDSQR did not converge, INFO specifies how many * superdiagonals of an intermediate bidiagonal form B * did not converge to zero. See the description of WORK * above for details. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. LOGICAL LQUERY, WNTUA, WNTUAS, WNTUN, WNTUO, WNTUS, $ WNTVA, WNTVAS, WNTVN, WNTVO, WNTVS INTEGER BDSPAC, BLK, CHUNK, I, IE, IERR, IR, ISCL, $ ITAU, ITAUP, ITAUQ, IU, IWORK, LDWRKR, LDWRKU, $ MAXWRK, MINMN, MINWRK, MNTHR, NCU, NCVT, NRU, $ NRVT, WRKBL DOUBLE PRECISION ANRM, BIGNUM, EPS, SMLNUM * .. * .. Local Arrays .. DOUBLE PRECISION DUM( 1 ) * .. * .. External Subroutines .. EXTERNAL DBDSQR, DGEBRD, DGELQF, DGEMM, DGEQRF, DLACPY, $ DLASCL, DLASET, DORGBR, DORGLQ, DORGQR, DORMBR, $ XERBLA * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANGE EXTERNAL LSAME, ILAENV, DLAMCH, DLANGE * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN, SQRT * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 MINMN = MIN( M, N ) MNTHR = ILAENV( 6, 'DGESVD', JOBU // JOBVT, M, N, 0, 0 ) WNTUA = LSAME( JOBU, 'A' ) WNTUS = LSAME( JOBU, 'S' ) WNTUAS = WNTUA .OR. WNTUS WNTUO = LSAME( JOBU, 'O' ) WNTUN = LSAME( JOBU, 'N' ) WNTVA = LSAME( JOBVT, 'A' ) WNTVS = LSAME( JOBVT, 'S' ) WNTVAS = WNTVA .OR. WNTVS WNTVO = LSAME( JOBVT, 'O' ) WNTVN = LSAME( JOBVT, 'N' ) MINWRK = 1 LQUERY = ( LWORK.EQ.-1 ) * IF( .NOT.( WNTUA .OR. WNTUS .OR. WNTUO .OR. WNTUN ) ) THEN INFO = -1 ELSE IF( .NOT.( WNTVA .OR. WNTVS .OR. WNTVO .OR. WNTVN ) .OR. $ ( WNTVO .AND. WNTUO ) ) THEN INFO = -2 ELSE IF( M.LT.0 ) THEN INFO = -3 ELSE IF( N.LT.0 ) THEN INFO = -4 ELSE IF( LDA.LT.MAX( 1, M ) ) THEN INFO = -6 ELSE IF( LDU.LT.1 .OR. ( WNTUAS .AND. LDU.LT.M ) ) THEN INFO = -9 ELSE IF( LDVT.LT.1 .OR. ( WNTVA .AND. LDVT.LT.N ) .OR. $ ( WNTVS .AND. LDVT.LT.MINMN ) ) THEN INFO = -11 END IF * * Compute workspace * (Note: Comments in the code beginning "Workspace:" describe the * minimal amount of workspace needed at that point in the code, * as well as the preferred amount for good performance. * NB refers to the optimal block size for the immediately * following subroutine, as returned by ILAENV.) * IF( INFO.EQ.0 .AND. ( LWORK.GE.1 .OR. LQUERY ) .AND. M.GT.0 .AND. $ N.GT.0 ) THEN IF( M.GE.N ) THEN * * Compute space needed for DBDSQR * BDSPAC = 5*N IF( M.GE.MNTHR ) THEN IF( WNTUN ) THEN * * Path 1 (M much larger than N, JOBU='N') * MAXWRK = N + N*ILAENV( 1, 'DGEQRF', ' ', M, N, -1, $ -1 ) MAXWRK = MAX( MAXWRK, 3*N+2*N* $ ILAENV( 1, 'DGEBRD', ' ', N, N, -1, -1 ) ) IF( WNTVO .OR. WNTVAS ) $ MAXWRK = MAX( MAXWRK, 3*N+( N-1 )* $ ILAENV( 1, 'DORGBR', 'P', N, N, N, -1 ) ) MAXWRK = MAX( MAXWRK, BDSPAC ) MINWRK = MAX( 4*N, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTUO .AND. WNTVN ) THEN * * Path 2 (M much larger than N, JOBU='O', JOBVT='N') * WRKBL = N + N*ILAENV( 1, 'DGEQRF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, N+N*ILAENV( 1, 'DORGQR', ' ', M, $ N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+2*N* $ ILAENV( 1, 'DGEBRD', ' ', N, N, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORGBR', 'Q', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = MAX( N*N+WRKBL, N*N+M*N+N ) MINWRK = MAX( 3*N+M, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTUO .AND. WNTVAS ) THEN * * Path 3 (M much larger than N, JOBU='O', JOBVT='S' or * 'A') * WRKBL = N + N*ILAENV( 1, 'DGEQRF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, N+N*ILAENV( 1, 'DORGQR', ' ', M, $ N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+2*N* $ ILAENV( 1, 'DGEBRD', ' ', N, N, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORGBR', 'Q', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+( N-1 )* $ ILAENV( 1, 'DORGBR', 'P', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = MAX( N*N+WRKBL, N*N+M*N+N ) MINWRK = MAX( 3*N+M, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTUS .AND. WNTVN ) THEN * * Path 4 (M much larger than N, JOBU='S', JOBVT='N') * WRKBL = N + N*ILAENV( 1, 'DGEQRF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, N+N*ILAENV( 1, 'DORGQR', ' ', M, $ N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+2*N* $ ILAENV( 1, 'DGEBRD', ' ', N, N, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORGBR', 'Q', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = N*N + WRKBL MINWRK = MAX( 3*N+M, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTUS .AND. WNTVO ) THEN * * Path 5 (M much larger than N, JOBU='S', JOBVT='O') * WRKBL = N + N*ILAENV( 1, 'DGEQRF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, N+N*ILAENV( 1, 'DORGQR', ' ', M, $ N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+2*N* $ ILAENV( 1, 'DGEBRD', ' ', N, N, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORGBR', 'Q', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+( N-1 )* $ ILAENV( 1, 'DORGBR', 'P', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = 2*N*N + WRKBL MINWRK = MAX( 3*N+M, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTUS .AND. WNTVAS ) THEN * * Path 6 (M much larger than N, JOBU='S', JOBVT='S' or * 'A') * WRKBL = N + N*ILAENV( 1, 'DGEQRF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, N+N*ILAENV( 1, 'DORGQR', ' ', M, $ N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+2*N* $ ILAENV( 1, 'DGEBRD', ' ', N, N, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORGBR', 'Q', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+( N-1 )* $ ILAENV( 1, 'DORGBR', 'P', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = N*N + WRKBL MINWRK = MAX( 3*N+M, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTUA .AND. WNTVN ) THEN * * Path 7 (M much larger than N, JOBU='A', JOBVT='N') * WRKBL = N + N*ILAENV( 1, 'DGEQRF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, N+M*ILAENV( 1, 'DORGQR', ' ', M, $ M, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+2*N* $ ILAENV( 1, 'DGEBRD', ' ', N, N, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORGBR', 'Q', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = N*N + WRKBL MINWRK = MAX( 3*N+M, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTUA .AND. WNTVO ) THEN * * Path 8 (M much larger than N, JOBU='A', JOBVT='O') * WRKBL = N + N*ILAENV( 1, 'DGEQRF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, N+M*ILAENV( 1, 'DORGQR', ' ', M, $ M, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+2*N* $ ILAENV( 1, 'DGEBRD', ' ', N, N, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORGBR', 'Q', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+( N-1 )* $ ILAENV( 1, 'DORGBR', 'P', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = 2*N*N + WRKBL MINWRK = MAX( 3*N+M, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTUA .AND. WNTVAS ) THEN * * Path 9 (M much larger than N, JOBU='A', JOBVT='S' or * 'A') * WRKBL = N + N*ILAENV( 1, 'DGEQRF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, N+M*ILAENV( 1, 'DORGQR', ' ', M, $ M, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+2*N* $ ILAENV( 1, 'DGEBRD', ' ', N, N, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORGBR', 'Q', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+( N-1 )* $ ILAENV( 1, 'DORGBR', 'P', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = N*N + WRKBL MINWRK = MAX( 3*N+M, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) END IF ELSE * * Path 10 (M at least N, but not much larger) * MAXWRK = 3*N + ( M+N )*ILAENV( 1, 'DGEBRD', ' ', M, N, $ -1, -1 ) IF( WNTUS .OR. WNTUO ) $ MAXWRK = MAX( MAXWRK, 3*N+N* $ ILAENV( 1, 'DORGBR', 'Q', M, N, N, -1 ) ) IF( WNTUA ) $ MAXWRK = MAX( MAXWRK, 3*N+M* $ ILAENV( 1, 'DORGBR', 'Q', M, M, N, -1 ) ) IF( .NOT.WNTVN ) $ MAXWRK = MAX( MAXWRK, 3*N+( N-1 )* $ ILAENV( 1, 'DORGBR', 'P', N, N, N, -1 ) ) MAXWRK = MAX( MAXWRK, BDSPAC ) MINWRK = MAX( 3*N+M, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) END IF ELSE * * Compute space needed for DBDSQR * BDSPAC = 5*M IF( N.GE.MNTHR ) THEN IF( WNTVN ) THEN * * Path 1t(N much larger than M, JOBVT='N') * MAXWRK = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, $ -1 ) MAXWRK = MAX( MAXWRK, 3*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) IF( WNTUO .OR. WNTUAS ) $ MAXWRK = MAX( MAXWRK, 3*M+M* $ ILAENV( 1, 'DORGBR', 'Q', M, M, M, -1 ) ) MAXWRK = MAX( MAXWRK, BDSPAC ) MINWRK = MAX( 4*M, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTVO .AND. WNTUN ) THEN * * Path 2t(N much larger than M, JOBU='N', JOBVT='O') * WRKBL = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, M+M*ILAENV( 1, 'DORGLQ', ' ', M, $ N, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*M+( M-1 )* $ ILAENV( 1, 'DORGBR', 'P', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = MAX( M*M+WRKBL, M*M+M*N+M ) MINWRK = MAX( 3*M+N, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTVO .AND. WNTUAS ) THEN * * Path 3t(N much larger than M, JOBU='S' or 'A', * JOBVT='O') * WRKBL = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, M+M*ILAENV( 1, 'DORGLQ', ' ', M, $ N, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*M+( M-1 )* $ ILAENV( 1, 'DORGBR', 'P', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORGBR', 'Q', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = MAX( M*M+WRKBL, M*M+M*N+M ) MINWRK = MAX( 3*M+N, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTVS .AND. WNTUN ) THEN * * Path 4t(N much larger than M, JOBU='N', JOBVT='S') * WRKBL = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, M+M*ILAENV( 1, 'DORGLQ', ' ', M, $ N, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*M+( M-1 )* $ ILAENV( 1, 'DORGBR', 'P', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = M*M + WRKBL MINWRK = MAX( 3*M+N, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTVS .AND. WNTUO ) THEN * * Path 5t(N much larger than M, JOBU='O', JOBVT='S') * WRKBL = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, M+M*ILAENV( 1, 'DORGLQ', ' ', M, $ N, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*M+( M-1 )* $ ILAENV( 1, 'DORGBR', 'P', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORGBR', 'Q', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = 2*M*M + WRKBL MINWRK = MAX( 3*M+N, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTVS .AND. WNTUAS ) THEN * * Path 6t(N much larger than M, JOBU='S' or 'A', * JOBVT='S') * WRKBL = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, M+M*ILAENV( 1, 'DORGLQ', ' ', M, $ N, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*M+( M-1 )* $ ILAENV( 1, 'DORGBR', 'P', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORGBR', 'Q', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = M*M + WRKBL MINWRK = MAX( 3*M+N, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTVA .AND. WNTUN ) THEN * * Path 7t(N much larger than M, JOBU='N', JOBVT='A') * WRKBL = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, M+N*ILAENV( 1, 'DORGLQ', ' ', N, $ N, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*M+( M-1 )* $ ILAENV( 1, 'DORGBR', 'P', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = M*M + WRKBL MINWRK = MAX( 3*M+N, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTVA .AND. WNTUO ) THEN * * Path 8t(N much larger than M, JOBU='O', JOBVT='A') * WRKBL = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, M+N*ILAENV( 1, 'DORGLQ', ' ', N, $ N, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*M+( M-1 )* $ ILAENV( 1, 'DORGBR', 'P', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORGBR', 'Q', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = 2*M*M + WRKBL MINWRK = MAX( 3*M+N, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTVA .AND. WNTUAS ) THEN * * Path 9t(N much larger than M, JOBU='S' or 'A', * JOBVT='A') * WRKBL = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, M+N*ILAENV( 1, 'DORGLQ', ' ', N, $ N, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*M+( M-1 )* $ ILAENV( 1, 'DORGBR', 'P', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORGBR', 'Q', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = M*M + WRKBL MINWRK = MAX( 3*M+N, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) END IF ELSE * * Path 10t(N greater than M, but not much larger) * MAXWRK = 3*M + ( M+N )*ILAENV( 1, 'DGEBRD', ' ', M, N, $ -1, -1 ) IF( WNTVS .OR. WNTVO ) $ MAXWRK = MAX( MAXWRK, 3*M+M* $ ILAENV( 1, 'DORGBR', 'P', M, N, M, -1 ) ) IF( WNTVA ) $ MAXWRK = MAX( MAXWRK, 3*M+N* $ ILAENV( 1, 'DORGBR', 'P', N, N, M, -1 ) ) IF( .NOT.WNTUN ) $ MAXWRK = MAX( MAXWRK, 3*M+( M-1 )* $ ILAENV( 1, 'DORGBR', 'Q', M, M, M, -1 ) ) MAXWRK = MAX( MAXWRK, BDSPAC ) MINWRK = MAX( 3*M+N, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) END IF END IF WORK( 1 ) = MAXWRK END IF * IF( LWORK.LT.MINWRK .AND. .NOT.LQUERY ) THEN INFO = -13 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGESVD', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( M.EQ.0 .OR. N.EQ.0 ) THEN IF( LWORK.GE.1 ) $ WORK( 1 ) = ONE RETURN END IF * * Get machine constants * EPS = DLAMCH( 'P' ) SMLNUM = SQRT( DLAMCH( 'S' ) ) / EPS BIGNUM = ONE / SMLNUM * * Scale A if max element outside range [SMLNUM,BIGNUM] * ANRM = DLANGE( 'M', M, N, A, LDA, DUM ) ISCL = 0 IF( ANRM.GT.ZERO .AND. ANRM.LT.SMLNUM ) THEN ISCL = 1 CALL DLASCL( 'G', 0, 0, ANRM, SMLNUM, M, N, A, LDA, IERR ) ELSE IF( ANRM.GT.BIGNUM ) THEN ISCL = 1 CALL DLASCL( 'G', 0, 0, ANRM, BIGNUM, M, N, A, LDA, IERR ) END IF * IF( M.GE.N ) THEN * * A has at least as many rows as columns. If A has sufficiently * more rows than columns, first reduce using the QR * decomposition (if sufficient workspace available) * IF( M.GE.MNTHR ) THEN * IF( WNTUN ) THEN * * Path 1 (M much larger than N, JOBU='N') * No left singular vectors to be computed * ITAU = 1 IWORK = ITAU + N * * Compute A=Q*R * (Workspace: need 2*N, prefer N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Zero out below R * CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, A( 2, 1 ), LDA ) IE = 1 ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize R in A * (Workspace: need 4*N, prefer 3*N+2*N*NB) * CALL DGEBRD( N, N, A, LDA, S, WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), LWORK-IWORK+1, $ IERR ) NCVT = 0 IF( WNTVO .OR. WNTVAS ) THEN * * If right singular vectors desired, generate P'. * (Workspace: need 4*N-1, prefer 3*N+(N-1)*NB) * CALL DORGBR( 'P', N, N, N, A, LDA, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) NCVT = N END IF IWORK = IE + N * * Perform bidiagonal QR iteration, computing right * singular vectors of A in A if desired * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', N, NCVT, 0, 0, S, WORK( IE ), A, LDA, $ DUM, 1, DUM, 1, WORK( IWORK ), INFO ) * * If right singular vectors desired in VT, copy them there * IF( WNTVAS ) $ CALL DLACPY( 'F', N, N, A, LDA, VT, LDVT ) * ELSE IF( WNTUO .AND. WNTVN ) THEN * * Path 2 (M much larger than N, JOBU='O', JOBVT='N') * N left singular vectors to be overwritten on A and * no right singular vectors to be computed * IF( LWORK.GE.N*N+MAX( 4*N, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IR = 1 IF( LWORK.GE.MAX( WRKBL, LDA*N+N )+LDA*N ) THEN * * WORK(IU) is LDA by N, WORK(IR) is LDA by N * LDWRKU = LDA LDWRKR = LDA ELSE IF( LWORK.GE.MAX( WRKBL, LDA*N+N )+N*N ) THEN * * WORK(IU) is LDA by N, WORK(IR) is N by N * LDWRKU = LDA LDWRKR = N ELSE * * WORK(IU) is LDWRKU by N, WORK(IR) is N by N * LDWRKU = ( LWORK-N*N-N ) / N LDWRKR = N END IF ITAU = IR + LDWRKR*N IWORK = ITAU + N * * Compute A=Q*R * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy R to WORK(IR) and zero out below it * CALL DLACPY( 'U', N, N, A, LDA, WORK( IR ), LDWRKR ) CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, WORK( IR+1 ), $ LDWRKR ) * * Generate Q in A * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DORGQR( M, N, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize R in WORK(IR) * (Workspace: need N*N+4*N, prefer N*N+3*N+2*N*NB) * CALL DGEBRD( N, N, WORK( IR ), LDWRKR, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Generate left vectors bidiagonalizing R * (Workspace: need N*N+4*N, prefer N*N+3*N+N*NB) * CALL DORGBR( 'Q', N, N, N, WORK( IR ), LDWRKR, $ WORK( ITAUQ ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of R in WORK(IR) * (Workspace: need N*N+BDSPAC) * CALL DBDSQR( 'U', N, 0, N, 0, S, WORK( IE ), DUM, 1, $ WORK( IR ), LDWRKR, DUM, 1, $ WORK( IWORK ), INFO ) IU = IE + N * * Multiply Q in A by left singular vectors of R in * WORK(IR), storing result in WORK(IU) and copying to A * (Workspace: need N*N+2*N, prefer N*N+M*N+N) * DO 10 I = 1, M, LDWRKU CHUNK = MIN( M-I+1, LDWRKU ) CALL DGEMM( 'N', 'N', CHUNK, N, N, ONE, A( I, 1 ), $ LDA, WORK( IR ), LDWRKR, ZERO, $ WORK( IU ), LDWRKU ) CALL DLACPY( 'F', CHUNK, N, WORK( IU ), LDWRKU, $ A( I, 1 ), LDA ) 10 CONTINUE * ELSE * * Insufficient workspace for a fast algorithm * IE = 1 ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize A * (Workspace: need 3*N+M, prefer 3*N+(M+N)*NB) * CALL DGEBRD( M, N, A, LDA, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Generate left vectors bidiagonalizing A * (Workspace: need 4*N, prefer 3*N+N*NB) * CALL DORGBR( 'Q', M, N, N, A, LDA, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of A in A * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', N, 0, M, 0, S, WORK( IE ), DUM, 1, $ A, LDA, DUM, 1, WORK( IWORK ), INFO ) * END IF * ELSE IF( WNTUO .AND. WNTVAS ) THEN * * Path 3 (M much larger than N, JOBU='O', JOBVT='S' or 'A') * N left singular vectors to be overwritten on A and * N right singular vectors to be computed in VT * IF( LWORK.GE.N*N+MAX( 4*N, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IR = 1 IF( LWORK.GE.MAX( WRKBL, LDA*N+N )+LDA*N ) THEN * * WORK(IU) is LDA by N and WORK(IR) is LDA by N * LDWRKU = LDA LDWRKR = LDA ELSE IF( LWORK.GE.MAX( WRKBL, LDA*N+N )+N*N ) THEN * * WORK(IU) is LDA by N and WORK(IR) is N by N * LDWRKU = LDA LDWRKR = N ELSE * * WORK(IU) is LDWRKU by N and WORK(IR) is N by N * LDWRKU = ( LWORK-N*N-N ) / N LDWRKR = N END IF ITAU = IR + LDWRKR*N IWORK = ITAU + N * * Compute A=Q*R * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy R to VT, zeroing out below it * CALL DLACPY( 'U', N, N, A, LDA, VT, LDVT ) CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, VT( 2, 1 ), $ LDVT ) * * Generate Q in A * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DORGQR( M, N, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize R in VT, copying result to WORK(IR) * (Workspace: need N*N+4*N, prefer N*N+3*N+2*N*NB) * CALL DGEBRD( N, N, VT, LDVT, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', N, N, VT, LDVT, WORK( IR ), LDWRKR ) * * Generate left vectors bidiagonalizing R in WORK(IR) * (Workspace: need N*N+4*N, prefer N*N+3*N+N*NB) * CALL DORGBR( 'Q', N, N, N, WORK( IR ), LDWRKR, $ WORK( ITAUQ ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate right vectors bidiagonalizing R in VT * (Workspace: need N*N+4*N-1, prefer N*N+3*N+(N-1)*NB) * CALL DORGBR( 'P', N, N, N, VT, LDVT, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of R in WORK(IR) and computing right * singular vectors of R in VT * (Workspace: need N*N+BDSPAC) * CALL DBDSQR( 'U', N, N, N, 0, S, WORK( IE ), VT, LDVT, $ WORK( IR ), LDWRKR, DUM, 1, $ WORK( IWORK ), INFO ) IU = IE + N * * Multiply Q in A by left singular vectors of R in * WORK(IR), storing result in WORK(IU) and copying to A * (Workspace: need N*N+2*N, prefer N*N+M*N+N) * DO 20 I = 1, M, LDWRKU CHUNK = MIN( M-I+1, LDWRKU ) CALL DGEMM( 'N', 'N', CHUNK, N, N, ONE, A( I, 1 ), $ LDA, WORK( IR ), LDWRKR, ZERO, $ WORK( IU ), LDWRKU ) CALL DLACPY( 'F', CHUNK, N, WORK( IU ), LDWRKU, $ A( I, 1 ), LDA ) 20 CONTINUE * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + N * * Compute A=Q*R * (Workspace: need 2*N, prefer N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy R to VT, zeroing out below it * CALL DLACPY( 'U', N, N, A, LDA, VT, LDVT ) CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, VT( 2, 1 ), $ LDVT ) * * Generate Q in A * (Workspace: need 2*N, prefer N+N*NB) * CALL DORGQR( M, N, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize R in VT * (Workspace: need 4*N, prefer 3*N+2*N*NB) * CALL DGEBRD( N, N, VT, LDVT, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply Q in A by left vectors bidiagonalizing R * (Workspace: need 3*N+M, prefer 3*N+M*NB) * CALL DORMBR( 'Q', 'R', 'N', M, N, N, VT, LDVT, $ WORK( ITAUQ ), A, LDA, WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate right vectors bidiagonalizing R in VT * (Workspace: need 4*N-1, prefer 3*N+(N-1)*NB) * CALL DORGBR( 'P', N, N, N, VT, LDVT, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of A in A and computing right * singular vectors of A in VT * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', N, N, M, 0, S, WORK( IE ), VT, LDVT, $ A, LDA, DUM, 1, WORK( IWORK ), INFO ) * END IF * ELSE IF( WNTUS ) THEN * IF( WNTVN ) THEN * * Path 4 (M much larger than N, JOBU='S', JOBVT='N') * N left singular vectors to be computed in U and * no right singular vectors to be computed * IF( LWORK.GE.N*N+MAX( 4*N, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IR = 1 IF( LWORK.GE.WRKBL+LDA*N ) THEN * * WORK(IR) is LDA by N * LDWRKR = LDA ELSE * * WORK(IR) is N by N * LDWRKR = N END IF ITAU = IR + LDWRKR*N IWORK = ITAU + N * * Compute A=Q*R * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy R to WORK(IR), zeroing out below it * CALL DLACPY( 'U', N, N, A, LDA, WORK( IR ), $ LDWRKR ) CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, $ WORK( IR+1 ), LDWRKR ) * * Generate Q in A * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DORGQR( M, N, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize R in WORK(IR) * (Workspace: need N*N+4*N, prefer N*N+3*N+2*N*NB) * CALL DGEBRD( N, N, WORK( IR ), LDWRKR, S, $ WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate left vectors bidiagonalizing R in WORK(IR) * (Workspace: need N*N+4*N, prefer N*N+3*N+N*NB) * CALL DORGBR( 'Q', N, N, N, WORK( IR ), LDWRKR, $ WORK( ITAUQ ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of R in WORK(IR) * (Workspace: need N*N+BDSPAC) * CALL DBDSQR( 'U', N, 0, N, 0, S, WORK( IE ), DUM, $ 1, WORK( IR ), LDWRKR, DUM, 1, $ WORK( IWORK ), INFO ) * * Multiply Q in A by left singular vectors of R in * WORK(IR), storing result in U * (Workspace: need N*N) * CALL DGEMM( 'N', 'N', M, N, N, ONE, A, LDA, $ WORK( IR ), LDWRKR, ZERO, U, LDU ) * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + N * * Compute A=Q*R, copying result to U * (Workspace: need 2*N, prefer N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', M, N, A, LDA, U, LDU ) * * Generate Q in U * (Workspace: need 2*N, prefer N+N*NB) * CALL DORGQR( M, N, N, U, LDU, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Zero out below R in A * CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, A( 2, 1 ), $ LDA ) * * Bidiagonalize R in A * (Workspace: need 4*N, prefer 3*N+2*N*NB) * CALL DGEBRD( N, N, A, LDA, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply Q in U by left vectors bidiagonalizing R * (Workspace: need 3*N+M, prefer 3*N+M*NB) * CALL DORMBR( 'Q', 'R', 'N', M, N, N, A, LDA, $ WORK( ITAUQ ), U, LDU, WORK( IWORK ), $ LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of A in U * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', N, 0, M, 0, S, WORK( IE ), DUM, $ 1, U, LDU, DUM, 1, WORK( IWORK ), $ INFO ) * END IF * ELSE IF( WNTVO ) THEN * * Path 5 (M much larger than N, JOBU='S', JOBVT='O') * N left singular vectors to be computed in U and * N right singular vectors to be overwritten on A * IF( LWORK.GE.2*N*N+MAX( 4*N, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IU = 1 IF( LWORK.GE.WRKBL+2*LDA*N ) THEN * * WORK(IU) is LDA by N and WORK(IR) is LDA by N * LDWRKU = LDA IR = IU + LDWRKU*N LDWRKR = LDA ELSE IF( LWORK.GE.WRKBL+( LDA+N )*N ) THEN * * WORK(IU) is LDA by N and WORK(IR) is N by N * LDWRKU = LDA IR = IU + LDWRKU*N LDWRKR = N ELSE * * WORK(IU) is N by N and WORK(IR) is N by N * LDWRKU = N IR = IU + LDWRKU*N LDWRKR = N END IF ITAU = IR + LDWRKR*N IWORK = ITAU + N * * Compute A=Q*R * (Workspace: need 2*N*N+2*N, prefer 2*N*N+N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy R to WORK(IU), zeroing out below it * CALL DLACPY( 'U', N, N, A, LDA, WORK( IU ), $ LDWRKU ) CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, $ WORK( IU+1 ), LDWRKU ) * * Generate Q in A * (Workspace: need 2*N*N+2*N, prefer 2*N*N+N+N*NB) * CALL DORGQR( M, N, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize R in WORK(IU), copying result to * WORK(IR) * (Workspace: need 2*N*N+4*N, * prefer 2*N*N+3*N+2*N*NB) * CALL DGEBRD( N, N, WORK( IU ), LDWRKU, S, $ WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) CALL DLACPY( 'U', N, N, WORK( IU ), LDWRKU, $ WORK( IR ), LDWRKR ) * * Generate left bidiagonalizing vectors in WORK(IU) * (Workspace: need 2*N*N+4*N, prefer 2*N*N+3*N+N*NB) * CALL DORGBR( 'Q', N, N, N, WORK( IU ), LDWRKU, $ WORK( ITAUQ ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate right bidiagonalizing vectors in WORK(IR) * (Workspace: need 2*N*N+4*N-1, * prefer 2*N*N+3*N+(N-1)*NB) * CALL DORGBR( 'P', N, N, N, WORK( IR ), LDWRKR, $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of R in WORK(IU) and computing * right singular vectors of R in WORK(IR) * (Workspace: need 2*N*N+BDSPAC) * CALL DBDSQR( 'U', N, N, N, 0, S, WORK( IE ), $ WORK( IR ), LDWRKR, WORK( IU ), $ LDWRKU, DUM, 1, WORK( IWORK ), INFO ) * * Multiply Q in A by left singular vectors of R in * WORK(IU), storing result in U * (Workspace: need N*N) * CALL DGEMM( 'N', 'N', M, N, N, ONE, A, LDA, $ WORK( IU ), LDWRKU, ZERO, U, LDU ) * * Copy right singular vectors of R to A * (Workspace: need N*N) * CALL DLACPY( 'F', N, N, WORK( IR ), LDWRKR, A, $ LDA ) * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + N * * Compute A=Q*R, copying result to U * (Workspace: need 2*N, prefer N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', M, N, A, LDA, U, LDU ) * * Generate Q in U * (Workspace: need 2*N, prefer N+N*NB) * CALL DORGQR( M, N, N, U, LDU, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Zero out below R in A * CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, A( 2, 1 ), $ LDA ) * * Bidiagonalize R in A * (Workspace: need 4*N, prefer 3*N+2*N*NB) * CALL DGEBRD( N, N, A, LDA, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply Q in U by left vectors bidiagonalizing R * (Workspace: need 3*N+M, prefer 3*N+M*NB) * CALL DORMBR( 'Q', 'R', 'N', M, N, N, A, LDA, $ WORK( ITAUQ ), U, LDU, WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate right vectors bidiagonalizing R in A * (Workspace: need 4*N-1, prefer 3*N+(N-1)*NB) * CALL DORGBR( 'P', N, N, N, A, LDA, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of A in U and computing right * singular vectors of A in A * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', N, N, M, 0, S, WORK( IE ), A, $ LDA, U, LDU, DUM, 1, WORK( IWORK ), $ INFO ) * END IF * ELSE IF( WNTVAS ) THEN * * Path 6 (M much larger than N, JOBU='S', JOBVT='S' * or 'A') * N left singular vectors to be computed in U and * N right singular vectors to be computed in VT * IF( LWORK.GE.N*N+MAX( 4*N, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IU = 1 IF( LWORK.GE.WRKBL+LDA*N ) THEN * * WORK(IU) is LDA by N * LDWRKU = LDA ELSE * * WORK(IU) is N by N * LDWRKU = N END IF ITAU = IU + LDWRKU*N IWORK = ITAU + N * * Compute A=Q*R * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy R to WORK(IU), zeroing out below it * CALL DLACPY( 'U', N, N, A, LDA, WORK( IU ), $ LDWRKU ) CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, $ WORK( IU+1 ), LDWRKU ) * * Generate Q in A * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DORGQR( M, N, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize R in WORK(IU), copying result to VT * (Workspace: need N*N+4*N, prefer N*N+3*N+2*N*NB) * CALL DGEBRD( N, N, WORK( IU ), LDWRKU, S, $ WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) CALL DLACPY( 'U', N, N, WORK( IU ), LDWRKU, VT, $ LDVT ) * * Generate left bidiagonalizing vectors in WORK(IU) * (Workspace: need N*N+4*N, prefer N*N+3*N+N*NB) * CALL DORGBR( 'Q', N, N, N, WORK( IU ), LDWRKU, $ WORK( ITAUQ ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate right bidiagonalizing vectors in VT * (Workspace: need N*N+4*N-1, * prefer N*N+3*N+(N-1)*NB) * CALL DORGBR( 'P', N, N, N, VT, LDVT, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of R in WORK(IU) and computing * right singular vectors of R in VT * (Workspace: need N*N+BDSPAC) * CALL DBDSQR( 'U', N, N, N, 0, S, WORK( IE ), VT, $ LDVT, WORK( IU ), LDWRKU, DUM, 1, $ WORK( IWORK ), INFO ) * * Multiply Q in A by left singular vectors of R in * WORK(IU), storing result in U * (Workspace: need N*N) * CALL DGEMM( 'N', 'N', M, N, N, ONE, A, LDA, $ WORK( IU ), LDWRKU, ZERO, U, LDU ) * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + N * * Compute A=Q*R, copying result to U * (Workspace: need 2*N, prefer N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', M, N, A, LDA, U, LDU ) * * Generate Q in U * (Workspace: need 2*N, prefer N+N*NB) * CALL DORGQR( M, N, N, U, LDU, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy R to VT, zeroing out below it * CALL DLACPY( 'U', N, N, A, LDA, VT, LDVT ) CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, VT( 2, 1 ), $ LDVT ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize R in VT * (Workspace: need 4*N, prefer 3*N+2*N*NB) * CALL DGEBRD( N, N, VT, LDVT, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply Q in U by left bidiagonalizing vectors * in VT * (Workspace: need 3*N+M, prefer 3*N+M*NB) * CALL DORMBR( 'Q', 'R', 'N', M, N, N, VT, LDVT, $ WORK( ITAUQ ), U, LDU, WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate right bidiagonalizing vectors in VT * (Workspace: need 4*N-1, prefer 3*N+(N-1)*NB) * CALL DORGBR( 'P', N, N, N, VT, LDVT, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of A in U and computing right * singular vectors of A in VT * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', N, N, M, 0, S, WORK( IE ), VT, $ LDVT, U, LDU, DUM, 1, WORK( IWORK ), $ INFO ) * END IF * END IF * ELSE IF( WNTUA ) THEN * IF( WNTVN ) THEN * * Path 7 (M much larger than N, JOBU='A', JOBVT='N') * M left singular vectors to be computed in U and * no right singular vectors to be computed * IF( LWORK.GE.N*N+MAX( N+M, 4*N, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IR = 1 IF( LWORK.GE.WRKBL+LDA*N ) THEN * * WORK(IR) is LDA by N * LDWRKR = LDA ELSE * * WORK(IR) is N by N * LDWRKR = N END IF ITAU = IR + LDWRKR*N IWORK = ITAU + N * * Compute A=Q*R, copying result to U * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', M, N, A, LDA, U, LDU ) * * Copy R to WORK(IR), zeroing out below it * CALL DLACPY( 'U', N, N, A, LDA, WORK( IR ), $ LDWRKR ) CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, $ WORK( IR+1 ), LDWRKR ) * * Generate Q in U * (Workspace: need N*N+N+M, prefer N*N+N+M*NB) * CALL DORGQR( M, M, N, U, LDU, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize R in WORK(IR) * (Workspace: need N*N+4*N, prefer N*N+3*N+2*N*NB) * CALL DGEBRD( N, N, WORK( IR ), LDWRKR, S, $ WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate left bidiagonalizing vectors in WORK(IR) * (Workspace: need N*N+4*N, prefer N*N+3*N+N*NB) * CALL DORGBR( 'Q', N, N, N, WORK( IR ), LDWRKR, $ WORK( ITAUQ ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of R in WORK(IR) * (Workspace: need N*N+BDSPAC) * CALL DBDSQR( 'U', N, 0, N, 0, S, WORK( IE ), DUM, $ 1, WORK( IR ), LDWRKR, DUM, 1, $ WORK( IWORK ), INFO ) * * Multiply Q in U by left singular vectors of R in * WORK(IR), storing result in A * (Workspace: need N*N) * CALL DGEMM( 'N', 'N', M, N, N, ONE, U, LDU, $ WORK( IR ), LDWRKR, ZERO, A, LDA ) * * Copy left singular vectors of A from A to U * CALL DLACPY( 'F', M, N, A, LDA, U, LDU ) * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + N * * Compute A=Q*R, copying result to U * (Workspace: need 2*N, prefer N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', M, N, A, LDA, U, LDU ) * * Generate Q in U * (Workspace: need N+M, prefer N+M*NB) * CALL DORGQR( M, M, N, U, LDU, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Zero out below R in A * CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, A( 2, 1 ), $ LDA ) * * Bidiagonalize R in A * (Workspace: need 4*N, prefer 3*N+2*N*NB) * CALL DGEBRD( N, N, A, LDA, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply Q in U by left bidiagonalizing vectors * in A * (Workspace: need 3*N+M, prefer 3*N+M*NB) * CALL DORMBR( 'Q', 'R', 'N', M, N, N, A, LDA, $ WORK( ITAUQ ), U, LDU, WORK( IWORK ), $ LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of A in U * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', N, 0, M, 0, S, WORK( IE ), DUM, $ 1, U, LDU, DUM, 1, WORK( IWORK ), $ INFO ) * END IF * ELSE IF( WNTVO ) THEN * * Path 8 (M much larger than N, JOBU='A', JOBVT='O') * M left singular vectors to be computed in U and * N right singular vectors to be overwritten on A * IF( LWORK.GE.2*N*N+MAX( N+M, 4*N, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IU = 1 IF( LWORK.GE.WRKBL+2*LDA*N ) THEN * * WORK(IU) is LDA by N and WORK(IR) is LDA by N * LDWRKU = LDA IR = IU + LDWRKU*N LDWRKR = LDA ELSE IF( LWORK.GE.WRKBL+( LDA+N )*N ) THEN * * WORK(IU) is LDA by N and WORK(IR) is N by N * LDWRKU = LDA IR = IU + LDWRKU*N LDWRKR = N ELSE * * WORK(IU) is N by N and WORK(IR) is N by N * LDWRKU = N IR = IU + LDWRKU*N LDWRKR = N END IF ITAU = IR + LDWRKR*N IWORK = ITAU + N * * Compute A=Q*R, copying result to U * (Workspace: need 2*N*N+2*N, prefer 2*N*N+N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', M, N, A, LDA, U, LDU ) * * Generate Q in U * (Workspace: need 2*N*N+N+M, prefer 2*N*N+N+M*NB) * CALL DORGQR( M, M, N, U, LDU, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy R to WORK(IU), zeroing out below it * CALL DLACPY( 'U', N, N, A, LDA, WORK( IU ), $ LDWRKU ) CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, $ WORK( IU+1 ), LDWRKU ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize R in WORK(IU), copying result to * WORK(IR) * (Workspace: need 2*N*N+4*N, * prefer 2*N*N+3*N+2*N*NB) * CALL DGEBRD( N, N, WORK( IU ), LDWRKU, S, $ WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) CALL DLACPY( 'U', N, N, WORK( IU ), LDWRKU, $ WORK( IR ), LDWRKR ) * * Generate left bidiagonalizing vectors in WORK(IU) * (Workspace: need 2*N*N+4*N, prefer 2*N*N+3*N+N*NB) * CALL DORGBR( 'Q', N, N, N, WORK( IU ), LDWRKU, $ WORK( ITAUQ ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate right bidiagonalizing vectors in WORK(IR) * (Workspace: need 2*N*N+4*N-1, * prefer 2*N*N+3*N+(N-1)*NB) * CALL DORGBR( 'P', N, N, N, WORK( IR ), LDWRKR, $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of R in WORK(IU) and computing * right singular vectors of R in WORK(IR) * (Workspace: need 2*N*N+BDSPAC) * CALL DBDSQR( 'U', N, N, N, 0, S, WORK( IE ), $ WORK( IR ), LDWRKR, WORK( IU ), $ LDWRKU, DUM, 1, WORK( IWORK ), INFO ) * * Multiply Q in U by left singular vectors of R in * WORK(IU), storing result in A * (Workspace: need N*N) * CALL DGEMM( 'N', 'N', M, N, N, ONE, U, LDU, $ WORK( IU ), LDWRKU, ZERO, A, LDA ) * * Copy left singular vectors of A from A to U * CALL DLACPY( 'F', M, N, A, LDA, U, LDU ) * * Copy right singular vectors of R from WORK(IR) to A * CALL DLACPY( 'F', N, N, WORK( IR ), LDWRKR, A, $ LDA ) * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + N * * Compute A=Q*R, copying result to U * (Workspace: need 2*N, prefer N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', M, N, A, LDA, U, LDU ) * * Generate Q in U * (Workspace: need N+M, prefer N+M*NB) * CALL DORGQR( M, M, N, U, LDU, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Zero out below R in A * CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, A( 2, 1 ), $ LDA ) * * Bidiagonalize R in A * (Workspace: need 4*N, prefer 3*N+2*N*NB) * CALL DGEBRD( N, N, A, LDA, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply Q in U by left bidiagonalizing vectors * in A * (Workspace: need 3*N+M, prefer 3*N+M*NB) * CALL DORMBR( 'Q', 'R', 'N', M, N, N, A, LDA, $ WORK( ITAUQ ), U, LDU, WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate right bidiagonalizing vectors in A * (Workspace: need 4*N-1, prefer 3*N+(N-1)*NB) * CALL DORGBR( 'P', N, N, N, A, LDA, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of A in U and computing right * singular vectors of A in A * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', N, N, M, 0, S, WORK( IE ), A, $ LDA, U, LDU, DUM, 1, WORK( IWORK ), $ INFO ) * END IF * ELSE IF( WNTVAS ) THEN * * Path 9 (M much larger than N, JOBU='A', JOBVT='S' * or 'A') * M left singular vectors to be computed in U and * N right singular vectors to be computed in VT * IF( LWORK.GE.N*N+MAX( N+M, 4*N, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IU = 1 IF( LWORK.GE.WRKBL+LDA*N ) THEN * * WORK(IU) is LDA by N * LDWRKU = LDA ELSE * * WORK(IU) is N by N * LDWRKU = N END IF ITAU = IU + LDWRKU*N IWORK = ITAU + N * * Compute A=Q*R, copying result to U * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', M, N, A, LDA, U, LDU ) * * Generate Q in U * (Workspace: need N*N+N+M, prefer N*N+N+M*NB) * CALL DORGQR( M, M, N, U, LDU, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy R to WORK(IU), zeroing out below it * CALL DLACPY( 'U', N, N, A, LDA, WORK( IU ), $ LDWRKU ) CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, $ WORK( IU+1 ), LDWRKU ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize R in WORK(IU), copying result to VT * (Workspace: need N*N+4*N, prefer N*N+3*N+2*N*NB) * CALL DGEBRD( N, N, WORK( IU ), LDWRKU, S, $ WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) CALL DLACPY( 'U', N, N, WORK( IU ), LDWRKU, VT, $ LDVT ) * * Generate left bidiagonalizing vectors in WORK(IU) * (Workspace: need N*N+4*N, prefer N*N+3*N+N*NB) * CALL DORGBR( 'Q', N, N, N, WORK( IU ), LDWRKU, $ WORK( ITAUQ ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate right bidiagonalizing vectors in VT * (Workspace: need N*N+4*N-1, * prefer N*N+3*N+(N-1)*NB) * CALL DORGBR( 'P', N, N, N, VT, LDVT, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of R in WORK(IU) and computing * right singular vectors of R in VT * (Workspace: need N*N+BDSPAC) * CALL DBDSQR( 'U', N, N, N, 0, S, WORK( IE ), VT, $ LDVT, WORK( IU ), LDWRKU, DUM, 1, $ WORK( IWORK ), INFO ) * * Multiply Q in U by left singular vectors of R in * WORK(IU), storing result in A * (Workspace: need N*N) * CALL DGEMM( 'N', 'N', M, N, N, ONE, U, LDU, $ WORK( IU ), LDWRKU, ZERO, A, LDA ) * * Copy left singular vectors of A from A to U * CALL DLACPY( 'F', M, N, A, LDA, U, LDU ) * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + N * * Compute A=Q*R, copying result to U * (Workspace: need 2*N, prefer N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', M, N, A, LDA, U, LDU ) * * Generate Q in U * (Workspace: need N+M, prefer N+M*NB) * CALL DORGQR( M, M, N, U, LDU, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy R from A to VT, zeroing out below it * CALL DLACPY( 'U', N, N, A, LDA, VT, LDVT ) CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, VT( 2, 1 ), $ LDVT ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize R in VT * (Workspace: need 4*N, prefer 3*N+2*N*NB) * CALL DGEBRD( N, N, VT, LDVT, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply Q in U by left bidiagonalizing vectors * in VT * (Workspace: need 3*N+M, prefer 3*N+M*NB) * CALL DORMBR( 'Q', 'R', 'N', M, N, N, VT, LDVT, $ WORK( ITAUQ ), U, LDU, WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate right bidiagonalizing vectors in VT * (Workspace: need 4*N-1, prefer 3*N+(N-1)*NB) * CALL DORGBR( 'P', N, N, N, VT, LDVT, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of A in U and computing right * singular vectors of A in VT * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', N, N, M, 0, S, WORK( IE ), VT, $ LDVT, U, LDU, DUM, 1, WORK( IWORK ), $ INFO ) * END IF * END IF * END IF * ELSE * * M .LT. MNTHR * * Path 10 (M at least N, but not much larger) * Reduce to bidiagonal form without QR decomposition * IE = 1 ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize A * (Workspace: need 3*N+M, prefer 3*N+(M+N)*NB) * CALL DGEBRD( M, N, A, LDA, S, WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), LWORK-IWORK+1, $ IERR ) IF( WNTUAS ) THEN * * If left singular vectors desired in U, copy result to U * and generate left bidiagonalizing vectors in U * (Workspace: need 3*N+NCU, prefer 3*N+NCU*NB) * CALL DLACPY( 'L', M, N, A, LDA, U, LDU ) IF( WNTUS ) $ NCU = N IF( WNTUA ) $ NCU = M CALL DORGBR( 'Q', M, NCU, N, U, LDU, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) END IF IF( WNTVAS ) THEN * * If right singular vectors desired in VT, copy result to * VT and generate right bidiagonalizing vectors in VT * (Workspace: need 4*N-1, prefer 3*N+(N-1)*NB) * CALL DLACPY( 'U', N, N, A, LDA, VT, LDVT ) CALL DORGBR( 'P', N, N, N, VT, LDVT, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) END IF IF( WNTUO ) THEN * * If left singular vectors desired in A, generate left * bidiagonalizing vectors in A * (Workspace: need 4*N, prefer 3*N+N*NB) * CALL DORGBR( 'Q', M, N, N, A, LDA, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) END IF IF( WNTVO ) THEN * * If right singular vectors desired in A, generate right * bidiagonalizing vectors in A * (Workspace: need 4*N-1, prefer 3*N+(N-1)*NB) * CALL DORGBR( 'P', N, N, N, A, LDA, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) END IF IWORK = IE + N IF( WNTUAS .OR. WNTUO ) $ NRU = M IF( WNTUN ) $ NRU = 0 IF( WNTVAS .OR. WNTVO ) $ NCVT = N IF( WNTVN ) $ NCVT = 0 IF( ( .NOT.WNTUO ) .AND. ( .NOT.WNTVO ) ) THEN * * Perform bidiagonal QR iteration, if desired, computing * left singular vectors in U and computing right singular * vectors in VT * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', N, NCVT, NRU, 0, S, WORK( IE ), VT, $ LDVT, U, LDU, DUM, 1, WORK( IWORK ), INFO ) ELSE IF( ( .NOT.WNTUO ) .AND. WNTVO ) THEN * * Perform bidiagonal QR iteration, if desired, computing * left singular vectors in U and computing right singular * vectors in A * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', N, NCVT, NRU, 0, S, WORK( IE ), A, LDA, $ U, LDU, DUM, 1, WORK( IWORK ), INFO ) ELSE * * Perform bidiagonal QR iteration, if desired, computing * left singular vectors in A and computing right singular * vectors in VT * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', N, NCVT, NRU, 0, S, WORK( IE ), VT, $ LDVT, A, LDA, DUM, 1, WORK( IWORK ), INFO ) END IF * END IF * ELSE * * A has more columns than rows. If A has sufficiently more * columns than rows, first reduce using the LQ decomposition (if * sufficient workspace available) * IF( N.GE.MNTHR ) THEN * IF( WNTVN ) THEN * * Path 1t(N much larger than M, JOBVT='N') * No right singular vectors to be computed * ITAU = 1 IWORK = ITAU + M * * Compute A=L*Q * (Workspace: need 2*M, prefer M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Zero out above L * CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, A( 1, 2 ), LDA ) IE = 1 ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize L in A * (Workspace: need 4*M, prefer 3*M+2*M*NB) * CALL DGEBRD( M, M, A, LDA, S, WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), LWORK-IWORK+1, $ IERR ) IF( WNTUO .OR. WNTUAS ) THEN * * If left singular vectors desired, generate Q * (Workspace: need 4*M, prefer 3*M+M*NB) * CALL DORGBR( 'Q', M, M, M, A, LDA, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) END IF IWORK = IE + M NRU = 0 IF( WNTUO .OR. WNTUAS ) $ NRU = M * * Perform bidiagonal QR iteration, computing left singular * vectors of A in A if desired * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', M, 0, NRU, 0, S, WORK( IE ), DUM, 1, A, $ LDA, DUM, 1, WORK( IWORK ), INFO ) * * If left singular vectors desired in U, copy them there * IF( WNTUAS ) $ CALL DLACPY( 'F', M, M, A, LDA, U, LDU ) * ELSE IF( WNTVO .AND. WNTUN ) THEN * * Path 2t(N much larger than M, JOBU='N', JOBVT='O') * M right singular vectors to be overwritten on A and * no left singular vectors to be computed * IF( LWORK.GE.M*M+MAX( 4*M, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IR = 1 IF( LWORK.GE.MAX( WRKBL, LDA*N+M )+LDA*M ) THEN * * WORK(IU) is LDA by N and WORK(IR) is LDA by M * LDWRKU = LDA CHUNK = N LDWRKR = LDA ELSE IF( LWORK.GE.MAX( WRKBL, LDA*N+M )+M*M ) THEN * * WORK(IU) is LDA by N and WORK(IR) is M by M * LDWRKU = LDA CHUNK = N LDWRKR = M ELSE * * WORK(IU) is M by CHUNK and WORK(IR) is M by M * LDWRKU = M CHUNK = ( LWORK-M*M-M ) / M LDWRKR = M END IF ITAU = IR + LDWRKR*M IWORK = ITAU + M * * Compute A=L*Q * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy L to WORK(IR) and zero out above it * CALL DLACPY( 'L', M, M, A, LDA, WORK( IR ), LDWRKR ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, $ WORK( IR+LDWRKR ), LDWRKR ) * * Generate Q in A * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DORGLQ( M, N, M, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize L in WORK(IR) * (Workspace: need M*M+4*M, prefer M*M+3*M+2*M*NB) * CALL DGEBRD( M, M, WORK( IR ), LDWRKR, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Generate right vectors bidiagonalizing L * (Workspace: need M*M+4*M-1, prefer M*M+3*M+(M-1)*NB) * CALL DORGBR( 'P', M, M, M, WORK( IR ), LDWRKR, $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing right * singular vectors of L in WORK(IR) * (Workspace: need M*M+BDSPAC) * CALL DBDSQR( 'U', M, M, 0, 0, S, WORK( IE ), $ WORK( IR ), LDWRKR, DUM, 1, DUM, 1, $ WORK( IWORK ), INFO ) IU = IE + M * * Multiply right singular vectors of L in WORK(IR) by Q * in A, storing result in WORK(IU) and copying to A * (Workspace: need M*M+2*M, prefer M*M+M*N+M) * DO 30 I = 1, N, CHUNK BLK = MIN( N-I+1, CHUNK ) CALL DGEMM( 'N', 'N', M, BLK, M, ONE, WORK( IR ), $ LDWRKR, A( 1, I ), LDA, ZERO, $ WORK( IU ), LDWRKU ) CALL DLACPY( 'F', M, BLK, WORK( IU ), LDWRKU, $ A( 1, I ), LDA ) 30 CONTINUE * ELSE * * Insufficient workspace for a fast algorithm * IE = 1 ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize A * (Workspace: need 3*M+N, prefer 3*M+(M+N)*NB) * CALL DGEBRD( M, N, A, LDA, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Generate right vectors bidiagonalizing A * (Workspace: need 4*M, prefer 3*M+M*NB) * CALL DORGBR( 'P', M, N, M, A, LDA, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing right * singular vectors of A in A * (Workspace: need BDSPAC) * CALL DBDSQR( 'L', M, N, 0, 0, S, WORK( IE ), A, LDA, $ DUM, 1, DUM, 1, WORK( IWORK ), INFO ) * END IF * ELSE IF( WNTVO .AND. WNTUAS ) THEN * * Path 3t(N much larger than M, JOBU='S' or 'A', JOBVT='O') * M right singular vectors to be overwritten on A and * M left singular vectors to be computed in U * IF( LWORK.GE.M*M+MAX( 4*M, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IR = 1 IF( LWORK.GE.MAX( WRKBL, LDA*N+M )+LDA*M ) THEN * * WORK(IU) is LDA by N and WORK(IR) is LDA by M * LDWRKU = LDA CHUNK = N LDWRKR = LDA ELSE IF( LWORK.GE.MAX( WRKBL, LDA*N+M )+M*M ) THEN * * WORK(IU) is LDA by N and WORK(IR) is M by M * LDWRKU = LDA CHUNK = N LDWRKR = M ELSE * * WORK(IU) is M by CHUNK and WORK(IR) is M by M * LDWRKU = M CHUNK = ( LWORK-M*M-M ) / M LDWRKR = M END IF ITAU = IR + LDWRKR*M IWORK = ITAU + M * * Compute A=L*Q * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy L to U, zeroing about above it * CALL DLACPY( 'L', M, M, A, LDA, U, LDU ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, U( 1, 2 ), $ LDU ) * * Generate Q in A * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DORGLQ( M, N, M, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize L in U, copying result to WORK(IR) * (Workspace: need M*M+4*M, prefer M*M+3*M+2*M*NB) * CALL DGEBRD( M, M, U, LDU, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'U', M, M, U, LDU, WORK( IR ), LDWRKR ) * * Generate right vectors bidiagonalizing L in WORK(IR) * (Workspace: need M*M+4*M-1, prefer M*M+3*M+(M-1)*NB) * CALL DORGBR( 'P', M, M, M, WORK( IR ), LDWRKR, $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate left vectors bidiagonalizing L in U * (Workspace: need M*M+4*M, prefer M*M+3*M+M*NB) * CALL DORGBR( 'Q', M, M, M, U, LDU, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing left * singular vectors of L in U, and computing right * singular vectors of L in WORK(IR) * (Workspace: need M*M+BDSPAC) * CALL DBDSQR( 'U', M, M, M, 0, S, WORK( IE ), $ WORK( IR ), LDWRKR, U, LDU, DUM, 1, $ WORK( IWORK ), INFO ) IU = IE + M * * Multiply right singular vectors of L in WORK(IR) by Q * in A, storing result in WORK(IU) and copying to A * (Workspace: need M*M+2*M, prefer M*M+M*N+M)) * DO 40 I = 1, N, CHUNK BLK = MIN( N-I+1, CHUNK ) CALL DGEMM( 'N', 'N', M, BLK, M, ONE, WORK( IR ), $ LDWRKR, A( 1, I ), LDA, ZERO, $ WORK( IU ), LDWRKU ) CALL DLACPY( 'F', M, BLK, WORK( IU ), LDWRKU, $ A( 1, I ), LDA ) 40 CONTINUE * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + M * * Compute A=L*Q * (Workspace: need 2*M, prefer M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy L to U, zeroing out above it * CALL DLACPY( 'L', M, M, A, LDA, U, LDU ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, U( 1, 2 ), $ LDU ) * * Generate Q in A * (Workspace: need 2*M, prefer M+M*NB) * CALL DORGLQ( M, N, M, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize L in U * (Workspace: need 4*M, prefer 3*M+2*M*NB) * CALL DGEBRD( M, M, U, LDU, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply right vectors bidiagonalizing L by Q in A * (Workspace: need 3*M+N, prefer 3*M+N*NB) * CALL DORMBR( 'P', 'L', 'T', M, N, M, U, LDU, $ WORK( ITAUP ), A, LDA, WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate left vectors bidiagonalizing L in U * (Workspace: need 4*M, prefer 3*M+M*NB) * CALL DORGBR( 'Q', M, M, M, U, LDU, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing left * singular vectors of A in U and computing right * singular vectors of A in A * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', M, N, M, 0, S, WORK( IE ), A, LDA, $ U, LDU, DUM, 1, WORK( IWORK ), INFO ) * END IF * ELSE IF( WNTVS ) THEN * IF( WNTUN ) THEN * * Path 4t(N much larger than M, JOBU='N', JOBVT='S') * M right singular vectors to be computed in VT and * no left singular vectors to be computed * IF( LWORK.GE.M*M+MAX( 4*M, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IR = 1 IF( LWORK.GE.WRKBL+LDA*M ) THEN * * WORK(IR) is LDA by M * LDWRKR = LDA ELSE * * WORK(IR) is M by M * LDWRKR = M END IF ITAU = IR + LDWRKR*M IWORK = ITAU + M * * Compute A=L*Q * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy L to WORK(IR), zeroing out above it * CALL DLACPY( 'L', M, M, A, LDA, WORK( IR ), $ LDWRKR ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, $ WORK( IR+LDWRKR ), LDWRKR ) * * Generate Q in A * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DORGLQ( M, N, M, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize L in WORK(IR) * (Workspace: need M*M+4*M, prefer M*M+3*M+2*M*NB) * CALL DGEBRD( M, M, WORK( IR ), LDWRKR, S, $ WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate right vectors bidiagonalizing L in * WORK(IR) * (Workspace: need M*M+4*M, prefer M*M+3*M+(M-1)*NB) * CALL DORGBR( 'P', M, M, M, WORK( IR ), LDWRKR, $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing right * singular vectors of L in WORK(IR) * (Workspace: need M*M+BDSPAC) * CALL DBDSQR( 'U', M, M, 0, 0, S, WORK( IE ), $ WORK( IR ), LDWRKR, DUM, 1, DUM, 1, $ WORK( IWORK ), INFO ) * * Multiply right singular vectors of L in WORK(IR) by * Q in A, storing result in VT * (Workspace: need M*M) * CALL DGEMM( 'N', 'N', M, N, M, ONE, WORK( IR ), $ LDWRKR, A, LDA, ZERO, VT, LDVT ) * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + M * * Compute A=L*Q * (Workspace: need 2*M, prefer M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy result to VT * CALL DLACPY( 'U', M, N, A, LDA, VT, LDVT ) * * Generate Q in VT * (Workspace: need 2*M, prefer M+M*NB) * CALL DORGLQ( M, N, M, VT, LDVT, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Zero out above L in A * CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, A( 1, 2 ), $ LDA ) * * Bidiagonalize L in A * (Workspace: need 4*M, prefer 3*M+2*M*NB) * CALL DGEBRD( M, M, A, LDA, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply right vectors bidiagonalizing L by Q in VT * (Workspace: need 3*M+N, prefer 3*M+N*NB) * CALL DORMBR( 'P', 'L', 'T', M, N, M, A, LDA, $ WORK( ITAUP ), VT, LDVT, $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing right * singular vectors of A in VT * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', M, N, 0, 0, S, WORK( IE ), VT, $ LDVT, DUM, 1, DUM, 1, WORK( IWORK ), $ INFO ) * END IF * ELSE IF( WNTUO ) THEN * * Path 5t(N much larger than M, JOBU='O', JOBVT='S') * M right singular vectors to be computed in VT and * M left singular vectors to be overwritten on A * IF( LWORK.GE.2*M*M+MAX( 4*M, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IU = 1 IF( LWORK.GE.WRKBL+2*LDA*M ) THEN * * WORK(IU) is LDA by M and WORK(IR) is LDA by M * LDWRKU = LDA IR = IU + LDWRKU*M LDWRKR = LDA ELSE IF( LWORK.GE.WRKBL+( LDA+M )*M ) THEN * * WORK(IU) is LDA by M and WORK(IR) is M by M * LDWRKU = LDA IR = IU + LDWRKU*M LDWRKR = M ELSE * * WORK(IU) is M by M and WORK(IR) is M by M * LDWRKU = M IR = IU + LDWRKU*M LDWRKR = M END IF ITAU = IR + LDWRKR*M IWORK = ITAU + M * * Compute A=L*Q * (Workspace: need 2*M*M+2*M, prefer 2*M*M+M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy L to WORK(IU), zeroing out below it * CALL DLACPY( 'L', M, M, A, LDA, WORK( IU ), $ LDWRKU ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, $ WORK( IU+LDWRKU ), LDWRKU ) * * Generate Q in A * (Workspace: need 2*M*M+2*M, prefer 2*M*M+M+M*NB) * CALL DORGLQ( M, N, M, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize L in WORK(IU), copying result to * WORK(IR) * (Workspace: need 2*M*M+4*M, * prefer 2*M*M+3*M+2*M*NB) * CALL DGEBRD( M, M, WORK( IU ), LDWRKU, S, $ WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', M, M, WORK( IU ), LDWRKU, $ WORK( IR ), LDWRKR ) * * Generate right bidiagonalizing vectors in WORK(IU) * (Workspace: need 2*M*M+4*M-1, * prefer 2*M*M+3*M+(M-1)*NB) * CALL DORGBR( 'P', M, M, M, WORK( IU ), LDWRKU, $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate left bidiagonalizing vectors in WORK(IR) * (Workspace: need 2*M*M+4*M, prefer 2*M*M+3*M+M*NB) * CALL DORGBR( 'Q', M, M, M, WORK( IR ), LDWRKR, $ WORK( ITAUQ ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing left * singular vectors of L in WORK(IR) and computing * right singular vectors of L in WORK(IU) * (Workspace: need 2*M*M+BDSPAC) * CALL DBDSQR( 'U', M, M, M, 0, S, WORK( IE ), $ WORK( IU ), LDWRKU, WORK( IR ), $ LDWRKR, DUM, 1, WORK( IWORK ), INFO ) * * Multiply right singular vectors of L in WORK(IU) by * Q in A, storing result in VT * (Workspace: need M*M) * CALL DGEMM( 'N', 'N', M, N, M, ONE, WORK( IU ), $ LDWRKU, A, LDA, ZERO, VT, LDVT ) * * Copy left singular vectors of L to A * (Workspace: need M*M) * CALL DLACPY( 'F', M, M, WORK( IR ), LDWRKR, A, $ LDA ) * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + M * * Compute A=L*Q, copying result to VT * (Workspace: need 2*M, prefer M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'U', M, N, A, LDA, VT, LDVT ) * * Generate Q in VT * (Workspace: need 2*M, prefer M+M*NB) * CALL DORGLQ( M, N, M, VT, LDVT, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Zero out above L in A * CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, A( 1, 2 ), $ LDA ) * * Bidiagonalize L in A * (Workspace: need 4*M, prefer 3*M+2*M*NB) * CALL DGEBRD( M, M, A, LDA, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply right vectors bidiagonalizing L by Q in VT * (Workspace: need 3*M+N, prefer 3*M+N*NB) * CALL DORMBR( 'P', 'L', 'T', M, N, M, A, LDA, $ WORK( ITAUP ), VT, LDVT, $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Generate left bidiagonalizing vectors of L in A * (Workspace: need 4*M, prefer 3*M+M*NB) * CALL DORGBR( 'Q', M, M, M, A, LDA, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, compute left * singular vectors of A in A and compute right * singular vectors of A in VT * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', M, N, M, 0, S, WORK( IE ), VT, $ LDVT, A, LDA, DUM, 1, WORK( IWORK ), $ INFO ) * END IF * ELSE IF( WNTUAS ) THEN * * Path 6t(N much larger than M, JOBU='S' or 'A', * JOBVT='S') * M right singular vectors to be computed in VT and * M left singular vectors to be computed in U * IF( LWORK.GE.M*M+MAX( 4*M, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IU = 1 IF( LWORK.GE.WRKBL+LDA*M ) THEN * * WORK(IU) is LDA by N * LDWRKU = LDA ELSE * * WORK(IU) is LDA by M * LDWRKU = M END IF ITAU = IU + LDWRKU*M IWORK = ITAU + M * * Compute A=L*Q * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy L to WORK(IU), zeroing out above it * CALL DLACPY( 'L', M, M, A, LDA, WORK( IU ), $ LDWRKU ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, $ WORK( IU+LDWRKU ), LDWRKU ) * * Generate Q in A * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DORGLQ( M, N, M, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize L in WORK(IU), copying result to U * (Workspace: need M*M+4*M, prefer M*M+3*M+2*M*NB) * CALL DGEBRD( M, M, WORK( IU ), LDWRKU, S, $ WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', M, M, WORK( IU ), LDWRKU, U, $ LDU ) * * Generate right bidiagonalizing vectors in WORK(IU) * (Workspace: need M*M+4*M-1, * prefer M*M+3*M+(M-1)*NB) * CALL DORGBR( 'P', M, M, M, WORK( IU ), LDWRKU, $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate left bidiagonalizing vectors in U * (Workspace: need M*M+4*M, prefer M*M+3*M+M*NB) * CALL DORGBR( 'Q', M, M, M, U, LDU, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing left * singular vectors of L in U and computing right * singular vectors of L in WORK(IU) * (Workspace: need M*M+BDSPAC) * CALL DBDSQR( 'U', M, M, M, 0, S, WORK( IE ), $ WORK( IU ), LDWRKU, U, LDU, DUM, 1, $ WORK( IWORK ), INFO ) * * Multiply right singular vectors of L in WORK(IU) by * Q in A, storing result in VT * (Workspace: need M*M) * CALL DGEMM( 'N', 'N', M, N, M, ONE, WORK( IU ), $ LDWRKU, A, LDA, ZERO, VT, LDVT ) * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + M * * Compute A=L*Q, copying result to VT * (Workspace: need 2*M, prefer M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'U', M, N, A, LDA, VT, LDVT ) * * Generate Q in VT * (Workspace: need 2*M, prefer M+M*NB) * CALL DORGLQ( M, N, M, VT, LDVT, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy L to U, zeroing out above it * CALL DLACPY( 'L', M, M, A, LDA, U, LDU ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, U( 1, 2 ), $ LDU ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize L in U * (Workspace: need 4*M, prefer 3*M+2*M*NB) * CALL DGEBRD( M, M, U, LDU, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply right bidiagonalizing vectors in U by Q * in VT * (Workspace: need 3*M+N, prefer 3*M+N*NB) * CALL DORMBR( 'P', 'L', 'T', M, N, M, U, LDU, $ WORK( ITAUP ), VT, LDVT, $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Generate left bidiagonalizing vectors in U * (Workspace: need 4*M, prefer 3*M+M*NB) * CALL DORGBR( 'Q', M, M, M, U, LDU, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing left * singular vectors of A in U and computing right * singular vectors of A in VT * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', M, N, M, 0, S, WORK( IE ), VT, $ LDVT, U, LDU, DUM, 1, WORK( IWORK ), $ INFO ) * END IF * END IF * ELSE IF( WNTVA ) THEN * IF( WNTUN ) THEN * * Path 7t(N much larger than M, JOBU='N', JOBVT='A') * N right singular vectors to be computed in VT and * no left singular vectors to be computed * IF( LWORK.GE.M*M+MAX( N+M, 4*M, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IR = 1 IF( LWORK.GE.WRKBL+LDA*M ) THEN * * WORK(IR) is LDA by M * LDWRKR = LDA ELSE * * WORK(IR) is M by M * LDWRKR = M END IF ITAU = IR + LDWRKR*M IWORK = ITAU + M * * Compute A=L*Q, copying result to VT * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'U', M, N, A, LDA, VT, LDVT ) * * Copy L to WORK(IR), zeroing out above it * CALL DLACPY( 'L', M, M, A, LDA, WORK( IR ), $ LDWRKR ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, $ WORK( IR+LDWRKR ), LDWRKR ) * * Generate Q in VT * (Workspace: need M*M+M+N, prefer M*M+M+N*NB) * CALL DORGLQ( N, N, M, VT, LDVT, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize L in WORK(IR) * (Workspace: need M*M+4*M, prefer M*M+3*M+2*M*NB) * CALL DGEBRD( M, M, WORK( IR ), LDWRKR, S, $ WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate right bidiagonalizing vectors in WORK(IR) * (Workspace: need M*M+4*M-1, * prefer M*M+3*M+(M-1)*NB) * CALL DORGBR( 'P', M, M, M, WORK( IR ), LDWRKR, $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing right * singular vectors of L in WORK(IR) * (Workspace: need M*M+BDSPAC) * CALL DBDSQR( 'U', M, M, 0, 0, S, WORK( IE ), $ WORK( IR ), LDWRKR, DUM, 1, DUM, 1, $ WORK( IWORK ), INFO ) * * Multiply right singular vectors of L in WORK(IR) by * Q in VT, storing result in A * (Workspace: need M*M) * CALL DGEMM( 'N', 'N', M, N, M, ONE, WORK( IR ), $ LDWRKR, VT, LDVT, ZERO, A, LDA ) * * Copy right singular vectors of A from A to VT * CALL DLACPY( 'F', M, N, A, LDA, VT, LDVT ) * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + M * * Compute A=L*Q, copying result to VT * (Workspace: need 2*M, prefer M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'U', M, N, A, LDA, VT, LDVT ) * * Generate Q in VT * (Workspace: need M+N, prefer M+N*NB) * CALL DORGLQ( N, N, M, VT, LDVT, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Zero out above L in A * CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, A( 1, 2 ), $ LDA ) * * Bidiagonalize L in A * (Workspace: need 4*M, prefer 3*M+2*M*NB) * CALL DGEBRD( M, M, A, LDA, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply right bidiagonalizing vectors in A by Q * in VT * (Workspace: need 3*M+N, prefer 3*M+N*NB) * CALL DORMBR( 'P', 'L', 'T', M, N, M, A, LDA, $ WORK( ITAUP ), VT, LDVT, $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing right * singular vectors of A in VT * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', M, N, 0, 0, S, WORK( IE ), VT, $ LDVT, DUM, 1, DUM, 1, WORK( IWORK ), $ INFO ) * END IF * ELSE IF( WNTUO ) THEN * * Path 8t(N much larger than M, JOBU='O', JOBVT='A') * N right singular vectors to be computed in VT and * M left singular vectors to be overwritten on A * IF( LWORK.GE.2*M*M+MAX( N+M, 4*M, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IU = 1 IF( LWORK.GE.WRKBL+2*LDA*M ) THEN * * WORK(IU) is LDA by M and WORK(IR) is LDA by M * LDWRKU = LDA IR = IU + LDWRKU*M LDWRKR = LDA ELSE IF( LWORK.GE.WRKBL+( LDA+M )*M ) THEN * * WORK(IU) is LDA by M and WORK(IR) is M by M * LDWRKU = LDA IR = IU + LDWRKU*M LDWRKR = M ELSE * * WORK(IU) is M by M and WORK(IR) is M by M * LDWRKU = M IR = IU + LDWRKU*M LDWRKR = M END IF ITAU = IR + LDWRKR*M IWORK = ITAU + M * * Compute A=L*Q, copying result to VT * (Workspace: need 2*M*M+2*M, prefer 2*M*M+M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'U', M, N, A, LDA, VT, LDVT ) * * Generate Q in VT * (Workspace: need 2*M*M+M+N, prefer 2*M*M+M+N*NB) * CALL DORGLQ( N, N, M, VT, LDVT, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy L to WORK(IU), zeroing out above it * CALL DLACPY( 'L', M, M, A, LDA, WORK( IU ), $ LDWRKU ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, $ WORK( IU+LDWRKU ), LDWRKU ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize L in WORK(IU), copying result to * WORK(IR) * (Workspace: need 2*M*M+4*M, * prefer 2*M*M+3*M+2*M*NB) * CALL DGEBRD( M, M, WORK( IU ), LDWRKU, S, $ WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', M, M, WORK( IU ), LDWRKU, $ WORK( IR ), LDWRKR ) * * Generate right bidiagonalizing vectors in WORK(IU) * (Workspace: need 2*M*M+4*M-1, * prefer 2*M*M+3*M+(M-1)*NB) * CALL DORGBR( 'P', M, M, M, WORK( IU ), LDWRKU, $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate left bidiagonalizing vectors in WORK(IR) * (Workspace: need 2*M*M+4*M, prefer 2*M*M+3*M+M*NB) * CALL DORGBR( 'Q', M, M, M, WORK( IR ), LDWRKR, $ WORK( ITAUQ ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing left * singular vectors of L in WORK(IR) and computing * right singular vectors of L in WORK(IU) * (Workspace: need 2*M*M+BDSPAC) * CALL DBDSQR( 'U', M, M, M, 0, S, WORK( IE ), $ WORK( IU ), LDWRKU, WORK( IR ), $ LDWRKR, DUM, 1, WORK( IWORK ), INFO ) * * Multiply right singular vectors of L in WORK(IU) by * Q in VT, storing result in A * (Workspace: need M*M) * CALL DGEMM( 'N', 'N', M, N, M, ONE, WORK( IU ), $ LDWRKU, VT, LDVT, ZERO, A, LDA ) * * Copy right singular vectors of A from A to VT * CALL DLACPY( 'F', M, N, A, LDA, VT, LDVT ) * * Copy left singular vectors of A from WORK(IR) to A * CALL DLACPY( 'F', M, M, WORK( IR ), LDWRKR, A, $ LDA ) * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + M * * Compute A=L*Q, copying result to VT * (Workspace: need 2*M, prefer M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'U', M, N, A, LDA, VT, LDVT ) * * Generate Q in VT * (Workspace: need M+N, prefer M+N*NB) * CALL DORGLQ( N, N, M, VT, LDVT, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Zero out above L in A * CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, A( 1, 2 ), $ LDA ) * * Bidiagonalize L in A * (Workspace: need 4*M, prefer 3*M+2*M*NB) * CALL DGEBRD( M, M, A, LDA, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply right bidiagonalizing vectors in A by Q * in VT * (Workspace: need 3*M+N, prefer 3*M+N*NB) * CALL DORMBR( 'P', 'L', 'T', M, N, M, A, LDA, $ WORK( ITAUP ), VT, LDVT, $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Generate left bidiagonalizing vectors in A * (Workspace: need 4*M, prefer 3*M+M*NB) * CALL DORGBR( 'Q', M, M, M, A, LDA, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing left * singular vectors of A in A and computing right * singular vectors of A in VT * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', M, N, M, 0, S, WORK( IE ), VT, $ LDVT, A, LDA, DUM, 1, WORK( IWORK ), $ INFO ) * END IF * ELSE IF( WNTUAS ) THEN * * Path 9t(N much larger than M, JOBU='S' or 'A', * JOBVT='A') * N right singular vectors to be computed in VT and * M left singular vectors to be computed in U * IF( LWORK.GE.M*M+MAX( N+M, 4*M, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IU = 1 IF( LWORK.GE.WRKBL+LDA*M ) THEN * * WORK(IU) is LDA by M * LDWRKU = LDA ELSE * * WORK(IU) is M by M * LDWRKU = M END IF ITAU = IU + LDWRKU*M IWORK = ITAU + M * * Compute A=L*Q, copying result to VT * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'U', M, N, A, LDA, VT, LDVT ) * * Generate Q in VT * (Workspace: need M*M+M+N, prefer M*M+M+N*NB) * CALL DORGLQ( N, N, M, VT, LDVT, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy L to WORK(IU), zeroing out above it * CALL DLACPY( 'L', M, M, A, LDA, WORK( IU ), $ LDWRKU ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, $ WORK( IU+LDWRKU ), LDWRKU ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize L in WORK(IU), copying result to U * (Workspace: need M*M+4*M, prefer M*M+3*M+2*M*NB) * CALL DGEBRD( M, M, WORK( IU ), LDWRKU, S, $ WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', M, M, WORK( IU ), LDWRKU, U, $ LDU ) * * Generate right bidiagonalizing vectors in WORK(IU) * (Workspace: need M*M+4*M, prefer M*M+3*M+(M-1)*NB) * CALL DORGBR( 'P', M, M, M, WORK( IU ), LDWRKU, $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate left bidiagonalizing vectors in U * (Workspace: need M*M+4*M, prefer M*M+3*M+M*NB) * CALL DORGBR( 'Q', M, M, M, U, LDU, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing left * singular vectors of L in U and computing right * singular vectors of L in WORK(IU) * (Workspace: need M*M+BDSPAC) * CALL DBDSQR( 'U', M, M, M, 0, S, WORK( IE ), $ WORK( IU ), LDWRKU, U, LDU, DUM, 1, $ WORK( IWORK ), INFO ) * * Multiply right singular vectors of L in WORK(IU) by * Q in VT, storing result in A * (Workspace: need M*M) * CALL DGEMM( 'N', 'N', M, N, M, ONE, WORK( IU ), $ LDWRKU, VT, LDVT, ZERO, A, LDA ) * * Copy right singular vectors of A from A to VT * CALL DLACPY( 'F', M, N, A, LDA, VT, LDVT ) * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + M * * Compute A=L*Q, copying result to VT * (Workspace: need 2*M, prefer M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'U', M, N, A, LDA, VT, LDVT ) * * Generate Q in VT * (Workspace: need M+N, prefer M+N*NB) * CALL DORGLQ( N, N, M, VT, LDVT, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy L to U, zeroing out above it * CALL DLACPY( 'L', M, M, A, LDA, U, LDU ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, U( 1, 2 ), $ LDU ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize L in U * (Workspace: need 4*M, prefer 3*M+2*M*NB) * CALL DGEBRD( M, M, U, LDU, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply right bidiagonalizing vectors in U by Q * in VT * (Workspace: need 3*M+N, prefer 3*M+N*NB) * CALL DORMBR( 'P', 'L', 'T', M, N, M, U, LDU, $ WORK( ITAUP ), VT, LDVT, $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Generate left bidiagonalizing vectors in U * (Workspace: need 4*M, prefer 3*M+M*NB) * CALL DORGBR( 'Q', M, M, M, U, LDU, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing left * singular vectors of A in U and computing right * singular vectors of A in VT * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', M, N, M, 0, S, WORK( IE ), VT, $ LDVT, U, LDU, DUM, 1, WORK( IWORK ), $ INFO ) * END IF * END IF * END IF * ELSE * * N .LT. MNTHR * * Path 10t(N greater than M, but not much larger) * Reduce to bidiagonal form without LQ decomposition * IE = 1 ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize A * (Workspace: need 3*M+N, prefer 3*M+(M+N)*NB) * CALL DGEBRD( M, N, A, LDA, S, WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), LWORK-IWORK+1, $ IERR ) IF( WNTUAS ) THEN * * If left singular vectors desired in U, copy result to U * and generate left bidiagonalizing vectors in U * (Workspace: need 4*M-1, prefer 3*M+(M-1)*NB) * CALL DLACPY( 'L', M, M, A, LDA, U, LDU ) CALL DORGBR( 'Q', M, M, N, U, LDU, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) END IF IF( WNTVAS ) THEN * * If right singular vectors desired in VT, copy result to * VT and generate right bidiagonalizing vectors in VT * (Workspace: need 3*M+NRVT, prefer 3*M+NRVT*NB) * CALL DLACPY( 'U', M, N, A, LDA, VT, LDVT ) IF( WNTVA ) $ NRVT = N IF( WNTVS ) $ NRVT = M CALL DORGBR( 'P', NRVT, N, M, VT, LDVT, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) END IF IF( WNTUO ) THEN * * If left singular vectors desired in A, generate left * bidiagonalizing vectors in A * (Workspace: need 4*M-1, prefer 3*M+(M-1)*NB) * CALL DORGBR( 'Q', M, M, N, A, LDA, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) END IF IF( WNTVO ) THEN * * If right singular vectors desired in A, generate right * bidiagonalizing vectors in A * (Workspace: need 4*M, prefer 3*M+M*NB) * CALL DORGBR( 'P', M, N, M, A, LDA, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) END IF IWORK = IE + M IF( WNTUAS .OR. WNTUO ) $ NRU = M IF( WNTUN ) $ NRU = 0 IF( WNTVAS .OR. WNTVO ) $ NCVT = N IF( WNTVN ) $ NCVT = 0 IF( ( .NOT.WNTUO ) .AND. ( .NOT.WNTVO ) ) THEN * * Perform bidiagonal QR iteration, if desired, computing * left singular vectors in U and computing right singular * vectors in VT * (Workspace: need BDSPAC) * CALL DBDSQR( 'L', M, NCVT, NRU, 0, S, WORK( IE ), VT, $ LDVT, U, LDU, DUM, 1, WORK( IWORK ), INFO ) ELSE IF( ( .NOT.WNTUO ) .AND. WNTVO ) THEN * * Perform bidiagonal QR iteration, if desired, computing * left singular vectors in U and computing right singular * vectors in A * (Workspace: need BDSPAC) * CALL DBDSQR( 'L', M, NCVT, NRU, 0, S, WORK( IE ), A, LDA, $ U, LDU, DUM, 1, WORK( IWORK ), INFO ) ELSE * * Perform bidiagonal QR iteration, if desired, computing * left singular vectors in A and computing right singular * vectors in VT * (Workspace: need BDSPAC) * CALL DBDSQR( 'L', M, NCVT, NRU, 0, S, WORK( IE ), VT, $ LDVT, A, LDA, DUM, 1, WORK( IWORK ), INFO ) END IF * END IF * END IF * * If DBDSQR failed to converge, copy unconverged superdiagonals * to WORK( 2:MINMN ) * IF( INFO.NE.0 ) THEN IF( IE.GT.2 ) THEN DO 50 I = 1, MINMN - 1 WORK( I+1 ) = WORK( I+IE-1 ) 50 CONTINUE END IF IF( IE.LT.2 ) THEN DO 60 I = MINMN - 1, 1, -1 WORK( I+1 ) = WORK( I+IE-1 ) 60 CONTINUE END IF END IF * * Undo scaling if necessary * IF( ISCL.EQ.1 ) THEN IF( ANRM.GT.BIGNUM ) $ CALL DLASCL( 'G', 0, 0, BIGNUM, ANRM, MINMN, 1, S, MINMN, $ IERR ) IF( INFO.NE.0 .AND. ANRM.GT.BIGNUM ) $ CALL DLASCL( 'G', 0, 0, BIGNUM, ANRM, MINMN-1, 1, WORK( 2 ), $ MINMN, IERR ) IF( ANRM.LT.SMLNUM ) $ CALL DLASCL( 'G', 0, 0, SMLNUM, ANRM, MINMN, 1, S, MINMN, $ IERR ) IF( INFO.NE.0 .AND. ANRM.LT.SMLNUM ) $ CALL DLASCL( 'G', 0, 0, SMLNUM, ANRM, MINMN-1, 1, WORK( 2 ), $ MINMN, IERR ) END IF * * Return optimal workspace in WORK(1) * WORK( 1 ) = MAXWRK * RETURN * * End of DGESVD * END SUBROUTINE DGESVX( FACT, TRANS, N, NRHS, A, LDA, AF, LDAF, IPIV, $ EQUED, R, C, B, LDB, X, LDX, RCOND, FERR, BERR, $ WORK, IWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER EQUED, FACT, TRANS INTEGER INFO, LDA, LDAF, LDB, LDX, N, NRHS DOUBLE PRECISION RCOND * .. * .. Array Arguments .. INTEGER IPIV( * ), IWORK( * ) DOUBLE PRECISION A( LDA, * ), AF( LDAF, * ), B( LDB, * ), $ BERR( * ), C( * ), FERR( * ), R( * ), $ WORK( * ), X( LDX, * ) * .. * * Purpose * ======= * * DGESVX uses the LU factorization to compute the solution to a real * system of linear equations * A * X = B, * where A is an N-by-N matrix and X and B are N-by-NRHS matrices. * * Error bounds on the solution and a condition estimate are also * provided. * * Description * =========== * * The following steps are performed: * * 1. If FACT = 'E', real scaling factors are computed to equilibrate * the system: * TRANS = 'N': diag(R)*A*diag(C) *inv(diag(C))*X = diag(R)*B * TRANS = 'T': (diag(R)*A*diag(C))**T *inv(diag(R))*X = diag(C)*B * TRANS = 'C': (diag(R)*A*diag(C))**H *inv(diag(R))*X = diag(C)*B * Whether or not the system will be equilibrated depends on the * scaling of the matrix A, but if equilibration is used, A is * overwritten by diag(R)*A*diag(C) and B by diag(R)*B (if TRANS='N') * or diag(C)*B (if TRANS = 'T' or 'C'). * * 2. If FACT = 'N' or 'E', the LU decomposition is used to factor the * matrix A (after equilibration if FACT = 'E') as * A = P * L * U, * where P is a permutation matrix, L is a unit lower triangular * matrix, and U is upper triangular. * * 3. If some U(i,i)=0, so that U is exactly singular, then the routine * returns with INFO = i. Otherwise, the factored form of A is used * to estimate the condition number of the matrix A. If the * reciprocal of the condition number is less than machine precision, * INFO = N+1 is returned as a warning, but the routine still goes on * to solve for X and compute error bounds as described below. * * 4. The system of equations is solved for X using the factored form * of A. * * 5. Iterative refinement is applied to improve the computed solution * matrix and calculate error bounds and backward error estimates * for it. * * 6. If equilibration was used, the matrix X is premultiplied by * diag(C) (if TRANS = 'N') or diag(R) (if TRANS = 'T' or 'C') so * that it solves the original system before equilibration. * * Arguments * ========= * * FACT (input) CHARACTER*1 * Specifies whether or not the factored form of the matrix A is * supplied on entry, and if not, whether the matrix A should be * equilibrated before it is factored. * = 'F': On entry, AF and IPIV contain the factored form of A. * If EQUED is not 'N', the matrix A has been * equilibrated with scaling factors given by R and C. * A, AF, and IPIV are not modified. * = 'N': The matrix A will be copied to AF and factored. * = 'E': The matrix A will be equilibrated if necessary, then * copied to AF and factored. * * TRANS (input) CHARACTER*1 * Specifies the form of the system of equations: * = 'N': A * X = B (No transpose) * = 'T': A**T * X = B (Transpose) * = 'C': A**H * X = B (Transpose) * * N (input) INTEGER * The number of linear equations, i.e., the order of the * matrix A. N >= 0. * * NRHS (input) INTEGER * The number of right hand sides, i.e., the number of columns * of the matrices B and X. NRHS >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the N-by-N matrix A. If FACT = 'F' and EQUED is * not 'N', then A must have been equilibrated by the scaling * factors in R and/or C. A is not modified if FACT = 'F' or * 'N', or if FACT = 'E' and EQUED = 'N' on exit. * * On exit, if EQUED .ne. 'N', A is scaled as follows: * EQUED = 'R': A := diag(R) * A * EQUED = 'C': A := A * diag(C) * EQUED = 'B': A := diag(R) * A * diag(C). * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * AF (input or output) DOUBLE PRECISION array, dimension (LDAF,N) * If FACT = 'F', then AF is an input argument and on entry * contains the factors L and U from the factorization * A = P*L*U as computed by DGETRF. If EQUED .ne. 'N', then * AF is the factored form of the equilibrated matrix A. * * If FACT = 'N', then AF is an output argument and on exit * returns the factors L and U from the factorization A = P*L*U * of the original matrix A. * * If FACT = 'E', then AF is an output argument and on exit * returns the factors L and U from the factorization A = P*L*U * of the equilibrated matrix A (see the description of A for * the form of the equilibrated matrix). * * LDAF (input) INTEGER * The leading dimension of the array AF. LDAF >= max(1,N). * * IPIV (input or output) INTEGER array, dimension (N) * If FACT = 'F', then IPIV is an input argument and on entry * contains the pivot indices from the factorization A = P*L*U * as computed by DGETRF; row i of the matrix was interchanged * with row IPIV(i). * * If FACT = 'N', then IPIV is an output argument and on exit * contains the pivot indices from the factorization A = P*L*U * of the original matrix A. * * If FACT = 'E', then IPIV is an output argument and on exit * contains the pivot indices from the factorization A = P*L*U * of the equilibrated matrix A. * * EQUED (input or output) CHARACTER*1 * Specifies the form of equilibration that was done. * = 'N': No equilibration (always true if FACT = 'N'). * = 'R': Row equilibration, i.e., A has been premultiplied by * diag(R). * = 'C': Column equilibration, i.e., A has been postmultiplied * by diag(C). * = 'B': Both row and column equilibration, i.e., A has been * replaced by diag(R) * A * diag(C). * EQUED is an input argument if FACT = 'F'; otherwise, it is an * output argument. * * R (input or output) DOUBLE PRECISION array, dimension (N) * The row scale factors for A. If EQUED = 'R' or 'B', A is * multiplied on the left by diag(R); if EQUED = 'N' or 'C', R * is not accessed. R is an input argument if FACT = 'F'; * otherwise, R is an output argument. If FACT = 'F' and * EQUED = 'R' or 'B', each element of R must be positive. * * C (input or output) DOUBLE PRECISION array, dimension (N) * The column scale factors for A. If EQUED = 'C' or 'B', A is * multiplied on the right by diag(C); if EQUED = 'N' or 'R', C * is not accessed. C is an input argument if FACT = 'F'; * otherwise, C is an output argument. If FACT = 'F' and * EQUED = 'C' or 'B', each element of C must be positive. * * B (input/output) DOUBLE PRECISION array, dimension (LDB,NRHS) * On entry, the N-by-NRHS right hand side matrix B. * On exit, * if EQUED = 'N', B is not modified; * if TRANS = 'N' and EQUED = 'R' or 'B', B is overwritten by * diag(R)*B; * if TRANS = 'T' or 'C' and EQUED = 'C' or 'B', B is * overwritten by diag(C)*B. * * LDB (input) INTEGER * The leading dimension of the array B. LDB >= max(1,N). * * X (output) DOUBLE PRECISION array, dimension (LDX,NRHS) * If INFO = 0 or INFO = N+1, the N-by-NRHS solution matrix X * to the original system of equations. Note that A and B are * modified on exit if EQUED .ne. 'N', and the solution to the * equilibrated system is inv(diag(C))*X if TRANS = 'N' and * EQUED = 'C' or 'B', or inv(diag(R))*X if TRANS = 'T' or 'C' * and EQUED = 'R' or 'B'. * * LDX (input) INTEGER * The leading dimension of the array X. LDX >= max(1,N). * * RCOND (output) DOUBLE PRECISION * The estimate of the reciprocal condition number of the matrix * A after equilibration (if done). If RCOND is less than the * machine precision (in particular, if RCOND = 0), the matrix * is singular to working precision. This condition is * indicated by a return code of INFO > 0. * * FERR (output) DOUBLE PRECISION array, dimension (NRHS) * The estimated forward error bound for each solution vector * X(j) (the j-th column of the solution matrix X). * If XTRUE is the true solution corresponding to X(j), FERR(j) * is an estimated upper bound for the magnitude of the largest * element in (X(j) - XTRUE) divided by the magnitude of the * largest element in X(j). The estimate is as reliable as * the estimate for RCOND, and is almost always a slight * overestimate of the true error. * * BERR (output) DOUBLE PRECISION array, dimension (NRHS) * The componentwise relative backward error of each solution * vector X(j) (i.e., the smallest relative change in * any element of A or B that makes X(j) an exact solution). * * WORK (workspace/output) DOUBLE PRECISION array, dimension (4*N) * On exit, WORK(1) contains the reciprocal pivot growth * factor norm(A)/norm(U). The "max absolute element" norm is * used. If WORK(1) is much less than 1, then the stability * of the LU factorization of the (equilibrated) matrix A * could be poor. This also means that the solution X, condition * estimator RCOND, and forward error bound FERR could be * unreliable. If factorization fails with 0 0: if INFO = i, and i is * <= N: U(i,i) is exactly zero. The factorization has * been completed, but the factor U is exactly * singular, so the solution and error bounds * could not be computed. RCOND = 0 is returned. * = N+1: U is nonsingular, but RCOND is less than machine * precision, meaning that the matrix is singular * to working precision. Nevertheless, the * solution and error bounds are computed because * there are a number of situations where the * computed solution can be more accurate than the * value of RCOND would suggest. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL COLEQU, EQUIL, NOFACT, NOTRAN, ROWEQU CHARACTER NORM INTEGER I, INFEQU, J DOUBLE PRECISION AMAX, ANORM, BIGNUM, COLCND, RCMAX, RCMIN, $ ROWCND, RPVGRW, SMLNUM * .. * .. External Functions .. LOGICAL LSAME DOUBLE PRECISION DLAMCH, DLANGE, DLANTR EXTERNAL LSAME, DLAMCH, DLANGE, DLANTR * .. * .. External Subroutines .. EXTERNAL DGECON, DGEEQU, DGERFS, DGETRF, DGETRS, DLACPY, $ DLAQGE, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN * .. * .. Executable Statements .. * INFO = 0 NOFACT = LSAME( FACT, 'N' ) EQUIL = LSAME( FACT, 'E' ) NOTRAN = LSAME( TRANS, 'N' ) IF( NOFACT .OR. EQUIL ) THEN EQUED = 'N' ROWEQU = .FALSE. COLEQU = .FALSE. ELSE ROWEQU = LSAME( EQUED, 'R' ) .OR. LSAME( EQUED, 'B' ) COLEQU = LSAME( EQUED, 'C' ) .OR. LSAME( EQUED, 'B' ) SMLNUM = DLAMCH( 'Safe minimum' ) BIGNUM = ONE / SMLNUM END IF * * Test the input parameters. * IF( .NOT.NOFACT .AND. .NOT.EQUIL .AND. .NOT.LSAME( FACT, 'F' ) ) $ THEN INFO = -1 ELSE IF( .NOT.NOTRAN .AND. .NOT.LSAME( TRANS, 'T' ) .AND. .NOT. $ LSAME( TRANS, 'C' ) ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( NRHS.LT.0 ) THEN INFO = -4 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -6 ELSE IF( LDAF.LT.MAX( 1, N ) ) THEN INFO = -8 ELSE IF( LSAME( FACT, 'F' ) .AND. .NOT. $ ( ROWEQU .OR. COLEQU .OR. LSAME( EQUED, 'N' ) ) ) THEN INFO = -10 ELSE IF( ROWEQU ) THEN RCMIN = BIGNUM RCMAX = ZERO DO 10 J = 1, N RCMIN = MIN( RCMIN, R( J ) ) RCMAX = MAX( RCMAX, R( J ) ) 10 CONTINUE IF( RCMIN.LE.ZERO ) THEN INFO = -11 ELSE IF( N.GT.0 ) THEN ROWCND = MAX( RCMIN, SMLNUM ) / MIN( RCMAX, BIGNUM ) ELSE ROWCND = ONE END IF END IF IF( COLEQU .AND. INFO.EQ.0 ) THEN RCMIN = BIGNUM RCMAX = ZERO DO 20 J = 1, N RCMIN = MIN( RCMIN, C( J ) ) RCMAX = MAX( RCMAX, C( J ) ) 20 CONTINUE IF( RCMIN.LE.ZERO ) THEN INFO = -12 ELSE IF( N.GT.0 ) THEN COLCND = MAX( RCMIN, SMLNUM ) / MIN( RCMAX, BIGNUM ) ELSE COLCND = ONE END IF END IF IF( INFO.EQ.0 ) THEN IF( LDB.LT.MAX( 1, N ) ) THEN INFO = -14 ELSE IF( LDX.LT.MAX( 1, N ) ) THEN INFO = -16 END IF END IF END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGESVX', -INFO ) RETURN END IF * IF( EQUIL ) THEN * * Compute row and column scalings to equilibrate the matrix A. * CALL DGEEQU( N, N, A, LDA, R, C, ROWCND, COLCND, AMAX, INFEQU ) IF( INFEQU.EQ.0 ) THEN * * Equilibrate the matrix. * CALL DLAQGE( N, N, A, LDA, R, C, ROWCND, COLCND, AMAX, $ EQUED ) ROWEQU = LSAME( EQUED, 'R' ) .OR. LSAME( EQUED, 'B' ) COLEQU = LSAME( EQUED, 'C' ) .OR. LSAME( EQUED, 'B' ) END IF END IF * * Scale the right hand side. * IF( NOTRAN ) THEN IF( ROWEQU ) THEN DO 40 J = 1, NRHS DO 30 I = 1, N B( I, J ) = R( I )*B( I, J ) 30 CONTINUE 40 CONTINUE END IF ELSE IF( COLEQU ) THEN DO 60 J = 1, NRHS DO 50 I = 1, N B( I, J ) = C( I )*B( I, J ) 50 CONTINUE 60 CONTINUE END IF * IF( NOFACT .OR. EQUIL ) THEN * * Compute the LU factorization of A. * CALL DLACPY( 'Full', N, N, A, LDA, AF, LDAF ) CALL DGETRF( N, N, AF, LDAF, IPIV, INFO ) * * Return if INFO is non-zero. * IF( INFO.NE.0 ) THEN IF( INFO.GT.0 ) THEN * * Compute the reciprocal pivot growth factor of the * leading rank-deficient INFO columns of A. * RPVGRW = DLANTR( 'M', 'U', 'N', INFO, INFO, AF, LDAF, $ WORK ) IF( RPVGRW.EQ.ZERO ) THEN RPVGRW = ONE ELSE RPVGRW = DLANGE( 'M', N, INFO, A, LDA, WORK ) / RPVGRW END IF WORK( 1 ) = RPVGRW RCOND = ZERO END IF RETURN END IF END IF * * Compute the norm of the matrix A and the * reciprocal pivot growth factor RPVGRW. * IF( NOTRAN ) THEN NORM = '1' ELSE NORM = 'I' END IF ANORM = DLANGE( NORM, N, N, A, LDA, WORK ) RPVGRW = DLANTR( 'M', 'U', 'N', N, N, AF, LDAF, WORK ) IF( RPVGRW.EQ.ZERO ) THEN RPVGRW = ONE ELSE RPVGRW = DLANGE( 'M', N, N, A, LDA, WORK ) / RPVGRW END IF * * Compute the reciprocal of the condition number of A. * CALL DGECON( NORM, N, AF, LDAF, ANORM, RCOND, WORK, IWORK, INFO ) * * Set INFO = N+1 if the matrix is singular to working precision. * IF( RCOND.LT.DLAMCH( 'Epsilon' ) ) $ INFO = N + 1 * * Compute the solution matrix X. * CALL DLACPY( 'Full', N, NRHS, B, LDB, X, LDX ) CALL DGETRS( TRANS, N, NRHS, AF, LDAF, IPIV, X, LDX, INFO ) * * Use iterative refinement to improve the computed solution and * compute error bounds and backward error estimates for it. * CALL DGERFS( TRANS, N, NRHS, A, LDA, AF, LDAF, IPIV, B, LDB, X, $ LDX, FERR, BERR, WORK, IWORK, INFO ) * * Transform the solution matrix X to a solution of the original * system. * IF( NOTRAN ) THEN IF( COLEQU ) THEN DO 80 J = 1, NRHS DO 70 I = 1, N X( I, J ) = C( I )*X( I, J ) 70 CONTINUE 80 CONTINUE DO 90 J = 1, NRHS FERR( J ) = FERR( J ) / COLCND 90 CONTINUE END IF ELSE IF( ROWEQU ) THEN DO 110 J = 1, NRHS DO 100 I = 1, N X( I, J ) = R( I )*X( I, J ) 100 CONTINUE 110 CONTINUE DO 120 J = 1, NRHS FERR( J ) = FERR( J ) / ROWCND 120 CONTINUE END IF * WORK( 1 ) = RPVGRW RETURN * * End of DGESVX * END SUBROUTINE DGGES( JOBVSL, JOBVSR, SORT, DELCTG, N, A, LDA, B, LDB, $ SDIM, ALPHAR, ALPHAI, BETA, VSL, LDVSL, VSR, $ LDVSR, WORK, LWORK, BWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBVSL, JOBVSR, SORT INTEGER INFO, LDA, LDB, LDVSL, LDVSR, LWORK, N, SDIM * .. * .. Array Arguments .. LOGICAL BWORK( * ) DOUBLE PRECISION A( LDA, * ), ALPHAI( * ), ALPHAR( * ), $ B( LDB, * ), BETA( * ), VSL( LDVSL, * ), $ VSR( LDVSR, * ), WORK( * ) * .. * .. Function Arguments .. LOGICAL DELCTG EXTERNAL DELCTG * .. * * Purpose * ======= * * DGGES computes for a pair of N-by-N real nonsymmetric matrices (A,B), * the generalized eigenvalues, the generalized real Schur form (S,T), * optionally, the left and/or right matrices of Schur vectors (VSL and * VSR). This gives the generalized Schur factorization * * (A,B) = ( (VSL)*S*(VSR)**T, (VSL)*T*(VSR)**T ) * * Optionally, it also orders the eigenvalues so that a selected cluster * of eigenvalues appears in the leading diagonal blocks of the upper * quasi-triangular matrix S and the upper triangular matrix T.The * leading columns of VSL and VSR then form an orthonormal basis for the * corresponding left and right eigenspaces (deflating subspaces). * * (If only the generalized eigenvalues are needed, use the driver * DGGEV instead, which is faster.) * * A generalized eigenvalue for a pair of matrices (A,B) is a scalar w * or a ratio alpha/beta = w, such that A - w*B is singular. It is * usually represented as the pair (alpha,beta), as there is a * reasonable interpretation for beta=0 or both being zero. * * A pair of matrices (S,T) is in generalized real Schur form if T is * upper triangular with non-negative diagonal and S is block upper * triangular with 1-by-1 and 2-by-2 blocks. 1-by-1 blocks correspond * to real generalized eigenvalues, while 2-by-2 blocks of S will be * "standardized" by making the corresponding elements of T have the * form: * [ a 0 ] * [ 0 b ] * * and the pair of corresponding 2-by-2 blocks in S and T will have a * complex conjugate pair of generalized eigenvalues. * * * Arguments * ========= * * JOBVSL (input) CHARACTER*1 * = 'N': do not compute the left Schur vectors; * = 'V': compute the left Schur vectors. * * JOBVSR (input) CHARACTER*1 * = 'N': do not compute the right Schur vectors; * = 'V': compute the right Schur vectors. * * SORT (input) CHARACTER*1 * Specifies whether or not to order the eigenvalues on the * diagonal of the generalized Schur form. * = 'N': Eigenvalues are not ordered; * = 'S': Eigenvalues are ordered (see DELZTG); * * DELZTG (input) LOGICAL FUNCTION of three DOUBLE PRECISION arguments * DELZTG must be declared EXTERNAL in the calling subroutine. * If SORT = 'N', DELZTG is not referenced. * If SORT = 'S', DELZTG is used to select eigenvalues to sort * to the top left of the Schur form. * An eigenvalue (ALPHAR(j)+ALPHAI(j))/BETA(j) is selected if * DELZTG(ALPHAR(j),ALPHAI(j),BETA(j)) is true; i.e. if either * one of a complex conjugate pair of eigenvalues is selected, * then both complex eigenvalues are selected. * * Note that in the ill-conditioned case, a selected complex * eigenvalue may no longer satisfy DELZTG(ALPHAR(j),ALPHAI(j), * BETA(j)) = .TRUE. after ordering. INFO is to be set to N+2 * in this case. * * N (input) INTEGER * The order of the matrices A, B, VSL, and VSR. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA, N) * On entry, the first of the pair of matrices. * On exit, A has been overwritten by its generalized Schur * form S. * * LDA (input) INTEGER * The leading dimension of A. LDA >= max(1,N). * * B (input/output) DOUBLE PRECISION array, dimension (LDB, N) * On entry, the second of the pair of matrices. * On exit, B has been overwritten by its generalized Schur * form T. * * LDB (input) INTEGER * The leading dimension of B. LDB >= max(1,N). * * SDIM (output) INTEGER * If SORT = 'N', SDIM = 0. * If SORT = 'S', SDIM = number of eigenvalues (after sorting) * for which DELZTG is true. (Complex conjugate pairs for which * DELZTG is true for either eigenvalue count as 2.) * * ALPHAR (output) DOUBLE PRECISION array, dimension (N) * ALPHAI (output) DOUBLE PRECISION array, dimension (N) * BETA (output) DOUBLE PRECISION array, dimension (N) * On exit, (ALPHAR(j) + ALPHAI(j)*i)/BETA(j), j=1,...,N, will * be the generalized eigenvalues. ALPHAR(j) + ALPHAI(j)*i, * and BETA(j),j=1,...,N are the diagonals of the complex Schur * form (S,T) that would result if the 2-by-2 diagonal blocks of * the real Schur form of (A,B) were further reduced to * triangular form using 2-by-2 complex unitary transformations. * If ALPHAI(j) is zero, then the j-th eigenvalue is real; if * positive, then the j-th and (j+1)-st eigenvalues are a * complex conjugate pair, with ALPHAI(j+1) negative. * * Note: the quotients ALPHAR(j)/BETA(j) and ALPHAI(j)/BETA(j) * may easily over- or underflow, and BETA(j) may even be zero. * Thus, the user should avoid naively computing the ratio. * However, ALPHAR and ALPHAI will be always less than and * usually comparable with norm(A) in magnitude, and BETA always * less than and usually comparable with norm(B). * * VSL (output) DOUBLE PRECISION array, dimension (LDVSL,N) * If JOBVSL = 'V', VSL will contain the left Schur vectors. * Not referenced if JOBVSL = 'N'. * * LDVSL (input) INTEGER * The leading dimension of the matrix VSL. LDVSL >=1, and * if JOBVSL = 'V', LDVSL >= N. * * VSR (output) DOUBLE PRECISION array, dimension (LDVSR,N) * If JOBVSR = 'V', VSR will contain the right Schur vectors. * Not referenced if JOBVSR = 'N'. * * LDVSR (input) INTEGER * The leading dimension of the matrix VSR. LDVSR >= 1, and * if JOBVSR = 'V', LDVSR >= N. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= 8*N+16. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * BWORK (workspace) LOGICAL array, dimension (N) * Not referenced if SORT = 'N'. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value. * = 1,...,N: * The QZ iteration failed. (A,B) are not in Schur * form, but ALPHAR(j), ALPHAI(j), and BETA(j) should * be correct for j=INFO+1,...,N. * > N: =N+1: other than QZ iteration failed in DHGEQZ. * =N+2: after reordering, roundoff changed values of * some complex eigenvalues so that leading * eigenvalues in the Generalized Schur form no * longer satisfy DELZTG=.TRUE. This could also * be caused due to scaling. * =N+3: reordering failed in DTGSEN. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL CURSL, ILASCL, ILBSCL, ILVSL, ILVSR, LASTSL, $ LQUERY, LST2SL, WANTST INTEGER I, ICOLS, IERR, IHI, IJOBVL, IJOBVR, ILEFT, $ ILO, IP, IRIGHT, IROWS, ITAU, IWRK, MAXWRK, $ MINWRK DOUBLE PRECISION ANRM, ANRMTO, BIGNUM, BNRM, BNRMTO, EPS, PVSL, $ PVSR, SAFMAX, SAFMIN, SMLNUM * .. * .. Local Arrays .. INTEGER IDUM( 1 ) DOUBLE PRECISION DIF( 2 ) * .. * .. External Subroutines .. EXTERNAL DGEQRF, DGGBAK, DGGBAL, DGGHRD, DHGEQZ, DLABAD, $ DLACPY, DLASCL, DLASET, DORGQR, DORMQR, DTGSEN, $ XERBLA * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANGE EXTERNAL LSAME, ILAENV, DLAMCH, DLANGE * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, SQRT * .. * .. Executable Statements .. * * Decode the input arguments * IF( LSAME( JOBVSL, 'N' ) ) THEN IJOBVL = 1 ILVSL = .FALSE. ELSE IF( LSAME( JOBVSL, 'V' ) ) THEN IJOBVL = 2 ILVSL = .TRUE. ELSE IJOBVL = -1 ILVSL = .FALSE. END IF * IF( LSAME( JOBVSR, 'N' ) ) THEN IJOBVR = 1 ILVSR = .FALSE. ELSE IF( LSAME( JOBVSR, 'V' ) ) THEN IJOBVR = 2 ILVSR = .TRUE. ELSE IJOBVR = -1 ILVSR = .FALSE. END IF * WANTST = LSAME( SORT, 'S' ) * * Test the input arguments * INFO = 0 LQUERY = ( LWORK.EQ.-1 ) IF( IJOBVL.LE.0 ) THEN INFO = -1 ELSE IF( IJOBVR.LE.0 ) THEN INFO = -2 ELSE IF( ( .NOT.WANTST ) .AND. ( .NOT.LSAME( SORT, 'N' ) ) ) THEN INFO = -3 ELSE IF( N.LT.0 ) THEN INFO = -5 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -7 ELSE IF( LDB.LT.MAX( 1, N ) ) THEN INFO = -9 ELSE IF( LDVSL.LT.1 .OR. ( ILVSL .AND. LDVSL.LT.N ) ) THEN INFO = -15 ELSE IF( LDVSR.LT.1 .OR. ( ILVSR .AND. LDVSR.LT.N ) ) THEN INFO = -17 END IF * * Compute workspace * (Note: Comments in the code beginning "Workspace:" describe the * minimal amount of workspace needed at that point in the code, * as well as the preferred amount for good performance. * NB refers to the optimal block size for the immediately * following subroutine, as returned by ILAENV.) * MINWRK = 1 IF( INFO.EQ.0 .AND. ( LWORK.GE.1 .OR. LQUERY ) ) THEN MINWRK = 7*( N+1 ) + 16 MAXWRK = 7*( N+1 ) + N*ILAENV( 1, 'DGEQRF', ' ', N, 1, N, 0 ) + $ 16 IF( ILVSL ) THEN MAXWRK = MAX( MAXWRK, 7*( N+1 )+N* $ ILAENV( 1, 'DORGQR', ' ', N, 1, N, -1 ) ) END IF WORK( 1 ) = MAXWRK END IF * IF( LWORK.LT.MINWRK .AND. .NOT.LQUERY ) $ INFO = -19 IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGGES ', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) THEN SDIM = 0 RETURN END IF * * Get machine constants * EPS = DLAMCH( 'P' ) SAFMIN = DLAMCH( 'S' ) SAFMAX = ONE / SAFMIN CALL DLABAD( SAFMIN, SAFMAX ) SMLNUM = SQRT( SAFMIN ) / EPS BIGNUM = ONE / SMLNUM * * Scale A if max element outside range [SMLNUM,BIGNUM] * ANRM = DLANGE( 'M', N, N, A, LDA, WORK ) ILASCL = .FALSE. IF( ANRM.GT.ZERO .AND. ANRM.LT.SMLNUM ) THEN ANRMTO = SMLNUM ILASCL = .TRUE. ELSE IF( ANRM.GT.BIGNUM ) THEN ANRMTO = BIGNUM ILASCL = .TRUE. END IF IF( ILASCL ) $ CALL DLASCL( 'G', 0, 0, ANRM, ANRMTO, N, N, A, LDA, IERR ) * * Scale B if max element outside range [SMLNUM,BIGNUM] * BNRM = DLANGE( 'M', N, N, B, LDB, WORK ) ILBSCL = .FALSE. IF( BNRM.GT.ZERO .AND. BNRM.LT.SMLNUM ) THEN BNRMTO = SMLNUM ILBSCL = .TRUE. ELSE IF( BNRM.GT.BIGNUM ) THEN BNRMTO = BIGNUM ILBSCL = .TRUE. END IF IF( ILBSCL ) $ CALL DLASCL( 'G', 0, 0, BNRM, BNRMTO, N, N, B, LDB, IERR ) * * Permute the matrix to make it more nearly triangular * (Workspace: need 6*N + 2*N space for storing balancing factors) * ILEFT = 1 IRIGHT = N + 1 IWRK = IRIGHT + N CALL DGGBAL( 'P', N, A, LDA, B, LDB, ILO, IHI, WORK( ILEFT ), $ WORK( IRIGHT ), WORK( IWRK ), IERR ) * * Reduce B to triangular form (QR decomposition of B) * (Workspace: need N, prefer N*NB) * IROWS = IHI + 1 - ILO ICOLS = N + 1 - ILO ITAU = IWRK IWRK = ITAU + IROWS CALL DGEQRF( IROWS, ICOLS, B( ILO, ILO ), LDB, WORK( ITAU ), $ WORK( IWRK ), LWORK+1-IWRK, IERR ) * * Apply the orthogonal transformation to matrix A * (Workspace: need N, prefer N*NB) * CALL DORMQR( 'L', 'T', IROWS, ICOLS, IROWS, B( ILO, ILO ), LDB, $ WORK( ITAU ), A( ILO, ILO ), LDA, WORK( IWRK ), $ LWORK+1-IWRK, IERR ) * * Initialize VSL * (Workspace: need N, prefer N*NB) * IF( ILVSL ) THEN CALL DLASET( 'Full', N, N, ZERO, ONE, VSL, LDVSL ) CALL DLACPY( 'L', IROWS-1, IROWS-1, B( ILO+1, ILO ), LDB, $ VSL( ILO+1, ILO ), LDVSL ) CALL DORGQR( IROWS, IROWS, IROWS, VSL( ILO, ILO ), LDVSL, $ WORK( ITAU ), WORK( IWRK ), LWORK+1-IWRK, IERR ) END IF * * Initialize VSR * IF( ILVSR ) $ CALL DLASET( 'Full', N, N, ZERO, ONE, VSR, LDVSR ) * * Reduce to generalized Hessenberg form * (Workspace: none needed) * CALL DGGHRD( JOBVSL, JOBVSR, N, ILO, IHI, A, LDA, B, LDB, VSL, $ LDVSL, VSR, LDVSR, IERR ) * * Perform QZ algorithm, computing Schur vectors if desired * (Workspace: need N) * IWRK = ITAU CALL DHGEQZ( 'S', JOBVSL, JOBVSR, N, ILO, IHI, A, LDA, B, LDB, $ ALPHAR, ALPHAI, BETA, VSL, LDVSL, VSR, LDVSR, $ WORK( IWRK ), LWORK+1-IWRK, IERR ) IF( IERR.NE.0 ) THEN IF( IERR.GT.0 .AND. IERR.LE.N ) THEN INFO = IERR ELSE IF( IERR.GT.N .AND. IERR.LE.2*N ) THEN INFO = IERR - N ELSE INFO = N + 1 END IF GO TO 50 END IF * * Sort eigenvalues ALPHA/BETA if desired * (Workspace: need 4*N+16 ) * SDIM = 0 IF( WANTST ) THEN * * Undo scaling on eigenvalues before DELZTGing * IF( ILASCL ) THEN CALL DLASCL( 'G', 0, 0, ANRMTO, ANRM, N, 1, ALPHAR, N, $ IERR ) CALL DLASCL( 'G', 0, 0, ANRMTO, ANRM, N, 1, ALPHAI, N, $ IERR ) END IF IF( ILBSCL ) $ CALL DLASCL( 'G', 0, 0, BNRMTO, BNRM, N, 1, BETA, N, IERR ) * * Select eigenvalues * DO 10 I = 1, N BWORK( I ) = DELCTG( ALPHAR( I ), ALPHAI( I ), BETA( I ) ) 10 CONTINUE * CALL DTGSEN( 0, ILVSL, ILVSR, BWORK, N, A, LDA, B, LDB, ALPHAR, $ ALPHAI, BETA, VSL, LDVSL, VSR, LDVSR, SDIM, PVSL, $ PVSR, DIF, WORK( IWRK ), LWORK-IWRK+1, IDUM, 1, $ IERR ) IF( IERR.EQ.1 ) $ INFO = N + 3 * END IF * * Apply back-permutation to VSL and VSR * (Workspace: none needed) * IF( ILVSL ) $ CALL DGGBAK( 'P', 'L', N, ILO, IHI, WORK( ILEFT ), $ WORK( IRIGHT ), N, VSL, LDVSL, IERR ) * IF( ILVSR ) $ CALL DGGBAK( 'P', 'R', N, ILO, IHI, WORK( ILEFT ), $ WORK( IRIGHT ), N, VSR, LDVSR, IERR ) * * Check if unscaling would cause over/underflow, if so, rescale * (ALPHAR(I),ALPHAI(I),BETA(I)) so BETA(I) is on the order of * B(I,I) and ALPHAR(I) and ALPHAI(I) are on the order of A(I,I) * IF( ILASCL ) THEN DO 20 I = 1, N IF( ALPHAI( I ).NE.ZERO ) THEN IF( ( ALPHAR( I ) / SAFMAX ).GT.( ANRMTO / ANRM ) .OR. $ ( SAFMIN / ALPHAR( I ) ).GT.( ANRM / ANRMTO ) ) THEN WORK( 1 ) = ABS( A( I, I ) / ALPHAR( I ) ) BETA( I ) = BETA( I )*WORK( 1 ) ALPHAR( I ) = ALPHAR( I )*WORK( 1 ) ALPHAI( I ) = ALPHAI( I )*WORK( 1 ) ELSE IF( ( ALPHAI( I ) / SAFMAX ).GT. $ ( ANRMTO / ANRM ) .OR. $ ( SAFMIN / ALPHAI( I ) ).GT.( ANRM / ANRMTO ) ) $ THEN WORK( 1 ) = ABS( A( I, I+1 ) / ALPHAI( I ) ) BETA( I ) = BETA( I )*WORK( 1 ) ALPHAR( I ) = ALPHAR( I )*WORK( 1 ) ALPHAI( I ) = ALPHAI( I )*WORK( 1 ) END IF END IF 20 CONTINUE END IF * IF( ILBSCL ) THEN DO 30 I = 1, N IF( ALPHAI( I ).NE.ZERO ) THEN IF( ( BETA( I ) / SAFMAX ).GT.( BNRMTO / BNRM ) .OR. $ ( SAFMIN / BETA( I ) ).GT.( BNRM / BNRMTO ) ) THEN WORK( 1 ) = ABS( B( I, I ) / BETA( I ) ) BETA( I ) = BETA( I )*WORK( 1 ) ALPHAR( I ) = ALPHAR( I )*WORK( 1 ) ALPHAI( I ) = ALPHAI( I )*WORK( 1 ) END IF END IF 30 CONTINUE END IF * * Undo scaling * IF( ILASCL ) THEN CALL DLASCL( 'H', 0, 0, ANRMTO, ANRM, N, N, A, LDA, IERR ) CALL DLASCL( 'G', 0, 0, ANRMTO, ANRM, N, 1, ALPHAR, N, IERR ) CALL DLASCL( 'G', 0, 0, ANRMTO, ANRM, N, 1, ALPHAI, N, IERR ) END IF * IF( ILBSCL ) THEN CALL DLASCL( 'U', 0, 0, BNRMTO, BNRM, N, N, B, LDB, IERR ) CALL DLASCL( 'G', 0, 0, BNRMTO, BNRM, N, 1, BETA, N, IERR ) END IF * IF( WANTST ) THEN * * Check if reordering is correct * LASTSL = .TRUE. LST2SL = .TRUE. SDIM = 0 IP = 0 DO 40 I = 1, N CURSL = DELCTG( ALPHAR( I ), ALPHAI( I ), BETA( I ) ) IF( ALPHAI( I ).EQ.ZERO ) THEN IF( CURSL ) $ SDIM = SDIM + 1 IP = 0 IF( CURSL .AND. .NOT.LASTSL ) $ INFO = N + 2 ELSE IF( IP.EQ.1 ) THEN * * Last eigenvalue of conjugate pair * CURSL = CURSL .OR. LASTSL LASTSL = CURSL IF( CURSL ) $ SDIM = SDIM + 2 IP = -1 IF( CURSL .AND. .NOT.LST2SL ) $ INFO = N + 2 ELSE * * First eigenvalue of conjugate pair * IP = 1 END IF END IF LST2SL = LASTSL LASTSL = CURSL 40 CONTINUE * END IF * 50 CONTINUE * WORK( 1 ) = MAXWRK * RETURN * * End of DGGES * END SUBROUTINE DGGESX( JOBVSL, JOBVSR, SORT, DELCTG, SENSE, N, A, LDA, $ B, LDB, SDIM, ALPHAR, ALPHAI, BETA, VSL, LDVSL, $ VSR, LDVSR, RCONDE, RCONDV, WORK, LWORK, IWORK, $ LIWORK, BWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBVSL, JOBVSR, SENSE, SORT INTEGER INFO, LDA, LDB, LDVSL, LDVSR, LIWORK, LWORK, N, $ SDIM * .. * .. Array Arguments .. LOGICAL BWORK( * ) INTEGER IWORK( * ) DOUBLE PRECISION A( LDA, * ), ALPHAI( * ), ALPHAR( * ), $ B( LDB, * ), BETA( * ), RCONDE( 2 ), $ RCONDV( 2 ), VSL( LDVSL, * ), VSR( LDVSR, * ), $ WORK( * ) * .. * .. Function Arguments .. LOGICAL DELCTG EXTERNAL DELCTG * .. * * Purpose * ======= * * DGGESX computes for a pair of N-by-N real nonsymmetric matrices * (A,B), the generalized eigenvalues, the real Schur form (S,T), and, * optionally, the left and/or right matrices of Schur vectors (VSL and * VSR). This gives the generalized Schur factorization * * (A,B) = ( (VSL) S (VSR)**T, (VSL) T (VSR)**T ) * * Optionally, it also orders the eigenvalues so that a selected cluster * of eigenvalues appears in the leading diagonal blocks of the upper * quasi-triangular matrix S and the upper triangular matrix T; computes * a reciprocal condition number for the average of the selected * eigenvalues (RCONDE); and computes a reciprocal condition number for * the right and left deflating subspaces corresponding to the selected * eigenvalues (RCONDV). The leading columns of VSL and VSR then form * an orthonormal basis for the corresponding left and right eigenspaces * (deflating subspaces). * * A generalized eigenvalue for a pair of matrices (A,B) is a scalar w * or a ratio alpha/beta = w, such that A - w*B is singular. It is * usually represented as the pair (alpha,beta), as there is a * reasonable interpretation for beta=0 or for both being zero. * * A pair of matrices (S,T) is in generalized real Schur form if T is * upper triangular with non-negative diagonal and S is block upper * triangular with 1-by-1 and 2-by-2 blocks. 1-by-1 blocks correspond * to real generalized eigenvalues, while 2-by-2 blocks of S will be * "standardized" by making the corresponding elements of T have the * form: * [ a 0 ] * [ 0 b ] * * and the pair of corresponding 2-by-2 blocks in S and T will have a * complex conjugate pair of generalized eigenvalues. * * * Arguments * ========= * * JOBVSL (input) CHARACTER*1 * = 'N': do not compute the left Schur vectors; * = 'V': compute the left Schur vectors. * * JOBVSR (input) CHARACTER*1 * = 'N': do not compute the right Schur vectors; * = 'V': compute the right Schur vectors. * * SORT (input) CHARACTER*1 * Specifies whether or not to order the eigenvalues on the * diagonal of the generalized Schur form. * = 'N': Eigenvalues are not ordered; * = 'S': Eigenvalues are ordered (see DELZTG). * * DELZTG (input) LOGICAL FUNCTION of three DOUBLE PRECISION arguments * DELZTG must be declared EXTERNAL in the calling subroutine. * If SORT = 'N', DELZTG is not referenced. * If SORT = 'S', DELZTG is used to select eigenvalues to sort * to the top left of the Schur form. * An eigenvalue (ALPHAR(j)+ALPHAI(j))/BETA(j) is selected if * DELZTG(ALPHAR(j),ALPHAI(j),BETA(j)) is true; i.e. if either * one of a complex conjugate pair of eigenvalues is selected, * then both complex eigenvalues are selected. * Note that a selected complex eigenvalue may no longer satisfy * DELZTG(ALPHAR(j),ALPHAI(j),BETA(j)) = .TRUE. after ordering, * since ordering may change the value of complex eigenvalues * (especially if the eigenvalue is ill-conditioned), in this * case INFO is set to N+3. * * SENSE (input) CHARACTER * Determines which reciprocal condition numbers are computed. * = 'N' : None are computed; * = 'E' : Computed for average of selected eigenvalues only; * = 'V' : Computed for selected deflating subspaces only; * = 'B' : Computed for both. * If SENSE = 'E', 'V', or 'B', SORT must equal 'S'. * * N (input) INTEGER * The order of the matrices A, B, VSL, and VSR. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA, N) * On entry, the first of the pair of matrices. * On exit, A has been overwritten by its generalized Schur * form S. * * LDA (input) INTEGER * The leading dimension of A. LDA >= max(1,N). * * B (input/output) DOUBLE PRECISION array, dimension (LDB, N) * On entry, the second of the pair of matrices. * On exit, B has been overwritten by its generalized Schur * form T. * * LDB (input) INTEGER * The leading dimension of B. LDB >= max(1,N). * * SDIM (output) INTEGER * If SORT = 'N', SDIM = 0. * If SORT = 'S', SDIM = number of eigenvalues (after sorting) * for which DELZTG is true. (Complex conjugate pairs for which * DELZTG is true for either eigenvalue count as 2.) * * ALPHAR (output) DOUBLE PRECISION array, dimension (N) * ALPHAI (output) DOUBLE PRECISION array, dimension (N) * BETA (output) DOUBLE PRECISION array, dimension (N) * On exit, (ALPHAR(j) + ALPHAI(j)*i)/BETA(j), j=1,...,N, will * be the generalized eigenvalues. ALPHAR(j) + ALPHAI(j)*i * and BETA(j),j=1,...,N are the diagonals of the complex Schur * form (S,T) that would result if the 2-by-2 diagonal blocks of * the real Schur form of (A,B) were further reduced to * triangular form using 2-by-2 complex unitary transformations. * If ALPHAI(j) is zero, then the j-th eigenvalue is real; if * positive, then the j-th and (j+1)-st eigenvalues are a * complex conjugate pair, with ALPHAI(j+1) negative. * * Note: the quotients ALPHAR(j)/BETA(j) and ALPHAI(j)/BETA(j) * may easily over- or underflow, and BETA(j) may even be zero. * Thus, the user should avoid naively computing the ratio. * However, ALPHAR and ALPHAI will be always less than and * usually comparable with norm(A) in magnitude, and BETA always * less than and usually comparable with norm(B). * * VSL (output) DOUBLE PRECISION array, dimension (LDVSL,N) * If JOBVSL = 'V', VSL will contain the left Schur vectors. * Not referenced if JOBVSL = 'N'. * * LDVSL (input) INTEGER * The leading dimension of the matrix VSL. LDVSL >=1, and * if JOBVSL = 'V', LDVSL >= N. * * VSR (output) DOUBLE PRECISION array, dimension (LDVSR,N) * If JOBVSR = 'V', VSR will contain the right Schur vectors. * Not referenced if JOBVSR = 'N'. * * LDVSR (input) INTEGER * The leading dimension of the matrix VSR. LDVSR >= 1, and * if JOBVSR = 'V', LDVSR >= N. * * RCONDE (output) DOUBLE PRECISION array, dimension ( 2 ) * If SENSE = 'E' or 'B', RCONDE(1) and RCONDE(2) contain the * reciprocal condition numbers for the average of the selected * eigenvalues. * Not referenced if SENSE = 'N' or 'V'. * * RCONDV (output) DOUBLE PRECISION array, dimension ( 2 ) * If SENSE = 'V' or 'B', RCONDV(1) and RCONDV(2) contain the * reciprocal condition numbers for the selected deflating * subspaces. * Not referenced if SENSE = 'N' or 'E'. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= 8*(N+1)+16. * If SENSE = 'E', 'V', or 'B', * LWORK >= MAX( 8*(N+1)+16, 2*SDIM*(N-SDIM) ). * * IWORK (workspace) INTEGER array, dimension (LIWORK) * Not referenced if SENSE = 'N'. * * LIWORK (input) INTEGER * The dimension of the array WORK. LIWORK >= N+6. * * BWORK (workspace) LOGICAL array, dimension (N) * Not referenced if SORT = 'N'. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value. * = 1,...,N: * The QZ iteration failed. (A,B) are not in Schur * form, but ALPHAR(j), ALPHAI(j), and BETA(j) should * be correct for j=INFO+1,...,N. * > N: =N+1: other than QZ iteration failed in DHGEQZ * =N+2: after reordering, roundoff changed values of * some complex eigenvalues so that leading * eigenvalues in the Generalized Schur form no * longer satisfy DELZTG=.TRUE. This could also * be caused due to scaling. * =N+3: reordering failed in DTGSEN. * * Further details * =============== * * An approximate (asymptotic) bound on the average absolute error of * the selected eigenvalues is * * EPS * norm((A, B)) / RCONDE( 1 ). * * An approximate (asymptotic) bound on the maximum angular error in * the computed deflating subspaces is * * EPS * norm((A, B)) / RCONDV( 2 ). * * See LAPACK User's Guide, section 4.11 for more information. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL CURSL, ILASCL, ILBSCL, ILVSL, ILVSR, LASTSL, $ LST2SL, WANTSB, WANTSE, WANTSN, WANTST, WANTSV INTEGER I, ICOLS, IERR, IHI, IJOB, IJOBVL, IJOBVR, $ ILEFT, ILO, IP, IRIGHT, IROWS, ITAU, IWRK, $ LIWMIN, MAXWRK, MINWRK DOUBLE PRECISION ANRM, ANRMTO, BIGNUM, BNRM, BNRMTO, EPS, PL, $ PR, SAFMAX, SAFMIN, SMLNUM * .. * .. Local Arrays .. DOUBLE PRECISION DIF( 2 ) * .. * .. External Subroutines .. EXTERNAL DGEQRF, DGGBAK, DGGBAL, DGGHRD, DHGEQZ, DLABAD, $ DLACPY, DLASCL, DLASET, DORGQR, DORMQR, DTGSEN, $ XERBLA * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANGE EXTERNAL LSAME, ILAENV, DLAMCH, DLANGE * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, SQRT * .. * .. Executable Statements .. * * Decode the input arguments * IF( LSAME( JOBVSL, 'N' ) ) THEN IJOBVL = 1 ILVSL = .FALSE. ELSE IF( LSAME( JOBVSL, 'V' ) ) THEN IJOBVL = 2 ILVSL = .TRUE. ELSE IJOBVL = -1 ILVSL = .FALSE. END IF * IF( LSAME( JOBVSR, 'N' ) ) THEN IJOBVR = 1 ILVSR = .FALSE. ELSE IF( LSAME( JOBVSR, 'V' ) ) THEN IJOBVR = 2 ILVSR = .TRUE. ELSE IJOBVR = -1 ILVSR = .FALSE. END IF * WANTST = LSAME( SORT, 'S' ) WANTSN = LSAME( SENSE, 'N' ) WANTSE = LSAME( SENSE, 'E' ) WANTSV = LSAME( SENSE, 'V' ) WANTSB = LSAME( SENSE, 'B' ) IF( WANTSN ) THEN IJOB = 0 IWORK( 1 ) = 1 ELSE IF( WANTSE ) THEN IJOB = 1 ELSE IF( WANTSV ) THEN IJOB = 2 ELSE IF( WANTSB ) THEN IJOB = 4 END IF * * Test the input arguments * INFO = 0 IF( IJOBVL.LE.0 ) THEN INFO = -1 ELSE IF( IJOBVR.LE.0 ) THEN INFO = -2 ELSE IF( ( .NOT.WANTST ) .AND. ( .NOT.LSAME( SORT, 'N' ) ) ) THEN INFO = -3 ELSE IF( .NOT.( WANTSN .OR. WANTSE .OR. WANTSV .OR. WANTSB ) .OR. $ ( .NOT.WANTST .AND. .NOT.WANTSN ) ) THEN INFO = -5 ELSE IF( N.LT.0 ) THEN INFO = -6 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -8 ELSE IF( LDB.LT.MAX( 1, N ) ) THEN INFO = -10 ELSE IF( LDVSL.LT.1 .OR. ( ILVSL .AND. LDVSL.LT.N ) ) THEN INFO = -16 ELSE IF( LDVSR.LT.1 .OR. ( ILVSR .AND. LDVSR.LT.N ) ) THEN INFO = -18 END IF * * Compute workspace * (Note: Comments in the code beginning "Workspace:" describe the * minimal amount of workspace needed at that point in the code, * as well as the preferred amount for good performance. * NB refers to the optimal block size for the immediately * following subroutine, as returned by ILAENV.) * MINWRK = 1 IF( INFO.EQ.0 .AND. LWORK.GE.1 ) THEN MINWRK = 8*( N+1 ) + 16 MAXWRK = 7*( N+1 ) + N*ILAENV( 1, 'DGEQRF', ' ', N, 1, N, 0 ) + $ 16 IF( ILVSL ) THEN MAXWRK = MAX( MAXWRK, 8*( N+1 )+N* $ ILAENV( 1, 'DORGQR', ' ', N, 1, N, -1 )+16 ) END IF WORK( 1 ) = MAXWRK END IF IF( .NOT.WANTSN ) THEN LIWMIN = 1 ELSE LIWMIN = N + 6 END IF IWORK( 1 ) = LIWMIN * IF( INFO.EQ.0 .AND. LWORK.LT.MINWRK ) THEN INFO = -22 ELSE IF( INFO.EQ.0 .AND. IJOB.GE.1 ) THEN IF( LIWORK.LT.LIWMIN ) $ INFO = -24 END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGGESX', -INFO ) RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) THEN SDIM = 0 RETURN END IF * * Get machine constants * EPS = DLAMCH( 'P' ) SAFMIN = DLAMCH( 'S' ) SAFMAX = ONE / SAFMIN CALL DLABAD( SAFMIN, SAFMAX ) SMLNUM = SQRT( SAFMIN ) / EPS BIGNUM = ONE / SMLNUM * * Scale A if max element outside range [SMLNUM,BIGNUM] * ANRM = DLANGE( 'M', N, N, A, LDA, WORK ) ILASCL = .FALSE. IF( ANRM.GT.ZERO .AND. ANRM.LT.SMLNUM ) THEN ANRMTO = SMLNUM ILASCL = .TRUE. ELSE IF( ANRM.GT.BIGNUM ) THEN ANRMTO = BIGNUM ILASCL = .TRUE. END IF IF( ILASCL ) $ CALL DLASCL( 'G', 0, 0, ANRM, ANRMTO, N, N, A, LDA, IERR ) * * Scale B if max element outside range [SMLNUM,BIGNUM] * BNRM = DLANGE( 'M', N, N, B, LDB, WORK ) ILBSCL = .FALSE. IF( BNRM.GT.ZERO .AND. BNRM.LT.SMLNUM ) THEN BNRMTO = SMLNUM ILBSCL = .TRUE. ELSE IF( BNRM.GT.BIGNUM ) THEN BNRMTO = BIGNUM ILBSCL = .TRUE. END IF IF( ILBSCL ) $ CALL DLASCL( 'G', 0, 0, BNRM, BNRMTO, N, N, B, LDB, IERR ) * * Permute the matrix to make it more nearly triangular * (Workspace: need 6*N + 2*N for permutation parameters) * ILEFT = 1 IRIGHT = N + 1 IWRK = IRIGHT + N CALL DGGBAL( 'P', N, A, LDA, B, LDB, ILO, IHI, WORK( ILEFT ), $ WORK( IRIGHT ), WORK( IWRK ), IERR ) * * Reduce B to triangular form (QR decomposition of B) * (Workspace: need N, prefer N*NB) * IROWS = IHI + 1 - ILO ICOLS = N + 1 - ILO ITAU = IWRK IWRK = ITAU + IROWS CALL DGEQRF( IROWS, ICOLS, B( ILO, ILO ), LDB, WORK( ITAU ), $ WORK( IWRK ), LWORK+1-IWRK, IERR ) * * Apply the orthogonal transformation to matrix A * (Workspace: need N, prefer N*NB) * CALL DORMQR( 'L', 'T', IROWS, ICOLS, IROWS, B( ILO, ILO ), LDB, $ WORK( ITAU ), A( ILO, ILO ), LDA, WORK( IWRK ), $ LWORK+1-IWRK, IERR ) * * Initialize VSL * (Workspace: need N, prefer N*NB) * IF( ILVSL ) THEN CALL DLASET( 'Full', N, N, ZERO, ONE, VSL, LDVSL ) CALL DLACPY( 'L', IROWS-1, IROWS-1, B( ILO+1, ILO ), LDB, $ VSL( ILO+1, ILO ), LDVSL ) CALL DORGQR( IROWS, IROWS, IROWS, VSL( ILO, ILO ), LDVSL, $ WORK( ITAU ), WORK( IWRK ), LWORK+1-IWRK, IERR ) END IF * * Initialize VSR * IF( ILVSR ) $ CALL DLASET( 'Full', N, N, ZERO, ONE, VSR, LDVSR ) * * Reduce to generalized Hessenberg form * (Workspace: none needed) * CALL DGGHRD( JOBVSL, JOBVSR, N, ILO, IHI, A, LDA, B, LDB, VSL, $ LDVSL, VSR, LDVSR, IERR ) * SDIM = 0 * * Perform QZ algorithm, computing Schur vectors if desired * (Workspace: need N) * IWRK = ITAU CALL DHGEQZ( 'S', JOBVSL, JOBVSR, N, ILO, IHI, A, LDA, B, LDB, $ ALPHAR, ALPHAI, BETA, VSL, LDVSL, VSR, LDVSR, $ WORK( IWRK ), LWORK+1-IWRK, IERR ) IF( IERR.NE.0 ) THEN IF( IERR.GT.0 .AND. IERR.LE.N ) THEN INFO = IERR ELSE IF( IERR.GT.N .AND. IERR.LE.2*N ) THEN INFO = IERR - N ELSE INFO = N + 1 END IF GO TO 60 END IF * * Sort eigenvalues ALPHA/BETA and compute the reciprocal of * condition number(s) * (Workspace: If IJOB >= 1, need MAX( 8*(N+1), 2*SDIM*(N-SDIM) ) * otherwise, need 8*(N+1) ) * IF( WANTST ) THEN * * Undo scaling on eigenvalues before DELZTGing * IF( ILASCL ) THEN CALL DLASCL( 'G', 0, 0, ANRMTO, ANRM, N, 1, ALPHAR, N, $ IERR ) CALL DLASCL( 'G', 0, 0, ANRMTO, ANRM, N, 1, ALPHAI, N, $ IERR ) END IF IF( ILBSCL ) $ CALL DLASCL( 'G', 0, 0, BNRMTO, BNRM, N, 1, BETA, N, IERR ) * * Select eigenvalues * DO 10 I = 1, N BWORK( I ) = DELCTG( ALPHAR( I ), ALPHAI( I ), BETA( I ) ) 10 CONTINUE * * Reorder eigenvalues, transform Generalized Schur vectors, and * compute reciprocal condition numbers * CALL DTGSEN( IJOB, ILVSL, ILVSR, BWORK, N, A, LDA, B, LDB, $ ALPHAR, ALPHAI, BETA, VSL, LDVSL, VSR, LDVSR, $ SDIM, PL, PR, DIF, WORK( IWRK ), LWORK-IWRK+1, $ IWORK, LIWORK, IERR ) * IF( IJOB.GE.1 ) $ MAXWRK = MAX( MAXWRK, 2*SDIM*( N-SDIM ) ) IF( IERR.EQ.-22 ) THEN * * not enough real workspace * INFO = -22 ELSE RCONDE( 1 ) = PL RCONDE( 2 ) = PR RCONDV( 1 ) = DIF( 1 ) RCONDV( 2 ) = DIF( 2 ) IF( IERR.EQ.1 ) $ INFO = N + 3 END IF * END IF * * Apply permutation to VSL and VSR * (Workspace: none needed) * IF( ILVSL ) $ CALL DGGBAK( 'P', 'L', N, ILO, IHI, WORK( ILEFT ), $ WORK( IRIGHT ), N, VSL, LDVSL, IERR ) * IF( ILVSR ) $ CALL DGGBAK( 'P', 'R', N, ILO, IHI, WORK( ILEFT ), $ WORK( IRIGHT ), N, VSR, LDVSR, IERR ) * * Check if unscaling would cause over/underflow, if so, rescale * (ALPHAR(I),ALPHAI(I),BETA(I)) so BETA(I) is on the order of * B(I,I) and ALPHAR(I) and ALPHAI(I) are on the order of A(I,I) * IF( ILASCL ) THEN DO 20 I = 1, N IF( ALPHAI( I ).NE.ZERO ) THEN IF( ( ALPHAR( I ) / SAFMAX ).GT.( ANRMTO / ANRM ) .OR. $ ( SAFMIN / ALPHAR( I ) ).GT.( ANRM / ANRMTO ) ) THEN WORK( 1 ) = ABS( A( I, I ) / ALPHAR( I ) ) BETA( I ) = BETA( I )*WORK( 1 ) ALPHAR( I ) = ALPHAR( I )*WORK( 1 ) ALPHAI( I ) = ALPHAI( I )*WORK( 1 ) ELSE IF( ( ALPHAI( I ) / SAFMAX ).GT. $ ( ANRMTO / ANRM ) .OR. $ ( SAFMIN / ALPHAI( I ) ).GT.( ANRM / ANRMTO ) ) $ THEN WORK( 1 ) = ABS( A( I, I+1 ) / ALPHAI( I ) ) BETA( I ) = BETA( I )*WORK( 1 ) ALPHAR( I ) = ALPHAR( I )*WORK( 1 ) ALPHAI( I ) = ALPHAI( I )*WORK( 1 ) END IF END IF 20 CONTINUE END IF * IF( ILBSCL ) THEN DO 30 I = 1, N IF( ALPHAI( I ).NE.ZERO ) THEN IF( ( BETA( I ) / SAFMAX ).GT.( BNRMTO / BNRM ) .OR. $ ( SAFMIN / BETA( I ) ).GT.( BNRM / BNRMTO ) ) THEN WORK( 1 ) = ABS( B( I, I ) / BETA( I ) ) BETA( I ) = BETA( I )*WORK( 1 ) ALPHAR( I ) = ALPHAR( I )*WORK( 1 ) ALPHAI( I ) = ALPHAI( I )*WORK( 1 ) END IF END IF 30 CONTINUE END IF * * Undo scaling * IF( ILASCL ) THEN CALL DLASCL( 'H', 0, 0, ANRMTO, ANRM, N, N, A, LDA, IERR ) CALL DLASCL( 'G', 0, 0, ANRMTO, ANRM, N, 1, ALPHAR, N, IERR ) CALL DLASCL( 'G', 0, 0, ANRMTO, ANRM, N, 1, ALPHAI, N, IERR ) END IF * IF( ILBSCL ) THEN CALL DLASCL( 'U', 0, 0, BNRMTO, BNRM, N, N, B, LDB, IERR ) CALL DLASCL( 'G', 0, 0, BNRMTO, BNRM, N, 1, BETA, N, IERR ) END IF * 40 CONTINUE * IF( WANTST ) THEN * * Check if reordering is correct * LASTSL = .TRUE. LST2SL = .TRUE. SDIM = 0 IP = 0 DO 50 I = 1, N CURSL = DELCTG( ALPHAR( I ), ALPHAI( I ), BETA( I ) ) IF( ALPHAI( I ).EQ.ZERO ) THEN IF( CURSL ) $ SDIM = SDIM + 1 IP = 0 IF( CURSL .AND. .NOT.LASTSL ) $ INFO = N + 2 ELSE IF( IP.EQ.1 ) THEN * * Last eigenvalue of conjugate pair * CURSL = CURSL .OR. LASTSL LASTSL = CURSL IF( CURSL ) $ SDIM = SDIM + 2 IP = -1 IF( CURSL .AND. .NOT.LST2SL ) $ INFO = N + 2 ELSE * * First eigenvalue of conjugate pair * IP = 1 END IF END IF LST2SL = LASTSL LASTSL = CURSL 50 CONTINUE * END IF * 60 CONTINUE * WORK( 1 ) = MAXWRK IWORK( 1 ) = LIWMIN * RETURN * * End of DGGESX * END SUBROUTINE DGGEV( JOBVL, JOBVR, N, A, LDA, B, LDB, ALPHAR, ALPHAI, $ BETA, VL, LDVL, VR, LDVR, WORK, LWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBVL, JOBVR INTEGER INFO, LDA, LDB, LDVL, LDVR, LWORK, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), ALPHAI( * ), ALPHAR( * ), $ B( LDB, * ), BETA( * ), VL( LDVL, * ), $ VR( LDVR, * ), WORK( * ) * .. * * Purpose * ======= * * DGGEV computes for a pair of N-by-N real nonsymmetric matrices (A,B) * the generalized eigenvalues, and optionally, the left and/or right * generalized eigenvectors. * * A generalized eigenvalue for a pair of matrices (A,B) is a scalar * lambda or a ratio alpha/beta = lambda, such that A - lambda*B is * singular. It is usually represented as the pair (alpha,beta), as * there is a reasonable interpretation for beta=0, and even for both * being zero. * * The right eigenvector v(j) corresponding to the eigenvalue lambda(j) * of (A,B) satisfies * * A * v(j) = lambda(j) * B * v(j). * * The left eigenvector u(j) corresponding to the eigenvalue lambda(j) * of (A,B) satisfies * * u(j)**H * A = lambda(j) * u(j)**H * B . * * where u(j)**H is the conjugate-transpose of u(j). * * * Arguments * ========= * * JOBVL (input) CHARACTER*1 * = 'N': do not compute the left generalized eigenvectors; * = 'V': compute the left generalized eigenvectors. * * JOBVR (input) CHARACTER*1 * = 'N': do not compute the right generalized eigenvectors; * = 'V': compute the right generalized eigenvectors. * * N (input) INTEGER * The order of the matrices A, B, VL, and VR. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA, N) * On entry, the matrix A in the pair (A,B). * On exit, A has been overwritten. * * LDA (input) INTEGER * The leading dimension of A. LDA >= max(1,N). * * B (input/output) DOUBLE PRECISION array, dimension (LDB, N) * On entry, the matrix B in the pair (A,B). * On exit, B has been overwritten. * * LDB (input) INTEGER * The leading dimension of B. LDB >= max(1,N). * * ALPHAR (output) DOUBLE PRECISION array, dimension (N) * ALPHAI (output) DOUBLE PRECISION array, dimension (N) * BETA (output) DOUBLE PRECISION array, dimension (N) * On exit, (ALPHAR(j) + ALPHAI(j)*i)/BETA(j), j=1,...,N, will * be the generalized eigenvalues. If ALPHAI(j) is zero, then * the j-th eigenvalue is real; if positive, then the j-th and * (j+1)-st eigenvalues are a complex conjugate pair, with * ALPHAI(j+1) negative. * * Note: the quotients ALPHAR(j)/BETA(j) and ALPHAI(j)/BETA(j) * may easily over- or underflow, and BETA(j) may even be zero. * Thus, the user should avoid naively computing the ratio * alpha/beta. However, ALPHAR and ALPHAI will be always less * than and usually comparable with norm(A) in magnitude, and * BETA always less than and usually comparable with norm(B). * * VL (output) DOUBLE PRECISION array, dimension (LDVL,N) * If JOBVL = 'V', the left eigenvectors u(j) are stored one * after another in the columns of VL, in the same order as * their eigenvalues. If the j-th eigenvalue is real, then * u(j) = VL(:,j), the j-th column of VL. If the j-th and * (j+1)-th eigenvalues form a complex conjugate pair, then * u(j) = VL(:,j)+i*VL(:,j+1) and u(j+1) = VL(:,j)-i*VL(:,j+1). * Each eigenvector will be scaled so the largest component have * abs(real part)+abs(imag. part)=1. * Not referenced if JOBVL = 'N'. * * LDVL (input) INTEGER * The leading dimension of the matrix VL. LDVL >= 1, and * if JOBVL = 'V', LDVL >= N. * * VR (output) DOUBLE PRECISION array, dimension (LDVR,N) * If JOBVR = 'V', the right eigenvectors v(j) are stored one * after another in the columns of VR, in the same order as * their eigenvalues. If the j-th eigenvalue is real, then * v(j) = VR(:,j), the j-th column of VR. If the j-th and * (j+1)-th eigenvalues form a complex conjugate pair, then * v(j) = VR(:,j)+i*VR(:,j+1) and v(j+1) = VR(:,j)-i*VR(:,j+1). * Each eigenvector will be scaled so the largest component have * abs(real part)+abs(imag. part)=1. * Not referenced if JOBVR = 'N'. * * LDVR (input) INTEGER * The leading dimension of the matrix VR. LDVR >= 1, and * if JOBVR = 'V', LDVR >= N. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= max(1,8*N). * For good performance, LWORK must generally be larger. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value. * = 1,...,N: * The QZ iteration failed. No eigenvectors have been * calculated, but ALPHAR(j), ALPHAI(j), and BETA(j) * should be correct for j=INFO+1,...,N. * > N: =N+1: other than QZ iteration failed in DHGEQZ. * =N+2: error return from DTGEVC. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL ILASCL, ILBSCL, ILV, ILVL, ILVR, LQUERY CHARACTER CHTEMP INTEGER ICOLS, IERR, IHI, IJOBVL, IJOBVR, ILEFT, ILO, $ IN, IRIGHT, IROWS, ITAU, IWRK, JC, JR, MAXWRK, $ MINWRK DOUBLE PRECISION ANRM, ANRMTO, BIGNUM, BNRM, BNRMTO, EPS, $ SMLNUM, TEMP * .. * .. Local Arrays .. LOGICAL LDUMMA( 1 ) * .. * .. External Subroutines .. EXTERNAL DGEQRF, DGGBAK, DGGBAL, DGGHRD, DHGEQZ, DLACPY, $ DLASCL, DLASET, DORGQR, DORMQR, DTGEVC, XERBLA * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANGE EXTERNAL LSAME, ILAENV, DLAMCH, DLANGE * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, SQRT * .. * .. Executable Statements .. * * Decode the input arguments * IF( LSAME( JOBVL, 'N' ) ) THEN IJOBVL = 1 ILVL = .FALSE. ELSE IF( LSAME( JOBVL, 'V' ) ) THEN IJOBVL = 2 ILVL = .TRUE. ELSE IJOBVL = -1 ILVL = .FALSE. END IF * IF( LSAME( JOBVR, 'N' ) ) THEN IJOBVR = 1 ILVR = .FALSE. ELSE IF( LSAME( JOBVR, 'V' ) ) THEN IJOBVR = 2 ILVR = .TRUE. ELSE IJOBVR = -1 ILVR = .FALSE. END IF ILV = ILVL .OR. ILVR * * Test the input arguments * INFO = 0 LQUERY = ( LWORK.EQ.-1 ) IF( IJOBVL.LE.0 ) THEN INFO = -1 ELSE IF( IJOBVR.LE.0 ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -5 ELSE IF( LDB.LT.MAX( 1, N ) ) THEN INFO = -7 ELSE IF( LDVL.LT.1 .OR. ( ILVL .AND. LDVL.LT.N ) ) THEN INFO = -12 ELSE IF( LDVR.LT.1 .OR. ( ILVR .AND. LDVR.LT.N ) ) THEN INFO = -14 END IF * * Compute workspace * (Note: Comments in the code beginning "Workspace:" describe the * minimal amount of workspace needed at that point in the code, * as well as the preferred amount for good performance. * NB refers to the optimal block size for the immediately * following subroutine, as returned by ILAENV. The workspace is * computed assuming ILO = 1 and IHI = N, the worst case.) * MINWRK = 1 IF( INFO.EQ.0 .AND. ( LWORK.GE.1 .OR. LQUERY ) ) THEN MAXWRK = 7*N + N*ILAENV( 1, 'DGEQRF', ' ', N, 1, N, 0 ) MINWRK = MAX( 1, 8*N ) WORK( 1 ) = MAXWRK END IF * IF( LWORK.LT.MINWRK .AND. .NOT.LQUERY ) $ INFO = -16 * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGGEV ', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * * Get machine constants * EPS = DLAMCH( 'P' ) SMLNUM = DLAMCH( 'S' ) BIGNUM = ONE / SMLNUM CALL DLABAD( SMLNUM, BIGNUM ) SMLNUM = SQRT( SMLNUM ) / EPS BIGNUM = ONE / SMLNUM * * Scale A if max element outside range [SMLNUM,BIGNUM] * ANRM = DLANGE( 'M', N, N, A, LDA, WORK ) ILASCL = .FALSE. IF( ANRM.GT.ZERO .AND. ANRM.LT.SMLNUM ) THEN ANRMTO = SMLNUM ILASCL = .TRUE. ELSE IF( ANRM.GT.BIGNUM ) THEN ANRMTO = BIGNUM ILASCL = .TRUE. END IF IF( ILASCL ) $ CALL DLASCL( 'G', 0, 0, ANRM, ANRMTO, N, N, A, LDA, IERR ) * * Scale B if max element outside range [SMLNUM,BIGNUM] * BNRM = DLANGE( 'M', N, N, B, LDB, WORK ) ILBSCL = .FALSE. IF( BNRM.GT.ZERO .AND. BNRM.LT.SMLNUM ) THEN BNRMTO = SMLNUM ILBSCL = .TRUE. ELSE IF( BNRM.GT.BIGNUM ) THEN BNRMTO = BIGNUM ILBSCL = .TRUE. END IF IF( ILBSCL ) $ CALL DLASCL( 'G', 0, 0, BNRM, BNRMTO, N, N, B, LDB, IERR ) * * Permute the matrices A, B to isolate eigenvalues if possible * (Workspace: need 6*N) * ILEFT = 1 IRIGHT = N + 1 IWRK = IRIGHT + N CALL DGGBAL( 'P', N, A, LDA, B, LDB, ILO, IHI, WORK( ILEFT ), $ WORK( IRIGHT ), WORK( IWRK ), IERR ) * * Reduce B to triangular form (QR decomposition of B) * (Workspace: need N, prefer N*NB) * IROWS = IHI + 1 - ILO IF( ILV ) THEN ICOLS = N + 1 - ILO ELSE ICOLS = IROWS END IF ITAU = IWRK IWRK = ITAU + IROWS CALL DGEQRF( IROWS, ICOLS, B( ILO, ILO ), LDB, WORK( ITAU ), $ WORK( IWRK ), LWORK+1-IWRK, IERR ) * * Apply the orthogonal transformation to matrix A * (Workspace: need N, prefer N*NB) * CALL DORMQR( 'L', 'T', IROWS, ICOLS, IROWS, B( ILO, ILO ), LDB, $ WORK( ITAU ), A( ILO, ILO ), LDA, WORK( IWRK ), $ LWORK+1-IWRK, IERR ) * * Initialize VL * (Workspace: need N, prefer N*NB) * IF( ILVL ) THEN CALL DLASET( 'Full', N, N, ZERO, ONE, VL, LDVL ) CALL DLACPY( 'L', IROWS-1, IROWS-1, B( ILO+1, ILO ), LDB, $ VL( ILO+1, ILO ), LDVL ) CALL DORGQR( IROWS, IROWS, IROWS, VL( ILO, ILO ), LDVL, $ WORK( ITAU ), WORK( IWRK ), LWORK+1-IWRK, IERR ) END IF * * Initialize VR * IF( ILVR ) $ CALL DLASET( 'Full', N, N, ZERO, ONE, VR, LDVR ) * * Reduce to generalized Hessenberg form * (Workspace: none needed) * IF( ILV ) THEN * * Eigenvectors requested -- work on whole matrix. * CALL DGGHRD( JOBVL, JOBVR, N, ILO, IHI, A, LDA, B, LDB, VL, $ LDVL, VR, LDVR, IERR ) ELSE CALL DGGHRD( 'N', 'N', IROWS, 1, IROWS, A( ILO, ILO ), LDA, $ B( ILO, ILO ), LDB, VL, LDVL, VR, LDVR, IERR ) END IF * * Perform QZ algorithm (Compute eigenvalues, and optionally, the * Schur forms and Schur vectors) * (Workspace: need N) * IWRK = ITAU IF( ILV ) THEN CHTEMP = 'S' ELSE CHTEMP = 'E' END IF CALL DHGEQZ( CHTEMP, JOBVL, JOBVR, N, ILO, IHI, A, LDA, B, LDB, $ ALPHAR, ALPHAI, BETA, VL, LDVL, VR, LDVR, $ WORK( IWRK ), LWORK+1-IWRK, IERR ) IF( IERR.NE.0 ) THEN IF( IERR.GT.0 .AND. IERR.LE.N ) THEN INFO = IERR ELSE IF( IERR.GT.N .AND. IERR.LE.2*N ) THEN INFO = IERR - N ELSE INFO = N + 1 END IF GO TO 110 END IF * * Compute Eigenvectors * (Workspace: need 6*N) * IF( ILV ) THEN IF( ILVL ) THEN IF( ILVR ) THEN CHTEMP = 'B' ELSE CHTEMP = 'L' END IF ELSE CHTEMP = 'R' END IF CALL DTGEVC( CHTEMP, 'B', LDUMMA, N, A, LDA, B, LDB, VL, LDVL, $ VR, LDVR, N, IN, WORK( IWRK ), IERR ) IF( IERR.NE.0 ) THEN INFO = N + 2 GO TO 110 END IF * * Undo balancing on VL and VR and normalization * (Workspace: none needed) * IF( ILVL ) THEN CALL DGGBAK( 'P', 'L', N, ILO, IHI, WORK( ILEFT ), $ WORK( IRIGHT ), N, VL, LDVL, IERR ) DO 50 JC = 1, N IF( ALPHAI( JC ).LT.ZERO ) $ GO TO 50 TEMP = ZERO IF( ALPHAI( JC ).EQ.ZERO ) THEN DO 10 JR = 1, N TEMP = MAX( TEMP, ABS( VL( JR, JC ) ) ) 10 CONTINUE ELSE DO 20 JR = 1, N TEMP = MAX( TEMP, ABS( VL( JR, JC ) )+ $ ABS( VL( JR, JC+1 ) ) ) 20 CONTINUE END IF IF( TEMP.LT.SMLNUM ) $ GO TO 50 TEMP = ONE / TEMP IF( ALPHAI( JC ).EQ.ZERO ) THEN DO 30 JR = 1, N VL( JR, JC ) = VL( JR, JC )*TEMP 30 CONTINUE ELSE DO 40 JR = 1, N VL( JR, JC ) = VL( JR, JC )*TEMP VL( JR, JC+1 ) = VL( JR, JC+1 )*TEMP 40 CONTINUE END IF 50 CONTINUE END IF IF( ILVR ) THEN CALL DGGBAK( 'P', 'R', N, ILO, IHI, WORK( ILEFT ), $ WORK( IRIGHT ), N, VR, LDVR, IERR ) DO 100 JC = 1, N IF( ALPHAI( JC ).LT.ZERO ) $ GO TO 100 TEMP = ZERO IF( ALPHAI( JC ).EQ.ZERO ) THEN DO 60 JR = 1, N TEMP = MAX( TEMP, ABS( VR( JR, JC ) ) ) 60 CONTINUE ELSE DO 70 JR = 1, N TEMP = MAX( TEMP, ABS( VR( JR, JC ) )+ $ ABS( VR( JR, JC+1 ) ) ) 70 CONTINUE END IF IF( TEMP.LT.SMLNUM ) $ GO TO 100 TEMP = ONE / TEMP IF( ALPHAI( JC ).EQ.ZERO ) THEN DO 80 JR = 1, N VR( JR, JC ) = VR( JR, JC )*TEMP 80 CONTINUE ELSE DO 90 JR = 1, N VR( JR, JC ) = VR( JR, JC )*TEMP VR( JR, JC+1 ) = VR( JR, JC+1 )*TEMP 90 CONTINUE END IF 100 CONTINUE END IF * * End of eigenvector calculation * END IF * * Undo scaling if necessary * IF( ILASCL ) THEN CALL DLASCL( 'G', 0, 0, ANRMTO, ANRM, N, 1, ALPHAR, N, IERR ) CALL DLASCL( 'G', 0, 0, ANRMTO, ANRM, N, 1, ALPHAI, N, IERR ) END IF * IF( ILBSCL ) THEN CALL DLASCL( 'G', 0, 0, BNRMTO, BNRM, N, 1, BETA, N, IERR ) END IF * 110 CONTINUE * WORK( 1 ) = MAXWRK * RETURN * * End of DGGEV * END SUBROUTINE DGGEVX( BALANC, JOBVL, JOBVR, SENSE, N, A, LDA, B, LDB, $ ALPHAR, ALPHAI, BETA, VL, LDVL, VR, LDVR, ILO, $ IHI, LSCALE, RSCALE, ABNRM, BBNRM, RCONDE, $ RCONDV, WORK, LWORK, IWORK, BWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER BALANC, JOBVL, JOBVR, SENSE INTEGER IHI, ILO, INFO, LDA, LDB, LDVL, LDVR, LWORK, N DOUBLE PRECISION ABNRM, BBNRM * .. * .. Array Arguments .. LOGICAL BWORK( * ) INTEGER IWORK( * ) DOUBLE PRECISION A( LDA, * ), ALPHAI( * ), ALPHAR( * ), $ B( LDB, * ), BETA( * ), LSCALE( * ), $ RCONDE( * ), RCONDV( * ), RSCALE( * ), $ VL( LDVL, * ), VR( LDVR, * ), WORK( * ) * .. * * Purpose * ======= * * DGGEVX computes for a pair of N-by-N real nonsymmetric matrices (A,B) * the generalized eigenvalues, and optionally, the left and/or right * generalized eigenvectors. * * Optionally also, it computes a balancing transformation to improve * the conditioning of the eigenvalues and eigenvectors (ILO, IHI, * LSCALE, RSCALE, ABNRM, and BBNRM), reciprocal condition numbers for * the eigenvalues (RCONDE), and reciprocal condition numbers for the * right eigenvectors (RCONDV). * * A generalized eigenvalue for a pair of matrices (A,B) is a scalar * lambda or a ratio alpha/beta = lambda, such that A - lambda*B is * singular. It is usually represented as the pair (alpha,beta), as * there is a reasonable interpretation for beta=0, and even for both * being zero. * * The right eigenvector v(j) corresponding to the eigenvalue lambda(j) * of (A,B) satisfies * * A * v(j) = lambda(j) * B * v(j) . * * The left eigenvector u(j) corresponding to the eigenvalue lambda(j) * of (A,B) satisfies * * u(j)**H * A = lambda(j) * u(j)**H * B. * * where u(j)**H is the conjugate-transpose of u(j). * * * Arguments * ========= * * BALANC (input) CHARACTER*1 * Specifies the balance option to be performed. * = 'N': do not diagonally scale or permute; * = 'P': permute only; * = 'S': scale only; * = 'B': both permute and scale. * Computed reciprocal condition numbers will be for the * matrices after permuting and/or balancing. Permuting does * not change condition numbers (in exact arithmetic), but * balancing does. * * JOBVL (input) CHARACTER*1 * = 'N': do not compute the left generalized eigenvectors; * = 'V': compute the left generalized eigenvectors. * * JOBVR (input) CHARACTER*1 * = 'N': do not compute the right generalized eigenvectors; * = 'V': compute the right generalized eigenvectors. * * SENSE (input) CHARACTER*1 * Determines which reciprocal condition numbers are computed. * = 'N': none are computed; * = 'E': computed for eigenvalues only; * = 'V': computed for eigenvectors only; * = 'B': computed for eigenvalues and eigenvectors. * * N (input) INTEGER * The order of the matrices A, B, VL, and VR. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA, N) * On entry, the matrix A in the pair (A,B). * On exit, A has been overwritten. If JOBVL='V' or JOBVR='V' * or both, then A contains the first part of the real Schur * form of the "balanced" versions of the input A and B. * * LDA (input) INTEGER * The leading dimension of A. LDA >= max(1,N). * * B (input/output) DOUBLE PRECISION array, dimension (LDB, N) * On entry, the matrix B in the pair (A,B). * On exit, B has been overwritten. If JOBVL='V' or JOBVR='V' * or both, then B contains the second part of the real Schur * form of the "balanced" versions of the input A and B. * * LDB (input) INTEGER * The leading dimension of B. LDB >= max(1,N). * * ALPHAR (output) DOUBLE PRECISION array, dimension (N) * ALPHAI (output) DOUBLE PRECISION array, dimension (N) * BETA (output) DOUBLE PRECISION array, dimension (N) * On exit, (ALPHAR(j) + ALPHAI(j)*i)/BETA(j), j=1,...,N, will * be the generalized eigenvalues. If ALPHAI(j) is zero, then * the j-th eigenvalue is real; if positive, then the j-th and * (j+1)-st eigenvalues are a complex conjugate pair, with * ALPHAI(j+1) negative. * * Note: the quotients ALPHAR(j)/BETA(j) and ALPHAI(j)/BETA(j) * may easily over- or underflow, and BETA(j) may even be zero. * Thus, the user should avoid naively computing the ratio * ALPHA/BETA. However, ALPHAR and ALPHAI will be always less * than and usually comparable with norm(A) in magnitude, and * BETA always less than and usually comparable with norm(B). * * VL (output) DOUBLE PRECISION array, dimension (LDVL,N) * If JOBVL = 'V', the left eigenvectors u(j) are stored one * after another in the columns of VL, in the same order as * their eigenvalues. If the j-th eigenvalue is real, then * u(j) = VL(:,j), the j-th column of VL. If the j-th and * (j+1)-th eigenvalues form a complex conjugate pair, then * u(j) = VL(:,j)+i*VL(:,j+1) and u(j+1) = VL(:,j)-i*VL(:,j+1). * Each eigenvector will be scaled so the largest component have * abs(real part) + abs(imag. part) = 1. * Not referenced if JOBVL = 'N'. * * LDVL (input) INTEGER * The leading dimension of the matrix VL. LDVL >= 1, and * if JOBVL = 'V', LDVL >= N. * * VR (output) DOUBLE PRECISION array, dimension (LDVR,N) * If JOBVR = 'V', the right eigenvectors v(j) are stored one * after another in the columns of VR, in the same order as * their eigenvalues. If the j-th eigenvalue is real, then * v(j) = VR(:,j), the j-th column of VR. If the j-th and * (j+1)-th eigenvalues form a complex conjugate pair, then * v(j) = VR(:,j)+i*VR(:,j+1) and v(j+1) = VR(:,j)-i*VR(:,j+1). * Each eigenvector will be scaled so the largest component have * abs(real part) + abs(imag. part) = 1. * Not referenced if JOBVR = 'N'. * * LDVR (input) INTEGER * The leading dimension of the matrix VR. LDVR >= 1, and * if JOBVR = 'V', LDVR >= N. * * ILO,IHI (output) INTEGER * ILO and IHI are integer values such that on exit * A(i,j) = 0 and B(i,j) = 0 if i > j and * j = 1,...,ILO-1 or i = IHI+1,...,N. * If BALANC = 'N' or 'S', ILO = 1 and IHI = N. * * LSCALE (output) DOUBLE PRECISION array, dimension (N) * Details of the permutations and scaling factors applied * to the left side of A and B. If PL(j) is the index of the * row interchanged with row j, and DL(j) is the scaling * factor applied to row j, then * LSCALE(j) = PL(j) for j = 1,...,ILO-1 * = DL(j) for j = ILO,...,IHI * = PL(j) for j = IHI+1,...,N. * The order in which the interchanges are made is N to IHI+1, * then 1 to ILO-1. * * RSCALE (output) DOUBLE PRECISION array, dimension (N) * Details of the permutations and scaling factors applied * to the right side of A and B. If PR(j) is the index of the * column interchanged with column j, and DR(j) is the scaling * factor applied to column j, then * RSCALE(j) = PR(j) for j = 1,...,ILO-1 * = DR(j) for j = ILO,...,IHI * = PR(j) for j = IHI+1,...,N * The order in which the interchanges are made is N to IHI+1, * then 1 to ILO-1. * * ABNRM (output) DOUBLE PRECISION * The one-norm of the balanced matrix A. * * BBNRM (output) DOUBLE PRECISION * The one-norm of the balanced matrix B. * * RCONDE (output) DOUBLE PRECISION array, dimension (N) * If SENSE = 'E' or 'B', the reciprocal condition numbers of * the selected eigenvalues, stored in consecutive elements of * the array. For a complex conjugate pair of eigenvalues two * consecutive elements of RCONDE are set to the same value. * Thus RCONDE(j), RCONDV(j), and the j-th columns of VL and VR * all correspond to the same eigenpair (but not in general the * j-th eigenpair, unless all eigenpairs are selected). * If SENSE = 'V', RCONDE is not referenced. * * RCONDV (output) DOUBLE PRECISION array, dimension (N) * If SENSE = 'V' or 'B', the estimated reciprocal condition * numbers of the selected eigenvectors, stored in consecutive * elements of the array. For a complex eigenvector two * consecutive elements of RCONDV are set to the same value. If * the eigenvalues cannot be reordered to compute RCONDV(j), * RCONDV(j) is set to 0; this can only occur when the true * value would be very small anyway. * If SENSE = 'E', RCONDV is not referenced. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= max(1,6*N). * If SENSE = 'E', LWORK >= 12*N. * If SENSE = 'V' or 'B', LWORK >= 2*N*N+12*N+16. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * IWORK (workspace) INTEGER array, dimension (N+6) * If SENSE = 'E', IWORK is not referenced. * * BWORK (workspace) LOGICAL array, dimension (N) * If SENSE = 'N', BWORK is not referenced. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value. * = 1,...,N: * The QZ iteration failed. No eigenvectors have been * calculated, but ALPHAR(j), ALPHAI(j), and BETA(j) * should be correct for j=INFO+1,...,N. * > N: =N+1: other than QZ iteration failed in DHGEQZ. * =N+2: error return from DTGEVC. * * Further Details * =============== * * Balancing a matrix pair (A,B) includes, first, permuting rows and * columns to isolate eigenvalues, second, applying diagonal similarity * transformation to the rows and columns to make the rows and columns * as close in norm as possible. The computed reciprocal condition * numbers correspond to the balanced matrix. Permuting rows and columns * will not change the condition numbers (in exact arithmetic) but * diagonal scaling will. For further explanation of balancing, see * section 4.11.1.2 of LAPACK Users' Guide. * * An approximate error bound on the chordal distance between the i-th * computed generalized eigenvalue w and the corresponding exact * eigenvalue lambda is * * chord(w, lambda) <= EPS * norm(ABNRM, BBNRM) / RCONDE(I) * * An approximate error bound for the angle between the i-th computed * eigenvector VL(i) or VR(i) is given by * * EPS * norm(ABNRM, BBNRM) / DIF(i). * * For further explanation of the reciprocal condition numbers RCONDE * and RCONDV, see section 4.11 of LAPACK User's Guide. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL ILASCL, ILBSCL, ILV, ILVL, ILVR, LQUERY, PAIR, $ WANTSB, WANTSE, WANTSN, WANTSV CHARACTER CHTEMP INTEGER I, ICOLS, IERR, IJOBVL, IJOBVR, IN, IROWS, $ ITAU, IWRK, IWRK1, J, JC, JR, M, MAXWRK, $ MINWRK, MM DOUBLE PRECISION ANRM, ANRMTO, BIGNUM, BNRM, BNRMTO, EPS, $ SMLNUM, TEMP * .. * .. Local Arrays .. LOGICAL LDUMMA( 1 ) * .. * .. External Subroutines .. EXTERNAL DGEQRF, DGGBAK, DGGBAL, DGGHRD, DHGEQZ, DLACPY, $ DLASCL, DLASET, DORGQR, DORMQR, DTGEVC, DTGSNA, $ XERBLA * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANGE EXTERNAL LSAME, ILAENV, DLAMCH, DLANGE * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, SQRT * .. * .. Executable Statements .. * * Decode the input arguments * IF( LSAME( JOBVL, 'N' ) ) THEN IJOBVL = 1 ILVL = .FALSE. ELSE IF( LSAME( JOBVL, 'V' ) ) THEN IJOBVL = 2 ILVL = .TRUE. ELSE IJOBVL = -1 ILVL = .FALSE. END IF * IF( LSAME( JOBVR, 'N' ) ) THEN IJOBVR = 1 ILVR = .FALSE. ELSE IF( LSAME( JOBVR, 'V' ) ) THEN IJOBVR = 2 ILVR = .TRUE. ELSE IJOBVR = -1 ILVR = .FALSE. END IF ILV = ILVL .OR. ILVR * WANTSN = LSAME( SENSE, 'N' ) WANTSE = LSAME( SENSE, 'E' ) WANTSV = LSAME( SENSE, 'V' ) WANTSB = LSAME( SENSE, 'B' ) * * Test the input arguments * INFO = 0 LQUERY = ( LWORK.EQ.-1 ) IF( .NOT.( LSAME( BALANC, 'N' ) .OR. LSAME( BALANC, $ 'S' ) .OR. LSAME( BALANC, 'P' ) .OR. LSAME( BALANC, 'B' ) ) ) $ THEN INFO = -1 ELSE IF( IJOBVL.LE.0 ) THEN INFO = -2 ELSE IF( IJOBVR.LE.0 ) THEN INFO = -3 ELSE IF( .NOT.( WANTSN .OR. WANTSE .OR. WANTSB .OR. WANTSV ) ) $ THEN INFO = -4 ELSE IF( N.LT.0 ) THEN INFO = -5 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -7 ELSE IF( LDB.LT.MAX( 1, N ) ) THEN INFO = -9 ELSE IF( LDVL.LT.1 .OR. ( ILVL .AND. LDVL.LT.N ) ) THEN INFO = -14 ELSE IF( LDVR.LT.1 .OR. ( ILVR .AND. LDVR.LT.N ) ) THEN INFO = -16 END IF * * Compute workspace * (Note: Comments in the code beginning "Workspace:" describe the * minimal amount of workspace needed at that point in the code, * as well as the preferred amount for good performance. * NB refers to the optimal block size for the immediately * following subroutine, as returned by ILAENV. The workspace is * computed assuming ILO = 1 and IHI = N, the worst case.) * MINWRK = 1 IF( INFO.EQ.0 .AND. ( LWORK.GE.1 .OR. LQUERY ) ) THEN MAXWRK = 5*N + N*ILAENV( 1, 'DGEQRF', ' ', N, 1, N, 0 ) MINWRK = MAX( 1, 6*N ) IF( WANTSE ) THEN MINWRK = MAX( 1, 12*N ) ELSE IF( WANTSV .OR. WANTSB ) THEN MINWRK = 2*N*N + 12*N + 16 MAXWRK = MAX( MAXWRK, 2*N*N+12*N+16 ) END IF WORK( 1 ) = MAXWRK END IF * IF( LWORK.LT.MINWRK .AND. .NOT.LQUERY ) THEN INFO = -26 END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGGEVX', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * * * Get machine constants * EPS = DLAMCH( 'P' ) SMLNUM = DLAMCH( 'S' ) BIGNUM = ONE / SMLNUM CALL DLABAD( SMLNUM, BIGNUM ) SMLNUM = SQRT( SMLNUM ) / EPS BIGNUM = ONE / SMLNUM * * Scale A if max element outside range [SMLNUM,BIGNUM] * ANRM = DLANGE( 'M', N, N, A, LDA, WORK ) ILASCL = .FALSE. IF( ANRM.GT.ZERO .AND. ANRM.LT.SMLNUM ) THEN ANRMTO = SMLNUM ILASCL = .TRUE. ELSE IF( ANRM.GT.BIGNUM ) THEN ANRMTO = BIGNUM ILASCL = .TRUE. END IF IF( ILASCL ) $ CALL DLASCL( 'G', 0, 0, ANRM, ANRMTO, N, N, A, LDA, IERR ) * * Scale B if max element outside range [SMLNUM,BIGNUM] * BNRM = DLANGE( 'M', N, N, B, LDB, WORK ) ILBSCL = .FALSE. IF( BNRM.GT.ZERO .AND. BNRM.LT.SMLNUM ) THEN BNRMTO = SMLNUM ILBSCL = .TRUE. ELSE IF( BNRM.GT.BIGNUM ) THEN BNRMTO = BIGNUM ILBSCL = .TRUE. END IF IF( ILBSCL ) $ CALL DLASCL( 'G', 0, 0, BNRM, BNRMTO, N, N, B, LDB, IERR ) * * Permute and/or balance the matrix pair (A,B) * (Workspace: need 6*N) * CALL DGGBAL( BALANC, N, A, LDA, B, LDB, ILO, IHI, LSCALE, RSCALE, $ WORK, IERR ) * * Compute ABNRM and BBNRM * ABNRM = DLANGE( '1', N, N, A, LDA, WORK( 1 ) ) IF( ILASCL ) THEN WORK( 1 ) = ABNRM CALL DLASCL( 'G', 0, 0, ANRMTO, ANRM, 1, 1, WORK( 1 ), 1, $ IERR ) ABNRM = WORK( 1 ) END IF * BBNRM = DLANGE( '1', N, N, B, LDB, WORK( 1 ) ) IF( ILBSCL ) THEN WORK( 1 ) = BBNRM CALL DLASCL( 'G', 0, 0, BNRMTO, BNRM, 1, 1, WORK( 1 ), 1, $ IERR ) BBNRM = WORK( 1 ) END IF * * Reduce B to triangular form (QR decomposition of B) * (Workspace: need N, prefer N*NB ) * IROWS = IHI + 1 - ILO IF( ILV .OR. .NOT.WANTSN ) THEN ICOLS = N + 1 - ILO ELSE ICOLS = IROWS END IF ITAU = 1 IWRK = ITAU + IROWS CALL DGEQRF( IROWS, ICOLS, B( ILO, ILO ), LDB, WORK( ITAU ), $ WORK( IWRK ), LWORK+1-IWRK, IERR ) * * Apply the orthogonal transformation to A * (Workspace: need N, prefer N*NB) * CALL DORMQR( 'L', 'T', IROWS, ICOLS, IROWS, B( ILO, ILO ), LDB, $ WORK( ITAU ), A( ILO, ILO ), LDA, WORK( IWRK ), $ LWORK+1-IWRK, IERR ) * * Initialize VL and/or VR * (Workspace: need N, prefer N*NB) * IF( ILVL ) THEN CALL DLASET( 'Full', N, N, ZERO, ONE, VL, LDVL ) CALL DLACPY( 'L', IROWS-1, IROWS-1, B( ILO+1, ILO ), LDB, $ VL( ILO+1, ILO ), LDVL ) CALL DORGQR( IROWS, IROWS, IROWS, VL( ILO, ILO ), LDVL, $ WORK( ITAU ), WORK( IWRK ), LWORK+1-IWRK, IERR ) END IF * IF( ILVR ) $ CALL DLASET( 'Full', N, N, ZERO, ONE, VR, LDVR ) * * Reduce to generalized Hessenberg form * (Workspace: none needed) * IF( ILV .OR. .NOT.WANTSN ) THEN * * Eigenvectors requested -- work on whole matrix. * CALL DGGHRD( JOBVL, JOBVR, N, ILO, IHI, A, LDA, B, LDB, VL, $ LDVL, VR, LDVR, IERR ) ELSE CALL DGGHRD( 'N', 'N', IROWS, 1, IROWS, A( ILO, ILO ), LDA, $ B( ILO, ILO ), LDB, VL, LDVL, VR, LDVR, IERR ) END IF * * Perform QZ algorithm (Compute eigenvalues, and optionally, the * Schur forms and Schur vectors) * (Workspace: need N) * IF( ILV .OR. .NOT.WANTSN ) THEN CHTEMP = 'S' ELSE CHTEMP = 'E' END IF * CALL DHGEQZ( CHTEMP, JOBVL, JOBVR, N, ILO, IHI, A, LDA, B, LDB, $ ALPHAR, ALPHAI, BETA, VL, LDVL, VR, LDVR, WORK, $ LWORK, IERR ) IF( IERR.NE.0 ) THEN IF( IERR.GT.0 .AND. IERR.LE.N ) THEN INFO = IERR ELSE IF( IERR.GT.N .AND. IERR.LE.2*N ) THEN INFO = IERR - N ELSE INFO = N + 1 END IF GO TO 130 END IF * * Compute Eigenvectors and estimate condition numbers if desired * (Workspace: DTGEVC: need 6*N * DTGSNA: need 2*N*(N+2)+16 if SENSE = 'V' or 'B', * need N otherwise ) * IF( ILV .OR. .NOT.WANTSN ) THEN IF( ILV ) THEN IF( ILVL ) THEN IF( ILVR ) THEN CHTEMP = 'B' ELSE CHTEMP = 'L' END IF ELSE CHTEMP = 'R' END IF * CALL DTGEVC( CHTEMP, 'B', LDUMMA, N, A, LDA, B, LDB, VL, $ LDVL, VR, LDVR, N, IN, WORK, IERR ) IF( IERR.NE.0 ) THEN INFO = N + 2 GO TO 130 END IF END IF * IF( .NOT.WANTSN ) THEN * * compute eigenvectors (DTGEVC) and estimate condition * numbers (DTGSNA). Note that the definition of the condition * number is not invariant under transformation (u,v) to * (Q*u, Z*v), where (u,v) are eigenvectors of the generalized * Schur form (S,T), Q and Z are orthogonal matrices. In order * to avoid using extra 2*N*N workspace, we have to recalculate * eigenvectors and estimate one condition numbers at a time. * PAIR = .FALSE. DO 20 I = 1, N * IF( PAIR ) THEN PAIR = .FALSE. GO TO 20 END IF MM = 1 IF( I.LT.N ) THEN IF( A( I+1, I ).NE.ZERO ) THEN PAIR = .TRUE. MM = 2 END IF END IF * DO 10 J = 1, N BWORK( J ) = .FALSE. 10 CONTINUE IF( MM.EQ.1 ) THEN BWORK( I ) = .TRUE. ELSE IF( MM.EQ.2 ) THEN BWORK( I ) = .TRUE. BWORK( I+1 ) = .TRUE. END IF * IWRK = MM*N + 1 IWRK1 = IWRK + MM*N * * Compute a pair of left and right eigenvectors. * (compute workspace: need up to 4*N + 6*N) * IF( WANTSE .OR. WANTSB ) THEN CALL DTGEVC( 'B', 'S', BWORK, N, A, LDA, B, LDB, $ WORK( 1 ), N, WORK( IWRK ), N, MM, M, $ WORK( IWRK1 ), IERR ) IF( IERR.NE.0 ) THEN INFO = N + 2 GO TO 130 END IF END IF * CALL DTGSNA( SENSE, 'S', BWORK, N, A, LDA, B, LDB, $ WORK( 1 ), N, WORK( IWRK ), N, RCONDE( I ), $ RCONDV( I ), MM, M, WORK( IWRK1 ), $ LWORK-IWRK1+1, IWORK, IERR ) * 20 CONTINUE END IF END IF * * Undo balancing on VL and VR and normalization * (Workspace: none needed) * IF( ILVL ) THEN CALL DGGBAK( BALANC, 'L', N, ILO, IHI, LSCALE, RSCALE, N, VL, $ LDVL, IERR ) * DO 70 JC = 1, N IF( ALPHAI( JC ).LT.ZERO ) $ GO TO 70 TEMP = ZERO IF( ALPHAI( JC ).EQ.ZERO ) THEN DO 30 JR = 1, N TEMP = MAX( TEMP, ABS( VL( JR, JC ) ) ) 30 CONTINUE ELSE DO 40 JR = 1, N TEMP = MAX( TEMP, ABS( VL( JR, JC ) )+ $ ABS( VL( JR, JC+1 ) ) ) 40 CONTINUE END IF IF( TEMP.LT.SMLNUM ) $ GO TO 70 TEMP = ONE / TEMP IF( ALPHAI( JC ).EQ.ZERO ) THEN DO 50 JR = 1, N VL( JR, JC ) = VL( JR, JC )*TEMP 50 CONTINUE ELSE DO 60 JR = 1, N VL( JR, JC ) = VL( JR, JC )*TEMP VL( JR, JC+1 ) = VL( JR, JC+1 )*TEMP 60 CONTINUE END IF 70 CONTINUE END IF IF( ILVR ) THEN CALL DGGBAK( BALANC, 'R', N, ILO, IHI, LSCALE, RSCALE, N, VR, $ LDVR, IERR ) DO 120 JC = 1, N IF( ALPHAI( JC ).LT.ZERO ) $ GO TO 120 TEMP = ZERO IF( ALPHAI( JC ).EQ.ZERO ) THEN DO 80 JR = 1, N TEMP = MAX( TEMP, ABS( VR( JR, JC ) ) ) 80 CONTINUE ELSE DO 90 JR = 1, N TEMP = MAX( TEMP, ABS( VR( JR, JC ) )+ $ ABS( VR( JR, JC+1 ) ) ) 90 CONTINUE END IF IF( TEMP.LT.SMLNUM ) $ GO TO 120 TEMP = ONE / TEMP IF( ALPHAI( JC ).EQ.ZERO ) THEN DO 100 JR = 1, N VR( JR, JC ) = VR( JR, JC )*TEMP 100 CONTINUE ELSE DO 110 JR = 1, N VR( JR, JC ) = VR( JR, JC )*TEMP VR( JR, JC+1 ) = VR( JR, JC+1 )*TEMP 110 CONTINUE END IF 120 CONTINUE END IF * * Undo scaling if necessary * IF( ILASCL ) THEN CALL DLASCL( 'G', 0, 0, ANRMTO, ANRM, N, 1, ALPHAR, N, IERR ) CALL DLASCL( 'G', 0, 0, ANRMTO, ANRM, N, 1, ALPHAI, N, IERR ) END IF * IF( ILBSCL ) THEN CALL DLASCL( 'G', 0, 0, BNRMTO, BNRM, N, 1, BETA, N, IERR ) END IF * 130 CONTINUE WORK( 1 ) = MAXWRK * RETURN * * End of DGGEVX * END SUBROUTINE DGGGLM( N, M, P, A, LDA, B, LDB, D, X, Y, WORK, LWORK, $ INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER INFO, LDA, LDB, LWORK, M, N, P * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), B( LDB, * ), D( * ), WORK( * ), $ X( * ), Y( * ) * .. * * Purpose * ======= * * DGGGLM solves a general Gauss-Markov linear model (GLM) problem: * * minimize || y ||_2 subject to d = A*x + B*y * x * * where A is an N-by-M matrix, B is an N-by-P matrix, and d is a * given N-vector. It is assumed that M <= N <= M+P, and * * rank(A) = M and rank( A B ) = N. * * Under these assumptions, the constrained equation is always * consistent, and there is a unique solution x and a minimal 2-norm * solution y, which is obtained using a generalized QR factorization * of A and B. * * In particular, if matrix B is square nonsingular, then the problem * GLM is equivalent to the following weighted linear least squares * problem * * minimize || inv(B)*(d-A*x) ||_2 * x * * where inv(B) denotes the inverse of B. * * Arguments * ========= * * N (input) INTEGER * The number of rows of the matrices A and B. N >= 0. * * M (input) INTEGER * The number of columns of the matrix A. 0 <= M <= N. * * P (input) INTEGER * The number of columns of the matrix B. P >= N-M. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,M) * On entry, the N-by-M matrix A. * On exit, A is destroyed. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * B (input/output) DOUBLE PRECISION array, dimension (LDB,P) * On entry, the N-by-P matrix B. * On exit, B is destroyed. * * LDB (input) INTEGER * The leading dimension of the array B. LDB >= max(1,N). * * D (input/output) DOUBLE PRECISION array, dimension (N) * On entry, D is the left hand side of the GLM equation. * On exit, D is destroyed. * * X (output) DOUBLE PRECISION array, dimension (M) * Y (output) DOUBLE PRECISION array, dimension (P) * On exit, X and Y are the solutions of the GLM problem. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= max(1,N+M+P). * For optimum performance, LWORK >= M+min(N,P)+max(N,P)*NB, * where NB is an upper bound for the optimal blocksizes for * DGEQRF, SGERQF, DORMQR and SORMRQ. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit. * < 0: if INFO = -i, the i-th argument had an illegal value. * * =================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL LQUERY INTEGER I, LOPT, LWKOPT, NB, NB1, NB2, NB3, NB4, NP * .. * .. External Subroutines .. EXTERNAL DCOPY, DGEMV, DGGQRF, DORMQR, DORMRQ, DTRSV, $ XERBLA * .. * .. External Functions .. INTEGER ILAENV EXTERNAL ILAENV * .. * .. Intrinsic Functions .. INTRINSIC INT, MAX, MIN * .. * .. Executable Statements .. * * Test the input parameters * INFO = 0 NP = MIN( N, P ) NB1 = ILAENV( 1, 'DGEQRF', ' ', N, M, -1, -1 ) NB2 = ILAENV( 1, 'DGERQF', ' ', N, M, -1, -1 ) NB3 = ILAENV( 1, 'DORMQR', ' ', N, M, P, -1 ) NB4 = ILAENV( 1, 'DORMRQ', ' ', N, M, P, -1 ) NB = MAX( NB1, NB2, NB3, NB4 ) LWKOPT = M + NP + MAX( N, P )*NB WORK( 1 ) = LWKOPT LQUERY = ( LWORK.EQ.-1 ) IF( N.LT.0 ) THEN INFO = -1 ELSE IF( M.LT.0 .OR. M.GT.N ) THEN INFO = -2 ELSE IF( P.LT.0 .OR. P.LT.N-M ) THEN INFO = -3 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -5 ELSE IF( LDB.LT.MAX( 1, N ) ) THEN INFO = -7 ELSE IF( LWORK.LT.MAX( 1, N+M+P ) .AND. .NOT.LQUERY ) THEN INFO = -12 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGGGLM', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * * Compute the GQR factorization of matrices A and B: * * Q'*A = ( R11 ) M, Q'*B*Z' = ( T11 T12 ) M * ( 0 ) N-M ( 0 T22 ) N-M * M M+P-N N-M * * where R11 and T22 are upper triangular, and Q and Z are * orthogonal. * CALL DGGQRF( N, M, P, A, LDA, WORK, B, LDB, WORK( M+1 ), $ WORK( M+NP+1 ), LWORK-M-NP, INFO ) LOPT = WORK( M+NP+1 ) * * Update left-hand-side vector d = Q'*d = ( d1 ) M * ( d2 ) N-M * CALL DORMQR( 'Left', 'Transpose', N, 1, M, A, LDA, WORK, D, $ MAX( 1, N ), WORK( M+NP+1 ), LWORK-M-NP, INFO ) LOPT = MAX( LOPT, INT( WORK( M+NP+1 ) ) ) * * Solve T22*y2 = d2 for y2 * CALL DTRSV( 'Upper', 'No transpose', 'Non unit', N-M, $ B( M+1, M+P-N+1 ), LDB, D( M+1 ), 1 ) CALL DCOPY( N-M, D( M+1 ), 1, Y( M+P-N+1 ), 1 ) * * Set y1 = 0 * DO 10 I = 1, M + P - N Y( I ) = ZERO 10 CONTINUE * * Update d1 = d1 - T12*y2 * CALL DGEMV( 'No transpose', M, N-M, -ONE, B( 1, M+P-N+1 ), LDB, $ Y( M+P-N+1 ), 1, ONE, D, 1 ) * * Solve triangular system: R11*x = d1 * CALL DTRSV( 'Upper', 'No Transpose', 'Non unit', M, A, LDA, D, 1 ) * * Copy D to X * CALL DCOPY( M, D, 1, X, 1 ) * * Backward transformation y = Z'*y * CALL DORMRQ( 'Left', 'Transpose', P, 1, NP, $ B( MAX( 1, N-P+1 ), 1 ), LDB, WORK( M+1 ), Y, $ MAX( 1, P ), WORK( M+NP+1 ), LWORK-M-NP, INFO ) WORK( 1 ) = M + NP + MAX( LOPT, INT( WORK( M+NP+1 ) ) ) * RETURN * * End of DGGGLM * END SUBROUTINE DGGLSE( M, N, P, A, LDA, B, LDB, C, D, X, WORK, LWORK, $ INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER INFO, LDA, LDB, LWORK, M, N, P * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), B( LDB, * ), C( * ), D( * ), $ WORK( * ), X( * ) * .. * * Purpose * ======= * * DGGLSE solves the linear equality-constrained least squares (LSE) * problem: * * minimize || c - A*x ||_2 subject to B*x = d * * where A is an M-by-N matrix, B is a P-by-N matrix, c is a given * M-vector, and d is a given P-vector. It is assumed that * P <= N <= M+P, and * * rank(B) = P and rank( ( A ) ) = N. * ( ( B ) ) * * These conditions ensure that the LSE problem has a unique solution, * which is obtained using a GRQ factorization of the matrices B and A. * * Arguments * ========= * * M (input) INTEGER * The number of rows of the matrix A. M >= 0. * * N (input) INTEGER * The number of columns of the matrices A and B. N >= 0. * * P (input) INTEGER * The number of rows of the matrix B. 0 <= P <= N <= M+P. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the M-by-N matrix A. * On exit, A is destroyed. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,M). * * B (input/output) DOUBLE PRECISION array, dimension (LDB,N) * On entry, the P-by-N matrix B. * On exit, B is destroyed. * * LDB (input) INTEGER * The leading dimension of the array B. LDB >= max(1,P). * * C (input/output) DOUBLE PRECISION array, dimension (M) * On entry, C contains the right hand side vector for the * least squares part of the LSE problem. * On exit, the residual sum of squares for the solution * is given by the sum of squares of elements N-P+1 to M of * vector C. * * D (input/output) DOUBLE PRECISION array, dimension (P) * On entry, D contains the right hand side vector for the * constrained equation. * On exit, D is destroyed. * * X (output) DOUBLE PRECISION array, dimension (N) * On exit, X is the solution of the LSE problem. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= max(1,M+N+P). * For optimum performance LWORK >= P+min(M,N)+max(M,N)*NB, * where NB is an upper bound for the optimal blocksizes for * DGEQRF, SGERQF, DORMQR and SORMRQ. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit. * < 0: if INFO = -i, the i-th argument had an illegal value. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE PARAMETER ( ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL LQUERY INTEGER LOPT, LWKOPT, MN, NB, NB1, NB2, NB3, NB4, NR * .. * .. External Subroutines .. EXTERNAL DAXPY, DCOPY, DGEMV, DGGRQF, DORMQR, DORMRQ, $ DTRMV, DTRSV, XERBLA * .. * .. External Functions .. INTEGER ILAENV EXTERNAL ILAENV * .. * .. Intrinsic Functions .. INTRINSIC INT, MAX, MIN * .. * .. Executable Statements .. * * Test the input parameters * INFO = 0 MN = MIN( M, N ) NB1 = ILAENV( 1, 'DGEQRF', ' ', M, N, -1, -1 ) NB2 = ILAENV( 1, 'DGERQF', ' ', M, N, -1, -1 ) NB3 = ILAENV( 1, 'DORMQR', ' ', M, N, P, -1 ) NB4 = ILAENV( 1, 'DORMRQ', ' ', M, N, P, -1 ) NB = MAX( NB1, NB2, NB3, NB4 ) LWKOPT = P + MN + MAX( M, N )*NB WORK( 1 ) = LWKOPT LQUERY = ( LWORK.EQ.-1 ) IF( M.LT.0 ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 ELSE IF( P.LT.0 .OR. P.GT.N .OR. P.LT.N-M ) THEN INFO = -3 ELSE IF( LDA.LT.MAX( 1, M ) ) THEN INFO = -5 ELSE IF( LDB.LT.MAX( 1, P ) ) THEN INFO = -7 ELSE IF( LWORK.LT.MAX( 1, M+N+P ) .AND. .NOT.LQUERY ) THEN INFO = -12 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGGLSE', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * * Compute the GRQ factorization of matrices B and A: * * B*Q' = ( 0 T12 ) P Z'*A*Q' = ( R11 R12 ) N-P * N-P P ( 0 R22 ) M+P-N * N-P P * * where T12 and R11 are upper triangular, and Q and Z are * orthogonal. * CALL DGGRQF( P, M, N, B, LDB, WORK, A, LDA, WORK( P+1 ), $ WORK( P+MN+1 ), LWORK-P-MN, INFO ) LOPT = WORK( P+MN+1 ) * * Update c = Z'*c = ( c1 ) N-P * ( c2 ) M+P-N * CALL DORMQR( 'Left', 'Transpose', M, 1, MN, A, LDA, WORK( P+1 ), $ C, MAX( 1, M ), WORK( P+MN+1 ), LWORK-P-MN, INFO ) LOPT = MAX( LOPT, INT( WORK( P+MN+1 ) ) ) * * Solve T12*x2 = d for x2 * CALL DTRSV( 'Upper', 'No transpose', 'Non unit', P, B( 1, N-P+1 ), $ LDB, D, 1 ) * * Update c1 * CALL DGEMV( 'No transpose', N-P, P, -ONE, A( 1, N-P+1 ), LDA, D, $ 1, ONE, C, 1 ) * * Sovle R11*x1 = c1 for x1 * CALL DTRSV( 'Upper', 'No transpose', 'Non unit', N-P, A, LDA, C, $ 1 ) * * Put the solutions in X * CALL DCOPY( N-P, C, 1, X, 1 ) CALL DCOPY( P, D, 1, X( N-P+1 ), 1 ) * * Compute the residual vector: * IF( M.LT.N ) THEN NR = M + P - N CALL DGEMV( 'No transpose', NR, N-M, -ONE, A( N-P+1, M+1 ), $ LDA, D( NR+1 ), 1, ONE, C( N-P+1 ), 1 ) ELSE NR = P END IF CALL DTRMV( 'Upper', 'No transpose', 'Non unit', NR, $ A( N-P+1, N-P+1 ), LDA, D, 1 ) CALL DAXPY( NR, -ONE, D, 1, C( N-P+1 ), 1 ) * * Backward transformation x = Q'*x * CALL DORMRQ( 'Left', 'Transpose', N, 1, P, B, LDB, WORK( 1 ), X, $ N, WORK( P+MN+1 ), LWORK-P-MN, INFO ) WORK( 1 ) = P + MN + MAX( LOPT, INT( WORK( P+MN+1 ) ) ) * RETURN * * End of DGGLSE * END SUBROUTINE DGGSVD( JOBU, JOBV, JOBQ, M, N, P, K, L, A, LDA, B, $ LDB, ALPHA, BETA, U, LDU, V, LDV, Q, LDQ, WORK, $ IWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBQ, JOBU, JOBV INTEGER INFO, K, L, LDA, LDB, LDQ, LDU, LDV, M, N, P * .. * .. Array Arguments .. INTEGER IWORK( * ) DOUBLE PRECISION A( LDA, * ), ALPHA( * ), B( LDB, * ), $ BETA( * ), Q( LDQ, * ), U( LDU, * ), $ V( LDV, * ), WORK( * ) * .. * * Purpose * ======= * * DGGSVD computes the generalized singular value decomposition (GSVD) * of an M-by-N real matrix A and P-by-N real matrix B: * * U'*A*Q = D1*( 0 R ), V'*B*Q = D2*( 0 R ) * * where U, V and Q are orthogonal matrices, and Z' is the transpose * of Z. Let K+L = the effective numerical rank of the matrix (A',B')', * then R is a K+L-by-K+L nonsingular upper triangular matrix, D1 and * D2 are M-by-(K+L) and P-by-(K+L) "diagonal" matrices and of the * following structures, respectively: * * 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 ) * L ( 0 0 R22 ) * * 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. * * (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 routine computes C, S, R, and optionally the orthogonal * transformation matrices U, V and Q. * * In particular, if B is an N-by-N nonsingular matrix, then the GSVD of * A and B implicitly gives the SVD of A*inv(B): * A*inv(B) = U*(D1*inv(D2))*V'. * If ( A',B')' has orthonormal columns, then the GSVD of A and B is * also equal to the CS decomposition of A and B. Furthermore, the GSVD * can be used to derive the solution of the eigenvalue problem: * A'*A x = lambda* B'*B x. * In some literature, the GSVD of A and B is presented in the form * U'*A*X = ( 0 D1 ), V'*B*X = ( 0 D2 ) * where U and V are orthogonal and X is nonsingular, D1 and D2 are * ``diagonal''. The former GSVD form can be converted to the latter * form by taking the nonsingular matrix X as * * X = Q*( I 0 ) * ( 0 inv(R) ). * * Arguments * ========= * * JOBU (input) CHARACTER*1 * = 'U': Orthogonal matrix U is computed; * = 'N': U is not computed. * * JOBV (input) CHARACTER*1 * = 'V': Orthogonal matrix V is computed; * = 'N': V is not computed. * * JOBQ (input) CHARACTER*1 * = 'Q': Orthogonal matrix Q is computed; * = 'N': Q is not computed. * * M (input) INTEGER * The number of rows of the matrix A. M >= 0. * * N (input) INTEGER * The number of columns of the matrices A and B. N >= 0. * * P (input) INTEGER * The number of rows of the matrix B. P >= 0. * * K (output) INTEGER * L (output) INTEGER * On exit, K and L specify the dimension of the subblocks * described in the Purpose section. * K + L = effective numerical rank of (A',B')'. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the M-by-N matrix A. * On exit, A 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) DOUBLE PRECISION array, dimension (LDB,N) * On entry, the P-by-N matrix B. * On exit, B contains the triangular matrix R if M-K-L < 0. * See Purpose for details. * * LDB (input) INTEGER * The leading dimension of the array B. LDA >= max(1,P). * * ALPHA (output) DOUBLE PRECISION array, dimension (N) * BETA (output) DOUBLE PRECISION 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) = C, * BETA(K+1:K+L) = 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 * and * ALPHA(K+L+1:N) = 0 * BETA(K+L+1:N) = 0 * * U (output) DOUBLE PRECISION array, dimension (LDU,M) * If JOBU = 'U', U contains the M-by-M orthogonal matrix 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 (output) DOUBLE PRECISION array, dimension (LDV,P) * If JOBV = 'V', V contains the P-by-P orthogonal matrix 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 (output) DOUBLE PRECISION array, dimension (LDQ,N) * If JOBQ = 'Q', Q contains the N-by-N orthogonal matrix 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) DOUBLE PRECISION array, * dimension (max(3*N,M,P)+N) * * IWORK (workspace/output) INTEGER array, dimension (N) * On exit, IWORK stores the sorting information. More * precisely, the following loop will sort ALPHA * for I = K+1, min(M,K+L) * swap ALPHA(I) and ALPHA(IWORK(I)) * endfor * such that ALPHA(1) >= ALPHA(2) >= ... >= ALPHA(N). * * INFO (output)INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: if INFO = 1, the Jacobi-type procedure failed to * converge. For further details, see subroutine DTGSJA. * * Internal Parameters * =================== * * TOLA DOUBLE PRECISION * TOLB DOUBLE PRECISION * TOLA and TOLB are the thresholds to determine the effective * rank of (A',B')'. Generally, they are set to * TOLA = MAX(M,N)*norm(A)*MAZHEPS, * TOLB = MAX(P,N)*norm(B)*MAZHEPS. * The size of TOLA and TOLB may affect the size of backward * errors of the decomposition. * * Further Details * =============== * * 2-96 Based on modifications by * Ming Gu and Huan Ren, Computer Science Division, University of * California at Berkeley, USA * * ===================================================================== * * .. Local Scalars .. LOGICAL WANTQ, WANTU, WANTV INTEGER I, IBND, ISUB, J, NCYCLE DOUBLE PRECISION ANORM, BNORM, SMAX, TEMP, TOLA, TOLB, ULP, UNFL * .. * .. External Functions .. LOGICAL LSAME DOUBLE PRECISION DLAMCH, DLANGE EXTERNAL LSAME, DLAMCH, DLANGE * .. * .. External Subroutines .. EXTERNAL DCOPY, DGGSVP, DTGSJA, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN * .. * .. Executable Statements .. * * Test the input parameters * WANTU = LSAME( JOBU, 'U' ) WANTV = LSAME( JOBV, 'V' ) WANTQ = LSAME( JOBQ, 'Q' ) * INFO = 0 IF( .NOT.( WANTU .OR. LSAME( JOBU, 'N' ) ) ) THEN INFO = -1 ELSE IF( .NOT.( WANTV .OR. LSAME( JOBV, 'N' ) ) ) THEN INFO = -2 ELSE IF( .NOT.( WANTQ .OR. LSAME( JOBQ, 'N' ) ) ) THEN INFO = -3 ELSE IF( M.LT.0 ) THEN INFO = -4 ELSE IF( N.LT.0 ) THEN INFO = -5 ELSE IF( P.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 = -16 ELSE IF( LDV.LT.1 .OR. ( WANTV .AND. LDV.LT.P ) ) THEN INFO = -18 ELSE IF( LDQ.LT.1 .OR. ( WANTQ .AND. LDQ.LT.N ) ) THEN INFO = -20 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGGSVD', -INFO ) RETURN END IF * * Compute the Frobenius norm of matrices A and B * ANORM = DLANGE( '1', M, N, A, LDA, WORK ) BNORM = DLANGE( '1', P, N, B, LDB, WORK ) * * Get machine precision and set up threshold for determining * the effective numerical rank of the matrices A and B. * ULP = DLAMCH( 'Precision' ) UNFL = DLAMCH( 'Safe Minimum' ) TOLA = MAX( M, N )*MAX( ANORM, UNFL )*ULP TOLB = MAX( P, N )*MAX( BNORM, UNFL )*ULP * * Preprocessing * CALL DGGSVP( JOBU, JOBV, JOBQ, M, P, N, A, LDA, B, LDB, TOLA, $ TOLB, K, L, U, LDU, V, LDV, Q, LDQ, IWORK, WORK, $ WORK( N+1 ), INFO ) * * Compute the GSVD of two upper "triangular" matrices * CALL DTGSJA( 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 ) * * Sort the singular values and store the pivot indices in IWORK * Copy ALPHA to WORK, then sort ALPHA in WORK * CALL DCOPY( N, ALPHA, 1, WORK, 1 ) IBND = MIN( L, M-K ) DO 20 I = 1, IBND * * Scan for largest ALPHA(K+I) * ISUB = I SMAX = WORK( K+I ) DO 10 J = I + 1, IBND TEMP = WORK( K+J ) IF( TEMP.GT.SMAX ) THEN ISUB = J SMAX = TEMP END IF 10 CONTINUE IF( ISUB.NE.I ) THEN WORK( K+ISUB ) = WORK( K+I ) WORK( K+I ) = SMAX IWORK( K+I ) = K + ISUB ELSE IWORK( K+I ) = K + I END IF 20 CONTINUE * RETURN * * End of DGGSVD * END SUBROUTINE DLANV2( A, B, C, D, RT1R, RT1I, RT2R, RT2I, CS, SN ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. DOUBLE PRECISION A, B, C, CS, D, RT1I, RT1R, RT2I, RT2R, SN * .. * * Purpose * ======= * * DLANV2 computes the Schur factorization of a real 2-by-2 nonsymmetric * matrix in standard form: * * [ A B ] = [ CS -SN ] [ AA BB ] [ CS SN ] * [ C D ] [ SN CS ] [ CC DD ] [-SN CS ] * * where either * 1) CC = 0 so that AA and DD are real eigenvalues of the matrix, or * 2) AA = DD and BB*CC < 0, so that AA + or - sqrt(BB*CC) are complex * conjugate eigenvalues. * * Arguments * ========= * * A (input/output) DOUBLE PRECISION * B (input/output) DOUBLE PRECISION * C (input/output) DOUBLE PRECISION * D (input/output) DOUBLE PRECISION * On entry, the elements of the input matrix. * On exit, they are overwritten by the elements of the * standardised Schur form. * * RT1R (output) DOUBLE PRECISION * RT1I (output) DOUBLE PRECISION * RT2R (output) DOUBLE PRECISION * RT2I (output) DOUBLE PRECISION * The real and imaginary parts of the eigenvalues. If the * eigenvalues are a complex conjugate pair, RT1I > 0. * * CS (output) DOUBLE PRECISION * SN (output) DOUBLE PRECISION * Parameters of the rotation matrix. * * Further Details * =============== * * Modified by V. Sima, Research Institute for Informatics, Bucharest, * Romania, to reduce the risk of cancellation errors, * when computing real eigenvalues, and to ensure, if possible, that * abs(RT1R) >= abs(RT2R). * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, HALF, ONE PARAMETER ( ZERO = 0.0D+0, HALF = 0.5D+0, ONE = 1.0D+0 ) DOUBLE PRECISION MULTPL PARAMETER ( MULTPL = 4.0D+0 ) * .. * .. Local Scalars .. DOUBLE PRECISION AA, BB, BCMAX, BCMIS, CC, CS1, DD, EPS, P, SAB, $ SAC, SCALE, SIGMA, SN1, TAU, TEMP, Z * .. * .. External Functions .. DOUBLE PRECISION DLAMCH, DLAPY2 EXTERNAL DLAMCH, DLAPY2 * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, MIN, SIGN, SQRT * .. * .. Executable Statements .. * EPS = DLAMCH( 'P' ) IF( C.EQ.ZERO ) THEN CS = ONE SN = ZERO GO TO 10 * ELSE IF( B.EQ.ZERO ) THEN * * Swap rows and columns * CS = ZERO SN = ONE TEMP = D D = A A = TEMP B = -C C = ZERO GO TO 10 ELSE IF( ( A-D ).EQ.ZERO .AND. SIGN( ONE, B ).NE.SIGN( ONE, C ) ) $ THEN CS = ONE SN = ZERO GO TO 10 ELSE * TEMP = A - D P = HALF*TEMP BCMAX = MAX( ABS( B ), ABS( C ) ) BCMIS = MIN( ABS( B ), ABS( C ) )*SIGN( ONE, B )*SIGN( ONE, C ) SCALE = MAX( ABS( P ), BCMAX ) Z = ( P / SCALE )*P + ( BCMAX / SCALE )*BCMIS * * If Z is of the order of the machine accuracy, postpone the * decision on the nature of eigenvalues * IF( Z.GE.MULTPL*EPS ) THEN * * Real eigenvalues. Compute A and D. * Z = P + SIGN( SQRT( SCALE )*SQRT( Z ), P ) A = D + Z D = D - ( BCMAX / Z )*BCMIS * * Compute B and the rotation matrix * TAU = DLAPY2( C, Z ) CS = Z / TAU SN = C / TAU B = B - C C = ZERO ELSE * * Complex eigenvalues, or real (almost) equal eigenvalues. * Make diagonal elements equal. * SIGMA = B + C TAU = DLAPY2( SIGMA, TEMP ) CS = SQRT( HALF*( ONE+ABS( SIGMA ) / TAU ) ) SN = -( P / ( TAU*CS ) )*SIGN( ONE, SIGMA ) * * Compute [ AA BB ] = [ A B ] [ CS -SN ] * [ CC DD ] [ C D ] [ SN CS ] * AA = A*CS + B*SN BB = -A*SN + B*CS CC = C*CS + D*SN DD = -C*SN + D*CS * * Compute [ A B ] = [ CS SN ] [ AA BB ] * [ C D ] [-SN CS ] [ CC DD ] * A = AA*CS + CC*SN B = BB*CS + DD*SN C = -AA*SN + CC*CS D = -BB*SN + DD*CS * TEMP = HALF*( A+D ) A = TEMP D = TEMP * IF( C.NE.ZERO ) THEN IF( B.NE.ZERO ) THEN IF( SIGN( ONE, B ).EQ.SIGN( ONE, C ) ) THEN * * Real eigenvalues: reduce to upper triangular form * SAB = SQRT( ABS( B ) ) SAC = SQRT( ABS( C ) ) P = SIGN( SAB*SAC, C ) TAU = ONE / SQRT( ABS( B+C ) ) A = TEMP + P D = TEMP - P B = B - C C = ZERO CS1 = SAB*TAU SN1 = SAC*TAU TEMP = CS*CS1 - SN*SN1 SN = CS*SN1 + SN*CS1 CS = TEMP END IF ELSE B = -C C = ZERO TEMP = CS CS = -SN SN = TEMP END IF END IF END IF * END IF * 10 CONTINUE * * Store eigenvalues in (RT1R,RT1I) and (RT2R,RT2I). * RT1R = A RT2R = D IF( C.EQ.ZERO ) THEN RT1I = ZERO RT2I = ZERO ELSE RT1I = SQRT( ABS( B ) )*SQRT( ABS( C ) ) RT2I = -RT1I END IF RETURN * * End of DLANV2 * END SUBROUTINE DPBSV( UPLO, N, KD, NRHS, AB, LDAB, B, LDB, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * March 31, 1993 * * .. Scalar Arguments .. CHARACTER UPLO INTEGER INFO, KD, LDAB, LDB, N, NRHS * .. * .. Array Arguments .. DOUBLE PRECISION AB( LDAB, * ), B( LDB, * ) * .. * * Purpose * ======= * * DPBSV computes the solution to a real system of linear equations * A * X = B, * where A is an N-by-N symmetric positive definite band matrix and X * and B are N-by-NRHS matrices. * * The Cholesky decomposition is used to factor A as * A = U**T * U, if UPLO = 'U', or * A = L * L**T, if UPLO = 'L', * where U is an upper triangular band matrix, and L is a lower * triangular band matrix, with the same number of superdiagonals or * subdiagonals as A. The factored form of A is then used to solve the * system of equations A * X = B. * * Arguments * ========= * * UPLO (input) CHARACTER*1 * = 'U': Upper triangle of A is stored; * = 'L': Lower triangle of A is stored. * * N (input) INTEGER * The number of linear equations, i.e., the order of the * matrix A. N >= 0. * * KD (input) INTEGER * The number of superdiagonals of the matrix A if UPLO = 'U', * or the number of subdiagonals if UPLO = 'L'. KD >= 0. * * NRHS (input) INTEGER * The number of right hand sides, i.e., the number of columns * of the matrix B. NRHS >= 0. * * AB (input/output) DOUBLE PRECISION array, dimension (LDAB,N) * On entry, the upper or lower triangle of the symmetric band * matrix A, stored in the first KD+1 rows of the array. The * j-th column of A is stored in the j-th column of the array AB * as follows: * if UPLO = 'U', AB(KD+1+i-j,j) = A(i,j) for max(1,j-KD)<=i<=j; * if UPLO = 'L', AB(1+i-j,j) = A(i,j) for j<=i<=min(N,j+KD). * See below for further details. * * On exit, if INFO = 0, the triangular factor U or L from the * Cholesky factorization A = U**T*U or A = L*L**T of the band * matrix A, in the same storage format as A. * * LDAB (input) INTEGER * The leading dimension of the array AB. LDAB >= KD+1. * * B (input/output) DOUBLE PRECISION array, dimension (LDB,NRHS) * On entry, the N-by-NRHS right hand side matrix B. * On exit, if INFO = 0, the N-by-NRHS solution matrix X. * * LDB (input) INTEGER * The leading dimension of the array B. LDB >= max(1,N). * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = i, the leading minor of order i of A is not * positive definite, so the factorization could not be * completed, and the solution has not been computed. * * Further Details * =============== * * The band storage scheme is illustrated by the following example, when * N = 6, KD = 2, and UPLO = 'U': * * On entry: On exit: * * * * a13 a24 a35 a46 * * u13 u24 u35 u46 * * a12 a23 a34 a45 a56 * u12 u23 u34 u45 u56 * a11 a22 a33 a44 a55 a66 u11 u22 u33 u44 u55 u66 * * Similarly, if UPLO = 'L' the format of A is as follows: * * On entry: On exit: * * a11 a22 a33 a44 a55 a66 l11 l22 l33 l44 l55 l66 * a21 a32 a43 a54 a65 * l21 l32 l43 l54 l65 * * a31 a42 a53 a64 * * l31 l42 l53 l64 * * * * Array elements marked * are not used by the routine. * * ===================================================================== * * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. External Subroutines .. EXTERNAL DPBTRF, DPBTRS, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 IF( .NOT.LSAME( UPLO, 'U' ) .AND. .NOT.LSAME( UPLO, 'L' ) ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 ELSE IF( KD.LT.0 ) THEN INFO = -3 ELSE IF( NRHS.LT.0 ) THEN INFO = -4 ELSE IF( LDAB.LT.KD+1 ) THEN INFO = -6 ELSE IF( LDB.LT.MAX( 1, N ) ) THEN INFO = -8 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DPBSV ', -INFO ) RETURN END IF * * Compute the Cholesky factorization A = U'*U or A = L*L'. * CALL DPBTRF( UPLO, N, KD, AB, LDAB, INFO ) IF( INFO.EQ.0 ) THEN * * Solve the system A*X = B, overwriting B with X. * CALL DPBTRS( UPLO, N, KD, NRHS, AB, LDAB, B, LDB, INFO ) * END IF RETURN * * End of DPBSV * END SUBROUTINE DPBSVX( FACT, UPLO, N, KD, NRHS, AB, LDAB, AFB, LDAFB, $ EQUED, S, B, LDB, X, LDX, RCOND, FERR, BERR, $ WORK, IWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER EQUED, FACT, UPLO INTEGER INFO, KD, LDAB, LDAFB, LDB, LDX, N, NRHS DOUBLE PRECISION RCOND * .. * .. Array Arguments .. INTEGER IWORK( * ) DOUBLE PRECISION AB( LDAB, * ), AFB( LDAFB, * ), B( LDB, * ), $ BERR( * ), FERR( * ), S( * ), WORK( * ), $ X( LDX, * ) * .. * * Purpose * ======= * * DPBSVX uses the Cholesky factorization A = U**T*U or A = L*L**T to * compute the solution to a real system of linear equations * A * X = B, * where A is an N-by-N symmetric positive definite band matrix and X * and B are N-by-NRHS matrices. * * Error bounds on the solution and a condition estimate are also * provided. * * Description * =========== * * The following steps are performed: * * 1. If FACT = 'E', real scaling factors are computed to equilibrate * the system: * diag(S) * A * diag(S) * inv(diag(S)) * X = diag(S) * B * Whether or not the system will be equilibrated depends on the * scaling of the matrix A, but if equilibration is used, A is * overwritten by diag(S)*A*diag(S) and B by diag(S)*B. * * 2. If FACT = 'N' or 'E', the Cholesky decomposition is used to * factor the matrix A (after equilibration if FACT = 'E') as * A = U**T * U, if UPLO = 'U', or * A = L * L**T, if UPLO = 'L', * where U is an upper triangular band matrix, and L is a lower * triangular band matrix. * * 3. If the leading i-by-i principal minor is not positive definite, * then the routine returns with INFO = i. Otherwise, the factored * form of A is used to estimate the condition number of the matrix * A. If the reciprocal of the condition number is less than machine * precision, INFO = N+1 is returned as a warning, but the routine * still goes on to solve for X and compute error bounds as * described below. * * 4. The system of equations is solved for X using the factored form * of A. * * 5. Iterative refinement is applied to improve the computed solution * matrix and calculate error bounds and backward error estimates * for it. * * 6. If equilibration was used, the matrix X is premultiplied by * diag(S) so that it solves the original system before * equilibration. * * Arguments * ========= * * FACT (input) CHARACTER*1 * Specifies whether or not the factored form of the matrix A is * supplied on entry, and if not, whether the matrix A should be * equilibrated before it is factored. * = 'F': On entry, AFB contains the factored form of A. * If EQUED = 'Y', the matrix A has been equilibrated * with scaling factors given by S. AB and AFB will not * be modified. * = 'N': The matrix A will be copied to AFB and factored. * = 'E': The matrix A will be equilibrated if necessary, then * copied to AFB and factored. * * UPLO (input) CHARACTER*1 * = 'U': Upper triangle of A is stored; * = 'L': Lower triangle of A is stored. * * N (input) INTEGER * The number of linear equations, i.e., the order of the * matrix A. N >= 0. * * KD (input) INTEGER * The number of superdiagonals of the matrix A if UPLO = 'U', * or the number of subdiagonals if UPLO = 'L'. KD >= 0. * * NRHS (input) INTEGER * The number of right-hand sides, i.e., the number of columns * of the matrices B and X. NRHS >= 0. * * AB (input/output) DOUBLE PRECISION array, dimension (LDAB,N) * On entry, the upper or lower triangle of the symmetric band * matrix A, stored in the first KD+1 rows of the array, except * if FACT = 'F' and EQUED = 'Y', then A must contain the * equilibrated matrix diag(S)*A*diag(S). The j-th column of A * is stored in the j-th column of the array AB as follows: * if UPLO = 'U', AB(KD+1+i-j,j) = A(i,j) for max(1,j-KD)<=i<=j; * if UPLO = 'L', AB(1+i-j,j) = A(i,j) for j<=i<=min(N,j+KD). * See below for further details. * * On exit, if FACT = 'E' and EQUED = 'Y', A is overwritten by * diag(S)*A*diag(S). * * LDAB (input) INTEGER * The leading dimension of the array A. LDAB >= KD+1. * * AFB (input or output) DOUBLE PRECISION array, dimension (LDAFB,N) * If FACT = 'F', then AFB is an input argument and on entry * contains the triangular factor U or L from the Cholesky * factorization A = U**T*U or A = L*L**T of the band matrix * A, in the same storage format as A (see AB). If EQUED = 'Y', * then AFB is the factored form of the equilibrated matrix A. * * If FACT = 'N', then AFB is an output argument and on exit * returns the triangular factor U or L from the Cholesky * factorization A = U**T*U or A = L*L**T. * * If FACT = 'E', then AFB is an output argument and on exit * returns the triangular factor U or L from the Cholesky * factorization A = U**T*U or A = L*L**T of the equilibrated * matrix A (see the description of A for the form of the * equilibrated matrix). * * LDAFB (input) INTEGER * The leading dimension of the array AFB. LDAFB >= KD+1. * * EQUED (input or output) CHARACTER*1 * Specifies the form of equilibration that was done. * = 'N': No equilibration (always true if FACT = 'N'). * = 'Y': Equilibration was done, i.e., A has been replaced by * diag(S) * A * diag(S). * EQUED is an input argument if FACT = 'F'; otherwise, it is an * output argument. * * S (input or output) DOUBLE PRECISION array, dimension (N) * The scale factors for A; not accessed if EQUED = 'N'. S is * an input argument if FACT = 'F'; otherwise, S is an output * argument. If FACT = 'F' and EQUED = 'Y', each element of S * must be positive. * * B (input/output) DOUBLE PRECISION array, dimension (LDB,NRHS) * On entry, the N-by-NRHS right hand side matrix B. * On exit, if EQUED = 'N', B is not modified; if EQUED = 'Y', * B is overwritten by diag(S) * B. * * LDB (input) INTEGER * The leading dimension of the array B. LDB >= max(1,N). * * X (output) DOUBLE PRECISION array, dimension (LDX,NRHS) * If INFO = 0 or INFO = N+1, the N-by-NRHS solution matrix X to * the original system of equations. Note that if EQUED = 'Y', * A and B are modified on exit, and the solution to the * equilibrated system is inv(diag(S))*X. * * LDX (input) INTEGER * The leading dimension of the array X. LDX >= max(1,N). * * RCOND (output) DOUBLE PRECISION * The estimate of the reciprocal condition number of the matrix * A after equilibration (if done). If RCOND is less than the * machine precision (in particular, if RCOND = 0), the matrix * is singular to working precision. This condition is * indicated by a return code of INFO > 0. * * FERR (output) DOUBLE PRECISION array, dimension (NRHS) * The estimated forward error bound for each solution vector * X(j) (the j-th column of the solution matrix X). * If XTRUE is the true solution corresponding to X(j), FERR(j) * is an estimated upper bound for the magnitude of the largest * element in (X(j) - XTRUE) divided by the magnitude of the * largest element in X(j). The estimate is as reliable as * the estimate for RCOND, and is almost always a slight * overestimate of the true error. * * BERR (output) DOUBLE PRECISION array, dimension (NRHS) * The componentwise relative backward error of each solution * vector X(j) (i.e., the smallest relative change in * any element of A or B that makes X(j) an exact solution). * * WORK (workspace) DOUBLE PRECISION array, dimension (3*N) * * IWORK (workspace) INTEGER array, dimension (N) * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = i, and i is * <= N: the leading minor of order i of A is * not positive definite, so the factorization * could not be completed, and the solution has not * been computed. RCOND = 0 is returned. * = N+1: U is nonsingular, but RCOND is less than machine * precision, meaning that the matrix is singular * to working precision. Nevertheless, the * solution and error bounds are computed because * there are a number of situations where the * computed solution can be more accurate than the * value of RCOND would suggest. * * Further Details * =============== * * The band storage scheme is illustrated by the following example, when * N = 6, KD = 2, and UPLO = 'U': * * Two-dimensional storage of the symmetric matrix A: * * a11 a12 a13 * a22 a23 a24 * a33 a34 a35 * a44 a45 a46 * a55 a56 * (aij=conjg(aji)) a66 * * Band storage of the upper triangle of A: * * * * a13 a24 a35 a46 * * a12 a23 a34 a45 a56 * a11 a22 a33 a44 a55 a66 * * Similarly, if UPLO = 'L' the format of A is as follows: * * a11 a22 a33 a44 a55 a66 * a21 a32 a43 a54 a65 * * a31 a42 a53 a64 * * * * Array elements marked * are not used by the routine. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL EQUIL, NOFACT, RCEQU, UPPER INTEGER I, INFEQU, J, J1, J2 DOUBLE PRECISION AMAX, ANORM, BIGNUM, SCOND, SMAX, SMIN, SMLNUM * .. * .. External Functions .. LOGICAL LSAME DOUBLE PRECISION DLAMCH, DLANSB EXTERNAL LSAME, DLAMCH, DLANSB * .. * .. External Subroutines .. EXTERNAL DCOPY, DLACPY, DLAQSB, DPBCON, DPBEQU, DPBRFS, $ DPBTRF, DPBTRS, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN * .. * .. Executable Statements .. * INFO = 0 NOFACT = LSAME( FACT, 'N' ) EQUIL = LSAME( FACT, 'E' ) UPPER = LSAME( UPLO, 'U' ) IF( NOFACT .OR. EQUIL ) THEN EQUED = 'N' RCEQU = .FALSE. ELSE RCEQU = LSAME( EQUED, 'Y' ) SMLNUM = DLAMCH( 'Safe minimum' ) BIGNUM = ONE / SMLNUM END IF * * Test the input parameters. * IF( .NOT.NOFACT .AND. .NOT.EQUIL .AND. .NOT.LSAME( FACT, 'F' ) ) $ THEN INFO = -1 ELSE IF( .NOT.UPPER .AND. .NOT.LSAME( UPLO, 'L' ) ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( KD.LT.0 ) THEN INFO = -4 ELSE IF( NRHS.LT.0 ) THEN INFO = -5 ELSE IF( LDAB.LT.KD+1 ) THEN INFO = -7 ELSE IF( LDAFB.LT.KD+1 ) THEN INFO = -9 ELSE IF( LSAME( FACT, 'F' ) .AND. .NOT. $ ( RCEQU .OR. LSAME( EQUED, 'N' ) ) ) THEN INFO = -10 ELSE IF( RCEQU ) THEN SMIN = BIGNUM SMAX = ZERO DO 10 J = 1, N SMIN = MIN( SMIN, S( J ) ) SMAX = MAX( SMAX, S( J ) ) 10 CONTINUE IF( SMIN.LE.ZERO ) THEN INFO = -11 ELSE IF( N.GT.0 ) THEN SCOND = MAX( SMIN, SMLNUM ) / MIN( SMAX, BIGNUM ) ELSE SCOND = ONE END IF END IF IF( INFO.EQ.0 ) THEN IF( LDB.LT.MAX( 1, N ) ) THEN INFO = -13 ELSE IF( LDX.LT.MAX( 1, N ) ) THEN INFO = -15 END IF END IF END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DPBSVX', -INFO ) RETURN END IF * IF( EQUIL ) THEN * * Compute row and column scalings to equilibrate the matrix A. * CALL DPBEQU( UPLO, N, KD, AB, LDAB, S, SCOND, AMAX, INFEQU ) IF( INFEQU.EQ.0 ) THEN * * Equilibrate the matrix. * CALL DLAQSB( UPLO, N, KD, AB, LDAB, S, SCOND, AMAX, EQUED ) RCEQU = LSAME( EQUED, 'Y' ) END IF END IF * * Scale the right-hand side. * IF( RCEQU ) THEN DO 30 J = 1, NRHS DO 20 I = 1, N B( I, J ) = S( I )*B( I, J ) 20 CONTINUE 30 CONTINUE END IF * IF( NOFACT .OR. EQUIL ) THEN * * Compute the Cholesky factorization A = U'*U or A = L*L'. * IF( UPPER ) THEN DO 40 J = 1, N J1 = MAX( J-KD, 1 ) CALL DCOPY( J-J1+1, AB( KD+1-J+J1, J ), 1, $ AFB( KD+1-J+J1, J ), 1 ) 40 CONTINUE ELSE DO 50 J = 1, N J2 = MIN( J+KD, N ) CALL DCOPY( J2-J+1, AB( 1, J ), 1, AFB( 1, J ), 1 ) 50 CONTINUE END IF * CALL DPBTRF( UPLO, N, KD, AFB, LDAFB, INFO ) * * Return if INFO is non-zero. * IF( INFO.NE.0 ) THEN IF( INFO.GT.0 ) $ RCOND = ZERO RETURN END IF END IF * * Compute the norm of the matrix A. * ANORM = DLANSB( '1', UPLO, N, KD, AB, LDAB, WORK ) * * Compute the reciprocal of the condition number of A. * CALL DPBCON( UPLO, N, KD, AFB, LDAFB, ANORM, RCOND, WORK, IWORK, $ INFO ) * * Set INFO = N+1 if the matrix is singular to working precision. * IF( RCOND.LT.DLAMCH( 'Epsilon' ) ) $ INFO = N + 1 * * Compute the solution matrix X. * CALL DLACPY( 'Full', N, NRHS, B, LDB, X, LDX ) CALL DPBTRS( UPLO, N, KD, NRHS, AFB, LDAFB, X, LDX, INFO ) * * Use iterative refinement to improve the computed solution and * compute error bounds and backward error estimates for it. * CALL DPBRFS( UPLO, N, KD, NRHS, AB, LDAB, AFB, LDAFB, B, LDB, X, $ LDX, FERR, BERR, WORK, IWORK, INFO ) * * Transform the solution matrix X to a solution of the original * system. * IF( RCEQU ) THEN DO 70 J = 1, NRHS DO 60 I = 1, N X( I, J ) = S( I )*X( I, J ) 60 CONTINUE 70 CONTINUE DO 80 J = 1, NRHS FERR( J ) = FERR( J ) / SCOND 80 CONTINUE END IF * RETURN * * End of DPBSVX * END SUBROUTINE DPOSV( UPLO, N, NRHS, A, LDA, B, LDB, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * March 31, 1993 * * .. Scalar Arguments .. CHARACTER UPLO INTEGER INFO, LDA, LDB, N, NRHS * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), B( LDB, * ) * .. * * Purpose * ======= * * DPOSV computes the solution to a real system of linear equations * A * X = B, * where A is an N-by-N symmetric positive definite matrix and X and B * are N-by-NRHS matrices. * * The Cholesky decomposition is used to factor A as * A = U**T* U, if UPLO = 'U', or * A = L * L**T, if UPLO = 'L', * where U is an upper triangular matrix and L is a lower triangular * matrix. The factored form of A is then used to solve the system of * equations A * X = B. * * Arguments * ========= * * UPLO (input) CHARACTER*1 * = 'U': Upper triangle of A is stored; * = 'L': Lower triangle of A is stored. * * N (input) INTEGER * The number of linear equations, i.e., the order of the * matrix A. N >= 0. * * NRHS (input) INTEGER * The number of right hand sides, i.e., the number of columns * of the matrix B. NRHS >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the symmetric matrix A. If UPLO = 'U', the leading * N-by-N upper triangular part of A contains the upper * triangular part of the matrix A, and the strictly lower * triangular part of A is not referenced. If UPLO = 'L', the * leading N-by-N lower triangular part of A contains the lower * triangular part of the matrix A, and the strictly upper * triangular part of A is not referenced. * * On exit, if INFO = 0, the factor U or L from the Cholesky * factorization A = U**T*U or A = L*L**T. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * B (input/output) DOUBLE PRECISION array, dimension (LDB,NRHS) * On entry, the N-by-NRHS right hand side matrix B. * On exit, if INFO = 0, the N-by-NRHS solution matrix X. * * LDB (input) INTEGER * The leading dimension of the array B. LDB >= max(1,N). * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = i, the leading minor of order i of A is not * positive definite, so the factorization could not be * completed, and the solution has not been computed. * * ===================================================================== * * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. External Subroutines .. EXTERNAL DPOTRF, DPOTRS, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 IF( .NOT.LSAME( UPLO, 'U' ) .AND. .NOT.LSAME( UPLO, 'L' ) ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 ELSE IF( NRHS.LT.0 ) THEN INFO = -3 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -5 ELSE IF( LDB.LT.MAX( 1, N ) ) THEN INFO = -7 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DPOSV ', -INFO ) RETURN END IF * * Compute the Cholesky factorization A = U'*U or A = L*L'. * CALL DPOTRF( UPLO, N, A, LDA, INFO ) IF( INFO.EQ.0 ) THEN * * Solve the system A*X = B, overwriting B with X. * CALL DPOTRS( UPLO, N, NRHS, A, LDA, B, LDB, INFO ) * END IF RETURN * * End of DPOSV * END SUBROUTINE DPOSVX( FACT, UPLO, N, NRHS, A, LDA, AF, LDAF, EQUED, $ S, B, LDB, X, LDX, RCOND, FERR, BERR, WORK, $ IWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER EQUED, FACT, UPLO INTEGER INFO, LDA, LDAF, LDB, LDX, N, NRHS DOUBLE PRECISION RCOND * .. * .. Array Arguments .. INTEGER IWORK( * ) DOUBLE PRECISION A( LDA, * ), AF( LDAF, * ), B( LDB, * ), $ BERR( * ), FERR( * ), S( * ), WORK( * ), $ X( LDX, * ) * .. * * Purpose * ======= * * DPOSVX uses the Cholesky factorization A = U**T*U or A = L*L**T to * compute the solution to a real system of linear equations * A * X = B, * where A is an N-by-N symmetric positive definite matrix and X and B * are N-by-NRHS matrices. * * Error bounds on the solution and a condition estimate are also * provided. * * Description * =========== * * The following steps are performed: * * 1. If FACT = 'E', real scaling factors are computed to equilibrate * the system: * diag(S) * A * diag(S) * inv(diag(S)) * X = diag(S) * B * Whether or not the system will be equilibrated depends on the * scaling of the matrix A, but if equilibration is used, A is * overwritten by diag(S)*A*diag(S) and B by diag(S)*B. * * 2. If FACT = 'N' or 'E', the Cholesky decomposition is used to * factor the matrix A (after equilibration if FACT = 'E') as * A = U**T* U, if UPLO = 'U', or * A = L * L**T, if UPLO = 'L', * where U is an upper triangular matrix and L is a lower triangular * matrix. * * 3. If the leading i-by-i principal minor is not positive definite, * then the routine returns with INFO = i. Otherwise, the factored * form of A is used to estimate the condition number of the matrix * A. If the reciprocal of the condition number is less than machine * precision, INFO = N+1 is returned as a warning, but the routine * still goes on to solve for X and compute error bounds as * described below. * * 4. The system of equations is solved for X using the factored form * of A. * * 5. Iterative refinement is applied to improve the computed solution * matrix and calculate error bounds and backward error estimates * for it. * * 6. If equilibration was used, the matrix X is premultiplied by * diag(S) so that it solves the original system before * equilibration. * * Arguments * ========= * * FACT (input) CHARACTER*1 * Specifies whether or not the factored form of the matrix A is * supplied on entry, and if not, whether the matrix A should be * equilibrated before it is factored. * = 'F': On entry, AF contains the factored form of A. * If EQUED = 'Y', the matrix A has been equilibrated * with scaling factors given by S. A and AF will not * be modified. * = 'N': The matrix A will be copied to AF and factored. * = 'E': The matrix A will be equilibrated if necessary, then * copied to AF and factored. * * UPLO (input) CHARACTER*1 * = 'U': Upper triangle of A is stored; * = 'L': Lower triangle of A is stored. * * N (input) INTEGER * The number of linear equations, i.e., the order of the * matrix A. N >= 0. * * NRHS (input) INTEGER * The number of right hand sides, i.e., the number of columns * of the matrices B and X. NRHS >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the symmetric matrix A, except if FACT = 'F' and * EQUED = 'Y', then A must contain the equilibrated matrix * diag(S)*A*diag(S). If UPLO = 'U', the leading * N-by-N upper triangular part of A contains the upper * triangular part of the matrix A, and the strictly lower * triangular part of A is not referenced. If UPLO = 'L', the * leading N-by-N lower triangular part of A contains the lower * triangular part of the matrix A, and the strictly upper * triangular part of A is not referenced. A is not modified if * FACT = 'F' or 'N', or if FACT = 'E' and EQUED = 'N' on exit. * * On exit, if FACT = 'E' and EQUED = 'Y', A is overwritten by * diag(S)*A*diag(S). * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * AF (input or output) DOUBLE PRECISION array, dimension (LDAF,N) * If FACT = 'F', then AF is an input argument and on entry * contains the triangular factor U or L from the Cholesky * factorization A = U**T*U or A = L*L**T, in the same storage * format as A. If EQUED .ne. 'N', then AF is the factored form * of the equilibrated matrix diag(S)*A*diag(S). * * If FACT = 'N', then AF is an output argument and on exit * returns the triangular factor U or L from the Cholesky * factorization A = U**T*U or A = L*L**T of the original * matrix A. * * If FACT = 'E', then AF is an output argument and on exit * returns the triangular factor U or L from the Cholesky * factorization A = U**T*U or A = L*L**T of the equilibrated * matrix A (see the description of A for the form of the * equilibrated matrix). * * LDAF (input) INTEGER * The leading dimension of the array AF. LDAF >= max(1,N). * * EQUED (input or output) CHARACTER*1 * Specifies the form of equilibration that was done. * = 'N': No equilibration (always true if FACT = 'N'). * = 'Y': Equilibration was done, i.e., A has been replaced by * diag(S) * A * diag(S). * EQUED is an input argument if FACT = 'F'; otherwise, it is an * output argument. * * S (input or output) DOUBLE PRECISION array, dimension (N) * The scale factors for A; not accessed if EQUED = 'N'. S is * an input argument if FACT = 'F'; otherwise, S is an output * argument. If FACT = 'F' and EQUED = 'Y', each element of S * must be positive. * * B (input/output) DOUBLE PRECISION array, dimension (LDB,NRHS) * On entry, the N-by-NRHS right hand side matrix B. * On exit, if EQUED = 'N', B is not modified; if EQUED = 'Y', * B is overwritten by diag(S) * B. * * LDB (input) INTEGER * The leading dimension of the array B. LDB >= max(1,N). * * X (output) DOUBLE PRECISION array, dimension (LDX,NRHS) * If INFO = 0 or INFO = N+1, the N-by-NRHS solution matrix X to * the original system of equations. Note that if EQUED = 'Y', * A and B are modified on exit, and the solution to the * equilibrated system is inv(diag(S))*X. * * LDX (input) INTEGER * The leading dimension of the array X. LDX >= max(1,N). * * RCOND (output) DOUBLE PRECISION * The estimate of the reciprocal condition number of the matrix * A after equilibration (if done). If RCOND is less than the * machine precision (in particular, if RCOND = 0), the matrix * is singular to working precision. This condition is * indicated by a return code of INFO > 0. * * FERR (output) DOUBLE PRECISION array, dimension (NRHS) * The estimated forward error bound for each solution vector * X(j) (the j-th column of the solution matrix X). * If XTRUE is the true solution corresponding to X(j), FERR(j) * is an estimated upper bound for the magnitude of the largest * element in (X(j) - XTRUE) divided by the magnitude of the * largest element in X(j). The estimate is as reliable as * the estimate for RCOND, and is almost always a slight * overestimate of the true error. * * BERR (output) DOUBLE PRECISION array, dimension (NRHS) * The componentwise relative backward error of each solution * vector X(j) (i.e., the smallest relative change in * any element of A or B that makes X(j) an exact solution). * * WORK (workspace) DOUBLE PRECISION array, dimension (3*N) * * IWORK (workspace) INTEGER array, dimension (N) * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = i, and i is * <= N: the leading minor of order i of A is * not positive definite, so the factorization * could not be completed, and the solution has not * been computed. RCOND = 0 is returned. * = N+1: U is nonsingular, but RCOND is less than machine * precision, meaning that the matrix is singular * to working precision. Nevertheless, the * solution and error bounds are computed because * there are a number of situations where the * computed solution can be more accurate than the * value of RCOND would suggest. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL EQUIL, NOFACT, RCEQU INTEGER I, INFEQU, J DOUBLE PRECISION AMAX, ANORM, BIGNUM, SCOND, SMAX, SMIN, SMLNUM * .. * .. External Functions .. LOGICAL LSAME DOUBLE PRECISION DLAMCH, DLANSY EXTERNAL LSAME, DLAMCH, DLANSY * .. * .. External Subroutines .. EXTERNAL DLACPY, DLAQSY, DPOCON, DPOEQU, DPORFS, DPOTRF, $ DPOTRS, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN * .. * .. Executable Statements .. * INFO = 0 NOFACT = LSAME( FACT, 'N' ) EQUIL = LSAME( FACT, 'E' ) IF( NOFACT .OR. EQUIL ) THEN EQUED = 'N' RCEQU = .FALSE. ELSE RCEQU = LSAME( EQUED, 'Y' ) SMLNUM = DLAMCH( 'Safe minimum' ) BIGNUM = ONE / SMLNUM END IF * * Test the input parameters. * IF( .NOT.NOFACT .AND. .NOT.EQUIL .AND. .NOT.LSAME( FACT, 'F' ) ) $ THEN INFO = -1 ELSE IF( .NOT.LSAME( UPLO, 'U' ) .AND. .NOT.LSAME( UPLO, 'L' ) ) $ THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( NRHS.LT.0 ) THEN INFO = -4 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -6 ELSE IF( LDAF.LT.MAX( 1, N ) ) THEN INFO = -8 ELSE IF( LSAME( FACT, 'F' ) .AND. .NOT. $ ( RCEQU .OR. LSAME( EQUED, 'N' ) ) ) THEN INFO = -9 ELSE IF( RCEQU ) THEN SMIN = BIGNUM SMAX = ZERO DO 10 J = 1, N SMIN = MIN( SMIN, S( J ) ) SMAX = MAX( SMAX, S( J ) ) 10 CONTINUE IF( SMIN.LE.ZERO ) THEN INFO = -10 ELSE IF( N.GT.0 ) THEN SCOND = MAX( SMIN, SMLNUM ) / MIN( SMAX, BIGNUM ) ELSE SCOND = ONE END IF END IF IF( INFO.EQ.0 ) THEN IF( LDB.LT.MAX( 1, N ) ) THEN INFO = -12 ELSE IF( LDX.LT.MAX( 1, N ) ) THEN INFO = -14 END IF END IF END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DPOSVX', -INFO ) RETURN END IF * IF( EQUIL ) THEN * * Compute row and column scalings to equilibrate the matrix A. * CALL DPOEQU( N, A, LDA, S, SCOND, AMAX, INFEQU ) IF( INFEQU.EQ.0 ) THEN * * Equilibrate the matrix. * CALL DLAQSY( UPLO, N, A, LDA, S, SCOND, AMAX, EQUED ) RCEQU = LSAME( EQUED, 'Y' ) END IF END IF * * Scale the right hand side. * IF( RCEQU ) THEN DO 30 J = 1, NRHS DO 20 I = 1, N B( I, J ) = S( I )*B( I, J ) 20 CONTINUE 30 CONTINUE END IF * IF( NOFACT .OR. EQUIL ) THEN * * Compute the Cholesky factorization A = U'*U or A = L*L'. * CALL DLACPY( UPLO, N, N, A, LDA, AF, LDAF ) CALL DPOTRF( UPLO, N, AF, LDAF, INFO ) * * Return if INFO is non-zero. * IF( INFO.NE.0 ) THEN IF( INFO.GT.0 ) $ RCOND = ZERO RETURN END IF END IF * * Compute the norm of the matrix A. * ANORM = DLANSY( '1', UPLO, N, A, LDA, WORK ) * * Compute the reciprocal of the condition number of A. * CALL DPOCON( UPLO, N, AF, LDAF, ANORM, RCOND, WORK, IWORK, INFO ) * * Set INFO = N+1 if the matrix is singular to working precision. * IF( RCOND.LT.DLAMCH( 'Epsilon' ) ) $ INFO = N + 1 * * Compute the solution matrix X. * CALL DLACPY( 'Full', N, NRHS, B, LDB, X, LDX ) CALL DPOTRS( UPLO, N, NRHS, AF, LDAF, X, LDX, INFO ) * * Use iterative refinement to improve the computed solution and * compute error bounds and backward error estimates for it. * CALL DPORFS( UPLO, N, NRHS, A, LDA, AF, LDAF, B, LDB, X, LDX, $ FERR, BERR, WORK, IWORK, INFO ) * * Transform the solution matrix X to a solution of the original * system. * IF( RCEQU ) THEN DO 50 J = 1, NRHS DO 40 I = 1, N X( I, J ) = S( I )*X( I, J ) 40 CONTINUE 50 CONTINUE DO 60 J = 1, NRHS FERR( J ) = FERR( J ) / SCOND 60 CONTINUE END IF * RETURN * * End of DPOSVX * END SUBROUTINE DPPSV( UPLO, N, NRHS, AP, B, LDB, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * March 31, 1993 * * .. Scalar Arguments .. CHARACTER UPLO INTEGER INFO, LDB, N, NRHS * .. * .. Array Arguments .. DOUBLE PRECISION AP( * ), B( LDB, * ) * .. * * Purpose * ======= * * DPPSV computes the solution to a real system of linear equations * A * X = B, * where A is an N-by-N symmetric positive definite matrix stored in * packed format and X and B are N-by-NRHS matrices. * * The Cholesky decomposition is used to factor A as * A = U**T* U, if UPLO = 'U', or * A = L * L**T, if UPLO = 'L', * where U is an upper triangular matrix and L is a lower triangular * matrix. The factored form of A is then used to solve the system of * equations A * X = B. * * Arguments * ========= * * UPLO (input) CHARACTER*1 * = 'U': Upper triangle of A is stored; * = 'L': Lower triangle of A is stored. * * N (input) INTEGER * The number of linear equations, i.e., the order of the * matrix A. N >= 0. * * NRHS (input) INTEGER * The number of right hand sides, i.e., the number of columns * of the matrix B. NRHS >= 0. * * AP (input/output) DOUBLE PRECISION array, dimension (N*(N+1)/2) * On entry, the upper or lower triangle of the symmetric matrix * A, packed columnwise in a linear array. The j-th column of A * is stored in the array AP as follows: * if UPLO = 'U', AP(i + (j-1)*j/2) = A(i,j) for 1<=i<=j; * if UPLO = 'L', AP(i + (j-1)*(2n-j)/2) = A(i,j) for j<=i<=n. * See below for further details. * * On exit, if INFO = 0, the factor U or L from the Cholesky * factorization A = U**T*U or A = L*L**T, in the same storage * format as A. * * B (input/output) DOUBLE PRECISION array, dimension (LDB,NRHS) * On entry, the N-by-NRHS right hand side matrix B. * On exit, if INFO = 0, the N-by-NRHS solution matrix X. * * LDB (input) INTEGER * The leading dimension of the array B. LDB >= max(1,N). * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = i, the leading minor of order i of A is not * positive definite, so the factorization could not be * completed, and the solution has not been computed. * * Further Details * =============== * * The packed storage scheme is illustrated by the following example * when N = 4, UPLO = 'U': * * Two-dimensional storage of the symmetric matrix A: * * a11 a12 a13 a14 * a22 a23 a24 * a33 a34 (aij = conjg(aji)) * a44 * * Packed storage of the upper triangle of A: * * AP = [ a11, a12, a22, a13, a23, a33, a14, a24, a34, a44 ] * * ===================================================================== * * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. External Subroutines .. EXTERNAL DPPTRF, DPPTRS, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 IF( .NOT.LSAME( UPLO, 'U' ) .AND. .NOT.LSAME( UPLO, 'L' ) ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 ELSE IF( NRHS.LT.0 ) THEN INFO = -3 ELSE IF( LDB.LT.MAX( 1, N ) ) THEN INFO = -6 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DPPSV ', -INFO ) RETURN END IF * * Compute the Cholesky factorization A = U'*U or A = L*L'. * CALL DPPTRF( UPLO, N, AP, INFO ) IF( INFO.EQ.0 ) THEN * * Solve the system A*X = B, overwriting B with X. * CALL DPPTRS( UPLO, N, NRHS, AP, B, LDB, INFO ) * END IF RETURN * * End of DPPSV * END SUBROUTINE DPPSVX( FACT, UPLO, N, NRHS, AP, AFP, EQUED, S, B, LDB, $ X, LDX, RCOND, FERR, BERR, WORK, IWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER EQUED, FACT, UPLO INTEGER INFO, LDB, LDX, N, NRHS DOUBLE PRECISION RCOND * .. * .. Array Arguments .. INTEGER IWORK( * ) DOUBLE PRECISION AFP( * ), AP( * ), B( LDB, * ), BERR( * ), $ FERR( * ), S( * ), WORK( * ), X( LDX, * ) * .. * * Purpose * ======= * * DPPSVX uses the Cholesky factorization A = U**T*U or A = L*L**T to * compute the solution to a real system of linear equations * A * X = B, * where A is an N-by-N symmetric positive definite matrix stored in * packed format and X and B are N-by-NRHS matrices. * * Error bounds on the solution and a condition estimate are also * provided. * * Description * =========== * * The following steps are performed: * * 1. If FACT = 'E', real scaling factors are computed to equilibrate * the system: * diag(S) * A * diag(S) * inv(diag(S)) * X = diag(S) * B * Whether or not the system will be equilibrated depends on the * scaling of the matrix A, but if equilibration is used, A is * overwritten by diag(S)*A*diag(S) and B by diag(S)*B. * * 2. If FACT = 'N' or 'E', the Cholesky decomposition is used to * factor the matrix A (after equilibration if FACT = 'E') as * A = U**T* U, if UPLO = 'U', or * A = L * L**T, if UPLO = 'L', * where U is an upper triangular matrix and L is a lower triangular * matrix. * * 3. If the leading i-by-i principal minor is not positive definite, * then the routine returns with INFO = i. Otherwise, the factored * form of A is used to estimate the condition number of the matrix * A. If the reciprocal of the condition number is less than machine * precision, INFO = N+1 is returned as a warning, but the routine * still goes on to solve for X and compute error bounds as * described below. * * 4. The system of equations is solved for X using the factored form * of A. * * 5. Iterative refinement is applied to improve the computed solution * matrix and calculate error bounds and backward error estimates * for it. * * 6. If equilibration was used, the matrix X is premultiplied by * diag(S) so that it solves the original system before * equilibration. * * Arguments * ========= * * FACT (input) CHARACTER*1 * Specifies whether or not the factored form of the matrix A is * supplied on entry, and if not, whether the matrix A should be * equilibrated before it is factored. * = 'F': On entry, AFP contains the factored form of A. * If EQUED = 'Y', the matrix A has been equilibrated * with scaling factors given by S. AP and AFP will not * be modified. * = 'N': The matrix A will be copied to AFP and factored. * = 'E': The matrix A will be equilibrated if necessary, then * copied to AFP and factored. * * UPLO (input) CHARACTER*1 * = 'U': Upper triangle of A is stored; * = 'L': Lower triangle of A is stored. * * N (input) INTEGER * The number of linear equations, i.e., the order of the * matrix A. N >= 0. * * NRHS (input) INTEGER * The number of right hand sides, i.e., the number of columns * of the matrices B and X. NRHS >= 0. * * AP (input/output) DOUBLE PRECISION array, dimension (N*(N+1)/2) * On entry, the upper or lower triangle of the symmetric matrix * A, packed columnwise in a linear array, except if FACT = 'F' * and EQUED = 'Y', then A must contain the equilibrated matrix * diag(S)*A*diag(S). The j-th column of A is stored in the * array AP as follows: * if UPLO = 'U', AP(i + (j-1)*j/2) = A(i,j) for 1<=i<=j; * if UPLO = 'L', AP(i + (j-1)*(2n-j)/2) = A(i,j) for j<=i<=n. * See below for further details. A is not modified if * FACT = 'F' or 'N', or if FACT = 'E' and EQUED = 'N' on exit. * * On exit, if FACT = 'E' and EQUED = 'Y', A is overwritten by * diag(S)*A*diag(S). * * AFP (input or output) DOUBLE PRECISION array, dimension * (N*(N+1)/2) * If FACT = 'F', then AFP is an input argument and on entry * contains the triangular factor U or L from the Cholesky * factorization A = U'*U or A = L*L', in the same storage * format as A. If EQUED .ne. 'N', then AFP is the factored * form of the equilibrated matrix A. * * If FACT = 'N', then AFP is an output argument and on exit * returns the triangular factor U or L from the Cholesky * factorization A = U'*U or A = L*L' of the original matrix A. * * If FACT = 'E', then AFP is an output argument and on exit * returns the triangular factor U or L from the Cholesky * factorization A = U'*U or A = L*L' of the equilibrated * matrix A (see the description of AP for the form of the * equilibrated matrix). * * EQUED (input or output) CHARACTER*1 * Specifies the form of equilibration that was done. * = 'N': No equilibration (always true if FACT = 'N'). * = 'Y': Equilibration was done, i.e., A has been replaced by * diag(S) * A * diag(S). * EQUED is an input argument if FACT = 'F'; otherwise, it is an * output argument. * * S (input or output) DOUBLE PRECISION array, dimension (N) * The scale factors for A; not accessed if EQUED = 'N'. S is * an input argument if FACT = 'F'; otherwise, S is an output * argument. If FACT = 'F' and EQUED = 'Y', each element of S * must be positive. * * B (input/output) DOUBLE PRECISION array, dimension (LDB,NRHS) * On entry, the N-by-NRHS right hand side matrix B. * On exit, if EQUED = 'N', B is not modified; if EQUED = 'Y', * B is overwritten by diag(S) * B. * * LDB (input) INTEGER * The leading dimension of the array B. LDB >= max(1,N). * * X (output) DOUBLE PRECISION array, dimension (LDX,NRHS) * If INFO = 0 or INFO = N+1, the N-by-NRHS solution matrix X to * the original system of equations. Note that if EQUED = 'Y', * A and B are modified on exit, and the solution to the * equilibrated system is inv(diag(S))*X. * * LDX (input) INTEGER * The leading dimension of the array X. LDX >= max(1,N). * * RCOND (output) DOUBLE PRECISION * The estimate of the reciprocal condition number of the matrix * A after equilibration (if done). If RCOND is less than the * machine precision (in particular, if RCOND = 0), the matrix * is singular to working precision. This condition is * indicated by a return code of INFO > 0. * * FERR (output) DOUBLE PRECISION array, dimension (NRHS) * The estimated forward error bound for each solution vector * X(j) (the j-th column of the solution matrix X). * If XTRUE is the true solution corresponding to X(j), FERR(j) * is an estimated upper bound for the magnitude of the largest * element in (X(j) - XTRUE) divided by the magnitude of the * largest element in X(j). The estimate is as reliable as * the estimate for RCOND, and is almost always a slight * overestimate of the true error. * * BERR (output) DOUBLE PRECISION array, dimension (NRHS) * The componentwise relative backward error of each solution * vector X(j) (i.e., the smallest relative change in * any element of A or B that makes X(j) an exact solution). * * WORK (workspace) DOUBLE PRECISION array, dimension (3*N) * * IWORK (workspace) INTEGER array, dimension (N) * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = i, and i is * <= N: the leading minor of order i of A is * not positive definite, so the factorization * could not be completed, and the solution has not * been computed. RCOND = 0 is returned. * = N+1: U is nonsingular, but RCOND is less than machine * precision, meaning that the matrix is singular * to working precision. Nevertheless, the * solution and error bounds are computed because * there are a number of situations where the * computed solution can be more accurate than the * value of RCOND would suggest. * * Further Details * =============== * * The packed storage scheme is illustrated by the following example * when N = 4, UPLO = 'U': * * Two-dimensional storage of the symmetric matrix A: * * a11 a12 a13 a14 * a22 a23 a24 * a33 a34 (aij = conjg(aji)) * a44 * * Packed storage of the upper triangle of A: * * AP = [ a11, a12, a22, a13, a23, a33, a14, a24, a34, a44 ] * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL EQUIL, NOFACT, RCEQU INTEGER I, INFEQU, J DOUBLE PRECISION AMAX, ANORM, BIGNUM, SCOND, SMAX, SMIN, SMLNUM * .. * .. External Functions .. LOGICAL LSAME DOUBLE PRECISION DLAMCH, DLANSP EXTERNAL LSAME, DLAMCH, DLANSP * .. * .. External Subroutines .. EXTERNAL DCOPY, DLACPY, DLAQSP, DPPCON, DPPEQU, DPPRFS, $ DPPTRF, DPPTRS, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN * .. * .. Executable Statements .. * INFO = 0 NOFACT = LSAME( FACT, 'N' ) EQUIL = LSAME( FACT, 'E' ) IF( NOFACT .OR. EQUIL ) THEN EQUED = 'N' RCEQU = .FALSE. ELSE RCEQU = LSAME( EQUED, 'Y' ) SMLNUM = DLAMCH( 'Safe minimum' ) BIGNUM = ONE / SMLNUM END IF * * Test the input parameters. * IF( .NOT.NOFACT .AND. .NOT.EQUIL .AND. .NOT.LSAME( FACT, 'F' ) ) $ THEN INFO = -1 ELSE IF( .NOT.LSAME( UPLO, 'U' ) .AND. .NOT.LSAME( UPLO, 'L' ) ) $ THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( NRHS.LT.0 ) THEN INFO = -4 ELSE IF( LSAME( FACT, 'F' ) .AND. .NOT. $ ( RCEQU .OR. LSAME( EQUED, 'N' ) ) ) THEN INFO = -7 ELSE IF( RCEQU ) THEN SMIN = BIGNUM SMAX = ZERO DO 10 J = 1, N SMIN = MIN( SMIN, S( J ) ) SMAX = MAX( SMAX, S( J ) ) 10 CONTINUE IF( SMIN.LE.ZERO ) THEN INFO = -8 ELSE IF( N.GT.0 ) THEN SCOND = MAX( SMIN, SMLNUM ) / MIN( SMAX, BIGNUM ) ELSE SCOND = ONE END IF END IF IF( INFO.EQ.0 ) THEN IF( LDB.LT.MAX( 1, N ) ) THEN INFO = -10 ELSE IF( LDX.LT.MAX( 1, N ) ) THEN INFO = -12 END IF END IF END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DPPSVX', -INFO ) RETURN END IF * IF( EQUIL ) THEN * * Compute row and column scalings to equilibrate the matrix A. * CALL DPPEQU( UPLO, N, AP, S, SCOND, AMAX, INFEQU ) IF( INFEQU.EQ.0 ) THEN * * Equilibrate the matrix. * CALL DLAQSP( UPLO, N, AP, S, SCOND, AMAX, EQUED ) RCEQU = LSAME( EQUED, 'Y' ) END IF END IF * * Scale the right-hand side. * IF( RCEQU ) THEN DO 30 J = 1, NRHS DO 20 I = 1, N B( I, J ) = S( I )*B( I, J ) 20 CONTINUE 30 CONTINUE END IF * IF( NOFACT .OR. EQUIL ) THEN * * Compute the Cholesky factorization A = U'*U or A = L*L'. * CALL DCOPY( N*( N+1 ) / 2, AP, 1, AFP, 1 ) CALL DPPTRF( UPLO, N, AFP, INFO ) * * Return if INFO is non-zero. * IF( INFO.NE.0 ) THEN IF( INFO.GT.0 ) $ RCOND = ZERO RETURN END IF END IF * * Compute the norm of the matrix A. * ANORM = DLANSP( 'I', UPLO, N, AP, WORK ) * * Compute the reciprocal of the condition number of A. * CALL DPPCON( UPLO, N, AFP, ANORM, RCOND, WORK, IWORK, INFO ) * * Set INFO = N+1 if the matrix is singular to working precision. * IF( RCOND.LT.DLAMCH( 'Epsilon' ) ) $ INFO = N + 1 * * Compute the solution matrix X. * CALL DLACPY( 'Full', N, NRHS, B, LDB, X, LDX ) CALL DPPTRS( UPLO, N, NRHS, AFP, X, LDX, INFO ) * * Use iterative refinement to improve the computed solution and * compute error bounds and backward error estimates for it. * CALL DPPRFS( UPLO, N, NRHS, AP, AFP, B, LDB, X, LDX, FERR, BERR, $ WORK, IWORK, INFO ) * * Transform the solution matrix X to a solution of the original * system. * IF( RCEQU ) THEN DO 50 J = 1, NRHS DO 40 I = 1, N X( I, J ) = S( I )*X( I, J ) 40 CONTINUE 50 CONTINUE DO 60 J = 1, NRHS FERR( J ) = FERR( J ) / SCOND 60 CONTINUE END IF * RETURN * * End of DPPSVX * END SUBROUTINE DSBEV( JOBZ, UPLO, N, KD, AB, LDAB, W, Z, LDZ, WORK, $ INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBZ, UPLO INTEGER INFO, KD, LDAB, LDZ, N * .. * .. Array Arguments .. DOUBLE PRECISION AB( LDAB, * ), W( * ), WORK( * ), Z( LDZ, * ) * .. * * Purpose * ======= * * DSBEV computes all the eigenvalues and, optionally, eigenvectors of * a real symmetric band matrix A. * * Arguments * ========= * * JOBZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only; * = 'V': Compute eigenvalues and eigenvectors. * * UPLO (input) CHARACTER*1 * = 'U': Upper triangle of A is stored; * = 'L': Lower triangle of A is stored. * * N (input) INTEGER * The order of the matrix A. N >= 0. * * KD (input) INTEGER * The number of superdiagonals of the matrix A if UPLO = 'U', * or the number of subdiagonals if UPLO = 'L'. KD >= 0. * * AB (input/output) DOUBLE PRECISION array, dimension (LDAB, N) * On entry, the upper or lower triangle of the symmetric band * matrix A, stored in the first KD+1 rows of the array. The * j-th column of A is stored in the j-th column of the array AB * as follows: * if UPLO = 'U', AB(kd+1+i-j,j) = A(i,j) for max(1,j-kd)<=i<=j; * if UPLO = 'L', AB(1+i-j,j) = A(i,j) for j<=i<=min(n,j+kd). * * On exit, AB is overwritten by values generated during the * reduction to tridiagonal form. If UPLO = 'U', the first * superdiagonal and the diagonal of the tridiagonal matrix T * are returned in rows KD and KD+1 of AB, and if UPLO = 'L', * the diagonal and first subdiagonal of T are returned in the * first two rows of AB. * * LDAB (input) INTEGER * The leading dimension of the array AB. LDAB >= KD + 1. * * W (output) DOUBLE PRECISION array, dimension (N) * If INFO = 0, the eigenvalues in ascending order. * * Z (output) DOUBLE PRECISION array, dimension (LDZ, N) * If JOBZ = 'V', then if INFO = 0, Z contains the orthonormal * eigenvectors of the matrix A, with the i-th column of Z * holding the eigenvector associated with W(i). * If JOBZ = 'N', then Z is not referenced. * * LDZ (input) INTEGER * The leading dimension of the array Z. LDZ >= 1, and if * JOBZ = 'V', LDZ >= max(1,N). * * WORK (workspace) DOUBLE PRECISION array, dimension (max(1,3*N-2)) * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = i, the algorithm failed to converge; i * off-diagonal elements of an intermediate tridiagonal * form did not converge to zero. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. LOGICAL LOWER, WANTZ INTEGER IINFO, IMAX, INDE, INDWRK, ISCALE DOUBLE PRECISION ANRM, BIGNUM, EPS, RMAX, RMIN, SAFMIN, SIGMA, $ SMLNUM * .. * .. External Functions .. LOGICAL LSAME DOUBLE PRECISION DLAMCH, DLANSB EXTERNAL LSAME, DLAMCH, DLANSB * .. * .. External Subroutines .. EXTERNAL DLASCL, DSBTRD, DSCAL, DSTEQR, DSTERF, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC SQRT * .. * .. Executable Statements .. * * Test the input parameters. * WANTZ = LSAME( JOBZ, 'V' ) LOWER = LSAME( UPLO, 'L' ) * INFO = 0 IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN INFO = -1 ELSE IF( .NOT.( LOWER .OR. LSAME( UPLO, 'U' ) ) ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( KD.LT.0 ) THEN INFO = -4 ELSE IF( LDAB.LT.KD+1 ) THEN INFO = -6 ELSE IF( LDZ.LT.1 .OR. ( WANTZ .AND. LDZ.LT.N ) ) THEN INFO = -9 END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSBEV ', -INFO ) RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * IF( N.EQ.1 ) THEN IF( LOWER ) THEN W( 1 ) = AB( 1, 1 ) ELSE W( 1 ) = AB( KD+1, 1 ) END IF IF( WANTZ ) $ Z( 1, 1 ) = ONE RETURN END IF * * Get machine constants. * SAFMIN = DLAMCH( 'Safe minimum' ) EPS = DLAMCH( 'Precision' ) SMLNUM = SAFMIN / EPS BIGNUM = ONE / SMLNUM RMIN = SQRT( SMLNUM ) RMAX = SQRT( BIGNUM ) * * Scale matrix to allowable range, if necessary. * ANRM = DLANSB( 'M', UPLO, N, KD, AB, LDAB, WORK ) ISCALE = 0 IF( ANRM.GT.ZERO .AND. ANRM.LT.RMIN ) THEN ISCALE = 1 SIGMA = RMIN / ANRM ELSE IF( ANRM.GT.RMAX ) THEN ISCALE = 1 SIGMA = RMAX / ANRM END IF IF( ISCALE.EQ.1 ) THEN IF( LOWER ) THEN CALL DLASCL( 'B', KD, KD, ONE, SIGMA, N, N, AB, LDAB, INFO ) ELSE CALL DLASCL( 'Q', KD, KD, ONE, SIGMA, N, N, AB, LDAB, INFO ) END IF END IF * * Call DSBTRD to reduce symmetric band matrix to tridiagonal form. * INDE = 1 INDWRK = INDE + N CALL DSBTRD( JOBZ, UPLO, N, KD, AB, LDAB, W, WORK( INDE ), Z, LDZ, $ WORK( INDWRK ), IINFO ) * * For eigenvalues only, call DSTERF. For eigenvectors, call SSTEQR. * IF( .NOT.WANTZ ) THEN CALL DSTERF( N, W, WORK( INDE ), INFO ) ELSE CALL DSTEQR( JOBZ, N, W, WORK( INDE ), Z, LDZ, WORK( INDWRK ), $ INFO ) END IF * * If matrix was scaled, then rescale eigenvalues appropriately. * IF( ISCALE.EQ.1 ) THEN IF( INFO.EQ.0 ) THEN IMAX = N ELSE IMAX = INFO - 1 END IF CALL DSCAL( IMAX, ONE / SIGMA, W, 1 ) END IF * RETURN * * End of DSBEV * END SUBROUTINE DSBEVD( JOBZ, UPLO, N, KD, AB, LDAB, W, Z, LDZ, WORK, $ LWORK, IWORK, LIWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBZ, UPLO INTEGER INFO, KD, LDAB, LDZ, LIWORK, LWORK, N * .. * .. Array Arguments .. INTEGER IWORK( * ) DOUBLE PRECISION AB( LDAB, * ), W( * ), WORK( * ), Z( LDZ, * ) * .. * * Purpose * ======= * * DSBEVD computes all the eigenvalues and, optionally, eigenvectors of * a real symmetric band matrix A. If eigenvectors are desired, it uses * a divide and conquer algorithm. * * The divide and conquer algorithm makes very mild assumptions about * floating point arithmetic. It will work on machines with a guard * digit in add/subtract, or on those binary machines without guard * digits which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or * Cray-2. It could conceivably fail on hexadecimal or decimal machines * without guard digits, but we know of none. * * Arguments * ========= * * JOBZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only; * = 'V': Compute eigenvalues and eigenvectors. * * UPLO (input) CHARACTER*1 * = 'U': Upper triangle of A is stored; * = 'L': Lower triangle of A is stored. * * N (input) INTEGER * The order of the matrix A. N >= 0. * * KD (input) INTEGER * The number of superdiagonals of the matrix A if UPLO = 'U', * or the number of subdiagonals if UPLO = 'L'. KD >= 0. * * AB (input/output) DOUBLE PRECISION array, dimension (LDAB, N) * On entry, the upper or lower triangle of the symmetric band * matrix A, stored in the first KD+1 rows of the array. The * j-th column of A is stored in the j-th column of the array AB * as follows: * if UPLO = 'U', AB(kd+1+i-j,j) = A(i,j) for max(1,j-kd)<=i<=j; * if UPLO = 'L', AB(1+i-j,j) = A(i,j) for j<=i<=min(n,j+kd). * * On exit, AB is overwritten by values generated during the * reduction to tridiagonal form. If UPLO = 'U', the first * superdiagonal and the diagonal of the tridiagonal matrix T * are returned in rows KD and KD+1 of AB, and if UPLO = 'L', * the diagonal and first subdiagonal of T are returned in the * first two rows of AB. * * LDAB (input) INTEGER * The leading dimension of the array AB. LDAB >= KD + 1. * * W (output) DOUBLE PRECISION array, dimension (N) * If INFO = 0, the eigenvalues in ascending order. * * Z (output) DOUBLE PRECISION array, dimension (LDZ, N) * If JOBZ = 'V', then if INFO = 0, Z contains the orthonormal * eigenvectors of the matrix A, with the i-th column of Z * holding the eigenvector associated with W(i). * If JOBZ = 'N', then Z is not referenced. * * LDZ (input) INTEGER * The leading dimension of the array Z. LDZ >= 1, and if * JOBZ = 'V', LDZ >= max(1,N). * * WORK (workspace/output) DOUBLE PRECISION array, * dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. * IF N <= 1, LWORK must be at least 1. * If JOBZ = 'N' and N > 2, LWORK must be at least 2*N. * If JOBZ = 'V' and N > 2, LWORK must be at least * ( 1 + 5*N + 2*N**2 ). * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * IWORK (workspace/output) INTEGER array, dimension (LIWORK) * On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK. * * LIWORK (input) INTEGER * The dimension of the array LIWORK. * If JOBZ = 'N' or N <= 1, LIWORK must be at least 1. * If JOBZ = 'V' and N > 2, LIWORK must be at least 3 + 5*N. * * If LIWORK = -1, then a workspace query is assumed; the * routine only calculates the optimal size of the IWORK array, * returns this value as the first entry of the IWORK array, and * no error message related to LIWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = i, the algorithm failed to converge; i * off-diagonal elements of an intermediate tridiagonal * form did not converge to zero. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL LOWER, LQUERY, WANTZ INTEGER IINFO, INDE, INDWK2, INDWRK, ISCALE, LIWMIN, $ LLWRK2, LWMIN DOUBLE PRECISION ANRM, BIGNUM, EPS, RMAX, RMIN, SAFMIN, SIGMA, $ SMLNUM * .. * .. External Functions .. LOGICAL LSAME DOUBLE PRECISION DLAMCH, DLANSB EXTERNAL LSAME, DLAMCH, DLANSB * .. * .. External Subroutines .. EXTERNAL DGEMM, DLACPY, DLASCL, DSBTRD, DSCAL, DSTEDC, $ DSTERF, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC SQRT * .. * .. Executable Statements .. * * Test the input parameters. * WANTZ = LSAME( JOBZ, 'V' ) LOWER = LSAME( UPLO, 'L' ) LQUERY = ( LWORK.EQ.-1 .OR. LIWORK.EQ.-1 ) * INFO = 0 IF( N.LE.1 ) THEN LIWMIN = 1 LWMIN = 1 ELSE IF( WANTZ ) THEN LIWMIN = 3 + 5*N LWMIN = 1 + 5*N + 2*N**2 ELSE LIWMIN = 1 LWMIN = 2*N END IF END IF IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN INFO = -1 ELSE IF( .NOT.( LOWER .OR. LSAME( UPLO, 'U' ) ) ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( KD.LT.0 ) THEN INFO = -4 ELSE IF( LDAB.LT.KD+1 ) THEN INFO = -6 ELSE IF( LDZ.LT.1 .OR. ( WANTZ .AND. LDZ.LT.N ) ) THEN INFO = -9 ELSE IF( LWORK.LT.LWMIN .AND. .NOT.LQUERY ) THEN INFO = -11 ELSE IF( LIWORK.LT.LIWMIN .AND. .NOT.LQUERY ) THEN INFO = -13 END IF * IF( INFO.EQ.0 ) THEN WORK( 1 ) = LWMIN IWORK( 1 ) = LIWMIN END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSBEVD', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * IF( N.EQ.1 ) THEN W( 1 ) = AB( 1, 1 ) IF( WANTZ ) $ Z( 1, 1 ) = ONE RETURN END IF * * Get machine constants. * SAFMIN = DLAMCH( 'Safe minimum' ) EPS = DLAMCH( 'Precision' ) SMLNUM = SAFMIN / EPS BIGNUM = ONE / SMLNUM RMIN = SQRT( SMLNUM ) RMAX = SQRT( BIGNUM ) * * Scale matrix to allowable range, if necessary. * ANRM = DLANSB( 'M', UPLO, N, KD, AB, LDAB, WORK ) ISCALE = 0 IF( ANRM.GT.ZERO .AND. ANRM.LT.RMIN ) THEN ISCALE = 1 SIGMA = RMIN / ANRM ELSE IF( ANRM.GT.RMAX ) THEN ISCALE = 1 SIGMA = RMAX / ANRM END IF IF( ISCALE.EQ.1 ) THEN IF( LOWER ) THEN CALL DLASCL( 'B', KD, KD, ONE, SIGMA, N, N, AB, LDAB, INFO ) ELSE CALL DLASCL( 'Q', KD, KD, ONE, SIGMA, N, N, AB, LDAB, INFO ) END IF END IF * * Call DSBTRD to reduce symmetric band matrix to tridiagonal form. * INDE = 1 INDWRK = INDE + N INDWK2 = INDWRK + N*N LLWRK2 = LWORK - INDWK2 + 1 CALL DSBTRD( JOBZ, UPLO, N, KD, AB, LDAB, W, WORK( INDE ), Z, LDZ, $ WORK( INDWRK ), IINFO ) * * For eigenvalues only, call DSTERF. For eigenvectors, call SSTEDC. * IF( .NOT.WANTZ ) THEN CALL DSTERF( N, W, WORK( INDE ), INFO ) ELSE CALL DSTEDC( 'I', N, W, WORK( INDE ), WORK( INDWRK ), N, $ WORK( INDWK2 ), LLWRK2, IWORK, LIWORK, INFO ) CALL DGEMM( 'N', 'N', N, N, N, ONE, Z, LDZ, WORK( INDWRK ), N, $ ZERO, WORK( INDWK2 ), N ) CALL DLACPY( 'A', N, N, WORK( INDWK2 ), N, Z, LDZ ) END IF * * If matrix was scaled, then rescale eigenvalues appropriately. * IF( ISCALE.EQ.1 ) $ CALL DSCAL( N, ONE / SIGMA, W, 1 ) * WORK( 1 ) = LWMIN IWORK( 1 ) = LIWMIN RETURN * * End of DSBEVD * END SUBROUTINE DSBEVX( JOBZ, RANGE, UPLO, N, KD, AB, LDAB, Q, LDQ, VL, $ VU, IL, IU, ABSTOL, M, W, Z, LDZ, WORK, IWORK, $ IFAIL, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBZ, RANGE, UPLO INTEGER IL, INFO, IU, KD, LDAB, LDQ, LDZ, M, N DOUBLE PRECISION ABSTOL, VL, VU * .. * .. Array Arguments .. INTEGER IFAIL( * ), IWORK( * ) DOUBLE PRECISION AB( LDAB, * ), Q( LDQ, * ), W( * ), WORK( * ), $ Z( LDZ, * ) * .. * * Purpose * ======= * * DSBEVX computes selected eigenvalues and, optionally, eigenvectors * of a real symmetric band matrix A. Eigenvalues and eigenvectors can * be selected by specifying either a range of values or a range of * indices for the desired eigenvalues. * * Arguments * ========= * * JOBZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only; * = 'V': Compute eigenvalues and eigenvectors. * * RANGE (input) CHARACTER*1 * = 'A': all eigenvalues will be found; * = 'V': all eigenvalues in the half-open interval (VL,VU] * will be found; * = 'I': the IL-th through IU-th eigenvalues will be found. * * UPLO (input) CHARACTER*1 * = 'U': Upper triangle of A is stored; * = 'L': Lower triangle of A is stored. * * N (input) INTEGER * The order of the matrix A. N >= 0. * * KD (input) INTEGER * The number of superdiagonals of the matrix A if UPLO = 'U', * or the number of subdiagonals if UPLO = 'L'. KD >= 0. * * AB (input/output) DOUBLE PRECISION array, dimension (LDAB, N) * On entry, the upper or lower triangle of the symmetric band * matrix A, stored in the first KD+1 rows of the array. The * j-th column of A is stored in the j-th column of the array AB * as follows: * if UPLO = 'U', AB(kd+1+i-j,j) = A(i,j) for max(1,j-kd)<=i<=j; * if UPLO = 'L', AB(1+i-j,j) = A(i,j) for j<=i<=min(n,j+kd). * * On exit, AB is overwritten by values generated during the * reduction to tridiagonal form. If UPLO = 'U', the first * superdiagonal and the diagonal of the tridiagonal matrix T * are returned in rows KD and KD+1 of AB, and if UPLO = 'L', * the diagonal and first subdiagonal of T are returned in the * first two rows of AB. * * LDAB (input) INTEGER * The leading dimension of the array AB. LDAB >= KD + 1. * * Q (output) DOUBLE PRECISION array, dimension (LDQ, N) * If JOBZ = 'V', the N-by-N orthogonal matrix used in the * reduction to tridiagonal form. * If JOBZ = 'N', the array Q is not referenced. * * LDQ (input) INTEGER * The leading dimension of the array Q. If JOBZ = 'V', then * LDQ >= max(1,N). * * VL (input) DOUBLE PRECISION * VU (input) DOUBLE PRECISION * If RANGE='V', the lower and upper bounds of the interval to * be searched for eigenvalues. VL < VU. * Not referenced if RANGE = 'A' or 'I'. * * IL (input) INTEGER * IU (input) INTEGER * If RANGE='I', the indices (in ascending order) of the * smallest and largest eigenvalues to be returned. * 1 <= IL <= IU <= N, if N > 0; IL = 1 and IU = 0 if N = 0. * Not referenced if RANGE = 'A' or 'V'. * * ABSTOL (input) DOUBLE PRECISION * The absolute error tolerance for the eigenvalues. * An approximate eigenvalue is accepted as converged * when it is determined to lie in an interval [a,b] * of width less than or equal to * * ABSTOL + EPS * max( |a|,|b| ) , * * where EPS is the machine precision. If ABSTOL is less than * or equal to zero, then EPS*|T| will be used in its place, * where |T| is the 1-norm of the tridiagonal matrix obtained * by reducing AB to tridiagonal form. * * Eigenvalues will be computed most accurately when ABSTOL is * set to twice the underflow threshold 2*DLAMCH('S'), not zero. * If this routine returns with INFO>0, indicating that some * eigenvectors did not converge, try setting ABSTOL to * 2*DLAMCH('S'). * * See "Computing Small Singular Values of Bidiagonal Matrices * with Guaranteed High Relative Accuracy," by Demmel and * Kahan, LAPACK Working Note #3. * * M (output) INTEGER * The total number of eigenvalues found. 0 <= M <= N. * If RANGE = 'A', M = N, and if RANGE = 'I', M = IU-IL+1. * * W (output) DOUBLE PRECISION array, dimension (N) * The first M elements contain the selected eigenvalues in * ascending order. * * Z (output) DOUBLE PRECISION array, dimension (LDZ, max(1,M)) * If JOBZ = 'V', then if INFO = 0, the first M columns of Z * contain the orthonormal eigenvectors of the matrix A * corresponding to the selected eigenvalues, with the i-th * column of Z holding the eigenvector associated with W(i). * If an eigenvector fails to converge, then that column of Z * contains the latest approximation to the eigenvector, and the * index of the eigenvector is returned in IFAIL. * If JOBZ = 'N', then Z is not referenced. * Note: the user must ensure that at least max(1,M) columns are * supplied in the array Z; if RANGE = 'V', the exact value of M * is not known in advance and an upper bound must be used. * * LDZ (input) INTEGER * The leading dimension of the array Z. LDZ >= 1, and if * JOBZ = 'V', LDZ >= max(1,N). * * WORK (workspace) DOUBLE PRECISION array, dimension (7*N) * * IWORK (workspace) INTEGER array, dimension (5*N) * * IFAIL (output) INTEGER array, dimension (N) * If JOBZ = 'V', then if INFO = 0, the first M elements of * IFAIL are zero. If INFO > 0, then IFAIL contains the * indices of the eigenvectors that failed to converge. * If JOBZ = 'N', then IFAIL is not referenced. * * INFO (output) INTEGER * = 0: successful exit. * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: if INFO = i, then i eigenvectors failed to converge. * Their indices are stored in array IFAIL. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. LOGICAL ALLEIG, INDEIG, LOWER, VALEIG, WANTZ CHARACTER ORDER INTEGER I, IINFO, IMAX, INDD, INDE, INDEE, INDIBL, $ INDISP, INDIWO, INDWRK, ISCALE, ITMP1, J, JJ, $ NSPLIT DOUBLE PRECISION ABSTLL, ANRM, BIGNUM, EPS, RMAX, RMIN, SAFMIN, $ SIGMA, SMLNUM, TMP1, VLL, VUU * .. * .. External Functions .. LOGICAL LSAME DOUBLE PRECISION DLAMCH, DLANSB EXTERNAL LSAME, DLAMCH, DLANSB * .. * .. External Subroutines .. EXTERNAL DCOPY, DGEMV, DLACPY, DLASCL, DSBTRD, DSCAL, $ DSTEBZ, DSTEIN, DSTEQR, DSTERF, DSWAP, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN, SQRT * .. * .. Executable Statements .. * * Test the input parameters. * WANTZ = LSAME( JOBZ, 'V' ) ALLEIG = LSAME( RANGE, 'A' ) VALEIG = LSAME( RANGE, 'V' ) INDEIG = LSAME( RANGE, 'I' ) LOWER = LSAME( UPLO, 'L' ) * INFO = 0 IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN INFO = -1 ELSE IF( .NOT.( ALLEIG .OR. VALEIG .OR. INDEIG ) ) THEN INFO = -2 ELSE IF( .NOT.( LOWER .OR. LSAME( UPLO, 'U' ) ) ) THEN INFO = -3 ELSE IF( N.LT.0 ) THEN INFO = -4 ELSE IF( KD.LT.0 ) THEN INFO = -5 ELSE IF( LDAB.LT.KD+1 ) THEN INFO = -7 ELSE IF( WANTZ .AND. LDQ.LT.MAX( 1, N ) ) THEN INFO = -9 ELSE IF( VALEIG ) THEN IF( N.GT.0 .AND. VU.LE.VL ) $ INFO = -11 ELSE IF( INDEIG ) THEN IF( IL.LT.1 .OR. IL.GT.MAX( 1, N ) ) THEN INFO = -12 ELSE IF( IU.LT.MIN( N, IL ) .OR. IU.GT.N ) THEN INFO = -13 END IF END IF END IF IF( INFO.EQ.0 ) THEN IF( LDZ.LT.1 .OR. ( WANTZ .AND. LDZ.LT.N ) ) $ INFO = -18 END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSBEVX', -INFO ) RETURN END IF * * Quick return if possible * M = 0 IF( N.EQ.0 ) $ RETURN * IF( N.EQ.1 ) THEN M = 1 IF( LOWER ) THEN TMP1 = AB( 1, 1 ) ELSE TMP1 = AB( KD+1, 1 ) END IF IF( VALEIG ) THEN IF( .NOT.( VL.LT.TMP1 .AND. VU.GE.TMP1 ) ) $ M = 0 END IF IF( M.EQ.1 ) THEN W( 1 ) = TMP1 IF( WANTZ ) $ Z( 1, 1 ) = ONE END IF RETURN END IF * * Get machine constants. * SAFMIN = DLAMCH( 'Safe minimum' ) EPS = DLAMCH( 'Precision' ) SMLNUM = SAFMIN / EPS BIGNUM = ONE / SMLNUM RMIN = SQRT( SMLNUM ) RMAX = MIN( SQRT( BIGNUM ), ONE / SQRT( SQRT( SAFMIN ) ) ) * * Scale matrix to allowable range, if necessary. * ISCALE = 0 ABSTLL = ABSTOL IF( VALEIG ) THEN VLL = VL VUU = VU ELSE VLL = ZERO VUU = ZERO END IF ANRM = DLANSB( 'M', UPLO, N, KD, AB, LDAB, WORK ) IF( ANRM.GT.ZERO .AND. ANRM.LT.RMIN ) THEN ISCALE = 1 SIGMA = RMIN / ANRM ELSE IF( ANRM.GT.RMAX ) THEN ISCALE = 1 SIGMA = RMAX / ANRM END IF IF( ISCALE.EQ.1 ) THEN IF( LOWER ) THEN CALL DLASCL( 'B', KD, KD, ONE, SIGMA, N, N, AB, LDAB, INFO ) ELSE CALL DLASCL( 'Q', KD, KD, ONE, SIGMA, N, N, AB, LDAB, INFO ) END IF IF( ABSTOL.GT.0 ) $ ABSTLL = ABSTOL*SIGMA IF( VALEIG ) THEN VLL = VL*SIGMA VUU = VU*SIGMA END IF END IF * * Call DSBTRD to reduce symmetric band matrix to tridiagonal form. * INDD = 1 INDE = INDD + N INDWRK = INDE + N CALL DSBTRD( JOBZ, UPLO, N, KD, AB, LDAB, WORK( INDD ), $ WORK( INDE ), Q, LDQ, WORK( INDWRK ), IINFO ) * * If all eigenvalues are desired and ABSTOL is less than or equal * to zero, then call DSTERF or SSTEQR. If this fails for some * eigenvalue, then try DSTEBZ. * IF( ( ALLEIG .OR. ( INDEIG .AND. IL.EQ.1 .AND. IU.EQ.N ) ) .AND. $ ( ABSTOL.LE.ZERO ) ) THEN CALL DCOPY( N, WORK( INDD ), 1, W, 1 ) INDEE = INDWRK + 2*N IF( .NOT.WANTZ ) THEN CALL DCOPY( N-1, WORK( INDE ), 1, WORK( INDEE ), 1 ) CALL DSTERF( N, W, WORK( INDEE ), INFO ) ELSE CALL DLACPY( 'A', N, N, Q, LDQ, Z, LDZ ) CALL DCOPY( N-1, WORK( INDE ), 1, WORK( INDEE ), 1 ) CALL DSTEQR( JOBZ, N, W, WORK( INDEE ), Z, LDZ, $ WORK( INDWRK ), INFO ) IF( INFO.EQ.0 ) THEN DO 10 I = 1, N IFAIL( I ) = 0 10 CONTINUE END IF END IF IF( INFO.EQ.0 ) THEN M = N GO TO 30 END IF INFO = 0 END IF * * Otherwise, call DSTEBZ and, if eigenvectors are desired, SSTEIN. * IF( WANTZ ) THEN ORDER = 'B' ELSE ORDER = 'E' END IF INDIBL = 1 INDISP = INDIBL + N INDIWO = INDISP + N CALL DSTEBZ( RANGE, ORDER, N, VLL, VUU, IL, IU, ABSTLL, $ WORK( INDD ), WORK( INDE ), M, NSPLIT, W, $ IWORK( INDIBL ), IWORK( INDISP ), WORK( INDWRK ), $ IWORK( INDIWO ), INFO ) * IF( WANTZ ) THEN CALL DSTEIN( N, WORK( INDD ), WORK( INDE ), M, W, $ IWORK( INDIBL ), IWORK( INDISP ), Z, LDZ, $ WORK( INDWRK ), IWORK( INDIWO ), IFAIL, INFO ) * * Apply orthogonal matrix used in reduction to tridiagonal * form to eigenvectors returned by DSTEIN. * DO 20 J = 1, M CALL DCOPY( N, Z( 1, J ), 1, WORK( 1 ), 1 ) CALL DGEMV( 'N', N, N, ONE, Q, LDQ, WORK, 1, ZERO, $ Z( 1, J ), 1 ) 20 CONTINUE END IF * * If matrix was scaled, then rescale eigenvalues appropriately. * 30 CONTINUE IF( ISCALE.EQ.1 ) THEN IF( INFO.EQ.0 ) THEN IMAX = M ELSE IMAX = INFO - 1 END IF CALL DSCAL( IMAX, ONE / SIGMA, W, 1 ) END IF * * If eigenvalues are not in order, then sort them, along with * eigenvectors. * IF( WANTZ ) THEN DO 50 J = 1, M - 1 I = 0 TMP1 = W( J ) DO 40 JJ = J + 1, M IF( W( JJ ).LT.TMP1 ) THEN I = JJ TMP1 = W( JJ ) END IF 40 CONTINUE * IF( I.NE.0 ) THEN ITMP1 = IWORK( INDIBL+I-1 ) W( I ) = W( J ) IWORK( INDIBL+I-1 ) = IWORK( INDIBL+J-1 ) W( J ) = TMP1 IWORK( INDIBL+J-1 ) = ITMP1 CALL DSWAP( N, Z( 1, I ), 1, Z( 1, J ), 1 ) IF( INFO.NE.0 ) THEN ITMP1 = IFAIL( I ) IFAIL( I ) = IFAIL( J ) IFAIL( J ) = ITMP1 END IF END IF 50 CONTINUE END IF * RETURN * * End of DSBEVX * END SUBROUTINE DSBGV( JOBZ, UPLO, N, KA, KB, AB, LDAB, BB, LDBB, W, Z, $ LDZ, WORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * September 30, 1994 * * .. Scalar Arguments .. CHARACTER JOBZ, UPLO INTEGER INFO, KA, KB, LDAB, LDBB, LDZ, N * .. * .. Array Arguments .. DOUBLE PRECISION AB( LDAB, * ), BB( LDBB, * ), W( * ), $ WORK( * ), Z( LDZ, * ) * .. * * Purpose * ======= * * DSBGV computes all the eigenvalues, and optionally, the eigenvectors * of a real generalized symmetric-definite banded eigenproblem, of * the form A*x=(lambda)*B*x. Here A and B are assumed to be symmetric * and banded, and B is also positive definite. * * Arguments * ========= * * JOBZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only; * = 'V': Compute eigenvalues and eigenvectors. * * UPLO (input) CHARACTER*1 * = 'U': Upper triangles of A and B are stored; * = 'L': Lower triangles of A and B are stored. * * N (input) INTEGER * The order of the matrices A and B. N >= 0. * * KA (input) INTEGER * The number of superdiagonals of the matrix A if UPLO = 'U', * or the number of subdiagonals if UPLO = 'L'. KA >= 0. * * KB (input) INTEGER * The number of superdiagonals of the matrix B if UPLO = 'U', * or the number of subdiagonals if UPLO = 'L'. KB >= 0. * * AB (input/output) DOUBLE PRECISION array, dimension (LDAB, N) * On entry, the upper or lower triangle of the symmetric band * matrix A, stored in the first ka+1 rows of the array. The * j-th column of A is stored in the j-th column of the array AB * as follows: * if UPLO = 'U', AB(ka+1+i-j,j) = A(i,j) for max(1,j-ka)<=i<=j; * if UPLO = 'L', AB(1+i-j,j) = A(i,j) for j<=i<=min(n,j+ka). * * On exit, the contents of AB are destroyed. * * LDAB (input) INTEGER * The leading dimension of the array AB. LDAB >= KA+1. * * BB (input/output) DOUBLE PRECISION array, dimension (LDBB, N) * On entry, the upper or lower triangle of the symmetric band * matrix B, stored in the first kb+1 rows of the array. The * j-th column of B is stored in the j-th column of the array BB * as follows: * if UPLO = 'U', BB(kb+1+i-j,j) = B(i,j) for max(1,j-kb)<=i<=j; * if UPLO = 'L', BB(1+i-j,j) = B(i,j) for j<=i<=min(n,j+kb). * * On exit, the factor S from the split Cholesky factorization * B = S**T*S, as returned by DPBSTF. * * LDBB (input) INTEGER * The leading dimension of the array BB. LDBB >= KB+1. * * W (output) DOUBLE PRECISION array, dimension (N) * If INFO = 0, the eigenvalues in ascending order. * * Z (output) DOUBLE PRECISION array, dimension (LDZ, N) * If JOBZ = 'V', then if INFO = 0, Z contains the matrix Z of * eigenvectors, with the i-th column of Z holding the * eigenvector associated with W(i). The eigenvectors are * normalized so that Z**T*B*Z = I. * If JOBZ = 'N', then Z is not referenced. * * LDZ (input) INTEGER * The leading dimension of the array Z. LDZ >= 1, and if * JOBZ = 'V', LDZ >= N. * * WORK (workspace) DOUBLE PRECISION array, dimension (3*N) * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = i, and i is: * <= N: the algorithm failed to converge: * i off-diagonal elements of an intermediate * tridiagonal form did not converge to zero; * > N: if INFO = N + i, for 1 <= i <= N, then DPBSTF * returned INFO = i: B is not positive definite. * The factorization of B could not be completed and * no eigenvalues or eigenvectors were computed. * * ===================================================================== * * .. Local Scalars .. LOGICAL UPPER, WANTZ CHARACTER VECT INTEGER IINFO, INDE, INDWRK * .. * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. External Subroutines .. EXTERNAL DPBSTF, DSBGST, DSBTRD, DSTEQR, DSTERF, XERBLA * .. * .. Executable Statements .. * * Test the input parameters. * WANTZ = LSAME( JOBZ, 'V' ) UPPER = LSAME( UPLO, 'U' ) * INFO = 0 IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN INFO = -1 ELSE IF( .NOT.( UPPER .OR. LSAME( UPLO, 'L' ) ) ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( KA.LT.0 ) THEN INFO = -4 ELSE IF( KB.LT.0 .OR. KB.GT.KA ) THEN INFO = -5 ELSE IF( LDAB.LT.KA+1 ) THEN INFO = -7 ELSE IF( LDBB.LT.KB+1 ) THEN INFO = -9 ELSE IF( LDZ.LT.1 .OR. ( WANTZ .AND. LDZ.LT.N ) ) THEN INFO = -12 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSBGV ', -INFO ) RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * * Form a split Cholesky factorization of B. * CALL DPBSTF( UPLO, N, KB, BB, LDBB, INFO ) IF( INFO.NE.0 ) THEN INFO = N + INFO RETURN END IF * * Transform problem to standard eigenvalue problem. * INDE = 1 INDWRK = INDE + N CALL DSBGST( JOBZ, UPLO, N, KA, KB, AB, LDAB, BB, LDBB, Z, LDZ, $ WORK( INDWRK ), IINFO ) * * Reduce to tridiagonal form. * IF( WANTZ ) THEN VECT = 'U' ELSE VECT = 'N' END IF CALL DSBTRD( VECT, UPLO, N, KA, AB, LDAB, W, WORK( INDE ), Z, LDZ, $ WORK( INDWRK ), IINFO ) * * For eigenvalues only, call DSTERF. For eigenvectors, call SSTEQR. * IF( .NOT.WANTZ ) THEN CALL DSTERF( N, W, WORK( INDE ), INFO ) ELSE CALL DSTEQR( JOBZ, N, W, WORK( INDE ), Z, LDZ, WORK( INDWRK ), $ INFO ) END IF RETURN * * End of DSBGV * END SUBROUTINE DSBGVD( JOBZ, UPLO, N, KA, KB, AB, LDAB, BB, LDBB, W, $ Z, LDZ, WORK, LWORK, IWORK, LIWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBZ, UPLO INTEGER INFO, KA, KB, LDAB, LDBB, LDZ, LIWORK, LWORK, N * .. * .. Array Arguments .. INTEGER IWORK( * ) DOUBLE PRECISION AB( LDAB, * ), BB( LDBB, * ), W( * ), $ WORK( * ), Z( LDZ, * ) * .. * * Purpose * ======= * * DSBGVD computes all the eigenvalues, and optionally, the eigenvectors * of a real generalized symmetric-definite banded eigenproblem, of the * form A*x=(lambda)*B*x. Here A and B are assumed to be symmetric and * banded, and B is also positive definite. If eigenvectors are * desired, it uses a divide and conquer algorithm. * * The divide and conquer algorithm makes very mild assumptions about * floating point arithmetic. It will work on machines with a guard * digit in add/subtract, or on those binary machines without guard * digits which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or * Cray-2. It could conceivably fail on hexadecimal or decimal machines * without guard digits, but we know of none. * * Arguments * ========= * * JOBZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only; * = 'V': Compute eigenvalues and eigenvectors. * * UPLO (input) CHARACTER*1 * = 'U': Upper triangles of A and B are stored; * = 'L': Lower triangles of A and B are stored. * * N (input) INTEGER * The order of the matrices A and B. N >= 0. * * KA (input) INTEGER * The number of superdiagonals of the matrix A if UPLO = 'U', * or the number of subdiagonals if UPLO = 'L'. KA >= 0. * * KB (input) INTEGER * The number of superdiagonals of the matrix B if UPLO = 'U', * or the number of subdiagonals if UPLO = 'L'. KB >= 0. * * AB (input/output) DOUBLE PRECISION array, dimension (LDAB, N) * On entry, the upper or lower triangle of the symmetric band * matrix A, stored in the first ka+1 rows of the array. The * j-th column of A is stored in the j-th column of the array AB * as follows: * if UPLO = 'U', AB(ka+1+i-j,j) = A(i,j) for max(1,j-ka)<=i<=j; * if UPLO = 'L', AB(1+i-j,j) = A(i,j) for j<=i<=min(n,j+ka). * * On exit, the contents of AB are destroyed. * * LDAB (input) INTEGER * The leading dimension of the array AB. LDAB >= KA+1. * * BB (input/output) DOUBLE PRECISION array, dimension (LDBB, N) * On entry, the upper or lower triangle of the symmetric band * matrix B, stored in the first kb+1 rows of the array. The * j-th column of B is stored in the j-th column of the array BB * as follows: * if UPLO = 'U', BB(ka+1+i-j,j) = B(i,j) for max(1,j-kb)<=i<=j; * if UPLO = 'L', BB(1+i-j,j) = B(i,j) for j<=i<=min(n,j+kb). * * On exit, the factor S from the split Cholesky factorization * B = S**T*S, as returned by DPBSTF. * * LDBB (input) INTEGER * The leading dimension of the array BB. LDBB >= KB+1. * * W (output) DOUBLE PRECISION array, dimension (N) * If INFO = 0, the eigenvalues in ascending order. * * Z (output) DOUBLE PRECISION array, dimension (LDZ, N) * If JOBZ = 'V', then if INFO = 0, Z contains the matrix Z of * eigenvectors, with the i-th column of Z holding the * eigenvector associated with W(i). The eigenvectors are * normalized so Z**T*B*Z = I. * If JOBZ = 'N', then Z is not referenced. * * LDZ (input) INTEGER * The leading dimension of the array Z. LDZ >= 1, and if * JOBZ = 'V', LDZ >= max(1,N). * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. * If N <= 1, LWORK >= 1. * If JOBZ = 'N' and N > 1, LWORK >= 3*N. * If JOBZ = 'V' and N > 1, LWORK >= 1 + 5*N + 2*N**2. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * IWORK (workspace/output) INTEGER array, dimension (LIWORK) * On exit, if LIWORK > 0, IWORK(1) returns the optimal LIWORK. * * LIWORK (input) INTEGER * The dimension of the array IWORK. * If JOBZ = 'N' or N <= 1, LIWORK >= 1. * If JOBZ = 'V' and N > 1, LIWORK >= 3 + 5*N. * * If LIWORK = -1, then a workspace query is assumed; the * routine only calculates the optimal size of the IWORK array, * returns this value as the first entry of the IWORK array, and * no error message related to LIWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = i, and i is: * <= N: the algorithm failed to converge: * i off-diagonal elements of an intermediate * tridiagonal form did not converge to zero; * > N: if INFO = N + i, for 1 <= i <= N, then DPBSTF * returned INFO = i: B is not positive definite. * The factorization of B could not be completed and * no eigenvalues or eigenvectors were computed. * * Further Details * =============== * * Based on contributions by * Mark Fahey, Department of Mathematics, Univ. of Kentucky, USA * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE, ZERO PARAMETER ( ONE = 1.0D+0, ZERO = 0.0D+0 ) * .. * .. Local Scalars .. LOGICAL LQUERY, UPPER, WANTZ CHARACTER VECT INTEGER IINFO, INDE, INDWK2, INDWRK, LIWMIN, LLWRK2, $ LWMIN * .. * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. External Subroutines .. EXTERNAL DGEMM, DLACPY, DPBSTF, DSBGST, DSBTRD, DSTEDC, $ DSTERF, XERBLA * .. * .. Executable Statements .. * * Test the input parameters. * WANTZ = LSAME( JOBZ, 'V' ) UPPER = LSAME( UPLO, 'U' ) LQUERY = ( LWORK.EQ.-1 .OR. LIWORK.EQ.-1 ) * INFO = 0 IF( N.LE.1 ) THEN LIWMIN = 1 LWMIN = 1 ELSE IF( WANTZ ) THEN LIWMIN = 3 + 5*N LWMIN = 1 + 5*N + 2*N**2 ELSE LIWMIN = 1 LWMIN = 2*N END IF END IF * IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN INFO = -1 ELSE IF( .NOT.( UPPER .OR. LSAME( UPLO, 'L' ) ) ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( KA.LT.0 ) THEN INFO = -4 ELSE IF( KB.LT.0 .OR. KB.GT.KA ) THEN INFO = -5 ELSE IF( LDAB.LT.KA+1 ) THEN INFO = -7 ELSE IF( LDBB.LT.KB+1 ) THEN INFO = -9 ELSE IF( LDZ.LT.1 .OR. ( WANTZ .AND. LDZ.LT.N ) ) THEN INFO = -12 ELSE IF( LWORK.LT.LWMIN .AND. .NOT.LQUERY ) THEN INFO = -14 ELSE IF( LIWORK.LT.LIWMIN .AND. .NOT.LQUERY ) THEN INFO = -16 END IF * IF( INFO.EQ.0 ) THEN WORK( 1 ) = LWMIN IWORK( 1 ) = LIWMIN END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSBGVD', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * * Form a split Cholesky factorization of B. * CALL DPBSTF( UPLO, N, KB, BB, LDBB, INFO ) IF( INFO.NE.0 ) THEN INFO = N + INFO RETURN END IF * * Transform problem to standard eigenvalue problem. * INDE = 1 INDWRK = INDE + N INDWK2 = INDWRK + N*N LLWRK2 = LWORK - INDWK2 + 1 CALL DSBGST( JOBZ, UPLO, N, KA, KB, AB, LDAB, BB, LDBB, Z, LDZ, $ WORK( INDWRK ), IINFO ) * * Reduce to tridiagonal form. * IF( WANTZ ) THEN VECT = 'U' ELSE VECT = 'N' END IF CALL DSBTRD( VECT, UPLO, N, KA, AB, LDAB, W, WORK( INDE ), Z, LDZ, $ WORK( INDWRK ), IINFO ) * * For eigenvalues only, call DSTERF. For eigenvectors, call SSTEDC. * IF( .NOT.WANTZ ) THEN CALL DSTERF( N, W, WORK( INDE ), INFO ) ELSE CALL DSTEDC( 'I', N, W, WORK( INDE ), WORK( INDWRK ), N, $ WORK( INDWK2 ), LLWRK2, IWORK, LIWORK, INFO ) CALL DGEMM( 'N', 'N', N, N, N, ONE, Z, LDZ, WORK( INDWRK ), N, $ ZERO, WORK( INDWK2 ), N ) CALL DLACPY( 'A', N, N, WORK( INDWK2 ), N, Z, LDZ ) END IF * WORK( 1 ) = LWMIN IWORK( 1 ) = LIWMIN * RETURN * * End of DSBGVD * END SUBROUTINE DSBGVX( JOBZ, RANGE, UPLO, N, KA, KB, AB, LDAB, BB, $ LDBB, Q, LDQ, VL, VU, IL, IU, ABSTOL, M, W, Z, $ LDZ, WORK, IWORK, IFAIL, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBZ, RANGE, UPLO INTEGER IL, INFO, IU, KA, KB, LDAB, LDBB, LDQ, LDZ, M, $ N DOUBLE PRECISION ABSTOL, VL, VU * .. * .. Array Arguments .. INTEGER IFAIL( * ), IWORK( * ) DOUBLE PRECISION AB( LDAB, * ), BB( LDBB, * ), Q( LDQ, * ), $ W( * ), WORK( * ), Z( LDZ, * ) * .. * * Purpose * ======= * * DSBGVX computes selected eigenvalues, and optionally, eigenvectors * of a real generalized symmetric-definite banded eigenproblem, of * the form A*x=(lambda)*B*x. Here A and B are assumed to be symmetric * and banded, and B is also positive definite. Eigenvalues and * eigenvectors can be selected by specifying either all eigenvalues, * a range of values or a range of indices for the desired eigenvalues. * * Arguments * ========= * * JOBZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only; * = 'V': Compute eigenvalues and eigenvectors. * * RANGE (input) CHARACTER*1 * = 'A': all eigenvalues will be found. * = 'V': all eigenvalues in the half-open interval (VL,VU] * will be found. * = 'I': the IL-th through IU-th eigenvalues will be found. * * UPLO (input) CHARACTER*1 * = 'U': Upper triangles of A and B are stored; * = 'L': Lower triangles of A and B are stored. * * N (input) INTEGER * The order of the matrices A and B. N >= 0. * * KA (input) INTEGER * The number of superdiagonals of the matrix A if UPLO = 'U', * or the number of subdiagonals if UPLO = 'L'. KA >= 0. * * KB (input) INTEGER * The number of superdiagonals of the matrix B if UPLO = 'U', * or the number of subdiagonals if UPLO = 'L'. KB >= 0. * * AB (input/output) DOUBLE PRECISION array, dimension (LDAB, N) * On entry, the upper or lower triangle of the symmetric band * matrix A, stored in the first ka+1 rows of the array. The * j-th column of A is stored in the j-th column of the array AB * as follows: * if UPLO = 'U', AB(ka+1+i-j,j) = A(i,j) for max(1,j-ka)<=i<=j; * if UPLO = 'L', AB(1+i-j,j) = A(i,j) for j<=i<=min(n,j+ka). * * On exit, the contents of AB are destroyed. * * LDAB (input) INTEGER * The leading dimension of the array AB. LDAB >= KA+1. * * BB (input/output) DOUBLE PRECISION array, dimension (LDBB, N) * On entry, the upper or lower triangle of the symmetric band * matrix B, stored in the first kb+1 rows of the array. The * j-th column of B is stored in the j-th column of the array BB * as follows: * if UPLO = 'U', BB(ka+1+i-j,j) = B(i,j) for max(1,j-kb)<=i<=j; * if UPLO = 'L', BB(1+i-j,j) = B(i,j) for j<=i<=min(n,j+kb). * * On exit, the factor S from the split Cholesky factorization * B = S**T*S, as returned by DPBSTF. * * LDBB (input) INTEGER * The leading dimension of the array BB. LDBB >= KB+1. * * Q (output) DOUBLE PRECISION array, dimension (LDQ, N) * If JOBZ = 'V', the n-by-n matrix used in the reduction of * A*x = (lambda)*B*x to standard form, i.e. C*x = (lambda)*x, * and consequently C to tridiagonal form. * If JOBZ = 'N', the array Q is not referenced. * * LDQ (input) INTEGER * The leading dimension of the array Q. If JOBZ = 'N', * LDQ >= 1. If JOBZ = 'V', LDQ >= max(1,N). * * VL (input) DOUBLE PRECISION * VU (input) DOUBLE PRECISION * If RANGE='V', the lower and upper bounds of the interval to * be searched for eigenvalues. VL < VU. * Not referenced if RANGE = 'A' or 'I'. * * IL (input) INTEGER * IU (input) INTEGER * If RANGE='I', the indices (in ascending order) of the * smallest and largest eigenvalues to be returned. * 1 <= IL <= IU <= N, if N > 0; IL = 1 and IU = 0 if N = 0. * Not referenced if RANGE = 'A' or 'V'. * * ABSTOL (input) DOUBLE PRECISION * The absolute error tolerance for the eigenvalues. * An approximate eigenvalue is accepted as converged * when it is determined to lie in an interval [a,b] * of width less than or equal to * * ABSTOL + EPS * max( |a|,|b| ) , * * where EPS is the machine precision. If ABSTOL is less than * or equal to zero, then EPS*|T| will be used in its place, * where |T| is the 1-norm of the tridiagonal matrix obtained * by reducing A to tridiagonal form. * * Eigenvalues will be computed most accurately when ABSTOL is * set to twice the underflow threshold 2*DLAMCH('S'), not zero. * If this routine returns with INFO>0, indicating that some * eigenvectors did not converge, try setting ABSTOL to * 2*DLAMCH('S'). * * M (output) INTEGER * The total number of eigenvalues found. 0 <= M <= N. * If RANGE = 'A', M = N, and if RANGE = 'I', M = IU-IL+1. * * W (output) DOUBLE PRECISION array, dimension (N) * If INFO = 0, the eigenvalues in ascending order. * * Z (output) DOUBLE PRECISION array, dimension (LDZ, N) * If JOBZ = 'V', then if INFO = 0, Z contains the matrix Z of * eigenvectors, with the i-th column of Z holding the * eigenvector associated with W(i). The eigenvectors are * normalized so Z**T*B*Z = I. * If JOBZ = 'N', then Z is not referenced. * * LDZ (input) INTEGER * The leading dimension of the array Z. LDZ >= 1, and if * JOBZ = 'V', LDZ >= max(1,N). * * WORK (workspace/output) DOUBLE PRECISION array, dimension (7N) * * IWORK (workspace/output) INTEGER array, dimension (5N) * * IFAIL (input) INTEGER array, dimension (M) * If JOBZ = 'V', then if INFO = 0, the first M elements of * IFAIL are zero. If INFO > 0, then IFAIL contains the * indices of the eigenvalues that failed to converge. * If JOBZ = 'N', then IFAIL is not referenced. * * INFO (output) INTEGER * = 0 : successful exit * < 0 : if INFO = -i, the i-th argument had an illegal value * <= N: if INFO = i, then i eigenvectors failed to converge. * Their indices are stored in IFAIL. * > N : DPBSTF returned an error code; i.e., * if INFO = N + i, for 1 <= i <= N, then the leading * minor of order i of B is not positive definite. * The factorization of B could not be completed and * no eigenvalues or eigenvectors were computed. * * Further Details * =============== * * Based on contributions by * Mark Fahey, Department of Mathematics, Univ. of Kentucky, USA * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL ALLEIG, INDEIG, UPPER, VALEIG, WANTZ CHARACTER ORDER, VECT INTEGER I, IINFO, INDD, INDE, INDEE, INDIBL, INDISP, $ INDIWO, INDWRK, ITMP1, J, JJ, NSPLIT DOUBLE PRECISION TMP1 * .. * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. External Subroutines .. EXTERNAL DCOPY, DGEMV, DLACPY, DPBSTF, DSBGST, DSBTRD, $ DSTEBZ, DSTEIN, DSTEQR, DSTERF, DSWAP, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MIN * .. * .. Executable Statements .. * * Test the input parameters. * WANTZ = LSAME( JOBZ, 'V' ) UPPER = LSAME( UPLO, 'U' ) ALLEIG = LSAME( RANGE, 'A' ) VALEIG = LSAME( RANGE, 'V' ) INDEIG = LSAME( RANGE, 'I' ) * INFO = 0 IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN INFO = -1 ELSE IF( .NOT.( ALLEIG .OR. VALEIG .OR. INDEIG ) ) THEN INFO = -2 ELSE IF( .NOT.( UPPER .OR. LSAME( UPLO, 'L' ) ) ) THEN INFO = -3 ELSE IF( N.LT.0 ) THEN INFO = -4 ELSE IF( KA.LT.0 ) THEN INFO = -5 ELSE IF( KB.LT.0 .OR. KB.GT.KA ) THEN INFO = -6 ELSE IF( LDAB.LT.KA+1 ) THEN INFO = -8 ELSE IF( LDBB.LT.KB+1 ) THEN INFO = -10 ELSE IF( LDQ.LT.1 ) THEN INFO = -12 ELSE IF( VALEIG .AND. N.GT.0 .AND. VU.LE.VL ) THEN INFO = -14 ELSE IF( INDEIG .AND. IL.LT.1 ) THEN INFO = -15 ELSE IF( INDEIG .AND. ( IU.LT.MIN( N, IL ) .OR. IU.GT.N ) ) THEN INFO = -16 ELSE IF( LDZ.LT.1 .OR. ( WANTZ .AND. LDZ.LT.N ) ) THEN INFO = -21 END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSBGVX', -INFO ) RETURN END IF * * Quick return if possible * M = 0 IF( N.EQ.0 ) THEN WORK( 1 ) = 1 RETURN END IF * * Form a split Cholesky factorization of B. * CALL DPBSTF( UPLO, N, KB, BB, LDBB, INFO ) IF( INFO.NE.0 ) THEN INFO = N + INFO RETURN END IF * * Transform problem to standard eigenvalue problem. * CALL DSBGST( JOBZ, UPLO, N, KA, KB, AB, LDAB, BB, LDBB, Q, LDQ, $ WORK, IINFO ) * * Reduce symmetric band matrix to tridiagonal form. * INDD = 1 INDE = INDD + N INDWRK = INDE + N IF( WANTZ ) THEN VECT = 'U' ELSE VECT = 'N' END IF CALL DSBTRD( VECT, UPLO, N, KA, AB, LDAB, WORK( INDD ), $ WORK( INDE ), Q, LDQ, WORK( INDWRK ), IINFO ) * * If all eigenvalues are desired and ABSTOL is less than or equal * to zero, then call DSTERF or SSTEQR. If this fails for some * eigenvalue, then try DSTEBZ. * IF( ( ALLEIG .OR. ( INDEIG .AND. IL.EQ.1 .AND. IU.EQ.N ) ) .AND. $ ( ABSTOL.LE.ZERO ) ) THEN CALL DCOPY( N, WORK( INDD ), 1, W, 1 ) INDEE = INDWRK + 2*N CALL DCOPY( N-1, WORK( INDE ), 1, WORK( INDEE ), 1 ) IF( .NOT.WANTZ ) THEN CALL DSTERF( N, W, WORK( INDEE ), INFO ) ELSE CALL DLACPY( 'A', N, N, Q, LDQ, Z, LDZ ) CALL DSTEQR( JOBZ, N, W, WORK( INDEE ), Z, LDZ, $ WORK( INDWRK ), INFO ) IF( INFO.EQ.0 ) THEN DO 10 I = 1, N IFAIL( I ) = 0 10 CONTINUE END IF END IF IF( INFO.EQ.0 ) THEN M = N GO TO 30 END IF INFO = 0 END IF * * Otherwise, call DSTEBZ and, if eigenvectors are desired, * call DSTEIN. * IF( WANTZ ) THEN ORDER = 'B' ELSE ORDER = 'E' END IF INDIBL = 1 INDISP = INDIBL + N INDIWO = INDISP + N CALL DSTEBZ( RANGE, ORDER, N, VL, VU, IL, IU, ABSTOL, $ WORK( INDD ), WORK( INDE ), M, NSPLIT, W, $ IWORK( INDIBL ), IWORK( INDISP ), WORK( INDWRK ), $ IWORK( INDIWO ), INFO ) * IF( WANTZ ) THEN CALL DSTEIN( N, WORK( INDD ), WORK( INDE ), M, W, $ IWORK( INDIBL ), IWORK( INDISP ), Z, LDZ, $ WORK( INDWRK ), IWORK( INDIWO ), IFAIL, INFO ) * * Apply transformation matrix used in reduction to tridiagonal * form to eigenvectors returned by DSTEIN. * DO 20 J = 1, M CALL DCOPY( N, Z( 1, J ), 1, WORK( 1 ), 1 ) CALL DGEMV( 'N', N, N, ONE, Q, LDQ, WORK, 1, ZERO, $ Z( 1, J ), 1 ) 20 CONTINUE END IF * 30 CONTINUE * * If eigenvalues are not in order, then sort them, along with * eigenvectors. * IF( WANTZ ) THEN DO 50 J = 1, M - 1 I = 0 TMP1 = W( J ) DO 40 JJ = J + 1, M IF( W( JJ ).LT.TMP1 ) THEN I = JJ TMP1 = W( JJ ) END IF 40 CONTINUE * IF( I.NE.0 ) THEN ITMP1 = IWORK( INDIBL+I-1 ) W( I ) = W( J ) IWORK( INDIBL+I-1 ) = IWORK( INDIBL+J-1 ) W( J ) = TMP1 IWORK( INDIBL+J-1 ) = ITMP1 CALL DSWAP( N, Z( 1, I ), 1, Z( 1, J ), 1 ) IF( INFO.NE.0 ) THEN ITMP1 = IFAIL( I ) IFAIL( I ) = IFAIL( J ) IFAIL( J ) = ITMP1 END IF END IF 50 CONTINUE END IF * RETURN * * End of DSBGVX * END SUBROUTINE DSPEV( JOBZ, UPLO, N, AP, W, Z, LDZ, WORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * March 31, 1993 * * .. Scalar Arguments .. CHARACTER JOBZ, UPLO INTEGER INFO, LDZ, N * .. * .. Array Arguments .. DOUBLE PRECISION AP( * ), W( * ), WORK( * ), Z( LDZ, * ) * .. * * Purpose * ======= * * DSPEV computes all the eigenvalues and, optionally, eigenvectors of a * real symmetric matrix A in packed storage. * * Arguments * ========= * * JOBZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only; * = 'V': Compute eigenvalues and eigenvectors. * * UPLO (input) CHARACTER*1 * = 'U': Upper triangle of A is stored; * = 'L': Lower triangle of A is stored. * * N (input) INTEGER * The order of the matrix A. N >= 0. * * AP (input/output) DOUBLE PRECISION array, dimension (N*(N+1)/2) * On entry, the upper or lower triangle of the symmetric matrix * A, packed columnwise in a linear array. The j-th column of A * is stored in the array AP as follows: * if UPLO = 'U', AP(i + (j-1)*j/2) = A(i,j) for 1<=i<=j; * if UPLO = 'L', AP(i + (j-1)*(2*n-j)/2) = A(i,j) for j<=i<=n. * * On exit, AP is overwritten by values generated during the * reduction to tridiagonal form. If UPLO = 'U', the diagonal * and first superdiagonal of the tridiagonal matrix T overwrite * the corresponding elements of A, and if UPLO = 'L', the * diagonal and first subdiagonal of T overwrite the * corresponding elements of A. * * W (output) DOUBLE PRECISION array, dimension (N) * If INFO = 0, the eigenvalues in ascending order. * * Z (output) DOUBLE PRECISION array, dimension (LDZ, N) * If JOBZ = 'V', then if INFO = 0, Z contains the orthonormal * eigenvectors of the matrix A, with the i-th column of Z * holding the eigenvector associated with W(i). * If JOBZ = 'N', then Z is not referenced. * * LDZ (input) INTEGER * The leading dimension of the array Z. LDZ >= 1, and if * JOBZ = 'V', LDZ >= max(1,N). * * WORK (workspace) DOUBLE PRECISION array, dimension (3*N) * * INFO (output) INTEGER * = 0: successful exit. * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: if INFO = i, the algorithm failed to converge; i * off-diagonal elements of an intermediate tridiagonal * form did not converge to zero. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. LOGICAL WANTZ INTEGER IINFO, IMAX, INDE, INDTAU, INDWRK, ISCALE DOUBLE PRECISION ANRM, BIGNUM, EPS, RMAX, RMIN, SAFMIN, SIGMA, $ SMLNUM * .. * .. External Functions .. LOGICAL LSAME DOUBLE PRECISION DLAMCH, DLANSP EXTERNAL LSAME, DLAMCH, DLANSP * .. * .. External Subroutines .. EXTERNAL DOPGTR, DSCAL, DSPTRD, DSTEQR, DSTERF, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC SQRT * .. * .. Executable Statements .. * * Test the input parameters. * WANTZ = LSAME( JOBZ, 'V' ) * INFO = 0 IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN INFO = -1 ELSE IF( .NOT.( LSAME( UPLO, 'U' ) .OR. LSAME( UPLO, 'L' ) ) ) $ THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( LDZ.LT.1 .OR. ( WANTZ .AND. LDZ.LT.N ) ) THEN INFO = -7 END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSPEV ', -INFO ) RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * IF( N.EQ.1 ) THEN W( 1 ) = AP( 1 ) IF( WANTZ ) $ Z( 1, 1 ) = ONE RETURN END IF * * Get machine constants. * SAFMIN = DLAMCH( 'Safe minimum' ) EPS = DLAMCH( 'Precision' ) SMLNUM = SAFMIN / EPS BIGNUM = ONE / SMLNUM RMIN = SQRT( SMLNUM ) RMAX = SQRT( BIGNUM ) * * Scale matrix to allowable range, if necessary. * ANRM = DLANSP( 'M', UPLO, N, AP, WORK ) ISCALE = 0 IF( ANRM.GT.ZERO .AND. ANRM.LT.RMIN ) THEN ISCALE = 1 SIGMA = RMIN / ANRM ELSE IF( ANRM.GT.RMAX ) THEN ISCALE = 1 SIGMA = RMAX / ANRM END IF IF( ISCALE.EQ.1 ) THEN CALL DSCAL( ( N*( N+1 ) ) / 2, SIGMA, AP, 1 ) END IF * * Call DSPTRD to reduce symmetric packed matrix to tridiagonal form. * INDE = 1 INDTAU = INDE + N CALL DSPTRD( UPLO, N, AP, W, WORK( INDE ), WORK( INDTAU ), IINFO ) * * For eigenvalues only, call DSTERF. For eigenvectors, first call * DOPGTR to generate the orthogonal matrix, then call DSTEQR. * IF( .NOT.WANTZ ) THEN CALL DSTERF( N, W, WORK( INDE ), INFO ) ELSE INDWRK = INDTAU + N CALL DOPGTR( UPLO, N, AP, WORK( INDTAU ), Z, LDZ, $ WORK( INDWRK ), IINFO ) CALL DSTEQR( JOBZ, N, W, WORK( INDE ), Z, LDZ, WORK( INDTAU ), $ INFO ) END IF * * If matrix was scaled, then rescale eigenvalues appropriately. * IF( ISCALE.EQ.1 ) THEN IF( INFO.EQ.0 ) THEN IMAX = N ELSE IMAX = INFO - 1 END IF CALL DSCAL( IMAX, ONE / SIGMA, W, 1 ) END IF * RETURN * * End of DSPEV * END SUBROUTINE DSPEVD( JOBZ, UPLO, N, AP, W, Z, LDZ, WORK, LWORK, $ IWORK, LIWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBZ, UPLO INTEGER INFO, LDZ, LIWORK, LWORK, N * .. * .. Array Arguments .. INTEGER IWORK( * ) DOUBLE PRECISION AP( * ), W( * ), WORK( * ), Z( LDZ, * ) * .. * * Purpose * ======= * * DSPEVD computes all the eigenvalues and, optionally, eigenvectors * of a real symmetric matrix A in packed storage. If eigenvectors are * desired, it uses a divide and conquer algorithm. * * The divide and conquer algorithm makes very mild assumptions about * floating point arithmetic. It will work on machines with a guard * digit in add/subtract, or on those binary machines without guard * digits which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or * Cray-2. It could conceivably fail on hexadecimal or decimal machines * without guard digits, but we know of none. * * Arguments * ========= * * JOBZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only; * = 'V': Compute eigenvalues and eigenvectors. * * UPLO (input) CHARACTER*1 * = 'U': Upper triangle of A is stored; * = 'L': Lower triangle of A is stored. * * N (input) INTEGER * The order of the matrix A. N >= 0. * * AP (input/output) DOUBLE PRECISION array, dimension (N*(N+1)/2) * On entry, the upper or lower triangle of the symmetric matrix * A, packed columnwise in a linear array. The j-th column of A * is stored in the array AP as follows: * if UPLO = 'U', AP(i + (j-1)*j/2) = A(i,j) for 1<=i<=j; * if UPLO = 'L', AP(i + (j-1)*(2*n-j)/2) = A(i,j) for j<=i<=n. * * On exit, AP is overwritten by values generated during the * reduction to tridiagonal form. If UPLO = 'U', the diagonal * and first superdiagonal of the tridiagonal matrix T overwrite * the corresponding elements of A, and if UPLO = 'L', the * diagonal and first subdiagonal of T overwrite the * corresponding elements of A. * * W (output) DOUBLE PRECISION array, dimension (N) * If INFO = 0, the eigenvalues in ascending order. * * Z (output) DOUBLE PRECISION array, dimension (LDZ, N) * If JOBZ = 'V', then if INFO = 0, Z contains the orthonormal * eigenvectors of the matrix A, with the i-th column of Z * holding the eigenvector associated with W(i). * If JOBZ = 'N', then Z is not referenced. * * LDZ (input) INTEGER * The leading dimension of the array Z. LDZ >= 1, and if * JOBZ = 'V', LDZ >= max(1,N). * * WORK (workspace/output) DOUBLE PRECISION array, * dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. * If N <= 1, LWORK must be at least 1. * If JOBZ = 'N' and N > 1, LWORK must be at least 2*N. * If JOBZ = 'V' and N > 1, LWORK must be at least * 1 + 6*N + N**2. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * IWORK (workspace/output) INTEGER array, dimension (LIWORK) * On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK. * * LIWORK (input) INTEGER * The dimension of the array IWORK. * If JOBZ = 'N' or N <= 1, LIWORK must be at least 1. * If JOBZ = 'V' and N > 1, LIWORK must be at least 3 + 5*N. * * If LIWORK = -1, then a workspace query is assumed; the * routine only calculates the optimal size of the IWORK array, * returns this value as the first entry of the IWORK array, and * no error message related to LIWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: if INFO = i, the algorithm failed to converge; i * off-diagonal elements of an intermediate tridiagonal * form did not converge to zero. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL LQUERY, WANTZ INTEGER IINFO, INDE, INDTAU, INDWRK, ISCALE, LIWMIN, $ LLWORK, LWMIN DOUBLE PRECISION ANRM, BIGNUM, EPS, RMAX, RMIN, SAFMIN, SIGMA, $ SMLNUM * .. * .. External Functions .. LOGICAL LSAME DOUBLE PRECISION DLAMCH, DLANSP EXTERNAL LSAME, DLAMCH, DLANSP * .. * .. External Subroutines .. EXTERNAL DOPMTR, DSCAL, DSPTRD, DSTEDC, DSTERF, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC SQRT * .. * .. Executable Statements .. * * Test the input parameters. * WANTZ = LSAME( JOBZ, 'V' ) LQUERY = ( LWORK.EQ.-1 .OR. LIWORK.EQ.-1 ) * INFO = 0 IF( N.LE.1 ) THEN LIWMIN = 1 LWMIN = 1 ELSE IF( WANTZ ) THEN LIWMIN = 3 + 5*N LWMIN = 1 + 6*N + N**2 ELSE LIWMIN = 1 LWMIN = 2*N END IF END IF IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN INFO = -1 ELSE IF( .NOT.( LSAME( UPLO, 'U' ) .OR. LSAME( UPLO, 'L' ) ) ) $ THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( LDZ.LT.1 .OR. ( WANTZ .AND. LDZ.LT.N ) ) THEN INFO = -7 ELSE IF( LWORK.LT.LWMIN .AND. .NOT.LQUERY ) THEN INFO = -9 ELSE IF( LIWORK.LT.LIWMIN .AND. .NOT.LQUERY ) THEN INFO = -11 END IF * IF( INFO.EQ.0 ) THEN WORK( 1 ) = LWMIN IWORK( 1 ) = LIWMIN END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSPEVD', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * IF( N.EQ.1 ) THEN W( 1 ) = AP( 1 ) IF( WANTZ ) $ Z( 1, 1 ) = ONE RETURN END IF * * Get machine constants. * SAFMIN = DLAMCH( 'Safe minimum' ) EPS = DLAMCH( 'Precision' ) SMLNUM = SAFMIN / EPS BIGNUM = ONE / SMLNUM RMIN = SQRT( SMLNUM ) RMAX = SQRT( BIGNUM ) * * Scale matrix to allowable range, if necessary. * ANRM = DLANSP( 'M', UPLO, N, AP, WORK ) ISCALE = 0 IF( ANRM.GT.ZERO .AND. ANRM.LT.RMIN ) THEN ISCALE = 1 SIGMA = RMIN / ANRM ELSE IF( ANRM.GT.RMAX ) THEN ISCALE = 1 SIGMA = RMAX / ANRM END IF IF( ISCALE.EQ.1 ) THEN CALL DSCAL( ( N*( N+1 ) ) / 2, SIGMA, AP, 1 ) END IF * * Call DSPTRD to reduce symmetric packed matrix to tridiagonal form. * INDE = 1 INDTAU = INDE + N CALL DSPTRD( UPLO, N, AP, W, WORK( INDE ), WORK( INDTAU ), IINFO ) * * For eigenvalues only, call DSTERF. For eigenvectors, first call * DSTEDC to generate the eigenvector matrix, WORK(INDWRK), of the * tridiagonal matrix, then call DOPMTR to multiply it by the * Householder transformations represented in AP. * IF( .NOT.WANTZ ) THEN CALL DSTERF( N, W, WORK( INDE ), INFO ) ELSE INDWRK = INDTAU + N LLWORK = LWORK - INDWRK + 1 CALL DSTEDC( 'I', N, W, WORK( INDE ), Z, LDZ, WORK( INDWRK ), $ LLWORK, IWORK, LIWORK, INFO ) CALL DOPMTR( 'L', UPLO, 'N', N, N, AP, WORK( INDTAU ), Z, LDZ, $ WORK( INDWRK ), IINFO ) END IF * * If matrix was scaled, then rescale eigenvalues appropriately. * IF( ISCALE.EQ.1 ) $ CALL DSCAL( N, ONE / SIGMA, W, 1 ) * WORK( 1 ) = LWMIN IWORK( 1 ) = LIWMIN RETURN * * End of DSPEVD * END SUBROUTINE DSPEVX( JOBZ, RANGE, UPLO, N, AP, VL, VU, IL, IU, $ ABSTOL, M, W, Z, LDZ, WORK, IWORK, IFAIL, $ INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBZ, RANGE, UPLO INTEGER IL, INFO, IU, LDZ, M, N DOUBLE PRECISION ABSTOL, VL, VU * .. * .. Array Arguments .. INTEGER IFAIL( * ), IWORK( * ) DOUBLE PRECISION AP( * ), W( * ), WORK( * ), Z( LDZ, * ) * .. * * Purpose * ======= * * DSPEVX computes selected eigenvalues and, optionally, eigenvectors * of a real symmetric matrix A in packed storage. Eigenvalues/vectors * can be selected by specifying either a range of values or a range of * indices for the desired eigenvalues. * * Arguments * ========= * * JOBZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only; * = 'V': Compute eigenvalues and eigenvectors. * * RANGE (input) CHARACTER*1 * = 'A': all eigenvalues will be found; * = 'V': all eigenvalues in the half-open interval (VL,VU] * will be found; * = 'I': the IL-th through IU-th eigenvalues will be found. * * UPLO (input) CHARACTER*1 * = 'U': Upper triangle of A is stored; * = 'L': Lower triangle of A is stored. * * N (input) INTEGER * The order of the matrix A. N >= 0. * * AP (input/output) DOUBLE PRECISION array, dimension (N*(N+1)/2) * On entry, the upper or lower triangle of the symmetric matrix * A, packed columnwise in a linear array. The j-th column of A * is stored in the array AP as follows: * if UPLO = 'U', AP(i + (j-1)*j/2) = A(i,j) for 1<=i<=j; * if UPLO = 'L', AP(i + (j-1)*(2*n-j)/2) = A(i,j) for j<=i<=n. * * On exit, AP is overwritten by values generated during the * reduction to tridiagonal form. If UPLO = 'U', the diagonal * and first superdiagonal of the tridiagonal matrix T overwrite * the corresponding elements of A, and if UPLO = 'L', the * diagonal and first subdiagonal of T overwrite the * corresponding elements of A. * * VL (input) DOUBLE PRECISION * VU (input) DOUBLE PRECISION * If RANGE='V', the lower and upper bounds of the interval to * be searched for eigenvalues. VL < VU. * Not referenced if RANGE = 'A' or 'I'. * * IL (input) INTEGER * IU (input) INTEGER * If RANGE='I', the indices (in ascending order) of the * smallest and largest eigenvalues to be returned. * 1 <= IL <= IU <= N, if N > 0; IL = 1 and IU = 0 if N = 0. * Not referenced if RANGE = 'A' or 'V'. * * ABSTOL (input) DOUBLE PRECISION * The absolute error tolerance for the eigenvalues. * An approximate eigenvalue is accepted as converged * when it is determined to lie in an interval [a,b] * of width less than or equal to * * ABSTOL + EPS * max( |a|,|b| ) , * * where EPS is the machine precision. If ABSTOL is less than * or equal to zero, then EPS*|T| will be used in its place, * where |T| is the 1-norm of the tridiagonal matrix obtained * by reducing AP to tridiagonal form. * * Eigenvalues will be computed most accurately when ABSTOL is * set to twice the underflow threshold 2*DLAMCH('S'), not zero. * If this routine returns with INFO>0, indicating that some * eigenvectors did not converge, try setting ABSTOL to * 2*DLAMCH('S'). * * See "Computing Small Singular Values of Bidiagonal Matrices * with Guaranteed High Relative Accuracy," by Demmel and * Kahan, LAPACK Working Note #3. * * M (output) INTEGER * The total number of eigenvalues found. 0 <= M <= N. * If RANGE = 'A', M = N, and if RANGE = 'I', M = IU-IL+1. * * W (output) DOUBLE PRECISION array, dimension (N) * If INFO = 0, the selected eigenvalues in ascending order. * * Z (output) DOUBLE PRECISION array, dimension (LDZ, max(1,M)) * If JOBZ = 'V', then if INFO = 0, the first M columns of Z * contain the orthonormal eigenvectors of the matrix A * corresponding to the selected eigenvalues, with the i-th * column of Z holding the eigenvector associated with W(i). * If an eigenvector fails to converge, then that column of Z * contains the latest approximation to the eigenvector, and the * index of the eigenvector is returned in IFAIL. * If JOBZ = 'N', then Z is not referenced. * Note: the user must ensure that at least max(1,M) columns are * supplied in the array Z; if RANGE = 'V', the exact value of M * is not known in advance and an upper bound must be used. * * LDZ (input) INTEGER * The leading dimension of the array Z. LDZ >= 1, and if * JOBZ = 'V', LDZ >= max(1,N). * * WORK (workspace) DOUBLE PRECISION array, dimension (8*N) * * IWORK (workspace) INTEGER array, dimension (5*N) * * IFAIL (output) INTEGER array, dimension (N) * If JOBZ = 'V', then if INFO = 0, the first M elements of * IFAIL are zero. If INFO > 0, then IFAIL contains the * indices of the eigenvectors that failed to converge. * If JOBZ = 'N', then IFAIL is not referenced. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = i, then i eigenvectors failed to converge. * Their indices are stored in array IFAIL. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. LOGICAL ALLEIG, INDEIG, VALEIG, WANTZ CHARACTER ORDER INTEGER I, IINFO, IMAX, INDD, INDE, INDEE, INDIBL, $ INDISP, INDIWO, INDTAU, INDWRK, ISCALE, ITMP1, $ J, JJ, NSPLIT DOUBLE PRECISION ABSTLL, ANRM, BIGNUM, EPS, RMAX, RMIN, SAFMIN, $ SIGMA, SMLNUM, TMP1, VLL, VUU * .. * .. External Functions .. LOGICAL LSAME DOUBLE PRECISION DLAMCH, DLANSP EXTERNAL LSAME, DLAMCH, DLANSP * .. * .. External Subroutines .. EXTERNAL DCOPY, DOPGTR, DOPMTR, DSCAL, DSPTRD, DSTEBZ, $ DSTEIN, DSTEQR, DSTERF, DSWAP, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN, SQRT * .. * .. Executable Statements .. * * Test the input parameters. * WANTZ = LSAME( JOBZ, 'V' ) ALLEIG = LSAME( RANGE, 'A' ) VALEIG = LSAME( RANGE, 'V' ) INDEIG = LSAME( RANGE, 'I' ) * INFO = 0 IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN INFO = -1 ELSE IF( .NOT.( ALLEIG .OR. VALEIG .OR. INDEIG ) ) THEN INFO = -2 ELSE IF( .NOT.( LSAME( UPLO, 'L' ) .OR. LSAME( UPLO, 'U' ) ) ) $ THEN INFO = -3 ELSE IF( N.LT.0 ) THEN INFO = -4 ELSE IF( VALEIG ) THEN IF( N.GT.0 .AND. VU.LE.VL ) $ INFO = -7 ELSE IF( INDEIG ) THEN IF( IL.LT.1 .OR. IL.GT.MAX( 1, N ) ) THEN INFO = -8 ELSE IF( IU.LT.MIN( N, IL ) .OR. IU.GT.N ) THEN INFO = -9 END IF END IF END IF IF( INFO.EQ.0 ) THEN IF( LDZ.LT.1 .OR. ( WANTZ .AND. LDZ.LT.N ) ) $ INFO = -14 END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSPEVX', -INFO ) RETURN END IF * * Quick return if possible * M = 0 IF( N.EQ.0 ) $ RETURN * IF( N.EQ.1 ) THEN IF( ALLEIG .OR. INDEIG ) THEN M = 1 W( 1 ) = AP( 1 ) ELSE IF( VL.LT.AP( 1 ) .AND. VU.GE.AP( 1 ) ) THEN M = 1 W( 1 ) = AP( 1 ) END IF END IF IF( WANTZ ) $ Z( 1, 1 ) = ONE RETURN END IF * * Get machine constants. * SAFMIN = DLAMCH( 'Safe minimum' ) EPS = DLAMCH( 'Precision' ) SMLNUM = SAFMIN / EPS BIGNUM = ONE / SMLNUM RMIN = SQRT( SMLNUM ) RMAX = MIN( SQRT( BIGNUM ), ONE / SQRT( SQRT( SAFMIN ) ) ) * * Scale matrix to allowable range, if necessary. * ISCALE = 0 ABSTLL = ABSTOL IF( VALEIG ) THEN VLL = VL VUU = VU ELSE VLL = ZERO VUU = ZERO END IF ANRM = DLANSP( 'M', UPLO, N, AP, WORK ) IF( ANRM.GT.ZERO .AND. ANRM.LT.RMIN ) THEN ISCALE = 1 SIGMA = RMIN / ANRM ELSE IF( ANRM.GT.RMAX ) THEN ISCALE = 1 SIGMA = RMAX / ANRM END IF IF( ISCALE.EQ.1 ) THEN CALL DSCAL( ( N*( N+1 ) ) / 2, SIGMA, AP, 1 ) IF( ABSTOL.GT.0 ) $ ABSTLL = ABSTOL*SIGMA IF( VALEIG ) THEN VLL = VL*SIGMA VUU = VU*SIGMA END IF END IF * * Call DSPTRD to reduce symmetric packed matrix to tridiagonal form. * INDTAU = 1 INDE = INDTAU + N INDD = INDE + N INDWRK = INDD + N CALL DSPTRD( UPLO, N, AP, WORK( INDD ), WORK( INDE ), $ WORK( INDTAU ), IINFO ) * * If all eigenvalues are desired and ABSTOL is less than or equal * to zero, then call DSTERF or DOPGTR and SSTEQR. If this fails * for some eigenvalue, then try DSTEBZ. * IF( ( ALLEIG .OR. ( INDEIG .AND. IL.EQ.1 .AND. IU.EQ.N ) ) .AND. $ ( ABSTOL.LE.ZERO ) ) THEN CALL DCOPY( N, WORK( INDD ), 1, W, 1 ) INDEE = INDWRK + 2*N IF( .NOT.WANTZ ) THEN CALL DCOPY( N-1, WORK( INDE ), 1, WORK( INDEE ), 1 ) CALL DSTERF( N, W, WORK( INDEE ), INFO ) ELSE CALL DOPGTR( UPLO, N, AP, WORK( INDTAU ), Z, LDZ, $ WORK( INDWRK ), IINFO ) CALL DCOPY( N-1, WORK( INDE ), 1, WORK( INDEE ), 1 ) CALL DSTEQR( JOBZ, N, W, WORK( INDEE ), Z, LDZ, $ WORK( INDWRK ), INFO ) IF( INFO.EQ.0 ) THEN DO 10 I = 1, N IFAIL( I ) = 0 10 CONTINUE END IF END IF IF( INFO.EQ.0 ) THEN M = N GO TO 20 END IF INFO = 0 END IF * * Otherwise, call DSTEBZ and, if eigenvectors are desired, SSTEIN. * IF( WANTZ ) THEN ORDER = 'B' ELSE ORDER = 'E' END IF INDIBL = 1 INDISP = INDIBL + N INDIWO = INDISP + N CALL DSTEBZ( RANGE, ORDER, N, VLL, VUU, IL, IU, ABSTLL, $ WORK( INDD ), WORK( INDE ), M, NSPLIT, W, $ IWORK( INDIBL ), IWORK( INDISP ), WORK( INDWRK ), $ IWORK( INDIWO ), INFO ) * IF( WANTZ ) THEN CALL DSTEIN( N, WORK( INDD ), WORK( INDE ), M, W, $ IWORK( INDIBL ), IWORK( INDISP ), Z, LDZ, $ WORK( INDWRK ), IWORK( INDIWO ), IFAIL, INFO ) * * Apply orthogonal matrix used in reduction to tridiagonal * form to eigenvectors returned by DSTEIN. * CALL DOPMTR( 'L', UPLO, 'N', N, M, AP, WORK( INDTAU ), Z, LDZ, $ WORK( INDWRK ), INFO ) END IF * * If matrix was scaled, then rescale eigenvalues appropriately. * 20 CONTINUE IF( ISCALE.EQ.1 ) THEN IF( INFO.EQ.0 ) THEN IMAX = M ELSE IMAX = INFO - 1 END IF CALL DSCAL( IMAX, ONE / SIGMA, W, 1 ) END IF * * If eigenvalues are not in order, then sort them, along with * eigenvectors. * IF( WANTZ ) THEN DO 40 J = 1, M - 1 I = 0 TMP1 = W( J ) DO 30 JJ = J + 1, M IF( W( JJ ).LT.TMP1 ) THEN I = JJ TMP1 = W( JJ ) END IF 30 CONTINUE * IF( I.NE.0 ) THEN ITMP1 = IWORK( INDIBL+I-1 ) W( I ) = W( J ) IWORK( INDIBL+I-1 ) = IWORK( INDIBL+J-1 ) W( J ) = TMP1 IWORK( INDIBL+J-1 ) = ITMP1 CALL DSWAP( N, Z( 1, I ), 1, Z( 1, J ), 1 ) IF( INFO.NE.0 ) THEN ITMP1 = IFAIL( I ) IFAIL( I ) = IFAIL( J ) IFAIL( J ) = ITMP1 END IF END IF 40 CONTINUE END IF * RETURN * * End of DSPEVX * END SUBROUTINE DSPGV( ITYPE, JOBZ, UPLO, N, AP, BP, W, Z, LDZ, WORK, $ INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * September 30, 1994 * * .. Scalar Arguments .. CHARACTER JOBZ, UPLO INTEGER INFO, ITYPE, LDZ, N * .. * .. Array Arguments .. DOUBLE PRECISION AP( * ), BP( * ), W( * ), WORK( * ), $ Z( LDZ, * ) * .. * * Purpose * ======= * * DSPGV computes all the eigenvalues and, optionally, the eigenvectors * of a real generalized symmetric-definite eigenproblem, of the form * A*x=(lambda)*B*x, A*Bx=(lambda)*x, or B*A*x=(lambda)*x. * Here A and B are assumed to be symmetric, stored in packed format, * and B is also positive definite. * * Arguments * ========= * * ITYPE (input) INTEGER * Specifies the problem type to be solved: * = 1: A*x = (lambda)*B*x * = 2: A*B*x = (lambda)*x * = 3: B*A*x = (lambda)*x * * JOBZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only; * = 'V': Compute eigenvalues and eigenvectors. * * UPLO (input) CHARACTER*1 * = 'U': Upper triangles of A and B are stored; * = 'L': Lower triangles of A and B are stored. * * N (input) INTEGER * The order of the matrices A and B. N >= 0. * * AP (input/output) DOUBLE PRECISION array, dimension * (N*(N+1)/2) * On entry, the upper or lower triangle of the symmetric matrix * A, packed columnwise in a linear array. The j-th column of A * is stored in the array AP as follows: * if UPLO = 'U', AP(i + (j-1)*j/2) = A(i,j) for 1<=i<=j; * if UPLO = 'L', AP(i + (j-1)*(2*n-j)/2) = A(i,j) for j<=i<=n. * * On exit, the contents of AP are destroyed. * * BP (input/output) DOUBLE PRECISION array, dimension (N*(N+1)/2) * On entry, the upper or lower triangle of the symmetric matrix * B, packed columnwise in a linear array. The j-th column of B * is stored in the array BP as follows: * if UPLO = 'U', BP(i + (j-1)*j/2) = B(i,j) for 1<=i<=j; * if UPLO = 'L', BP(i + (j-1)*(2*n-j)/2) = B(i,j) for j<=i<=n. * * On exit, the triangular factor U or L from the Cholesky * factorization B = U**T*U or B = L*L**T, in the same storage * format as B. * * W (output) DOUBLE PRECISION array, dimension (N) * If INFO = 0, the eigenvalues in ascending order. * * Z (output) DOUBLE PRECISION array, dimension (LDZ, N) * If JOBZ = 'V', then if INFO = 0, Z contains the matrix Z of * eigenvectors. The eigenvectors are normalized as follows: * if ITYPE = 1 or 2, Z**T*B*Z = I; * if ITYPE = 3, Z**T*inv(B)*Z = I. * If JOBZ = 'N', then Z is not referenced. * * LDZ (input) INTEGER * The leading dimension of the array Z. LDZ >= 1, and if * JOBZ = 'V', LDZ >= max(1,N). * * WORK (workspace) DOUBLE PRECISION array, dimension (3*N) * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: DPPTRF or DSPEV returned an error code: * <= N: if INFO = i, DSPEV failed to converge; * i off-diagonal elements of an intermediate * tridiagonal form did not converge to zero. * > N: if INFO = n + i, for 1 <= i <= n, then the leading * minor of order i of B is not positive definite. * The factorization of B could not be completed and * no eigenvalues or eigenvectors were computed. * * ===================================================================== * * .. Local Scalars .. LOGICAL UPPER, WANTZ CHARACTER TRANS INTEGER J, NEIG * .. * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. External Subroutines .. EXTERNAL DPPTRF, DSPEV, DSPGST, DTPMV, DTPSV, XERBLA * .. * .. Executable Statements .. * * Test the input parameters. * WANTZ = LSAME( JOBZ, 'V' ) UPPER = LSAME( UPLO, 'U' ) * INFO = 0 IF( ITYPE.LT.0 .OR. ITYPE.GT.3 ) THEN INFO = -1 ELSE IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN INFO = -2 ELSE IF( .NOT.( UPPER .OR. LSAME( UPLO, 'L' ) ) ) THEN INFO = -3 ELSE IF( N.LT.0 ) THEN INFO = -4 ELSE IF( LDZ.LT.1 .OR. ( WANTZ .AND. LDZ.LT.N ) ) THEN INFO = -9 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSPGV ', -INFO ) RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * * Form a Cholesky factorization of B. * CALL DPPTRF( UPLO, N, BP, INFO ) IF( INFO.NE.0 ) THEN INFO = N + INFO RETURN END IF * * Transform problem to standard eigenvalue problem and solve. * CALL DSPGST( ITYPE, UPLO, N, AP, BP, INFO ) CALL DSPEV( JOBZ, UPLO, N, AP, W, Z, LDZ, WORK, INFO ) * IF( WANTZ ) THEN * * Backtransform eigenvectors to the original problem. * NEIG = N IF( INFO.GT.0 ) $ NEIG = INFO - 1 IF( ITYPE.EQ.1 .OR. ITYPE.EQ.2 ) THEN * * For A*x=(lambda)*B*x and A*B*x=(lambda)*x; * backtransform eigenvectors: x = inv(L)'*y or inv(U)*y * IF( UPPER ) THEN TRANS = 'N' ELSE TRANS = 'T' END IF * DO 10 J = 1, NEIG CALL DTPSV( UPLO, TRANS, 'Non-unit', N, BP, Z( 1, J ), $ 1 ) 10 CONTINUE * ELSE IF( ITYPE.EQ.3 ) THEN * * For B*A*x=(lambda)*x; * backtransform eigenvectors: x = L*y or U'*y * IF( UPPER ) THEN TRANS = 'T' ELSE TRANS = 'N' END IF * DO 20 J = 1, NEIG CALL DTPMV( UPLO, TRANS, 'Non-unit', N, BP, Z( 1, J ), $ 1 ) 20 CONTINUE END IF END IF RETURN * * End of DSPGV * END SUBROUTINE DSPGVD( ITYPE, JOBZ, UPLO, N, AP, BP, W, Z, LDZ, WORK, $ LWORK, IWORK, LIWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBZ, UPLO INTEGER INFO, ITYPE, LDZ, LIWORK, LWORK, N * .. * .. Array Arguments .. INTEGER IWORK( * ) DOUBLE PRECISION AP( * ), BP( * ), W( * ), WORK( * ), $ Z( LDZ, * ) * .. * * Purpose * ======= * * DSPGVD computes all the eigenvalues, and optionally, the eigenvectors * of a real generalized symmetric-definite eigenproblem, of the form * A*x=(lambda)*B*x, A*Bx=(lambda)*x, or B*A*x=(lambda)*x. Here A and * B are assumed to be symmetric, stored in packed format, and B is also * positive definite. * If eigenvectors are desired, it uses a divide and conquer algorithm. * * The divide and conquer algorithm makes very mild assumptions about * floating point arithmetic. It will work on machines with a guard * digit in add/subtract, or on those binary machines without guard * digits which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or * Cray-2. It could conceivably fail on hexadecimal or decimal machines * without guard digits, but we know of none. * * Arguments * ========= * * ITYPE (input) INTEGER * Specifies the problem type to be solved: * = 1: A*x = (lambda)*B*x * = 2: A*B*x = (lambda)*x * = 3: B*A*x = (lambda)*x * * JOBZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only; * = 'V': Compute eigenvalues and eigenvectors. * * UPLO (input) CHARACTER*1 * = 'U': Upper triangles of A and B are stored; * = 'L': Lower triangles of A and B are stored. * * N (input) INTEGER * The order of the matrices A and B. N >= 0. * * AP (input/output) DOUBLE PRECISION array, dimension (N*(N+1)/2) * On entry, the upper or lower triangle of the symmetric matrix * A, packed columnwise in a linear array. The j-th column of A * is stored in the array AP as follows: * if UPLO = 'U', AP(i + (j-1)*j/2) = A(i,j) for 1<=i<=j; * if UPLO = 'L', AP(i + (j-1)*(2*n-j)/2) = A(i,j) for j<=i<=n. * * On exit, the contents of AP are destroyed. * * BP (input/output) DOUBLE PRECISION array, dimension (N*(N+1)/2) * On entry, the upper or lower triangle of the symmetric matrix * B, packed columnwise in a linear array. The j-th column of B * is stored in the array BP as follows: * if UPLO = 'U', BP(i + (j-1)*j/2) = B(i,j) for 1<=i<=j; * if UPLO = 'L', BP(i + (j-1)*(2*n-j)/2) = B(i,j) for j<=i<=n. * * On exit, the triangular factor U or L from the Cholesky * factorization B = U**T*U or B = L*L**T, in the same storage * format as B. * * W (output) DOUBLE PRECISION array, dimension (N) * If INFO = 0, the eigenvalues in ascending order. * * Z (output) DOUBLE PRECISION array, dimension (LDZ, N) * If JOBZ = 'V', then if INFO = 0, Z contains the matrix Z of * eigenvectors. The eigenvectors are normalized as follows: * if ITYPE = 1 or 2, Z**T*B*Z = I; * if ITYPE = 3, Z**T*inv(B)*Z = I. * If JOBZ = 'N', then Z is not referenced. * * LDZ (input) INTEGER * The leading dimension of the array Z. LDZ >= 1, and if * JOBZ = 'V', LDZ >= max(1,N). * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. * If N <= 1, LWORK >= 1. * If JOBZ = 'N' and N > 1, LWORK >= 2*N. * If JOBZ = 'V' and N > 1, LWORK >= 1 + 6*N + 2*N**2. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * IWORK (workspace/output) INTEGER array, dimension (LIWORK) * On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK. * * LIWORK (input) INTEGER * The dimension of the array IWORK. * If JOBZ = 'N' or N <= 1, LIWORK >= 1. * If JOBZ = 'V' and N > 1, LIWORK >= 3 + 5*N. * * If LIWORK = -1, then a workspace query is assumed; the * routine only calculates the optimal size of the IWORK array, * returns this value as the first entry of the IWORK array, and * no error message related to LIWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: DPPTRF or DSPEVD returned an error code: * <= N: if INFO = i, DSPEVD failed to converge; * i off-diagonal elements of an intermediate * tridiagonal form did not converge to zero; * > N: if INFO = N + i, for 1 <= i <= N, then the leading * minor of order i of B is not positive definite. * The factorization of B could not be completed and * no eigenvalues or eigenvectors were computed. * * Further Details * =============== * * Based on contributions by * Mark Fahey, Department of Mathematics, Univ. of Kentucky, USA * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION TWO PARAMETER ( TWO = 2.0D+0 ) * .. * .. Local Scalars .. LOGICAL LQUERY, UPPER, WANTZ CHARACTER TRANS INTEGER J, LGN, LIWMIN, LWMIN, NEIG * .. * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. External Subroutines .. EXTERNAL DPPTRF, DSPEVD, DSPGST, DTPMV, DTPSV, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC DBLE, INT, LOG, MAX * .. * .. Executable Statements .. * * Test the input parameters. * WANTZ = LSAME( JOBZ, 'V' ) UPPER = LSAME( UPLO, 'U' ) LQUERY = ( LWORK.EQ.-1 .OR. LIWORK.EQ.-1 ) * INFO = 0 IF( N.LE.1 ) THEN LGN = 0 LIWMIN = 1 LWMIN = 1 ELSE LGN = INT( LOG( DBLE( N ) ) / LOG( TWO ) ) IF( 2**LGN.LT.N ) $ LGN = LGN + 1 IF( 2**LGN.LT.N ) $ LGN = LGN + 1 IF( WANTZ ) THEN LIWMIN = 3 + 5*N LWMIN = 1 + 5*N + 2*N*LGN + 2*N**2 ELSE LIWMIN = 1 LWMIN = 2*N END IF END IF * IF( ITYPE.LT.0 .OR. ITYPE.GT.3 ) THEN INFO = -1 ELSE IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN INFO = -2 ELSE IF( .NOT.( UPPER .OR. LSAME( UPLO, 'L' ) ) ) THEN INFO = -3 ELSE IF( N.LT.0 ) THEN INFO = -4 ELSE IF( LDZ.LT.MAX( 1, N ) ) THEN INFO = -9 ELSE IF( LWORK.LT.LWMIN .AND. .NOT.LQUERY ) THEN INFO = -11 ELSE IF( LIWORK.LT.LIWMIN .AND. .NOT.LQUERY ) THEN INFO = -13 END IF * IF( INFO.EQ.0 ) THEN WORK( 1 ) = LWMIN IWORK( 1 ) = LIWMIN END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSPGVD', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * * Form a Cholesky factorization of BP. * CALL DPPTRF( UPLO, N, BP, INFO ) IF( INFO.NE.0 ) THEN INFO = N + INFO RETURN END IF * * Transform problem to standard eigenvalue problem and solve. * CALL DSPGST( ITYPE, UPLO, N, AP, BP, INFO ) CALL DSPEVD( JOBZ, UPLO, N, AP, W, Z, LDZ, WORK, LWORK, IWORK, $ LIWORK, INFO ) LWMIN = MAX( DBLE( LWMIN ), DBLE( WORK( 1 ) ) ) LIWMIN = MAX( DBLE( LIWMIN ), DBLE( IWORK( 1 ) ) ) * IF( WANTZ ) THEN * * Backtransform eigenvectors to the original problem. * NEIG = N IF( INFO.GT.0 ) $ NEIG = INFO - 1 IF( ITYPE.EQ.1 .OR. ITYPE.EQ.2 ) THEN * * For A*x=(lambda)*B*x and A*B*x=(lambda)*x; * backtransform eigenvectors: x = inv(L)'*y or inv(U)*y * IF( UPPER ) THEN TRANS = 'N' ELSE TRANS = 'T' END IF * DO 10 J = 1, NEIG CALL DTPSV( UPLO, TRANS, 'Non-unit', N, BP, Z( 1, J ), $ 1 ) 10 CONTINUE * ELSE IF( ITYPE.EQ.3 ) THEN * * For B*A*x=(lambda)*x; * backtransform eigenvectors: x = L*y or U'*y * IF( UPPER ) THEN TRANS = 'T' ELSE TRANS = 'N' END IF * DO 20 J = 1, NEIG CALL DTPMV( UPLO, TRANS, 'Non-unit', N, BP, Z( 1, J ), $ 1 ) 20 CONTINUE END IF END IF * WORK( 1 ) = LWMIN IWORK( 1 ) = LIWMIN * RETURN * * End of DSPGVD * END SUBROUTINE DSPGVX( ITYPE, JOBZ, RANGE, UPLO, N, AP, BP, VL, VU, $ IL, IU, ABSTOL, M, W, Z, LDZ, WORK, IWORK, $ IFAIL, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBZ, RANGE, UPLO INTEGER IL, INFO, ITYPE, IU, LDZ, M, N DOUBLE PRECISION ABSTOL, VL, VU * .. * .. Array Arguments .. INTEGER IFAIL( * ), IWORK( * ) DOUBLE PRECISION AP( * ), BP( * ), W( * ), WORK( * ), $ Z( LDZ, * ) * .. * * Purpose * ======= * * DSPGVX computes selected eigenvalues, and optionally, eigenvectors * of a real generalized symmetric-definite eigenproblem, of the form * A*x=(lambda)*B*x, A*Bx=(lambda)*x, or B*A*x=(lambda)*x. Here A * and B are assumed to be symmetric, stored in packed storage, and B * is also positive definite. Eigenvalues and eigenvectors can be * selected by specifying either a range of values or a range of indices * for the desired eigenvalues. * * Arguments * ========= * * ITYPE (input) INTEGER * Specifies the problem type to be solved: * = 1: A*x = (lambda)*B*x * = 2: A*B*x = (lambda)*x * = 3: B*A*x = (lambda)*x * * JOBZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only; * = 'V': Compute eigenvalues and eigenvectors. * * RANGE (input) CHARACTER*1 * = 'A': all eigenvalues will be found. * = 'V': all eigenvalues in the half-open interval (VL,VU] * will be found. * = 'I': the IL-th through IU-th eigenvalues will be found. * * UPLO (input) CHARACTER*1 * = 'U': Upper triangle of A and B are stored; * = 'L': Lower triangle of A and B are stored. * * N (input) INTEGER * The order of the matrix pencil (A,B). N >= 0. * * AP (input/output) DOUBLE PRECISION array, dimension (N*(N+1)/2) * On entry, the upper or lower triangle of the symmetric matrix * A, packed columnwise in a linear array. The j-th column of A * is stored in the array AP as follows: * if UPLO = 'U', AP(i + (j-1)*j/2) = A(i,j) for 1<=i<=j; * if UPLO = 'L', AP(i + (j-1)*(2*n-j)/2) = A(i,j) for j<=i<=n. * * On exit, the contents of AP are destroyed. * * BP (input/output) DOUBLE PRECISION array, dimension (N*(N+1)/2) * On entry, the upper or lower triangle of the symmetric matrix * B, packed columnwise in a linear array. The j-th column of B * is stored in the array BP as follows: * if UPLO = 'U', BP(i + (j-1)*j/2) = B(i,j) for 1<=i<=j; * if UPLO = 'L', BP(i + (j-1)*(2*n-j)/2) = B(i,j) for j<=i<=n. * * On exit, the triangular factor U or L from the Cholesky * factorization B = U**T*U or B = L*L**T, in the same storage * format as B. * * VL (input) DOUBLE PRECISION * VU (input) DOUBLE PRECISION * If RANGE='V', the lower and upper bounds of the interval to * be searched for eigenvalues. VL < VU. * Not referenced if RANGE = 'A' or 'I'. * * IL (input) INTEGER * IU (input) INTEGER * If RANGE='I', the indices (in ascending order) of the * smallest and largest eigenvalues to be returned. * 1 <= IL <= IU <= N, if N > 0; IL = 1 and IU = 0 if N = 0. * Not referenced if RANGE = 'A' or 'V'. * * ABSTOL (input) DOUBLE PRECISION * The absolute error tolerance for the eigenvalues. * An approximate eigenvalue is accepted as converged * when it is determined to lie in an interval [a,b] * of width less than or equal to * * ABSTOL + EPS * max( |a|,|b| ) , * * where EPS is the machine precision. If ABSTOL is less than * or equal to zero, then EPS*|T| will be used in its place, * where |T| is the 1-norm of the tridiagonal matrix obtained * by reducing A to tridiagonal form. * * Eigenvalues will be computed most accurately when ABSTOL is * set to twice the underflow threshold 2*DLAMCH('S'), not zero. * If this routine returns with INFO>0, indicating that some * eigenvectors did not converge, try setting ABSTOL to * 2*DLAMCH('S'). * * M (output) INTEGER * The total number of eigenvalues found. 0 <= M <= N. * If RANGE = 'A', M = N, and if RANGE = 'I', M = IU-IL+1. * * W (output) DOUBLE PRECISION array, dimension (N) * On normal exit, the first M elements contain the selected * eigenvalues in ascending order. * * Z (output) DOUBLE PRECISION array, dimension (LDZ, max(1,M)) * If JOBZ = 'N', then Z is not referenced. * If JOBZ = 'V', then if INFO = 0, the first M columns of Z * contain the orthonormal eigenvectors of the matrix A * corresponding to the selected eigenvalues, with the i-th * column of Z holding the eigenvector associated with W(i). * The eigenvectors are normalized as follows: * if ITYPE = 1 or 2, Z**T*B*Z = I; * if ITYPE = 3, Z**T*inv(B)*Z = I. * * If an eigenvector fails to converge, then that column of Z * contains the latest approximation to the eigenvector, and the * index of the eigenvector is returned in IFAIL. * Note: the user must ensure that at least max(1,M) columns are * supplied in the array Z; if RANGE = 'V', the exact value of M * is not known in advance and an upper bound must be used. * * LDZ (input) INTEGER * The leading dimension of the array Z. LDZ >= 1, and if * JOBZ = 'V', LDZ >= max(1,N). * * WORK (workspace) DOUBLE PRECISION array, dimension (8*N) * * IWORK (workspace) INTEGER array, dimension (5*N) * * IFAIL (output) INTEGER array, dimension (N) * If JOBZ = 'V', then if INFO = 0, the first M elements of * IFAIL are zero. If INFO > 0, then IFAIL contains the * indices of the eigenvectors that failed to converge. * If JOBZ = 'N', then IFAIL is not referenced. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: DPPTRF or DSPEVX returned an error code: * <= N: if INFO = i, DSPEVX failed to converge; * i eigenvectors failed to converge. Their indices * are stored in array IFAIL. * > N: if INFO = N + i, for 1 <= i <= N, then the leading * minor of order i of B is not positive definite. * The factorization of B could not be completed and * no eigenvalues or eigenvectors were computed. * * Further Details * =============== * * Based on contributions by * Mark Fahey, Department of Mathematics, Univ. of Kentucky, USA * * ===================================================================== * * .. Local Scalars .. LOGICAL ALLEIG, INDEIG, UPPER, VALEIG, WANTZ CHARACTER TRANS INTEGER J * .. * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. External Subroutines .. EXTERNAL DPPTRF, DSPEVX, DSPGST, DTPMV, DTPSV, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MIN * .. * .. Executable Statements .. * * Test the input parameters. * UPPER = LSAME( UPLO, 'U' ) WANTZ = LSAME( JOBZ, 'V' ) ALLEIG = LSAME( RANGE, 'A' ) VALEIG = LSAME( RANGE, 'V' ) INDEIG = LSAME( RANGE, 'I' ) * INFO = 0 IF( ITYPE.LT.0 .OR. ITYPE.GT.3 ) THEN INFO = -1 ELSE IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN INFO = -2 ELSE IF( .NOT.( ALLEIG .OR. VALEIG .OR. INDEIG ) ) THEN INFO = -3 ELSE IF( .NOT.( UPPER .OR. LSAME( UPLO, 'L' ) ) ) THEN INFO = -4 ELSE IF( N.LT.0 ) THEN INFO = -5 ELSE IF( VALEIG .AND. N.GT.0 .AND. VU.LE.VL ) THEN INFO = -9 ELSE IF( INDEIG .AND. IL.LT.1 ) THEN INFO = -10 ELSE IF( INDEIG .AND. ( IU.LT.MIN( N, IL ) .OR. IU.GT.N ) ) THEN INFO = -11 ELSE IF( LDZ.LT.1 .OR. ( WANTZ .AND. LDZ.LT.N ) ) THEN INFO = -16 END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSPGVX', -INFO ) RETURN END IF * * Quick return if possible * M = 0 IF( N.EQ.0 ) THEN WORK( 1 ) = 1 RETURN END IF * * Form a Cholesky factorization of B. * CALL DPPTRF( UPLO, N, BP, INFO ) IF( INFO.NE.0 ) THEN INFO = N + INFO RETURN END IF * * Transform problem to standard eigenvalue problem and solve. * CALL DSPGST( ITYPE, UPLO, N, AP, BP, INFO ) CALL DSPEVX( JOBZ, RANGE, UPLO, N, AP, VL, VU, IL, IU, ABSTOL, M, $ W, Z, LDZ, WORK, IWORK, IFAIL, INFO ) * IF( WANTZ ) THEN * * Backtransform eigenvectors to the original problem. * IF( INFO.GT.0 ) $ M = INFO - 1 IF( ITYPE.EQ.1 .OR. ITYPE.EQ.2 ) THEN * * For A*x=(lambda)*B*x and A*B*x=(lambda)*x; * backtransform eigenvectors: x = inv(L)'*y or inv(U)*y * IF( UPPER ) THEN TRANS = 'N' ELSE TRANS = 'T' END IF * DO 10 J = 1, M CALL DTPSV( UPLO, TRANS, 'Non-unit', N, BP, Z( 1, J ), $ 1 ) 10 CONTINUE * ELSE IF( ITYPE.EQ.3 ) THEN * * For B*A*x=(lambda)*x; * backtransform eigenvectors: x = L*y or U'*y * IF( UPPER ) THEN TRANS = 'T' ELSE TRANS = 'N' END IF * DO 20 J = 1, M CALL DTPMV( UPLO, TRANS, 'Non-unit', N, BP, Z( 1, J ), $ 1 ) 20 CONTINUE END IF END IF * RETURN * * End of DSPGVX * END SUBROUTINE DSPSV( UPLO, N, NRHS, AP, IPIV, B, LDB, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * March 31, 1993 * * .. Scalar Arguments .. CHARACTER UPLO INTEGER INFO, LDB, N, NRHS * .. * .. Array Arguments .. INTEGER IPIV( * ) DOUBLE PRECISION AP( * ), B( LDB, * ) * .. * * Purpose * ======= * * DSPSV computes the solution to a real system of linear equations * A * X = B, * where A is an N-by-N symmetric matrix stored in packed format and X * and B are N-by-NRHS matrices. * * The diagonal pivoting method is used to factor A as * A = U * D * U**T, if UPLO = 'U', or * A = L * D * L**T, if UPLO = 'L', * where U (or L) is a product of permutation and unit upper (lower) * triangular matrices, D is symmetric and block diagonal with 1-by-1 * and 2-by-2 diagonal blocks. The factored form of A is then used to * solve the system of equations A * X = B. * * Arguments * ========= * * UPLO (input) CHARACTER*1 * = 'U': Upper triangle of A is stored; * = 'L': Lower triangle of A is stored. * * N (input) INTEGER * The number of linear equations, i.e., the order of the * matrix A. N >= 0. * * NRHS (input) INTEGER * The number of right hand sides, i.e., the number of columns * of the matrix B. NRHS >= 0. * * AP (input/output) DOUBLE PRECISION array, dimension (N*(N+1)/2) * On entry, the upper or lower triangle of the symmetric matrix * A, packed columnwise in a linear array. The j-th column of A * is stored in the array AP as follows: * if UPLO = 'U', AP(i + (j-1)*j/2) = A(i,j) for 1<=i<=j; * if UPLO = 'L', AP(i + (j-1)*(2n-j)/2) = A(i,j) for j<=i<=n. * See below for further details. * * On exit, the block diagonal matrix D and the multipliers used * to obtain the factor U or L from the factorization * A = U*D*U**T or A = L*D*L**T as computed by DSPTRF, stored as * a packed triangular matrix in the same storage format as A. * * IPIV (output) INTEGER array, dimension (N) * Details of the interchanges and the block structure of D, as * determined by DSPTRF. If IPIV(k) > 0, then rows and columns * k and IPIV(k) were interchanged, and D(k,k) is a 1-by-1 * diagonal block. If UPLO = 'U' and IPIV(k) = IPIV(k-1) < 0, * then rows and columns k-1 and -IPIV(k) were interchanged and * D(k-1:k,k-1:k) is a 2-by-2 diagonal block. If UPLO = 'L' and * IPIV(k) = IPIV(k+1) < 0, then rows and columns k+1 and * -IPIV(k) were interchanged and D(k:k+1,k:k+1) is a 2-by-2 * diagonal block. * * B (input/output) DOUBLE PRECISION array, dimension (LDB,NRHS) * On entry, the N-by-NRHS right hand side matrix B. * On exit, if INFO = 0, the N-by-NRHS solution matrix X. * * LDB (input) INTEGER * The leading dimension of the array B. LDB >= max(1,N). * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = i, D(i,i) is exactly zero. The factorization * has been completed, but the block diagonal matrix D is * exactly singular, so the solution could not be * computed. * * Further Details * =============== * * The packed storage scheme is illustrated by the following example * when N = 4, UPLO = 'U': * * Two-dimensional storage of the symmetric matrix A: * * a11 a12 a13 a14 * a22 a23 a24 * a33 a34 (aij = aji) * a44 * * Packed storage of the upper triangle of A: * * AP = [ a11, a12, a22, a13, a23, a33, a14, a24, a34, a44 ] * * ===================================================================== * * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. External Subroutines .. EXTERNAL DSPTRF, DSPTRS, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 IF( .NOT.LSAME( UPLO, 'U' ) .AND. .NOT.LSAME( UPLO, 'L' ) ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 ELSE IF( NRHS.LT.0 ) THEN INFO = -3 ELSE IF( LDB.LT.MAX( 1, N ) ) THEN INFO = -7 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSPSV ', -INFO ) RETURN END IF * * Compute the factorization A = U*D*U' or A = L*D*L'. * CALL DSPTRF( UPLO, N, AP, IPIV, INFO ) IF( INFO.EQ.0 ) THEN * * Solve the system A*X = B, overwriting B with X. * CALL DSPTRS( UPLO, N, NRHS, AP, IPIV, B, LDB, INFO ) * END IF RETURN * * End of DSPSV * END SUBROUTINE DSPSVX( FACT, UPLO, N, NRHS, AP, AFP, IPIV, B, LDB, X, $ LDX, RCOND, FERR, BERR, WORK, IWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER FACT, UPLO INTEGER INFO, LDB, LDX, N, NRHS DOUBLE PRECISION RCOND * .. * .. Array Arguments .. INTEGER IPIV( * ), IWORK( * ) DOUBLE PRECISION AFP( * ), AP( * ), B( LDB, * ), BERR( * ), $ FERR( * ), WORK( * ), X( LDX, * ) * .. * * Purpose * ======= * * DSPSVX uses the diagonal pivoting factorization A = U*D*U**T or * A = L*D*L**T to compute the solution to a real system of linear * equations A * X = B, where A is an N-by-N symmetric matrix stored * in packed format and X and B are N-by-NRHS matrices. * * Error bounds on the solution and a condition estimate are also * provided. * * Description * =========== * * The following steps are performed: * * 1. If FACT = 'N', the diagonal pivoting method is used to factor A as * A = U * D * U**T, if UPLO = 'U', or * A = L * D * L**T, if UPLO = 'L', * where U (or L) is a product of permutation and unit upper (lower) * triangular matrices and D is symmetric and block diagonal with * 1-by-1 and 2-by-2 diagonal blocks. * * 2. If some D(i,i)=0, so that D is exactly singular, then the routine * returns with INFO = i. Otherwise, the factored form of A is used * to estimate the condition number of the matrix A. If the * reciprocal of the condition number is less than machine precision, * INFO = N+1 is returned as a warning, but the routine still goes on * to solve for X and compute error bounds as described below. * * 3. The system of equations is solved for X using the factored form * of A. * * 4. Iterative refinement is applied to improve the computed solution * matrix and calculate error bounds and backward error estimates * for it. * * Arguments * ========= * * FACT (input) CHARACTER*1 * Specifies whether or not the factored form of A has been * supplied on entry. * = 'F': On entry, AFP and IPIV contain the factored form of * A. AP, AFP and IPIV will not be modified. * = 'N': The matrix A will be copied to AFP and factored. * * UPLO (input) CHARACTER*1 * = 'U': Upper triangle of A is stored; * = 'L': Lower triangle of A is stored. * * N (input) INTEGER * The number of linear equations, i.e., the order of the * matrix A. N >= 0. * * NRHS (input) INTEGER * The number of right hand sides, i.e., the number of columns * of the matrices B and X. NRHS >= 0. * * AP (input) DOUBLE PRECISION array, dimension (N*(N+1)/2) * The upper or lower triangle of the symmetric matrix A, packed * columnwise in a linear array. The j-th column of A is stored * in the array AP as follows: * if UPLO = 'U', AP(i + (j-1)*j/2) = A(i,j) for 1<=i<=j; * if UPLO = 'L', AP(i + (j-1)*(2*n-j)/2) = A(i,j) for j<=i<=n. * See below for further details. * * AFP (input or output) DOUBLE PRECISION array, dimension * (N*(N+1)/2) * If FACT = 'F', then AFP is an input argument and on entry * contains the block diagonal matrix D and the multipliers used * to obtain the factor U or L from the factorization * A = U*D*U**T or A = L*D*L**T as computed by DSPTRF, stored as * a packed triangular matrix in the same storage format as A. * * If FACT = 'N', then AFP is an output argument and on exit * contains the block diagonal matrix D and the multipliers used * to obtain the factor U or L from the factorization * A = U*D*U**T or A = L*D*L**T as computed by DSPTRF, stored as * a packed triangular matrix in the same storage format as A. * * IPIV (input or output) INTEGER array, dimension (N) * If FACT = 'F', then IPIV is an input argument and on entry * contains details of the interchanges and the block structure * of D, as determined by DSPTRF. * If IPIV(k) > 0, then rows and columns k and IPIV(k) were * interchanged and D(k,k) is a 1-by-1 diagonal block. * If UPLO = 'U' and IPIV(k) = IPIV(k-1) < 0, then rows and * columns k-1 and -IPIV(k) were interchanged and D(k-1:k,k-1:k) * is a 2-by-2 diagonal block. If UPLO = 'L' and IPIV(k) = * IPIV(k+1) < 0, then rows and columns k+1 and -IPIV(k) were * interchanged and D(k:k+1,k:k+1) is a 2-by-2 diagonal block. * * If FACT = 'N', then IPIV is an output argument and on exit * contains details of the interchanges and the block structure * of D, as determined by DSPTRF. * * B (input) DOUBLE PRECISION array, dimension (LDB,NRHS) * The N-by-NRHS right hand side matrix B. * * LDB (input) INTEGER * The leading dimension of the array B. LDB >= max(1,N). * * X (output) DOUBLE PRECISION array, dimension (LDX,NRHS) * If INFO = 0 or INFO = N+1, the N-by-NRHS solution matrix X. * * LDX (input) INTEGER * The leading dimension of the array X. LDX >= max(1,N). * * RCOND (output) DOUBLE PRECISION * The estimate of the reciprocal condition number of the matrix * A. If RCOND is less than the machine precision (in * particular, if RCOND = 0), the matrix is singular to working * precision. This condition is indicated by a return code of * INFO > 0. * * FERR (output) DOUBLE PRECISION array, dimension (NRHS) * The estimated forward error bound for each solution vector * X(j) (the j-th column of the solution matrix X). * If XTRUE is the true solution corresponding to X(j), FERR(j) * is an estimated upper bound for the magnitude of the largest * element in (X(j) - XTRUE) divided by the magnitude of the * largest element in X(j). The estimate is as reliable as * the estimate for RCOND, and is almost always a slight * overestimate of the true error. * * BERR (output) DOUBLE PRECISION array, dimension (NRHS) * The componentwise relative backward error of each solution * vector X(j) (i.e., the smallest relative change in * any element of A or B that makes X(j) an exact solution). * * WORK (workspace) DOUBLE PRECISION array, dimension (3*N) * * IWORK (workspace) INTEGER array, dimension (N) * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = i, and i is * <= N: D(i,i) is exactly zero. The factorization * has been completed but the factor D is exactly * singular, so the solution and error bounds could * not be computed. RCOND = 0 is returned. * = N+1: D is nonsingular, but RCOND is less than machine * precision, meaning that the matrix is singular * to working precision. Nevertheless, the * solution and error bounds are computed because * there are a number of situations where the * computed solution can be more accurate than the * value of RCOND would suggest. * * Further Details * =============== * * The packed storage scheme is illustrated by the following example * when N = 4, UPLO = 'U': * * Two-dimensional storage of the symmetric matrix A: * * a11 a12 a13 a14 * a22 a23 a24 * a33 a34 (aij = aji) * a44 * * Packed storage of the upper triangle of A: * * AP = [ a11, a12, a22, a13, a23, a33, a14, a24, a34, a44 ] * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO PARAMETER ( ZERO = 0.0D+0 ) * .. * .. Local Scalars .. LOGICAL NOFACT DOUBLE PRECISION ANORM * .. * .. External Functions .. LOGICAL LSAME DOUBLE PRECISION DLAMCH, DLANSP EXTERNAL LSAME, DLAMCH, DLANSP * .. * .. External Subroutines .. EXTERNAL DCOPY, DLACPY, DSPCON, DSPRFS, DSPTRF, DSPTRS, $ XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 NOFACT = LSAME( FACT, 'N' ) IF( .NOT.NOFACT .AND. .NOT.LSAME( FACT, 'F' ) ) THEN INFO = -1 ELSE IF( .NOT.LSAME( UPLO, 'U' ) .AND. .NOT.LSAME( UPLO, 'L' ) ) $ THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( NRHS.LT.0 ) THEN INFO = -4 ELSE IF( LDB.LT.MAX( 1, N ) ) THEN INFO = -9 ELSE IF( LDX.LT.MAX( 1, N ) ) THEN INFO = -11 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSPSVX', -INFO ) RETURN END IF * IF( NOFACT ) THEN * * Compute the factorization A = U*D*U' or A = L*D*L'. * CALL DCOPY( N*( N+1 ) / 2, AP, 1, AFP, 1 ) CALL DSPTRF( UPLO, N, AFP, IPIV, INFO ) * * Return if INFO is non-zero. * IF( INFO.NE.0 ) THEN IF( INFO.GT.0 ) $ RCOND = ZERO RETURN END IF END IF * * Compute the norm of the matrix A. * ANORM = DLANSP( 'I', UPLO, N, AP, WORK ) * * Compute the reciprocal of the condition number of A. * CALL DSPCON( UPLO, N, AFP, IPIV, ANORM, RCOND, WORK, IWORK, INFO ) * * Set INFO = N+1 if the matrix is singular to working precision. * IF( RCOND.LT.DLAMCH( 'Epsilon' ) ) $ INFO = N + 1 * * Compute the solution vectors X. * CALL DLACPY( 'Full', N, NRHS, B, LDB, X, LDX ) CALL DSPTRS( UPLO, N, NRHS, AFP, IPIV, X, LDX, INFO ) * * Use iterative refinement to improve the computed solutions and * compute error bounds and backward error estimates for them. * CALL DSPRFS( UPLO, N, NRHS, AP, AFP, IPIV, B, LDB, X, LDX, FERR, $ BERR, WORK, IWORK, INFO ) * RETURN * * End of DSPSVX * END SUBROUTINE DSTEDC( COMPZ, N, D, E, Z, LDZ, WORK, LWORK, IWORK, $ LIWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER COMPZ INTEGER INFO, LDZ, LIWORK, LWORK, N * .. * .. Array Arguments .. INTEGER IWORK( * ) DOUBLE PRECISION D( * ), E( * ), WORK( * ), Z( LDZ, * ) * .. * * Purpose * ======= * * DSTEDC computes all eigenvalues and, optionally, eigenvectors of a * symmetric tridiagonal matrix using the divide and conquer method. * The eigenvectors of a full or band real symmetric matrix can also be * found if DSYTRD or DSPTRD or DSBTRD has been used to reduce this * matrix to tridiagonal form. * * This code makes very mild assumptions about floating point * arithmetic. It will work on machines with a guard digit in * add/subtract, or on those binary machines without guard digits * which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or Cray-2. * It could conceivably fail on hexadecimal or decimal machines * without guard digits, but we know of none. See DLAED3 for details. * * Arguments * ========= * * COMPZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only. * = 'I': Compute eigenvectors of tridiagonal matrix also. * = 'V': Compute eigenvectors of original dense symmetric * matrix also. On entry, Z contains the orthogonal * matrix used to reduce the original matrix to * tridiagonal form. * * N (input) INTEGER * The dimension of the symmetric tridiagonal matrix. N >= 0. * * D (input/output) DOUBLE PRECISION array, dimension (N) * On entry, the diagonal elements of the tridiagonal matrix. * On exit, if INFO = 0, the eigenvalues in ascending order. * * E (input/output) DOUBLE PRECISION array, dimension (N-1) * On entry, the subdiagonal elements of the tridiagonal matrix. * On exit, E has been destroyed. * * Z (input/output) DOUBLE PRECISION array, dimension (LDZ,N) * On entry, if COMPZ = 'V', then Z contains the orthogonal * 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 symmetric matrix, * and if COMPZ = 'I', Z contains the orthonormal eigenvectors * of the symmetric tridiagonal matrix. * If COMPZ = 'N', then Z is not referenced. * * LDZ (input) INTEGER * The leading dimension of the array Z. LDZ >= 1. * If eigenvectors are desired, then LDZ >= max(1,N). * * WORK (workspace/output) DOUBLE PRECISION array, * dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. * If COMPZ = 'N' or N <= 1 then LWORK must be at least 1. * If COMPZ = 'V' and N > 1 then LWORK must be at least * ( 1 + 3*N + 2*N*lg N + 3*N**2 ), * where lg( N ) = smallest integer k such * that 2**k >= N. * If COMPZ = 'I' and N > 1 then LWORK must be at least * ( 1 + 4*N + N**2 ). * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * IWORK (workspace/output) INTEGER array, dimension (LIWORK) * On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK. * * LIWORK (input) INTEGER * The dimension of the array IWORK. * If COMPZ = 'N' or N <= 1 then LIWORK must be at least 1. * If COMPZ = 'V' and N > 1 then LIWORK must be at least * ( 6 + 6*N + 5*N*lg N ). * If COMPZ = 'I' and N > 1 then LIWORK must be at least * ( 3 + 5*N ). * * If LIWORK = -1, then a workspace query is assumed; the * routine only calculates the optimal size of the IWORK array, * returns this value as the first entry of the IWORK array, and * no error message related to LIWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit. * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: The algorithm failed to compute an eigenvalue while * working on the submatrix lying in rows and columns * INFO/(N+1) through mod(INFO,N+1). * * Further Details * =============== * * Based on contributions by * Jeff Rutter, Computer Science Division, University of California * at Berkeley, USA * Modified by Francoise Tisseur, University of Tennessee. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE, TWO PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0, TWO = 2.0D0 ) * .. * .. Local Scalars .. LOGICAL LQUERY INTEGER DTRTRW, END, I, ICOMPZ, II, J, K, LGN, LIWMIN, $ LWMIN, M, SMLSIZ, START, STOREZ DOUBLE PRECISION EPS, ORGNRM, P, TINY * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANST EXTERNAL LSAME, ILAENV, DLAMCH, DLANST * .. * .. External Subroutines .. EXTERNAL DGEMM, DLACPY, DLAED0, DLASCL, DLASET, DLASRT, $ DSTEQR, DSTERF, DSWAP, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC ABS, DBLE, INT, LOG, MAX, MOD, SQRT * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 LQUERY = ( LWORK.EQ.-1 .OR. LIWORK.EQ.-1 ) * 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( N.LE.1 .OR. ICOMPZ.LE.0 ) THEN LIWMIN = 1 LWMIN = 1 ELSE LGN = INT( LOG( DBLE( N ) ) / LOG( TWO ) ) IF( 2**LGN.LT.N ) $ LGN = LGN + 1 IF( 2**LGN.LT.N ) $ LGN = LGN + 1 IF( ICOMPZ.EQ.1 ) THEN LWMIN = 1 + 3*N + 2*N*LGN + 3*N**2 LIWMIN = 6 + 6*N + 5*N*LGN ELSE IF( ICOMPZ.EQ.2 ) THEN LWMIN = 1 + 4*N + N**2 LIWMIN = 3 + 5*N END IF 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 ELSE IF( LWORK.LT.LWMIN .AND. .NOT.LQUERY ) THEN INFO = -8 ELSE IF( LIWORK.LT.LIWMIN .AND. .NOT.LQUERY ) THEN INFO = -10 END IF * IF( INFO.EQ.0 ) THEN WORK( 1 ) = LWMIN IWORK( 1 ) = LIWMIN END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSTEDC', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN IF( N.EQ.1 ) THEN IF( ICOMPZ.NE.0 ) $ Z( 1, 1 ) = ONE RETURN END IF * SMLSIZ = ILAENV( 9, 'DSTEDC', ' ', 0, 0, 0, 0 ) * * If the following conditional clause is removed, then the routine * will use the Divide and Conquer routine to compute only the * eigenvalues, which requires (3N + 3N**2) real workspace and * (2 + 5N + 2N lg(N)) integer workspace. * Since on many architectures DSTERF is much faster than any other * algorithm for finding eigenvalues only, it is used here * as the default. * * If COMPZ = 'N', use DSTERF to compute the eigenvalues. * IF( ICOMPZ.EQ.0 ) THEN CALL DSTERF( N, D, E, INFO ) RETURN END IF * * If N is smaller than the minimum divide size (SMLSIZ+1), then * solve the problem with another solver. * IF( N.LE.SMLSIZ ) THEN IF( ICOMPZ.EQ.0 ) THEN CALL DSTERF( N, D, E, INFO ) RETURN ELSE IF( ICOMPZ.EQ.2 ) THEN CALL DSTEQR( 'I', N, D, E, Z, LDZ, WORK, INFO ) RETURN ELSE CALL DSTEQR( 'V', N, D, E, Z, LDZ, WORK, INFO ) RETURN END IF END IF * * If COMPZ = 'V', the Z matrix must be stored elsewhere for later * use. * IF( ICOMPZ.EQ.1 ) THEN STOREZ = 1 + N*N ELSE STOREZ = 1 END IF * IF( ICOMPZ.EQ.2 ) THEN CALL DLASET( 'Full', N, N, ZERO, ONE, Z, LDZ ) END IF * * Scale. * ORGNRM = DLANST( 'M', N, D, E ) IF( ORGNRM.EQ.ZERO ) $ RETURN * EPS = DLAMCH( 'Epsilon' ) * START = 1 * * while ( START <= N ) * 10 CONTINUE IF( START.LE.N ) THEN * * Let END be the position of the next subdiagonal entry such that * E( END ) <= TINY or END = N if no such subdiagonal exists. The * matrix identified by the elements between START and END * constitutes an independent sub-problem. * END = START 20 CONTINUE IF( END.LT.N ) THEN TINY = EPS*SQRT( ABS( D( END ) ) )*SQRT( ABS( D( END+1 ) ) ) IF( ABS( E( END ) ).GT.TINY ) THEN END = END + 1 GO TO 20 END IF END IF * * (Sub) Problem determined. Compute its size and solve it. * M = END - START + 1 IF( M.EQ.1 ) THEN START = END + 1 GO TO 10 END IF IF( M.GT.SMLSIZ ) THEN INFO = SMLSIZ * * Scale. * ORGNRM = DLANST( 'M', M, D( START ), E( START ) ) CALL DLASCL( 'G', 0, 0, ORGNRM, ONE, M, 1, D( START ), M, $ INFO ) CALL DLASCL( 'G', 0, 0, ORGNRM, ONE, M-1, 1, E( START ), $ M-1, INFO ) * IF( ICOMPZ.EQ.1 ) THEN DTRTRW = 1 ELSE DTRTRW = START END IF CALL DLAED0( ICOMPZ, N, M, D( START ), E( START ), $ Z( DTRTRW, START ), LDZ, WORK( 1 ), N, $ WORK( STOREZ ), IWORK, INFO ) IF( INFO.NE.0 ) THEN INFO = ( INFO / ( M+1 )+START-1 )*( N+1 ) + $ MOD( INFO, ( M+1 ) ) + START - 1 RETURN END IF * * Scale back. * CALL DLASCL( 'G', 0, 0, ONE, ORGNRM, M, 1, D( START ), M, $ INFO ) * ELSE IF( ICOMPZ.EQ.1 ) THEN * * Since QR won't update a Z matrix which is larger than the * length of D, we must solve the sub-problem in a workspace and * then multiply back into Z. * CALL DSTEQR( 'I', M, D( START ), E( START ), WORK, M, $ WORK( M*M+1 ), INFO ) CALL DLACPY( 'A', N, M, Z( 1, START ), LDZ, $ WORK( STOREZ ), N ) CALL DGEMM( 'N', 'N', N, M, M, ONE, WORK( STOREZ ), LDZ, $ WORK, M, ZERO, Z( 1, START ), LDZ ) ELSE IF( ICOMPZ.EQ.2 ) THEN CALL DSTEQR( 'I', M, D( START ), E( START ), $ Z( START, START ), LDZ, WORK, INFO ) ELSE CALL DSTERF( M, D( START ), E( START ), INFO ) END IF IF( INFO.NE.0 ) THEN INFO = START*( N+1 ) + END RETURN END IF END IF * START = END + 1 GO TO 10 END IF * * endwhile * * If the problem split any number of times, then the eigenvalues * will not be properly ordered. Here we permute the eigenvalues * (and the associated eigenvectors) into ascending order. * IF( M.NE.N ) THEN IF( ICOMPZ.EQ.0 ) THEN * * Use Quick Sort * CALL DLASRT( 'I', N, D, INFO ) * ELSE * * Use Selection Sort to minimize swaps of eigenvectors * DO 40 II = 2, N I = II - 1 K = I P = D( I ) DO 30 J = II, N IF( D( J ).LT.P ) THEN K = J P = D( J ) END IF 30 CONTINUE IF( K.NE.I ) THEN D( K ) = D( I ) D( I ) = P CALL DSWAP( N, Z( 1, I ), 1, Z( 1, K ), 1 ) END IF 40 CONTINUE END IF END IF * WORK( 1 ) = LWMIN IWORK( 1 ) = LIWMIN * RETURN * * End of DSTEDC * END SUBROUTINE DSTEV( JOBZ, N, D, E, Z, LDZ, WORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * September 30, 1994 * * .. Scalar Arguments .. CHARACTER JOBZ INTEGER INFO, LDZ, N * .. * .. Array Arguments .. DOUBLE PRECISION D( * ), E( * ), WORK( * ), Z( LDZ, * ) * .. * * Purpose * ======= * * DSTEV computes all eigenvalues and, optionally, eigenvectors of a * real symmetric tridiagonal matrix A. * * Arguments * ========= * * JOBZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only; * = 'V': Compute eigenvalues and eigenvectors. * * N (input) INTEGER * The order of the matrix. N >= 0. * * D (input/output) DOUBLE PRECISION array, dimension (N) * On entry, the n diagonal elements of the tridiagonal matrix * A. * On exit, if INFO = 0, the eigenvalues in ascending order. * * E (input/output) DOUBLE PRECISION array, dimension (N) * On entry, the (n-1) subdiagonal elements of the tridiagonal * matrix A, stored in elements 1 to N-1 of E; E(N) need not * be set, but is used by the routine. * On exit, the contents of E are destroyed. * * Z (output) DOUBLE PRECISION array, dimension (LDZ, N) * If JOBZ = 'V', then if INFO = 0, Z contains the orthonormal * eigenvectors of the matrix A, with the i-th column of Z * holding the eigenvector associated with D(i). * If JOBZ = 'N', then Z is not referenced. * * LDZ (input) INTEGER * The leading dimension of the array Z. LDZ >= 1, and if * JOBZ = 'V', LDZ >= max(1,N). * * WORK (workspace) DOUBLE PRECISION array, dimension (max(1,2*N-2)) * If JOBZ = 'N', WORK is not referenced. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = i, the algorithm failed to converge; i * off-diagonal elements of E did not converge to zero. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. LOGICAL WANTZ INTEGER IMAX, ISCALE DOUBLE PRECISION BIGNUM, EPS, RMAX, RMIN, SAFMIN, SIGMA, SMLNUM, $ TNRM * .. * .. External Functions .. LOGICAL LSAME DOUBLE PRECISION DLAMCH, DLANST EXTERNAL LSAME, DLAMCH, DLANST * .. * .. External Subroutines .. EXTERNAL DSCAL, DSTEQR, DSTERF, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC SQRT * .. * .. Executable Statements .. * * Test the input parameters. * WANTZ = LSAME( JOBZ, 'V' ) * INFO = 0 IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 ELSE IF( LDZ.LT.1 .OR. ( WANTZ .AND. LDZ.LT.N ) ) THEN INFO = -6 END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSTEV ', -INFO ) RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * IF( N.EQ.1 ) THEN IF( WANTZ ) $ Z( 1, 1 ) = ONE RETURN END IF * * Get machine constants. * SAFMIN = DLAMCH( 'Safe minimum' ) EPS = DLAMCH( 'Precision' ) SMLNUM = SAFMIN / EPS BIGNUM = ONE / SMLNUM RMIN = SQRT( SMLNUM ) RMAX = SQRT( BIGNUM ) * * Scale matrix to allowable range, if necessary. * ISCALE = 0 TNRM = DLANST( 'M', N, D, E ) IF( TNRM.GT.ZERO .AND. TNRM.LT.RMIN ) THEN ISCALE = 1 SIGMA = RMIN / TNRM ELSE IF( TNRM.GT.RMAX ) THEN ISCALE = 1 SIGMA = RMAX / TNRM END IF IF( ISCALE.EQ.1 ) THEN CALL DSCAL( N, SIGMA, D, 1 ) CALL DSCAL( N-1, SIGMA, E( 1 ), 1 ) END IF * * For eigenvalues only, call DSTERF. For eigenvalues and * eigenvectors, call DSTEQR. * IF( .NOT.WANTZ ) THEN CALL DSTERF( N, D, E, INFO ) ELSE CALL DSTEQR( 'I', N, D, E, Z, LDZ, WORK, INFO ) END IF * * If matrix was scaled, then rescale eigenvalues appropriately. * IF( ISCALE.EQ.1 ) THEN IF( INFO.EQ.0 ) THEN IMAX = N ELSE IMAX = INFO - 1 END IF CALL DSCAL( IMAX, ONE / SIGMA, D, 1 ) END IF * RETURN * * End of DSTEV * END SUBROUTINE DSTEVD( JOBZ, N, D, E, Z, LDZ, WORK, LWORK, IWORK, $ LIWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBZ INTEGER INFO, LDZ, LIWORK, LWORK, N * .. * .. Array Arguments .. INTEGER IWORK( * ) DOUBLE PRECISION D( * ), E( * ), WORK( * ), Z( LDZ, * ) * .. * * Purpose * ======= * * DSTEVD computes all eigenvalues and, optionally, eigenvectors of a * real symmetric tridiagonal matrix. If eigenvectors are desired, it * uses a divide and conquer algorithm. * * The divide and conquer algorithm makes very mild assumptions about * floating point arithmetic. It will work on machines with a guard * digit in add/subtract, or on those binary machines without guard * digits which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or * Cray-2. It could conceivably fail on hexadecimal or decimal machines * without guard digits, but we know of none. * * Arguments * ========= * * JOBZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only; * = 'V': Compute eigenvalues and eigenvectors. * * N (input) INTEGER * The order of the matrix. N >= 0. * * D (input/output) DOUBLE PRECISION array, dimension (N) * On entry, the n diagonal elements of the tridiagonal matrix * A. * On exit, if INFO = 0, the eigenvalues in ascending order. * * E (input/output) DOUBLE PRECISION array, dimension (N) * On entry, the (n-1) subdiagonal elements of the tridiagonal * matrix A, stored in elements 1 to N-1 of E; E(N) need not * be set, but is used by the routine. * On exit, the contents of E are destroyed. * * Z (output) DOUBLE PRECISION array, dimension (LDZ, N) * If JOBZ = 'V', then if INFO = 0, Z contains the orthonormal * eigenvectors of the matrix A, with the i-th column of Z * holding the eigenvector associated with D(i). * If JOBZ = 'N', then Z is not referenced. * * LDZ (input) INTEGER * The leading dimension of the array Z. LDZ >= 1, and if * JOBZ = 'V', LDZ >= max(1,N). * * WORK (workspace/output) DOUBLE PRECISION array, * dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. * If JOBZ = 'N' or N <= 1 then LWORK must be at least 1. * If JOBZ = 'V' and N > 1 then LWORK must be at least * ( 1 + 4*N + N**2 ). * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * IWORK (workspace/output) INTEGER array, dimension (LIWORK) * On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK. * * LIWORK (input) INTEGER * The dimension of the array IWORK. * If JOBZ = 'N' or N <= 1 then LIWORK must be at least 1. * If JOBZ = 'V' and N > 1 then LIWORK must be at least 3+5*N. * * If LIWORK = -1, then a workspace query is assumed; the * routine only calculates the optimal size of the IWORK array, * returns this value as the first entry of the IWORK array, and * no error message related to LIWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = i, the algorithm failed to converge; i * off-diagonal elements of E did not converge to zero. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. LOGICAL LQUERY, WANTZ INTEGER ISCALE, LIWMIN, LWMIN DOUBLE PRECISION BIGNUM, EPS, RMAX, RMIN, SAFMIN, SIGMA, SMLNUM, $ TNRM * .. * .. External Functions .. LOGICAL LSAME DOUBLE PRECISION DLAMCH, DLANST EXTERNAL LSAME, DLAMCH, DLANST * .. * .. External Subroutines .. EXTERNAL DSCAL, DSTEDC, DSTERF, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC SQRT * .. * .. Executable Statements .. * * Test the input parameters. * WANTZ = LSAME( JOBZ, 'V' ) LQUERY = ( LWORK.EQ.-1 .OR. LIWORK.EQ.-1 ) * INFO = 0 LIWMIN = 1 LWMIN = 1 IF( N.GT.1 .AND. WANTZ ) THEN LWMIN = 1 + 4*N + N**2 LIWMIN = 3 + 5*N END IF * IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 ELSE IF( LDZ.LT.1 .OR. ( WANTZ .AND. LDZ.LT.N ) ) THEN INFO = -6 ELSE IF( LWORK.LT.LWMIN .AND. .NOT.LQUERY ) THEN INFO = -8 ELSE IF( LIWORK.LT.LIWMIN .AND. .NOT.LQUERY ) THEN INFO = -10 END IF * IF( INFO.EQ.0 ) THEN WORK( 1 ) = LWMIN IWORK( 1 ) = LIWMIN END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSTEVD', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * IF( N.EQ.1 ) THEN IF( WANTZ ) $ Z( 1, 1 ) = ONE RETURN END IF * * Get machine constants. * SAFMIN = DLAMCH( 'Safe minimum' ) EPS = DLAMCH( 'Precision' ) SMLNUM = SAFMIN / EPS BIGNUM = ONE / SMLNUM RMIN = SQRT( SMLNUM ) RMAX = SQRT( BIGNUM ) * * Scale matrix to allowable range, if necessary. * ISCALE = 0 TNRM = DLANST( 'M', N, D, E ) IF( TNRM.GT.ZERO .AND. TNRM.LT.RMIN ) THEN ISCALE = 1 SIGMA = RMIN / TNRM ELSE IF( TNRM.GT.RMAX ) THEN ISCALE = 1 SIGMA = RMAX / TNRM END IF IF( ISCALE.EQ.1 ) THEN CALL DSCAL( N, SIGMA, D, 1 ) CALL DSCAL( N-1, SIGMA, E( 1 ), 1 ) END IF * * For eigenvalues only, call DSTERF. For eigenvalues and * eigenvectors, call DSTEDC. * IF( .NOT.WANTZ ) THEN CALL DSTERF( N, D, E, INFO ) ELSE CALL DSTEDC( 'I', N, D, E, Z, LDZ, WORK, LWORK, IWORK, LIWORK, $ INFO ) END IF * * If matrix was scaled, then rescale eigenvalues appropriately. * IF( ISCALE.EQ.1 ) $ CALL DSCAL( N, ONE / SIGMA, D, 1 ) * WORK( 1 ) = LWMIN IWORK( 1 ) = LIWMIN * RETURN * * End of DSTEVD * END SUBROUTINE DSTEVR( JOBZ, RANGE, N, D, E, VL, VU, IL, IU, ABSTOL, $ M, W, Z, LDZ, ISUPPZ, WORK, LWORK, IWORK, $ LIWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * March 20, 2000 * * .. Scalar Arguments .. CHARACTER JOBZ, RANGE INTEGER IL, INFO, IU, LDZ, LIWORK, LWORK, M, N DOUBLE PRECISION ABSTOL, VL, VU * .. * .. Array Arguments .. INTEGER ISUPPZ( * ), IWORK( * ) DOUBLE PRECISION D( * ), E( * ), W( * ), WORK( * ), Z( LDZ, * ) * .. * * Purpose * ======= * * DSTEVR computes selected eigenvalues and, optionally, eigenvectors * of a real symmetric tridiagonal matrix T. Eigenvalues and * eigenvectors can be selected by specifying either a range of values * or a range of indices for the desired eigenvalues. * * Whenever possible, DSTEVR calls SSTEGR to compute the * eigenspectrum using Relatively Robust Representations. DSTEGR * computes eigenvalues by the dqds algorithm, while orthogonal * eigenvectors are computed from various "good" L D L^T representations * (also known as Relatively Robust Representations). Gram-Schmidt * orthogonalization is avoided as far as possible. More specifically, * the various steps of the algorithm are as follows. For the i-th * unreduced block of T, * (a) Compute T - sigma_i = L_i D_i L_i^T, such that L_i D_i L_i^T * is a relatively robust representation, * (b) Compute the eigenvalues, lambda_j, of L_i D_i L_i^T to high * relative accuracy by the dqds algorithm, * (c) If there is a cluster of close eigenvalues, "choose" sigma_i * close to the cluster, and go to step (a), * (d) Given the approximate eigenvalue lambda_j of L_i D_i L_i^T, * compute the corresponding eigenvector by forming a * rank-revealing twisted factorization. * The desired accuracy of the output can be specified by the input * parameter ABSTOL. * * For more details, see "A new O(n^2) algorithm for the symmetric * tridiagonal eigenvalue/eigenvector problem", by Inderjit Dhillon, * Computer Science Division Technical Report No. UCB//CSD-97-971, * UC Berkeley, May 1997. * * * Note 1 : DSTEVR calls SSTEGR when the full spectrum is requested * on machines which conform to the ieee-754 floating point standard. * DSTEVR calls SSTEBZ and SSTEIN on non-ieee machines and * when partial spectrum requests are made. * * Normal execution of DSTEGR may create NaNs and infinities and * hence may abort due to a floating point exception in environments * which do not handle NaNs and infinities in the ieee standard default * manner. * * Arguments * ========= * * JOBZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only; * = 'V': Compute eigenvalues and eigenvectors. * * RANGE (input) CHARACTER*1 * = 'A': all eigenvalues will be found. * = 'V': all eigenvalues in the half-open interval (VL,VU] * will be found. * = 'I': the IL-th through IU-th eigenvalues will be found. ********** For RANGE = 'V' or 'I' and IU - IL < N - 1, DSTEBZ and ********** DSTEIN are called * * N (input) INTEGER * The order of the matrix. N >= 0. * * D (input/output) DOUBLE PRECISION array, dimension (N) * On entry, the n diagonal elements of the tridiagonal matrix * A. * On exit, D may be multiplied by a constant factor chosen * to avoid over/underflow in computing the eigenvalues. * * E (input/output) DOUBLE PRECISION array, dimension (N) * On entry, the (n-1) subdiagonal elements of the tridiagonal * matrix A in elements 1 to N-1 of E; E(N) need not be set. * On exit, E may be multiplied by a constant factor chosen * to avoid over/underflow in computing the eigenvalues. * * VL (input) DOUBLE PRECISION * VU (input) DOUBLE PRECISION * If RANGE='V', the lower and upper bounds of the interval to * be searched for eigenvalues. VL < VU. * Not referenced if RANGE = 'A' or 'I'. * * IL (input) INTEGER * IU (input) INTEGER * If RANGE='I', the indices (in ascending order) of the * smallest and largest eigenvalues to be returned. * 1 <= IL <= IU <= N, if N > 0; IL = 1 and IU = 0 if N = 0. * Not referenced if RANGE = 'A' or 'V'. * * ABSTOL (input) DOUBLE PRECISION * The absolute error tolerance for the eigenvalues. * An approximate eigenvalue is accepted as converged * when it is determined to lie in an interval [a,b] * of width less than or equal to * * ABSTOL + EPS * max( |a|,|b| ) , * * where EPS is the machine precision. If ABSTOL is less than * or equal to zero, then EPS*|T| will be used in its place, * where |T| is the 1-norm of the tridiagonal matrix obtained * by reducing A to tridiagonal form. * * See "Computing Small Singular Values of Bidiagonal Matrices * with Guaranteed High Relative Accuracy," by Demmel and * Kahan, LAPACK Working Note #3. * * If high relative accuracy is important, set ABSTOL to * DLAMCH( 'Safe minimum' ). Doing so will guarantee that * eigenvalues are computed to high relative accuracy when * possible in future releases. The current code does not * make any guarantees about high relative accuracy, but * future releases will. See J. Barlow and J. Demmel, * "Computing Accurate Eigensystems of Scaled Diagonally * Dominant Matrices", LAPACK Working Note #7, for a discussion * of which matrices define their eigenvalues to high relative * accuracy. * * M (output) INTEGER * The total number of eigenvalues found. 0 <= M <= N. * If RANGE = 'A', M = N, and if RANGE = 'I', M = IU-IL+1. * * W (output) DOUBLE PRECISION array, dimension (N) * The first M elements contain the selected eigenvalues in * ascending order. * * Z (output) DOUBLE PRECISION array, dimension (LDZ, max(1,M) ) * If JOBZ = 'V', then if INFO = 0, the first M columns of Z * contain the orthonormal eigenvectors of the matrix A * corresponding to the selected eigenvalues, with the i-th * column of Z holding the eigenvector associated with W(i). * Note: the user must ensure that at least max(1,M) columns are * supplied in the array Z; if RANGE = 'V', the exact value of M * is not known in advance and an upper bound must be used. * * LDZ (input) INTEGER * The leading dimension of the array Z. LDZ >= 1, and if * JOBZ = 'V', LDZ >= max(1,N). * * ISUPPZ (output) INTEGER array, dimension ( 2*max(1,M) ) * The support of the eigenvectors in Z, i.e., the indices * indicating the nonzero elements in Z. The i-th eigenvector * is nonzero only in elements ISUPPZ( 2*i-1 ) through * ISUPPZ( 2*i ). ********** Implemented only for RANGE = 'A' or 'I' and IU - IL = N - 1 * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal (and * minimal) LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= 20*N. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * IWORK (workspace/output) INTEGER array, dimension (LIWORK) * On exit, if INFO = 0, IWORK(1) returns the optimal (and * minimal) LIWORK. * * LIWORK (input) INTEGER * The dimension of the array IWORK. LIWORK >= 10*N. * * If LIWORK = -1, then a workspace query is assumed; the * routine only calculates the optimal size of the IWORK array, * returns this value as the first entry of the IWORK array, and * no error message related to LIWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: Internal error * * Further Details * =============== * * Based on contributions by * Inderjit Dhillon, IBM Almaden, USA * Osni Marques, LBNL/NERSC, USA * Ken Stanley, Computer Science Division, University of * California at Berkeley, USA * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL ALLEIG, INDEIG, LQUERY, VALEIG, WANTZ CHARACTER ORDER INTEGER I, IEEEOK, IMAX, INDIBL, INDIFL, INDISP, $ INDIWO, ISCALE, ITMP1, J, JJ, LIWMIN, LWMIN, $ NSPLIT DOUBLE PRECISION BIGNUM, EPS, RMAX, RMIN, SAFMIN, SIGMA, SMLNUM, $ TMP1, TNRM, VLL, VUU * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANST EXTERNAL LSAME, ILAENV, DLAMCH, DLANST * .. * .. External Subroutines .. EXTERNAL DCOPY, DSCAL, DSTEBZ, DSTEGR, DSTEIN, DSTERF, $ DSWAP, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN, SQRT * .. * .. Executable Statements .. * * * Test the input parameters. * IEEEOK = ILAENV( 10, 'DSTEVR', 'N', 1, 2, 3, 4 ) * WANTZ = LSAME( JOBZ, 'V' ) ALLEIG = LSAME( RANGE, 'A' ) VALEIG = LSAME( RANGE, 'V' ) INDEIG = LSAME( RANGE, 'I' ) * LQUERY = ( ( LWORK.EQ.-1 ) .OR. ( LIWORK.EQ.-1 ) ) LWMIN = 20*N LIWMIN = 10*N * * INFO = 0 IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN INFO = -1 ELSE IF( .NOT.( ALLEIG .OR. VALEIG .OR. INDEIG ) ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( VALEIG ) THEN IF( N.GT.0 .AND. VU.LE.VL ) $ INFO = -7 ELSE IF( INDEIG ) THEN IF( IL.LT.1 .OR. IL.GT.MAX( 1, N ) ) THEN INFO = -8 ELSE IF( IU.LT.MIN( N, IL ) .OR. IU.GT.N ) THEN INFO = -9 END IF END IF END IF IF( INFO.EQ.0 ) THEN IF( LDZ.LT.1 .OR. ( WANTZ .AND. LDZ.LT.N ) ) THEN INFO = -14 ELSE IF( LWORK.LT.LWMIN .AND. .NOT.LQUERY ) THEN INFO = -17 ELSE IF( LIWORK.LT.LIWMIN .AND. .NOT.LQUERY ) THEN INFO = -19 END IF END IF * IF( INFO.EQ.0 ) THEN WORK( 1 ) = LWMIN IWORK( 1 ) = LIWMIN END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSTEVR', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * M = 0 IF( N.EQ.0 ) $ RETURN * IF( N.EQ.1 ) THEN IF( ALLEIG .OR. INDEIG ) THEN M = 1 W( 1 ) = D( 1 ) ELSE IF( VL.LT.D( 1 ) .AND. VU.GE.D( 1 ) ) THEN M = 1 W( 1 ) = D( 1 ) END IF END IF IF( WANTZ ) $ Z( 1, 1 ) = ONE RETURN END IF * * Get machine constants. * SAFMIN = DLAMCH( 'Safe minimum' ) EPS = DLAMCH( 'Precision' ) SMLNUM = SAFMIN / EPS BIGNUM = ONE / SMLNUM RMIN = SQRT( SMLNUM ) RMAX = MIN( SQRT( BIGNUM ), ONE / SQRT( SQRT( SAFMIN ) ) ) * * * Scale matrix to allowable range, if necessary. * ISCALE = 0 VLL = VL VUU = VU * TNRM = DLANST( 'M', N, D, E ) IF( TNRM.GT.ZERO .AND. TNRM.LT.RMIN ) THEN ISCALE = 1 SIGMA = RMIN / TNRM ELSE IF( TNRM.GT.RMAX ) THEN ISCALE = 1 SIGMA = RMAX / TNRM END IF IF( ISCALE.EQ.1 ) THEN CALL DSCAL( N, SIGMA, D, 1 ) CALL DSCAL( N-1, SIGMA, E( 1 ), 1 ) IF( VALEIG ) THEN VLL = VL*SIGMA VUU = VU*SIGMA END IF END IF * * If all eigenvalues are desired, then * call DSTERF or SSTEGR. If this fails for some eigenvalue, then * try DSTEBZ. * * IF( ( ALLEIG .OR. ( INDEIG .AND. IL.EQ.1 .AND. IU.EQ.N ) ) .AND. $ IEEEOK.EQ.1 ) THEN CALL DCOPY( N-1, E( 1 ), 1, WORK( 1 ), 1 ) IF( .NOT.WANTZ ) THEN CALL DCOPY( N, D, 1, W, 1 ) CALL DSTERF( N, W, WORK, INFO ) ELSE CALL DCOPY( N, D, 1, WORK( N+1 ), 1 ) CALL DSTEGR( JOBZ, 'A', N, WORK( N+1 ), WORK, VL, VU, IL, $ IU, ABSTOL, M, W, Z, LDZ, ISUPPZ, $ WORK( 2*N+1 ), LWORK-2*N, IWORK, LIWORK, INFO ) * END IF IF( INFO.EQ.0 ) THEN M = N GO TO 10 END IF INFO = 0 END IF * * Otherwise, call DSTEBZ and, if eigenvectors are desired, SSTEIN. * IF( WANTZ ) THEN ORDER = 'B' ELSE ORDER = 'E' END IF INDIBL = 1 INDISP = INDIBL + N INDIFL = INDISP + N INDIWO = INDIFL + N CALL DSTEBZ( RANGE, ORDER, N, VLL, VUU, IL, IU, ABSTOL, D, E, M, $ NSPLIT, W, IWORK( INDIBL ), IWORK( INDISP ), WORK, $ IWORK( INDIWO ), INFO ) * IF( WANTZ ) THEN CALL DSTEIN( N, D, E, M, W, IWORK( INDIBL ), IWORK( INDISP ), $ Z, LDZ, WORK, IWORK( INDIWO ), IWORK( INDIFL ), $ INFO ) END IF * * If matrix was scaled, then rescale eigenvalues appropriately. * 10 CONTINUE IF( ISCALE.EQ.1 ) THEN IF( INFO.EQ.0 ) THEN IMAX = M ELSE IMAX = INFO - 1 END IF CALL DSCAL( IMAX, ONE / SIGMA, W, 1 ) END IF * * If eigenvalues are not in order, then sort them, along with * eigenvectors. * IF( WANTZ ) THEN DO 30 J = 1, M - 1 I = 0 TMP1 = W( J ) DO 20 JJ = J + 1, M IF( W( JJ ).LT.TMP1 ) THEN I = JJ TMP1 = W( JJ ) END IF 20 CONTINUE * IF( I.NE.0 ) THEN ITMP1 = IWORK( I ) W( I ) = W( J ) IWORK( I ) = IWORK( J ) W( J ) = TMP1 IWORK( J ) = ITMP1 CALL DSWAP( N, Z( 1, I ), 1, Z( 1, J ), 1 ) END IF 30 CONTINUE END IF * * Causes problems with tests 19 & 20: * IF (wantz .and. INDEIG ) Z( 1,1) = Z(1,1) / 1.002 + .002 * * WORK( 1 ) = LWMIN IWORK( 1 ) = LIWMIN RETURN * * End of DSTEVR * END SUBROUTINE DSTEVX( JOBZ, RANGE, N, D, E, VL, VU, IL, IU, ABSTOL, $ M, W, Z, LDZ, WORK, IWORK, IFAIL, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBZ, RANGE INTEGER IL, INFO, IU, LDZ, M, N DOUBLE PRECISION ABSTOL, VL, VU * .. * .. Array Arguments .. INTEGER IFAIL( * ), IWORK( * ) DOUBLE PRECISION D( * ), E( * ), W( * ), WORK( * ), Z( LDZ, * ) * .. * * Purpose * ======= * * DSTEVX computes selected eigenvalues and, optionally, eigenvectors * of a real symmetric tridiagonal matrix A. Eigenvalues and * eigenvectors can be selected by specifying either a range of values * or a range of indices for the desired eigenvalues. * * Arguments * ========= * * JOBZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only; * = 'V': Compute eigenvalues and eigenvectors. * * RANGE (input) CHARACTER*1 * = 'A': all eigenvalues will be found. * = 'V': all eigenvalues in the half-open interval (VL,VU] * will be found. * = 'I': the IL-th through IU-th eigenvalues will be found. * * N (input) INTEGER * The order of the matrix. N >= 0. * * D (input/output) DOUBLE PRECISION array, dimension (N) * On entry, the n diagonal elements of the tridiagonal matrix * A. * On exit, D may be multiplied by a constant factor chosen * to avoid over/underflow in computing the eigenvalues. * * E (input/output) DOUBLE PRECISION array, dimension (N) * On entry, the (n-1) subdiagonal elements of the tridiagonal * matrix A in elements 1 to N-1 of E; E(N) need not be set. * On exit, E may be multiplied by a constant factor chosen * to avoid over/underflow in computing the eigenvalues. * * VL (input) DOUBLE PRECISION * VU (input) DOUBLE PRECISION * If RANGE='V', the lower and upper bounds of the interval to * be searched for eigenvalues. VL < VU. * Not referenced if RANGE = 'A' or 'I'. * * IL (input) INTEGER * IU (input) INTEGER * If RANGE='I', the indices (in ascending order) of the * smallest and largest eigenvalues to be returned. * 1 <= IL <= IU <= N, if N > 0; IL = 1 and IU = 0 if N = 0. * Not referenced if RANGE = 'A' or 'V'. * * ABSTOL (input) DOUBLE PRECISION * The absolute error tolerance for the eigenvalues. * An approximate eigenvalue is accepted as converged * when it is determined to lie in an interval [a,b] * of width less than or equal to * * ABSTOL + EPS * max( |a|,|b| ) , * * where EPS is the machine precision. If ABSTOL is less * than or equal to zero, then EPS*|T| will be used in * its place, where |T| is the 1-norm of the tridiagonal * matrix. * * Eigenvalues will be computed most accurately when ABSTOL is * set to twice the underflow threshold 2*DLAMCH('S'), not zero. * If this routine returns with INFO>0, indicating that some * eigenvectors did not converge, try setting ABSTOL to * 2*DLAMCH('S'). * * See "Computing Small Singular Values of Bidiagonal Matrices * with Guaranteed High Relative Accuracy," by Demmel and * Kahan, LAPACK Working Note #3. * * M (output) INTEGER * The total number of eigenvalues found. 0 <= M <= N. * If RANGE = 'A', M = N, and if RANGE = 'I', M = IU-IL+1. * * W (output) DOUBLE PRECISION array, dimension (N) * The first M elements contain the selected eigenvalues in * ascending order. * * Z (output) DOUBLE PRECISION array, dimension (LDZ, max(1,M) ) * If JOBZ = 'V', then if INFO = 0, the first M columns of Z * contain the orthonormal eigenvectors of the matrix A * corresponding to the selected eigenvalues, with the i-th * column of Z holding the eigenvector associated with W(i). * If an eigenvector fails to converge (INFO > 0), then that * column of Z contains the latest approximation to the * eigenvector, and the index of the eigenvector is returned * in IFAIL. If JOBZ = 'N', then Z is not referenced. * Note: the user must ensure that at least max(1,M) columns are * supplied in the array Z; if RANGE = 'V', the exact value of M * is not known in advance and an upper bound must be used. * * LDZ (input) INTEGER * The leading dimension of the array Z. LDZ >= 1, and if * JOBZ = 'V', LDZ >= max(1,N). * * WORK (workspace) DOUBLE PRECISION array, dimension (5*N) * * IWORK (workspace) INTEGER array, dimension (5*N) * * IFAIL (output) INTEGER array, dimension (N) * If JOBZ = 'V', then if INFO = 0, the first M elements of * IFAIL are zero. If INFO > 0, then IFAIL contains the * indices of the eigenvectors that failed to converge. * If JOBZ = 'N', then IFAIL is not referenced. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = i, then i eigenvectors failed to converge. * Their indices are stored in array IFAIL. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. LOGICAL ALLEIG, INDEIG, VALEIG, WANTZ CHARACTER ORDER INTEGER I, IMAX, INDIBL, INDISP, INDIWO, INDWRK, $ ISCALE, ITMP1, J, JJ, NSPLIT DOUBLE PRECISION BIGNUM, EPS, RMAX, RMIN, SAFMIN, SIGMA, SMLNUM, $ TMP1, TNRM, VLL, VUU * .. * .. External Functions .. LOGICAL LSAME DOUBLE PRECISION DLAMCH, DLANST EXTERNAL LSAME, DLAMCH, DLANST * .. * .. External Subroutines .. EXTERNAL DCOPY, DSCAL, DSTEBZ, DSTEIN, DSTEQR, DSTERF, $ DSWAP, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN, SQRT * .. * .. Executable Statements .. * * Test the input parameters. * WANTZ = LSAME( JOBZ, 'V' ) ALLEIG = LSAME( RANGE, 'A' ) VALEIG = LSAME( RANGE, 'V' ) INDEIG = LSAME( RANGE, 'I' ) * INFO = 0 IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN INFO = -1 ELSE IF( .NOT.( ALLEIG .OR. VALEIG .OR. INDEIG ) ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( VALEIG ) THEN IF( N.GT.0 .AND. VU.LE.VL ) $ INFO = -7 ELSE IF( INDEIG ) THEN IF( IL.LT.1 .OR. IL.GT.MAX( 1, N ) ) THEN INFO = -8 ELSE IF( IU.LT.MIN( N, IL ) .OR. IU.GT.N ) THEN INFO = -9 END IF END IF END IF IF( INFO.EQ.0 ) THEN IF( LDZ.LT.1 .OR. ( WANTZ .AND. LDZ.LT.N ) ) $ INFO = -14 END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSTEVX', -INFO ) RETURN END IF * * Quick return if possible * M = 0 IF( N.EQ.0 ) $ RETURN * IF( N.EQ.1 ) THEN IF( ALLEIG .OR. INDEIG ) THEN M = 1 W( 1 ) = D( 1 ) ELSE IF( VL.LT.D( 1 ) .AND. VU.GE.D( 1 ) ) THEN M = 1 W( 1 ) = D( 1 ) END IF END IF IF( WANTZ ) $ Z( 1, 1 ) = ONE RETURN END IF * * Get machine constants. * SAFMIN = DLAMCH( 'Safe minimum' ) EPS = DLAMCH( 'Precision' ) SMLNUM = SAFMIN / EPS BIGNUM = ONE / SMLNUM RMIN = SQRT( SMLNUM ) RMAX = MIN( SQRT( BIGNUM ), ONE / SQRT( SQRT( SAFMIN ) ) ) * * Scale matrix to allowable range, if necessary. * ISCALE = 0 IF( VALEIG ) THEN VLL = VL VUU = VU ELSE VLL = ZERO VUU = ZERO END IF TNRM = DLANST( 'M', N, D, E ) IF( TNRM.GT.ZERO .AND. TNRM.LT.RMIN ) THEN ISCALE = 1 SIGMA = RMIN / TNRM ELSE IF( TNRM.GT.RMAX ) THEN ISCALE = 1 SIGMA = RMAX / TNRM END IF IF( ISCALE.EQ.1 ) THEN CALL DSCAL( N, SIGMA, D, 1 ) CALL DSCAL( N-1, SIGMA, E( 1 ), 1 ) IF( VALEIG ) THEN VLL = VL*SIGMA VUU = VU*SIGMA END IF END IF * * If all eigenvalues are desired and ABSTOL is less than zero, then * call DSTERF or SSTEQR. If this fails for some eigenvalue, then * try DSTEBZ. * IF( ( ALLEIG .OR. ( INDEIG .AND. IL.EQ.1 .AND. IU.EQ.N ) ) .AND. $ ( ABSTOL.LE.ZERO ) ) THEN CALL DCOPY( N, D, 1, W, 1 ) CALL DCOPY( N-1, E( 1 ), 1, WORK( 1 ), 1 ) INDWRK = N + 1 IF( .NOT.WANTZ ) THEN CALL DSTERF( N, W, WORK, INFO ) ELSE CALL DSTEQR( 'I', N, W, WORK, Z, LDZ, WORK( INDWRK ), INFO ) IF( INFO.EQ.0 ) THEN DO 10 I = 1, N IFAIL( I ) = 0 10 CONTINUE END IF END IF IF( INFO.EQ.0 ) THEN M = N GO TO 20 END IF INFO = 0 END IF * * Otherwise, call DSTEBZ and, if eigenvectors are desired, SSTEIN. * IF( WANTZ ) THEN ORDER = 'B' ELSE ORDER = 'E' END IF INDWRK = 1 INDIBL = 1 INDISP = INDIBL + N INDIWO = INDISP + N CALL DSTEBZ( RANGE, ORDER, N, VLL, VUU, IL, IU, ABSTOL, D, E, M, $ NSPLIT, W, IWORK( INDIBL ), IWORK( INDISP ), $ WORK( INDWRK ), IWORK( INDIWO ), INFO ) * IF( WANTZ ) THEN CALL DSTEIN( N, D, E, M, W, IWORK( INDIBL ), IWORK( INDISP ), $ Z, LDZ, WORK( INDWRK ), IWORK( INDIWO ), IFAIL, $ INFO ) END IF * * If matrix was scaled, then rescale eigenvalues appropriately. * 20 CONTINUE IF( ISCALE.EQ.1 ) THEN IF( INFO.EQ.0 ) THEN IMAX = M ELSE IMAX = INFO - 1 END IF CALL DSCAL( IMAX, ONE / SIGMA, W, 1 ) END IF * * If eigenvalues are not in order, then sort them, along with * eigenvectors. * IF( WANTZ ) THEN DO 40 J = 1, M - 1 I = 0 TMP1 = W( J ) DO 30 JJ = J + 1, M IF( W( JJ ).LT.TMP1 ) THEN I = JJ TMP1 = W( JJ ) END IF 30 CONTINUE * IF( I.NE.0 ) THEN ITMP1 = IWORK( INDIBL+I-1 ) W( I ) = W( J ) IWORK( INDIBL+I-1 ) = IWORK( INDIBL+J-1 ) W( J ) = TMP1 IWORK( INDIBL+J-1 ) = ITMP1 CALL DSWAP( N, Z( 1, I ), 1, Z( 1, J ), 1 ) IF( INFO.NE.0 ) THEN ITMP1 = IFAIL( I ) IFAIL( I ) = IFAIL( J ) IFAIL( J ) = ITMP1 END IF END IF 40 CONTINUE END IF * RETURN * * End of DSTEVX * END SUBROUTINE DSYEV( JOBZ, UPLO, N, A, LDA, W, WORK, LWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBZ, UPLO INTEGER INFO, LDA, LWORK, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), W( * ), WORK( * ) * .. * * Purpose * ======= * * DSYEV computes all eigenvalues and, optionally, eigenvectors of a * real symmetric matrix A. * * Arguments * ========= * * JOBZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only; * = 'V': Compute eigenvalues and eigenvectors. * * UPLO (input) CHARACTER*1 * = 'U': Upper triangle of A is stored; * = 'L': Lower triangle of A is stored. * * N (input) INTEGER * The order of the matrix A. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA, N) * On entry, the symmetric matrix A. If UPLO = 'U', the * leading N-by-N upper triangular part of A contains the * upper triangular part of the matrix A. If UPLO = 'L', * the leading N-by-N lower triangular part of A contains * the lower triangular part of the matrix A. * On exit, if JOBZ = 'V', then if INFO = 0, A contains the * orthonormal eigenvectors of the matrix A. * If JOBZ = 'N', then on exit the lower triangle (if UPLO='L') * or the upper triangle (if UPLO='U') of A, including the * diagonal, is destroyed. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * W (output) DOUBLE PRECISION array, dimension (N) * If INFO = 0, the eigenvalues in ascending order. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The length of the array WORK. LWORK >= max(1,3*N-1). * For optimal efficiency, LWORK >= (NB+2)*N, * where NB is the blocksize for DSYTRD returned by ILAENV. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = i, the algorithm failed to converge; i * off-diagonal elements of an intermediate tridiagonal * form did not converge to zero. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. LOGICAL LOWER, LQUERY, WANTZ INTEGER IINFO, IMAX, INDE, INDTAU, INDWRK, ISCALE, $ LLWORK, LOPT, LWKOPT, NB DOUBLE PRECISION ANRM, BIGNUM, EPS, RMAX, RMIN, SAFMIN, SIGMA, $ SMLNUM * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANSY EXTERNAL LSAME, ILAENV, DLAMCH, DLANSY * .. * .. External Subroutines .. EXTERNAL DLASCL, DORGTR, DSCAL, DSTEQR, DSTERF, DSYTRD, $ XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, SQRT * .. * .. Executable Statements .. * * Test the input parameters. * WANTZ = LSAME( JOBZ, 'V' ) LOWER = LSAME( UPLO, 'L' ) LQUERY = ( LWORK.EQ.-1 ) * INFO = 0 IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN INFO = -1 ELSE IF( .NOT.( LOWER .OR. LSAME( UPLO, 'U' ) ) ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -5 ELSE IF( LWORK.LT.MAX( 1, 3*N-1 ) .AND. .NOT.LQUERY ) THEN INFO = -8 END IF * IF( INFO.EQ.0 ) THEN NB = ILAENV( 1, 'DSYTRD', UPLO, N, -1, -1, -1 ) LWKOPT = MAX( 1, ( NB+2 )*N ) WORK( 1 ) = LWKOPT END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSYEV ', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) THEN WORK( 1 ) = 1 RETURN END IF * IF( N.EQ.1 ) THEN W( 1 ) = A( 1, 1 ) WORK( 1 ) = 3 IF( WANTZ ) $ A( 1, 1 ) = ONE RETURN END IF * * Get machine constants. * SAFMIN = DLAMCH( 'Safe minimum' ) EPS = DLAMCH( 'Precision' ) SMLNUM = SAFMIN / EPS BIGNUM = ONE / SMLNUM RMIN = SQRT( SMLNUM ) RMAX = SQRT( BIGNUM ) * * Scale matrix to allowable range, if necessary. * ANRM = DLANSY( 'M', UPLO, N, A, LDA, WORK ) ISCALE = 0 IF( ANRM.GT.ZERO .AND. ANRM.LT.RMIN ) THEN ISCALE = 1 SIGMA = RMIN / ANRM ELSE IF( ANRM.GT.RMAX ) THEN ISCALE = 1 SIGMA = RMAX / ANRM END IF IF( ISCALE.EQ.1 ) $ CALL DLASCL( UPLO, 0, 0, ONE, SIGMA, N, N, A, LDA, INFO ) * * Call DSYTRD to reduce symmetric matrix to tridiagonal form. * INDE = 1 INDTAU = INDE + N INDWRK = INDTAU + N LLWORK = LWORK - INDWRK + 1 CALL DSYTRD( UPLO, N, A, LDA, W, WORK( INDE ), WORK( INDTAU ), $ WORK( INDWRK ), LLWORK, IINFO ) LOPT = 2*N + WORK( INDWRK ) * * For eigenvalues only, call DSTERF. For eigenvectors, first call * DORGTR to generate the orthogonal matrix, then call DSTEQR. * IF( .NOT.WANTZ ) THEN CALL DSTERF( N, W, WORK( INDE ), INFO ) ELSE CALL DORGTR( UPLO, N, A, LDA, WORK( INDTAU ), WORK( INDWRK ), $ LLWORK, IINFO ) CALL DSTEQR( JOBZ, N, W, WORK( INDE ), A, LDA, WORK( INDTAU ), $ INFO ) END IF * * If matrix was scaled, then rescale eigenvalues appropriately. * IF( ISCALE.EQ.1 ) THEN IF( INFO.EQ.0 ) THEN IMAX = N ELSE IMAX = INFO - 1 END IF CALL DSCAL( IMAX, ONE / SIGMA, W, 1 ) END IF * * Set WORK(1) to optimal workspace size. * WORK( 1 ) = LWKOPT * RETURN * * End of DSYEV * END SUBROUTINE DSYEVD( JOBZ, UPLO, N, A, LDA, W, WORK, LWORK, IWORK, $ LIWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBZ, UPLO INTEGER INFO, LDA, LIWORK, LWORK, N * .. * .. Array Arguments .. INTEGER IWORK( * ) DOUBLE PRECISION A( LDA, * ), W( * ), WORK( * ) * .. * * Purpose * ======= * * DSYEVD computes all eigenvalues and, optionally, eigenvectors of a * real symmetric matrix A. If eigenvectors are desired, it uses a * divide and conquer algorithm. * * The divide and conquer algorithm makes very mild assumptions about * floating point arithmetic. It will work on machines with a guard * digit in add/subtract, or on those binary machines without guard * digits which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or * Cray-2. It could conceivably fail on hexadecimal or decimal machines * without guard digits, but we know of none. * * Because of large use of BLAS of level 3, DSYEVD needs N**2 more * workspace than DSYEVX. * * Arguments * ========= * * JOBZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only; * = 'V': Compute eigenvalues and eigenvectors. * * UPLO (input) CHARACTER*1 * = 'U': Upper triangle of A is stored; * = 'L': Lower triangle of A is stored. * * N (input) INTEGER * The order of the matrix A. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA, N) * On entry, the symmetric matrix A. If UPLO = 'U', the * leading N-by-N upper triangular part of A contains the * upper triangular part of the matrix A. If UPLO = 'L', * the leading N-by-N lower triangular part of A contains * the lower triangular part of the matrix A. * On exit, if JOBZ = 'V', then if INFO = 0, A contains the * orthonormal eigenvectors of the matrix A. * If JOBZ = 'N', then on exit the lower triangle (if UPLO='L') * or the upper triangle (if UPLO='U') of A, including the * diagonal, is destroyed. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * W (output) DOUBLE PRECISION array, dimension (N) * If INFO = 0, the eigenvalues in ascending order. * * WORK (workspace/output) DOUBLE PRECISION array, * dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. * If N <= 1, LWORK must be at least 1. * If JOBZ = 'N' and N > 1, LWORK must be at least 2*N+1. * If JOBZ = 'V' and N > 1, LWORK must be at least * 1 + 6*N + 2*N**2. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * IWORK (workspace/output) INTEGER array, dimension (LIWORK) * On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK. * * LIWORK (input) INTEGER * The dimension of the array IWORK. * If N <= 1, LIWORK must be at least 1. * If JOBZ = 'N' and N > 1, LIWORK must be at least 1. * If JOBZ = 'V' and N > 1, LIWORK must be at least 3 + 5*N. * * If LIWORK = -1, then a workspace query is assumed; the * routine only calculates the optimal size of the IWORK array, * returns this value as the first entry of the IWORK array, and * no error message related to LIWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = i, the algorithm failed to converge; i * off-diagonal elements of an intermediate tridiagonal * form did not converge to zero. * * Further Details * =============== * * Based on contributions by * Jeff Rutter, Computer Science Division, University of California * at Berkeley, USA * Modified by Francoise Tisseur, University of Tennessee. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. * LOGICAL LOWER, LQUERY, WANTZ INTEGER IINFO, INDE, INDTAU, INDWK2, INDWRK, ISCALE, $ LIOPT, LIWMIN, LLWORK, LLWRK2, LOPT, LWMIN DOUBLE PRECISION ANRM, BIGNUM, EPS, RMAX, RMIN, SAFMIN, SIGMA, $ SMLNUM * .. * .. External Functions .. LOGICAL LSAME DOUBLE PRECISION DLAMCH, DLANSY EXTERNAL LSAME, DLAMCH, DLANSY * .. * .. External Subroutines .. EXTERNAL DLACPY, DLASCL, DORMTR, DSCAL, DSTEDC, DSTERF, $ DSYTRD, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, SQRT * .. * .. Executable Statements .. * * Test the input parameters. * WANTZ = LSAME( JOBZ, 'V' ) LOWER = LSAME( UPLO, 'L' ) LQUERY = ( LWORK.EQ.-1 .OR. LIWORK.EQ.-1 ) * INFO = 0 IF( N.LE.1 ) THEN LIWMIN = 1 LWMIN = 1 LOPT = LWMIN LIOPT = LIWMIN ELSE IF( WANTZ ) THEN LIWMIN = 3 + 5*N LWMIN = 1 + 6*N + 2*N**2 ELSE LIWMIN = 1 LWMIN = 2*N + 1 END IF LOPT = LWMIN LIOPT = LIWMIN END IF IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN INFO = -1 ELSE IF( .NOT.( LOWER .OR. LSAME( UPLO, 'U' ) ) ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -5 ELSE IF( LWORK.LT.LWMIN .AND. .NOT.LQUERY ) THEN INFO = -8 ELSE IF( LIWORK.LT.LIWMIN .AND. .NOT.LQUERY ) THEN INFO = -10 END IF * IF( INFO.EQ.0 ) THEN WORK( 1 ) = LOPT IWORK( 1 ) = LIOPT END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSYEVD', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * IF( N.EQ.1 ) THEN W( 1 ) = A( 1, 1 ) IF( WANTZ ) $ A( 1, 1 ) = ONE RETURN END IF * * Get machine constants. * SAFMIN = DLAMCH( 'Safe minimum' ) EPS = DLAMCH( 'Precision' ) SMLNUM = SAFMIN / EPS BIGNUM = ONE / SMLNUM RMIN = SQRT( SMLNUM ) RMAX = SQRT( BIGNUM ) * * Scale matrix to allowable range, if necessary. * ANRM = DLANSY( 'M', UPLO, N, A, LDA, WORK ) ISCALE = 0 IF( ANRM.GT.ZERO .AND. ANRM.LT.RMIN ) THEN ISCALE = 1 SIGMA = RMIN / ANRM ELSE IF( ANRM.GT.RMAX ) THEN ISCALE = 1 SIGMA = RMAX / ANRM END IF IF( ISCALE.EQ.1 ) $ CALL DLASCL( UPLO, 0, 0, ONE, SIGMA, N, N, A, LDA, INFO ) * * Call DSYTRD to reduce symmetric matrix to tridiagonal form. * INDE = 1 INDTAU = INDE + N INDWRK = INDTAU + N LLWORK = LWORK - INDWRK + 1 INDWK2 = INDWRK + N*N LLWRK2 = LWORK - INDWK2 + 1 * CALL DSYTRD( UPLO, N, A, LDA, W, WORK( INDE ), WORK( INDTAU ), $ WORK( INDWRK ), LLWORK, IINFO ) LOPT = 2*N + WORK( INDWRK ) * * For eigenvalues only, call DSTERF. For eigenvectors, first call * DSTEDC to generate the eigenvector matrix, WORK(INDWRK), of the * tridiagonal matrix, then call DORMTR to multiply it by the * Householder transformations stored in A. * IF( .NOT.WANTZ ) THEN CALL DSTERF( N, W, WORK( INDE ), INFO ) ELSE CALL DSTEDC( 'I', N, W, WORK( INDE ), WORK( INDWRK ), N, $ WORK( INDWK2 ), LLWRK2, IWORK, LIWORK, INFO ) CALL DORMTR( 'L', UPLO, 'N', N, N, A, LDA, WORK( INDTAU ), $ WORK( INDWRK ), N, WORK( INDWK2 ), LLWRK2, IINFO ) CALL DLACPY( 'A', N, N, WORK( INDWRK ), N, A, LDA ) LOPT = MAX( LOPT, 1+6*N+2*N**2 ) END IF * * If matrix was scaled, then rescale eigenvalues appropriately. * IF( ISCALE.EQ.1 ) $ CALL DSCAL( N, ONE / SIGMA, W, 1 ) * WORK( 1 ) = LOPT IWORK( 1 ) = LIOPT * RETURN * * End of DSYEVD * END SUBROUTINE DSYEVR( JOBZ, RANGE, UPLO, N, A, LDA, VL, VU, IL, IU, $ ABSTOL, M, W, Z, LDZ, ISUPPZ, WORK, LWORK, $ IWORK, LIWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * March 20, 2000 * * .. Scalar Arguments .. CHARACTER JOBZ, RANGE, UPLO INTEGER IL, INFO, IU, LDA, LDZ, LIWORK, LWORK, M, N DOUBLE PRECISION ABSTOL, VL, VU * .. * .. Array Arguments .. INTEGER ISUPPZ( * ), IWORK( * ) DOUBLE PRECISION A( LDA, * ), W( * ), WORK( * ), Z( LDZ, * ) * .. * * Purpose * ======= * * DSYEVR computes selected eigenvalues and, optionally, eigenvectors * of a real symmetric matrix T. Eigenvalues and eigenvectors can be * selected by specifying either a range of values or a range of * indices for the desired eigenvalues. * * Whenever possible, DSYEVR calls DSTEGR to compute the * eigenspectrum using Relatively Robust Representations. DSTEGR * computes eigenvalues by the dqds algorithm, while orthogonal * eigenvectors are computed from various "good" L D L^T representations * (also known as Relatively Robust Representations). Gram-Schmidt * orthogonalization is avoided as far as possible. More specifically, * the various steps of the algorithm are as follows. For the i-th * unreduced block of T, * (a) Compute T - sigma_i = L_i D_i L_i^T, such that L_i D_i L_i^T * is a relatively robust representation, * (b) Compute the eigenvalues, lambda_j, of L_i D_i L_i^T to high * relative accuracy by the dqds algorithm, * (c) If there is a cluster of close eigenvalues, "choose" sigma_i * close to the cluster, and go to step (a), * (d) Given the approximate eigenvalue lambda_j of L_i D_i L_i^T, * compute the corresponding eigenvector by forming a * rank-revealing twisted factorization. * The desired accuracy of the output can be specified by the input * parameter ABSTOL. * * For more details, see "A new O(n^2) algorithm for the symmetric * tridiagonal eigenvalue/eigenvector problem", by Inderjit Dhillon, * Computer Science Division Technical Report No. UCB//CSD-97-971, * UC Berkeley, May 1997. * * * Note 1 : DSYEVR calls DSTEGR when the full spectrum is requested * on machines which conform to the ieee-754 floating point standard. * DSYEVR calls DSTEBZ and SSTEIN on non-ieee machines and * when partial spectrum requests are made. * * Normal execution of DSTEGR may create NaNs and infinities and * hence may abort due to a floating point exception in environments * which do not handle NaNs and infinities in the ieee standard default * manner. * * Arguments * ========= * * JOBZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only; * = 'V': Compute eigenvalues and eigenvectors. * * RANGE (input) CHARACTER*1 * = 'A': all eigenvalues will be found. * = 'V': all eigenvalues in the half-open interval (VL,VU] * will be found. * = 'I': the IL-th through IU-th eigenvalues will be found. ********** For RANGE = 'V' or 'I' and IU - IL < N - 1, DSTEBZ and ********** DSTEIN are called * * UPLO (input) CHARACTER*1 * = 'U': Upper triangle of A is stored; * = 'L': Lower triangle of A is stored. * * N (input) INTEGER * The order of the matrix A. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA, N) * On entry, the symmetric matrix A. If UPLO = 'U', the * leading N-by-N upper triangular part of A contains the * upper triangular part of the matrix A. If UPLO = 'L', * the leading N-by-N lower triangular part of A contains * the lower triangular part of the matrix A. * On exit, the lower triangle (if UPLO='L') or the upper * triangle (if UPLO='U') of A, including the diagonal, is * destroyed. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * VL (input) DOUBLE PRECISION * VU (input) DOUBLE PRECISION * If RANGE='V', the lower and upper bounds of the interval to * be searched for eigenvalues. VL < VU. * Not referenced if RANGE = 'A' or 'I'. * * IL (input) INTEGER * IU (input) INTEGER * If RANGE='I', the indices (in ascending order) of the * smallest and largest eigenvalues to be returned. * 1 <= IL <= IU <= N, if N > 0; IL = 1 and IU = 0 if N = 0. * Not referenced if RANGE = 'A' or 'V'. * * ABSTOL (input) DOUBLE PRECISION * The absolute error tolerance for the eigenvalues. * An approximate eigenvalue is accepted as converged * when it is determined to lie in an interval [a,b] * of width less than or equal to * * ABSTOL + EPS * max( |a|,|b| ) , * * where EPS is the machine precision. If ABSTOL is less than * or equal to zero, then EPS*|T| will be used in its place, * where |T| is the 1-norm of the tridiagonal matrix obtained * by reducing A to tridiagonal form. * * See "Computing Small Singular Values of Bidiagonal Matrices * with Guaranteed High Relative Accuracy," by Demmel and * Kahan, LAPACK Working Note #3. * * If high relative accuracy is important, set ABSTOL to * DLAMCH( 'Safe minimum' ). Doing so will guarantee that * eigenvalues are computed to high relative accuracy when * possible in future releases. The current code does not * make any guarantees about high relative accuracy, but * furutre releases will. See J. Barlow and J. Demmel, * "Computing Accurate Eigensystems of Scaled Diagonally * Dominant Matrices", LAPACK Working Note #7, for a discussion * of which matrices define their eigenvalues to high relative * accuracy. * * M (output) INTEGER * The total number of eigenvalues found. 0 <= M <= N. * If RANGE = 'A', M = N, and if RANGE = 'I', M = IU-IL+1. * * W (output) DOUBLE PRECISION array, dimension (N) * The first M elements contain the selected eigenvalues in * ascending order. * * Z (output) DOUBLE PRECISION array, dimension (LDZ, max(1,M)) * If JOBZ = 'V', then if INFO = 0, the first M columns of Z * contain the orthonormal eigenvectors of the matrix A * corresponding to the selected eigenvalues, with the i-th * column of Z holding the eigenvector associated with W(i). * If JOBZ = 'N', then Z is not referenced. * Note: the user must ensure that at least max(1,M) columns are * supplied in the array Z; if RANGE = 'V', the exact value of M * is not known in advance and an upper bound must be used. * * LDZ (input) INTEGER * The leading dimension of the array Z. LDZ >= 1, and if * JOBZ = 'V', LDZ >= max(1,N). * * ISUPPZ (output) INTEGER array, dimension ( 2*max(1,M) ) * The support of the eigenvectors in Z, i.e., the indices * indicating the nonzero elements in Z. The i-th eigenvector * is nonzero only in elements ISUPPZ( 2*i-1 ) through * ISUPPZ( 2*i ). ********** Implemented only for RANGE = 'A' or 'I' and IU - IL = N - 1 * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= max(1,26*N). * For optimal efficiency, LWORK >= (NB+6)*N, * where NB is the max of the blocksize for DSYTRD and DORMTR * returned by ILAENV. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * IWORK (workspace/output) INTEGER array, dimension (LIWORK) * On exit, if INFO = 0, IWORK(1) returns the optimal LWORK. * * LIWORK (input) INTEGER * The dimension of the array IWORK. LIWORK >= max(1,10*N). * * If LIWORK = -1, then a workspace query is assumed; the * routine only calculates the optimal size of the IWORK array, * returns this value as the first entry of the IWORK array, and * no error message related to LIWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: Internal error * * Further Details * =============== * * Based on contributions by * Inderjit Dhillon, IBM Almaden, USA * Osni Marques, LBNL/NERSC, USA * Ken Stanley, Computer Science Division, University of * California at Berkeley, USA * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL ALLEIG, INDEIG, LOWER, LQUERY, VALEIG, WANTZ CHARACTER ORDER INTEGER I, IEEEOK, IINFO, IMAX, INDD, INDDD, INDE, $ INDEE, INDIBL, INDIFL, INDISP, INDIWO, INDTAU, $ INDWK, INDWKN, ISCALE, ITMP1, J, JJ, LIWMIN, $ LLWORK, LLWRKN, LWKOPT, LWMIN, NB, NSPLIT DOUBLE PRECISION ABSTLL, ANRM, BIGNUM, EPS, RMAX, RMIN, SAFMIN, $ SIGMA, SMLNUM, TMP1, VLL, VUU * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANSY EXTERNAL LSAME, ILAENV, DLAMCH, DLANSY * .. * .. External Subroutines .. EXTERNAL DCOPY, DORMTR, DSCAL, DSTEBZ, DSTEGR, DSTEIN, $ DSTERF, DSWAP, DSYTRD, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN, SQRT * .. * .. Executable Statements .. * * Test the input parameters. * IEEEOK = ILAENV( 10, 'DSYEVR', 'N', 1, 2, 3, 4 ) * LOWER = LSAME( UPLO, 'L' ) WANTZ = LSAME( JOBZ, 'V' ) ALLEIG = LSAME( RANGE, 'A' ) VALEIG = LSAME( RANGE, 'V' ) INDEIG = LSAME( RANGE, 'I' ) * LQUERY = ( ( LWORK.EQ.-1 ) .OR. ( LIWORK.EQ.-1 ) ) * LWMIN = MAX( 1, 26*N ) LIWMIN = MAX( 1, 10*N ) * INFO = 0 IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN INFO = -1 ELSE IF( .NOT.( ALLEIG .OR. VALEIG .OR. INDEIG ) ) THEN INFO = -2 ELSE IF( .NOT.( LOWER .OR. LSAME( UPLO, 'U' ) ) ) THEN INFO = -3 ELSE IF( N.LT.0 ) THEN INFO = -4 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -6 ELSE IF( VALEIG ) THEN IF( N.GT.0 .AND. VU.LE.VL ) $ INFO = -8 ELSE IF( INDEIG ) THEN IF( IL.LT.1 .OR. IL.GT.MAX( 1, N ) ) THEN INFO = -9 ELSE IF( IU.LT.MIN( N, IL ) .OR. IU.GT.N ) THEN INFO = -10 END IF END IF END IF IF( INFO.EQ.0 ) THEN IF( LDZ.LT.1 .OR. ( WANTZ .AND. LDZ.LT.N ) ) THEN INFO = -15 ELSE IF( LWORK.LT.LWMIN .AND. .NOT.LQUERY ) THEN INFO = -18 ELSE IF( LIWORK.LT.LIWMIN .AND. .NOT.LQUERY ) THEN INFO = -20 END IF END IF * IF( INFO.EQ.0 ) THEN NB = ILAENV( 1, 'ZHETRD', UPLO, N, -1, -1, -1 ) NB = MAX( NB, ILAENV( 1, 'ZUNMTR', UPLO, N, -1, -1, -1 ) ) LWKOPT = MAX( ( NB+1 )*N, LWMIN ) WORK( 1 ) = LWKOPT IWORK( 1 ) = LIWMIN END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSYEVR', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * M = 0 IF( N.EQ.0 ) THEN WORK( 1 ) = 1 RETURN END IF * IF( N.EQ.1 ) THEN WORK( 1 ) = 7 IF( ALLEIG .OR. INDEIG ) THEN M = 1 W( 1 ) = A( 1, 1 ) ELSE IF( VL.LT.A( 1, 1 ) .AND. VU.GE.A( 1, 1 ) ) THEN M = 1 W( 1 ) = A( 1, 1 ) END IF END IF IF( WANTZ ) $ Z( 1, 1 ) = ONE RETURN END IF * * Get machine constants. * SAFMIN = DLAMCH( 'Safe minimum' ) EPS = DLAMCH( 'Precision' ) SMLNUM = SAFMIN / EPS BIGNUM = ONE / SMLNUM RMIN = SQRT( SMLNUM ) RMAX = MIN( SQRT( BIGNUM ), ONE / SQRT( SQRT( SAFMIN ) ) ) * * Scale matrix to allowable range, if necessary. * ISCALE = 0 ABSTLL = ABSTOL VLL = VL VUU = VU ANRM = DLANSY( 'M', UPLO, N, A, LDA, WORK ) IF( ANRM.GT.ZERO .AND. ANRM.LT.RMIN ) THEN ISCALE = 1 SIGMA = RMIN / ANRM ELSE IF( ANRM.GT.RMAX ) THEN ISCALE = 1 SIGMA = RMAX / ANRM END IF IF( ISCALE.EQ.1 ) THEN IF( LOWER ) THEN DO 10 J = 1, N CALL DSCAL( N-J+1, SIGMA, A( J, J ), 1 ) 10 CONTINUE ELSE DO 20 J = 1, N CALL DSCAL( J, SIGMA, A( 1, J ), 1 ) 20 CONTINUE END IF IF( ABSTOL.GT.0 ) $ ABSTLL = ABSTOL*SIGMA IF( VALEIG ) THEN VLL = VL*SIGMA VUU = VU*SIGMA END IF END IF * * Call DSYTRD to reduce symmetric matrix to tridiagonal form. * INDTAU = 1 INDE = INDTAU + N INDD = INDE + N INDEE = INDD + N INDDD = INDEE + N INDIFL = INDDD + N INDWK = INDIFL + N LLWORK = LWORK - INDWK + 1 CALL DSYTRD( UPLO, N, A, LDA, WORK( INDD ), WORK( INDE ), $ WORK( INDTAU ), WORK( INDWK ), LLWORK, IINFO ) * * If all eigenvalues are desired * then call DSTERF or SSTEGR and DORMTR. * IF( ( ALLEIG .OR. ( INDEIG .AND. IL.EQ.1 .AND. IU.EQ.N ) ) .AND. $ IEEEOK.EQ.1 ) THEN IF( .NOT.WANTZ ) THEN CALL DCOPY( N, WORK( INDD ), 1, W, 1 ) CALL DCOPY( N-1, WORK( INDE ), 1, WORK( INDEE ), 1 ) CALL DSTERF( N, W, WORK( INDEE ), INFO ) ELSE CALL DCOPY( N-1, WORK( INDE ), 1, WORK( INDEE ), 1 ) CALL DCOPY( N, WORK( INDD ), 1, WORK( INDDD ), 1 ) * CALL DSTEGR( JOBZ, 'A', N, WORK( INDDD ), WORK( INDEE ), $ VL, VU, IL, IU, ABSTOL, M, W, Z, LDZ, ISUPPZ, $ WORK( INDWK ), LWORK, IWORK, LIWORK, INFO ) * * * * Apply orthogonal matrix used in reduction to tridiagonal * form to eigenvectors returned by DSTEIN. * IF( WANTZ .AND. INFO.EQ.0 ) THEN INDWKN = INDE LLWRKN = LWORK - INDWKN + 1 CALL DORMTR( 'L', UPLO, 'N', N, M, A, LDA, $ WORK( INDTAU ), Z, LDZ, WORK( INDWKN ), $ LLWRKN, IINFO ) END IF END IF * * IF( INFO.EQ.0 ) THEN M = N GO TO 30 END IF INFO = 0 END IF * * Otherwise, call DSTEBZ and, if eigenvectors are desired, SSTEIN. * Also call DSTEBZ and SSTEIN if SSTEGR fails. * IF( WANTZ ) THEN ORDER = 'B' ELSE ORDER = 'E' END IF INDIFL = 1 INDIBL = INDIFL + N INDISP = INDIBL + N INDIWO = INDISP + N CALL DSTEBZ( RANGE, ORDER, N, VLL, VUU, IL, IU, ABSTLL, $ WORK( INDD ), WORK( INDE ), M, NSPLIT, W, $ IWORK( INDIBL ), IWORK( INDISP ), WORK( INDWK ), $ IWORK( INDIWO ), INFO ) * IF( WANTZ ) THEN CALL DSTEIN( N, WORK( INDD ), WORK( INDE ), M, W, $ IWORK( INDIBL ), IWORK( INDISP ), Z, LDZ, $ WORK( INDWK ), IWORK( INDIWO ), IWORK( INDIFL ), $ INFO ) * * Apply orthogonal matrix used in reduction to tridiagonal * form to eigenvectors returned by DSTEIN. * INDWKN = INDE LLWRKN = LWORK - INDWKN + 1 CALL DORMTR( 'L', UPLO, 'N', N, M, A, LDA, WORK( INDTAU ), Z, $ LDZ, WORK( INDWKN ), LLWRKN, IINFO ) END IF * * If matrix was scaled, then rescale eigenvalues appropriately. * 30 CONTINUE IF( ISCALE.EQ.1 ) THEN IF( INFO.EQ.0 ) THEN IMAX = M ELSE IMAX = INFO - 1 END IF CALL DSCAL( IMAX, ONE / SIGMA, W, 1 ) END IF * * If eigenvalues are not in order, then sort them, along with * eigenvectors. * IF( WANTZ ) THEN DO 50 J = 1, M - 1 I = 0 TMP1 = W( J ) DO 40 JJ = J + 1, M IF( W( JJ ).LT.TMP1 ) THEN I = JJ TMP1 = W( JJ ) END IF 40 CONTINUE * IF( I.NE.0 ) THEN ITMP1 = IWORK( INDIBL+I-1 ) W( I ) = W( J ) IWORK( INDIBL+I-1 ) = IWORK( INDIBL+J-1 ) W( J ) = TMP1 IWORK( INDIBL+J-1 ) = ITMP1 CALL DSWAP( N, Z( 1, I ), 1, Z( 1, J ), 1 ) END IF 50 CONTINUE END IF * * Set WORK(1) to optimal workspace size. * WORK( 1 ) = LWKOPT IWORK( 1 ) = LIWMIN * RETURN * * End of DSYEVR * END SUBROUTINE DSYEVX( JOBZ, RANGE, UPLO, N, A, LDA, VL, VU, IL, IU, $ ABSTOL, M, W, Z, LDZ, WORK, LWORK, IWORK, $ IFAIL, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBZ, RANGE, UPLO INTEGER IL, INFO, IU, LDA, LDZ, LWORK, M, N DOUBLE PRECISION ABSTOL, VL, VU * .. * .. Array Arguments .. INTEGER IFAIL( * ), IWORK( * ) DOUBLE PRECISION A( LDA, * ), W( * ), WORK( * ), Z( LDZ, * ) * .. * * Purpose * ======= * * DSYEVX computes selected eigenvalues and, optionally, eigenvectors * of a real symmetric matrix A. Eigenvalues and eigenvectors can be * selected by specifying either a range of values or a range of indices * for the desired eigenvalues. * * Arguments * ========= * * JOBZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only; * = 'V': Compute eigenvalues and eigenvectors. * * RANGE (input) CHARACTER*1 * = 'A': all eigenvalues will be found. * = 'V': all eigenvalues in the half-open interval (VL,VU] * will be found. * = 'I': the IL-th through IU-th eigenvalues will be found. * * UPLO (input) CHARACTER*1 * = 'U': Upper triangle of A is stored; * = 'L': Lower triangle of A is stored. * * N (input) INTEGER * The order of the matrix A. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA, N) * On entry, the symmetric matrix A. If UPLO = 'U', the * leading N-by-N upper triangular part of A contains the * upper triangular part of the matrix A. If UPLO = 'L', * the leading N-by-N lower triangular part of A contains * the lower triangular part of the matrix A. * On exit, the lower triangle (if UPLO='L') or the upper * triangle (if UPLO='U') of A, including the diagonal, is * destroyed. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * VL (input) DOUBLE PRECISION * VU (input) DOUBLE PRECISION * If RANGE='V', the lower and upper bounds of the interval to * be searched for eigenvalues. VL < VU. * Not referenced if RANGE = 'A' or 'I'. * * IL (input) INTEGER * IU (input) INTEGER * If RANGE='I', the indices (in ascending order) of the * smallest and largest eigenvalues to be returned. * 1 <= IL <= IU <= N, if N > 0; IL = 1 and IU = 0 if N = 0. * Not referenced if RANGE = 'A' or 'V'. * * ABSTOL (input) DOUBLE PRECISION * The absolute error tolerance for the eigenvalues. * An approximate eigenvalue is accepted as converged * when it is determined to lie in an interval [a,b] * of width less than or equal to * * ABSTOL + EPS * max( |a|,|b| ) , * * where EPS is the machine precision. If ABSTOL is less than * or equal to zero, then EPS*|T| will be used in its place, * where |T| is the 1-norm of the tridiagonal matrix obtained * by reducing A to tridiagonal form. * * Eigenvalues will be computed most accurately when ABSTOL is * set to twice the underflow threshold 2*DLAMCH('S'), not zero. * If this routine returns with INFO>0, indicating that some * eigenvectors did not converge, try setting ABSTOL to * 2*DLAMCH('S'). * * See "Computing Small Singular Values of Bidiagonal Matrices * with Guaranteed High Relative Accuracy," by Demmel and * Kahan, LAPACK Working Note #3. * * M (output) INTEGER * The total number of eigenvalues found. 0 <= M <= N. * If RANGE = 'A', M = N, and if RANGE = 'I', M = IU-IL+1. * * W (output) DOUBLE PRECISION array, dimension (N) * On normal exit, the first M elements contain the selected * eigenvalues in ascending order. * * Z (output) DOUBLE PRECISION array, dimension (LDZ, max(1,M)) * If JOBZ = 'V', then if INFO = 0, the first M columns of Z * contain the orthonormal eigenvectors of the matrix A * corresponding to the selected eigenvalues, with the i-th * column of Z holding the eigenvector associated with W(i). * If an eigenvector fails to converge, then that column of Z * contains the latest approximation to the eigenvector, and the * index of the eigenvector is returned in IFAIL. * If JOBZ = 'N', then Z is not referenced. * Note: the user must ensure that at least max(1,M) columns are * supplied in the array Z; if RANGE = 'V', the exact value of M * is not known in advance and an upper bound must be used. * * LDZ (input) INTEGER * The leading dimension of the array Z. LDZ >= 1, and if * JOBZ = 'V', LDZ >= max(1,N). * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The length of the array WORK. LWORK >= max(1,8*N). * For optimal efficiency, LWORK >= (NB+3)*N, * where NB is the max of the blocksize for DSYTRD and DORMTR * returned by ILAENV. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * IWORK (workspace) INTEGER array, dimension (5*N) * * IFAIL (output) INTEGER array, dimension (N) * If JOBZ = 'V', then if INFO = 0, the first M elements of * IFAIL are zero. If INFO > 0, then IFAIL contains the * indices of the eigenvectors that failed to converge. * If JOBZ = 'N', then IFAIL is not referenced. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = i, then i eigenvectors failed to converge. * Their indices are stored in array IFAIL. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL ALLEIG, INDEIG, LOWER, LQUERY, VALEIG, WANTZ CHARACTER ORDER INTEGER I, IINFO, IMAX, INDD, INDE, INDEE, INDIBL, $ INDISP, INDIWO, INDTAU, INDWKN, INDWRK, ISCALE, $ ITMP1, J, JJ, LLWORK, LLWRKN, LOPT, LWKOPT, NB, $ NSPLIT DOUBLE PRECISION ABSTLL, ANRM, BIGNUM, EPS, RMAX, RMIN, SAFMIN, $ SIGMA, SMLNUM, TMP1, VLL, VUU * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANSY EXTERNAL LSAME, ILAENV, DLAMCH, DLANSY * .. * .. External Subroutines .. EXTERNAL DCOPY, DLACPY, DORGTR, DORMTR, DSCAL, DSTEBZ, $ DSTEIN, DSTEQR, DSTERF, DSWAP, DSYTRD, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN, SQRT * .. * .. Executable Statements .. * * Test the input parameters. * LOWER = LSAME( UPLO, 'L' ) WANTZ = LSAME( JOBZ, 'V' ) ALLEIG = LSAME( RANGE, 'A' ) VALEIG = LSAME( RANGE, 'V' ) INDEIG = LSAME( RANGE, 'I' ) LQUERY = ( LWORK.EQ.-1 ) * INFO = 0 IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN INFO = -1 ELSE IF( .NOT.( ALLEIG .OR. VALEIG .OR. INDEIG ) ) THEN INFO = -2 ELSE IF( .NOT.( LOWER .OR. LSAME( UPLO, 'U' ) ) ) THEN INFO = -3 ELSE IF( N.LT.0 ) THEN INFO = -4 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -6 ELSE IF( VALEIG ) THEN IF( N.GT.0 .AND. VU.LE.VL ) $ INFO = -8 ELSE IF( INDEIG ) THEN IF( IL.LT.1 .OR. IL.GT.MAX( 1, N ) ) THEN INFO = -9 ELSE IF( IU.LT.MIN( N, IL ) .OR. IU.GT.N ) THEN INFO = -10 END IF END IF END IF IF( INFO.EQ.0 ) THEN IF( LDZ.LT.1 .OR. ( WANTZ .AND. LDZ.LT.N ) ) THEN INFO = -15 ELSE IF( LWORK.LT.MAX( 1, 8*N ) .AND. .NOT.LQUERY ) THEN INFO = -17 END IF END IF * IF( INFO.EQ.0 ) THEN NB = ILAENV( 1, 'DSYTRD', UPLO, N, -1, -1, -1 ) NB = MAX( NB, ILAENV( 1, 'DORMTR', UPLO, N, -1, -1, -1 ) ) LWKOPT = ( NB+3 )*N WORK( 1 ) = LWKOPT END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSYEVX', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * M = 0 IF( N.EQ.0 ) THEN WORK( 1 ) = 1 RETURN END IF * IF( N.EQ.1 ) THEN WORK( 1 ) = 7 IF( ALLEIG .OR. INDEIG ) THEN M = 1 W( 1 ) = A( 1, 1 ) ELSE IF( VL.LT.A( 1, 1 ) .AND. VU.GE.A( 1, 1 ) ) THEN M = 1 W( 1 ) = A( 1, 1 ) END IF END IF IF( WANTZ ) $ Z( 1, 1 ) = ONE RETURN END IF * * Get machine constants. * SAFMIN = DLAMCH( 'Safe minimum' ) EPS = DLAMCH( 'Precision' ) SMLNUM = SAFMIN / EPS BIGNUM = ONE / SMLNUM RMIN = SQRT( SMLNUM ) RMAX = MIN( SQRT( BIGNUM ), ONE / SQRT( SQRT( SAFMIN ) ) ) * * Scale matrix to allowable range, if necessary. * ISCALE = 0 ABSTLL = ABSTOL VLL = VL VUU = VU ANRM = DLANSY( 'M', UPLO, N, A, LDA, WORK ) IF( ANRM.GT.ZERO .AND. ANRM.LT.RMIN ) THEN ISCALE = 1 SIGMA = RMIN / ANRM ELSE IF( ANRM.GT.RMAX ) THEN ISCALE = 1 SIGMA = RMAX / ANRM END IF IF( ISCALE.EQ.1 ) THEN IF( LOWER ) THEN DO 10 J = 1, N CALL DSCAL( N-J+1, SIGMA, A( J, J ), 1 ) 10 CONTINUE ELSE DO 20 J = 1, N CALL DSCAL( J, SIGMA, A( 1, J ), 1 ) 20 CONTINUE END IF IF( ABSTOL.GT.0 ) $ ABSTLL = ABSTOL*SIGMA IF( VALEIG ) THEN VLL = VL*SIGMA VUU = VU*SIGMA END IF END IF * * Call DSYTRD to reduce symmetric matrix to tridiagonal form. * INDTAU = 1 INDE = INDTAU + N INDD = INDE + N INDWRK = INDD + N LLWORK = LWORK - INDWRK + 1 CALL DSYTRD( UPLO, N, A, LDA, WORK( INDD ), WORK( INDE ), $ WORK( INDTAU ), WORK( INDWRK ), LLWORK, IINFO ) LOPT = 3*N + WORK( INDWRK ) * * If all eigenvalues are desired and ABSTOL is less than or equal to * zero, then call DSTERF or DORGTR and SSTEQR. If this fails for * some eigenvalue, then try DSTEBZ. * IF( ( ALLEIG .OR. ( INDEIG .AND. IL.EQ.1 .AND. IU.EQ.N ) ) .AND. $ ( ABSTOL.LE.ZERO ) ) THEN CALL DCOPY( N, WORK( INDD ), 1, W, 1 ) INDEE = INDWRK + 2*N IF( .NOT.WANTZ ) THEN CALL DCOPY( N-1, WORK( INDE ), 1, WORK( INDEE ), 1 ) CALL DSTERF( N, W, WORK( INDEE ), INFO ) ELSE CALL DLACPY( 'A', N, N, A, LDA, Z, LDZ ) CALL DORGTR( UPLO, N, Z, LDZ, WORK( INDTAU ), $ WORK( INDWRK ), LLWORK, IINFO ) CALL DCOPY( N-1, WORK( INDE ), 1, WORK( INDEE ), 1 ) CALL DSTEQR( JOBZ, N, W, WORK( INDEE ), Z, LDZ, $ WORK( INDWRK ), INFO ) IF( INFO.EQ.0 ) THEN DO 30 I = 1, N IFAIL( I ) = 0 30 CONTINUE END IF END IF IF( INFO.EQ.0 ) THEN M = N GO TO 40 END IF INFO = 0 END IF * * Otherwise, call DSTEBZ and, if eigenvectors are desired, SSTEIN. * IF( WANTZ ) THEN ORDER = 'B' ELSE ORDER = 'E' END IF INDIBL = 1 INDISP = INDIBL + N INDIWO = INDISP + N CALL DSTEBZ( RANGE, ORDER, N, VLL, VUU, IL, IU, ABSTLL, $ WORK( INDD ), WORK( INDE ), M, NSPLIT, W, $ IWORK( INDIBL ), IWORK( INDISP ), WORK( INDWRK ), $ IWORK( INDIWO ), INFO ) * IF( WANTZ ) THEN CALL DSTEIN( N, WORK( INDD ), WORK( INDE ), M, W, $ IWORK( INDIBL ), IWORK( INDISP ), Z, LDZ, $ WORK( INDWRK ), IWORK( INDIWO ), IFAIL, INFO ) * * Apply orthogonal matrix used in reduction to tridiagonal * form to eigenvectors returned by DSTEIN. * INDWKN = INDE LLWRKN = LWORK - INDWKN + 1 CALL DORMTR( 'L', UPLO, 'N', N, M, A, LDA, WORK( INDTAU ), Z, $ LDZ, WORK( INDWKN ), LLWRKN, IINFO ) END IF * * If matrix was scaled, then rescale eigenvalues appropriately. * 40 CONTINUE IF( ISCALE.EQ.1 ) THEN IF( INFO.EQ.0 ) THEN IMAX = M ELSE IMAX = INFO - 1 END IF CALL DSCAL( IMAX, ONE / SIGMA, W, 1 ) END IF * * If eigenvalues are not in order, then sort them, along with * eigenvectors. * IF( WANTZ ) THEN DO 60 J = 1, M - 1 I = 0 TMP1 = W( J ) DO 50 JJ = J + 1, M IF( W( JJ ).LT.TMP1 ) THEN I = JJ TMP1 = W( JJ ) END IF 50 CONTINUE * IF( I.NE.0 ) THEN ITMP1 = IWORK( INDIBL+I-1 ) W( I ) = W( J ) IWORK( INDIBL+I-1 ) = IWORK( INDIBL+J-1 ) W( J ) = TMP1 IWORK( INDIBL+J-1 ) = ITMP1 CALL DSWAP( N, Z( 1, I ), 1, Z( 1, J ), 1 ) IF( INFO.NE.0 ) THEN ITMP1 = IFAIL( I ) IFAIL( I ) = IFAIL( J ) IFAIL( J ) = ITMP1 END IF END IF 60 CONTINUE END IF * * Set WORK(1) to optimal workspace size. * WORK( 1 ) = LWKOPT * RETURN * * End of DSYEVX * END SUBROUTINE DSYGV( ITYPE, JOBZ, UPLO, N, A, LDA, B, LDB, W, WORK, $ LWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBZ, UPLO INTEGER INFO, ITYPE, LDA, LDB, LWORK, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), B( LDB, * ), W( * ), WORK( * ) * .. * * Purpose * ======= * * DSYGV computes all the eigenvalues, and optionally, the eigenvectors * of a real generalized symmetric-definite eigenproblem, of the form * A*x=(lambda)*B*x, A*Bx=(lambda)*x, or B*A*x=(lambda)*x. * Here A and B are assumed to be symmetric and B is also * positive definite. * * Arguments * ========= * * ITYPE (input) INTEGER * Specifies the problem type to be solved: * = 1: A*x = (lambda)*B*x * = 2: A*B*x = (lambda)*x * = 3: B*A*x = (lambda)*x * * JOBZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only; * = 'V': Compute eigenvalues and eigenvectors. * * UPLO (input) CHARACTER*1 * = 'U': Upper triangles of A and B are stored; * = 'L': Lower triangles of A and B are stored. * * N (input) INTEGER * The order of the matrices A and B. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA, N) * On entry, the symmetric matrix A. If UPLO = 'U', the * leading N-by-N upper triangular part of A contains the * upper triangular part of the matrix A. If UPLO = 'L', * the leading N-by-N lower triangular part of A contains * the lower triangular part of the matrix A. * * On exit, if JOBZ = 'V', then if INFO = 0, A contains the * matrix Z of eigenvectors. The eigenvectors are normalized * as follows: * if ITYPE = 1 or 2, Z**T*B*Z = I; * if ITYPE = 3, Z**T*inv(B)*Z = I. * If JOBZ = 'N', then on exit the upper triangle (if UPLO='U') * or the lower triangle (if UPLO='L') of A, including the * diagonal, is destroyed. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * B (input/output) DOUBLE PRECISION array, dimension (LDB, N) * On entry, the symmetric positive definite matrix B. * If UPLO = 'U', the leading N-by-N upper triangular part of B * contains the upper triangular part of the matrix B. * If UPLO = 'L', the leading N-by-N lower triangular part of B * contains the lower triangular part of the matrix B. * * On exit, if INFO <= N, the part of B containing the matrix is * overwritten by the triangular factor U or L from the Cholesky * factorization B = U**T*U or B = L*L**T. * * LDB (input) INTEGER * The leading dimension of the array B. LDB >= max(1,N). * * W (output) DOUBLE PRECISION array, dimension (N) * If INFO = 0, the eigenvalues in ascending order. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The length of the array WORK. LWORK >= max(1,3*N-1). * For optimal efficiency, LWORK >= (NB+2)*N, * where NB is the blocksize for DSYTRD returned by ILAENV. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: DPOTRF or DSYEV returned an error code: * <= N: if INFO = i, DSYEV failed to converge; * i off-diagonal elements of an intermediate * tridiagonal form did not converge to zero; * > N: if INFO = N + i, for 1 <= i <= N, then the leading * minor of order i of B is not positive definite. * The factorization of B could not be completed and * no eigenvalues or eigenvectors were computed. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE PARAMETER ( ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL LQUERY, UPPER, WANTZ CHARACTER TRANS INTEGER LWKOPT, NB, NEIG * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV EXTERNAL LSAME, ILAENV * .. * .. External Subroutines .. EXTERNAL DPOTRF, DSYEV, DSYGST, DTRMM, DTRSM, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX * .. * .. Executable Statements .. * * Test the input parameters. * WANTZ = LSAME( JOBZ, 'V' ) UPPER = LSAME( UPLO, 'U' ) LQUERY = ( LWORK.EQ.-1 ) * INFO = 0 IF( ITYPE.LT.1 .OR. ITYPE.GT.3 ) THEN INFO = -1 ELSE IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN INFO = -2 ELSE IF( .NOT.( UPPER .OR. LSAME( UPLO, 'L' ) ) ) THEN INFO = -3 ELSE IF( N.LT.0 ) THEN INFO = -4 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -6 ELSE IF( LDB.LT.MAX( 1, N ) ) THEN INFO = -8 ELSE IF( LWORK.LT.MAX( 1, 3*N-1 ) .AND. .NOT.LQUERY ) THEN INFO = -11 END IF * IF( INFO.EQ.0 ) THEN NB = ILAENV( 1, 'DSYTRD', UPLO, N, -1, -1, -1 ) LWKOPT = ( NB+2 )*N WORK( 1 ) = LWKOPT END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSYGV ', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * * Form a Cholesky factorization of B. * CALL DPOTRF( UPLO, N, B, LDB, INFO ) IF( INFO.NE.0 ) THEN INFO = N + INFO RETURN END IF * * Transform problem to standard eigenvalue problem and solve. * CALL DSYGST( ITYPE, UPLO, N, A, LDA, B, LDB, INFO ) CALL DSYEV( JOBZ, UPLO, N, A, LDA, W, WORK, LWORK, INFO ) * IF( WANTZ ) THEN * * Backtransform eigenvectors to the original problem. * NEIG = N IF( INFO.GT.0 ) $ NEIG = INFO - 1 IF( ITYPE.EQ.1 .OR. ITYPE.EQ.2 ) THEN * * For A*x=(lambda)*B*x and A*B*x=(lambda)*x; * backtransform eigenvectors: x = inv(L)'*y or inv(U)*y * IF( UPPER ) THEN TRANS = 'N' ELSE TRANS = 'T' END IF * CALL DTRSM( 'Left', UPLO, TRANS, 'Non-unit', N, NEIG, ONE, $ B, LDB, A, LDA ) * ELSE IF( ITYPE.EQ.3 ) THEN * * For B*A*x=(lambda)*x; * backtransform eigenvectors: x = L*y or U'*y * IF( UPPER ) THEN TRANS = 'T' ELSE TRANS = 'N' END IF * CALL DTRMM( 'Left', UPLO, TRANS, 'Non-unit', N, NEIG, ONE, $ B, LDB, A, LDA ) END IF END IF * WORK( 1 ) = LWKOPT RETURN * * End of DSYGV * END SUBROUTINE DSYGVD( ITYPE, JOBZ, UPLO, N, A, LDA, B, LDB, W, WORK, $ LWORK, IWORK, LIWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBZ, UPLO INTEGER INFO, ITYPE, LDA, LDB, LIWORK, LWORK, N * .. * .. Array Arguments .. INTEGER IWORK( * ) DOUBLE PRECISION A( LDA, * ), B( LDB, * ), W( * ), WORK( * ) * .. * * Purpose * ======= * * DSYGVD computes all the eigenvalues, and optionally, the eigenvectors * of a real generalized symmetric-definite eigenproblem, of the form * A*x=(lambda)*B*x, A*Bx=(lambda)*x, or B*A*x=(lambda)*x. Here A and * B are assumed to be symmetric and B is also positive definite. * If eigenvectors are desired, it uses a divide and conquer algorithm. * * The divide and conquer algorithm makes very mild assumptions about * floating point arithmetic. It will work on machines with a guard * digit in add/subtract, or on those binary machines without guard * digits which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or * Cray-2. It could conceivably fail on hexadecimal or decimal machines * without guard digits, but we know of none. * * Arguments * ========= * * ITYPE (input) INTEGER * Specifies the problem type to be solved: * = 1: A*x = (lambda)*B*x * = 2: A*B*x = (lambda)*x * = 3: B*A*x = (lambda)*x * * JOBZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only; * = 'V': Compute eigenvalues and eigenvectors. * * UPLO (input) CHARACTER*1 * = 'U': Upper triangles of A and B are stored; * = 'L': Lower triangles of A and B are stored. * * N (input) INTEGER * The order of the matrices A and B. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA, N) * On entry, the symmetric matrix A. If UPLO = 'U', the * leading N-by-N upper triangular part of A contains the * upper triangular part of the matrix A. If UPLO = 'L', * the leading N-by-N lower triangular part of A contains * the lower triangular part of the matrix A. * * On exit, if JOBZ = 'V', then if INFO = 0, A contains the * matrix Z of eigenvectors. The eigenvectors are normalized * as follows: * if ITYPE = 1 or 2, Z**T*B*Z = I; * if ITYPE = 3, Z**T*inv(B)*Z = I. * If JOBZ = 'N', then on exit the upper triangle (if UPLO='U') * or the lower triangle (if UPLO='L') of A, including the * diagonal, is destroyed. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * B (input/output) DOUBLE PRECISION array, dimension (LDB, N) * On entry, the symmetric matrix B. If UPLO = 'U', the * leading N-by-N upper triangular part of B contains the * upper triangular part of the matrix B. If UPLO = 'L', * the leading N-by-N lower triangular part of B contains * the lower triangular part of the matrix B. * * On exit, if INFO <= N, the part of B containing the matrix is * overwritten by the triangular factor U or L from the Cholesky * factorization B = U**T*U or B = L*L**T. * * LDB (input) INTEGER * The leading dimension of the array B. LDB >= max(1,N). * * W (output) DOUBLE PRECISION array, dimension (N) * If INFO = 0, the eigenvalues in ascending order. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. * If N <= 1, LWORK >= 1. * If JOBZ = 'N' and N > 1, LWORK >= 2*N+1. * If JOBZ = 'V' and N > 1, LWORK >= 1 + 6*N + 2*N**2. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * IWORK (workspace/output) INTEGER array, dimension (LIWORK) * On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK. * * LIWORK (input) INTEGER * The dimension of the array IWORK. * If N <= 1, LIWORK >= 1. * If JOBZ = 'N' and N > 1, LIWORK >= 1. * If JOBZ = 'V' and N > 1, LIWORK >= 3 + 5*N. * * If LIWORK = -1, then a workspace query is assumed; the * routine only calculates the optimal size of the IWORK array, * returns this value as the first entry of the IWORK array, and * no error message related to LIWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: DPOTRF or DSYEVD returned an error code: * <= N: if INFO = i, DSYEVD failed to converge; * i off-diagonal elements of an intermediate * tridiagonal form did not converge to zero; * > N: if INFO = N + i, for 1 <= i <= N, then the leading * minor of order i of B is not positive definite. * The factorization of B could not be completed and * no eigenvalues or eigenvectors were computed. * * Further Details * =============== * * Based on contributions by * Mark Fahey, Department of Mathematics, Univ. of Kentucky, USA * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE PARAMETER ( ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL LQUERY, UPPER, WANTZ CHARACTER TRANS INTEGER LIOPT, LIWMIN, LOPT, LWMIN, NEIG * .. * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. External Subroutines .. EXTERNAL DPOTRF, DSYEVD, DSYGST, DTRMM, DTRSM, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC DBLE, MAX * .. * .. Executable Statements .. * * Test the input parameters. * WANTZ = LSAME( JOBZ, 'V' ) UPPER = LSAME( UPLO, 'U' ) LQUERY = ( LWORK.EQ.-1 .OR. LIWORK.EQ.-1 ) * INFO = 0 IF( N.LE.1 ) THEN LIWMIN = 1 LWMIN = 1 LOPT = LWMIN LIOPT = LIWMIN ELSE IF( WANTZ ) THEN LIWMIN = 3 + 5*N LWMIN = 1 + 6*N + 2*N**2 ELSE LIWMIN = 1 LWMIN = 2*N + 1 END IF LOPT = LWMIN LIOPT = LIWMIN END IF IF( ITYPE.LT.0 .OR. ITYPE.GT.3 ) THEN INFO = -1 ELSE IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN INFO = -2 ELSE IF( .NOT.( UPPER .OR. LSAME( UPLO, 'L' ) ) ) THEN INFO = -3 ELSE IF( N.LT.0 ) THEN INFO = -4 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -6 ELSE IF( LDB.LT.MAX( 1, N ) ) THEN INFO = -8 ELSE IF( LWORK.LT.LWMIN .AND. .NOT.LQUERY ) THEN INFO = -11 ELSE IF( LIWORK.LT.LIWMIN .AND. .NOT.LQUERY ) THEN INFO = -13 END IF * IF( INFO.EQ.0 ) THEN WORK( 1 ) = LOPT IWORK( 1 ) = LIOPT END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSYGVD', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * * Form a Cholesky factorization of B. * CALL DPOTRF( UPLO, N, B, LDB, INFO ) IF( INFO.NE.0 ) THEN INFO = N + INFO RETURN END IF * * Transform problem to standard eigenvalue problem and solve. * CALL DSYGST( ITYPE, UPLO, N, A, LDA, B, LDB, INFO ) CALL DSYEVD( JOBZ, UPLO, N, A, LDA, W, WORK, LWORK, IWORK, LIWORK, $ INFO ) LOPT = MAX( DBLE( LOPT ), DBLE( WORK( 1 ) ) ) LIOPT = MAX( DBLE( LIOPT ), DBLE( IWORK( 1 ) ) ) * IF( WANTZ ) THEN * * Backtransform eigenvectors to the original problem. * NEIG = N IF( INFO.GT.0 ) $ NEIG = INFO - 1 IF( ITYPE.EQ.1 .OR. ITYPE.EQ.2 ) THEN * * For A*x=(lambda)*B*x and A*B*x=(lambda)*x; * backtransform eigenvectors: x = inv(L)'*y or inv(U)*y * IF( UPPER ) THEN TRANS = 'N' ELSE TRANS = 'T' END IF * CALL DTRSM( 'Left', UPLO, TRANS, 'Non-unit', N, NEIG, ONE, $ B, LDB, A, LDA ) * ELSE IF( ITYPE.EQ.3 ) THEN * * For B*A*x=(lambda)*x; * backtransform eigenvectors: x = L*y or U'*y * IF( UPPER ) THEN TRANS = 'T' ELSE TRANS = 'N' END IF * CALL DTRMM( 'Left', UPLO, TRANS, 'Non-unit', N, NEIG, ONE, $ B, LDB, A, LDA ) END IF END IF * WORK( 1 ) = LOPT IWORK( 1 ) = LIOPT * RETURN * * End of DSYGVD * END SUBROUTINE DSYGVX( ITYPE, JOBZ, RANGE, UPLO, N, A, LDA, B, LDB, $ VL, VU, IL, IU, ABSTOL, M, W, Z, LDZ, WORK, $ LWORK, IWORK, IFAIL, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBZ, RANGE, UPLO INTEGER IL, INFO, ITYPE, IU, LDA, LDB, LDZ, LWORK, M, N DOUBLE PRECISION ABSTOL, VL, VU * .. * .. Array Arguments .. INTEGER IFAIL( * ), IWORK( * ) DOUBLE PRECISION A( LDA, * ), B( LDB, * ), W( * ), WORK( * ), $ Z( LDZ, * ) * .. * * Purpose * ======= * * DSYGVX computes selected eigenvalues, and optionally, eigenvectors * of a real generalized symmetric-definite eigenproblem, of the form * A*x=(lambda)*B*x, A*Bx=(lambda)*x, or B*A*x=(lambda)*x. Here A * and B are assumed to be symmetric and B is also positive definite. * Eigenvalues and eigenvectors can be selected by specifying either a * range of values or a range of indices for the desired eigenvalues. * * Arguments * ========= * * ITYPE (input) INTEGER * Specifies the problem type to be solved: * = 1: A*x = (lambda)*B*x * = 2: A*B*x = (lambda)*x * = 3: B*A*x = (lambda)*x * * JOBZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only; * = 'V': Compute eigenvalues and eigenvectors. * * RANGE (input) CHARACTER*1 * = 'A': all eigenvalues will be found. * = 'V': all eigenvalues in the half-open interval (VL,VU] * will be found. * = 'I': the IL-th through IU-th eigenvalues will be found. * * UPLO (input) CHARACTER*1 * = 'U': Upper triangle of A and B are stored; * = 'L': Lower triangle of A and B are stored. * * N (input) INTEGER * The order of the matrix pencil (A,B). N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA, N) * On entry, the symmetric matrix A. If UPLO = 'U', the * leading N-by-N upper triangular part of A contains the * upper triangular part of the matrix A. If UPLO = 'L', * the leading N-by-N lower triangular part of A contains * the lower triangular part of the matrix A. * * On exit, the lower triangle (if UPLO='L') or the upper * triangle (if UPLO='U') of A, including the diagonal, is * destroyed. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * B (input/output) DOUBLE PRECISION array, dimension (LDA, N) * On entry, the symmetric matrix B. If UPLO = 'U', the * leading N-by-N upper triangular part of B contains the * upper triangular part of the matrix B. If UPLO = 'L', * the leading N-by-N lower triangular part of B contains * the lower triangular part of the matrix B. * * On exit, if INFO <= N, the part of B containing the matrix is * overwritten by the triangular factor U or L from the Cholesky * factorization B = U**T*U or B = L*L**T. * * LDB (input) INTEGER * The leading dimension of the array B. LDB >= max(1,N). * * VL (input) DOUBLE PRECISION * VU (input) DOUBLE PRECISION * If RANGE='V', the lower and upper bounds of the interval to * be searched for eigenvalues. VL < VU. * Not referenced if RANGE = 'A' or 'I'. * * IL (input) INTEGER * IU (input) INTEGER * If RANGE='I', the indices (in ascending order) of the * smallest and largest eigenvalues to be returned. * 1 <= IL <= IU <= N, if N > 0; IL = 1 and IU = 0 if N = 0. * Not referenced if RANGE = 'A' or 'V'. * * ABSTOL (input) DOUBLE PRECISION * The absolute error tolerance for the eigenvalues. * An approximate eigenvalue is accepted as converged * when it is determined to lie in an interval [a,b] * of width less than or equal to * * ABSTOL + EPS * max( |a|,|b| ) , * * where EPS is the machine precision. If ABSTOL is less than * or equal to zero, then EPS*|T| will be used in its place, * where |T| is the 1-norm of the tridiagonal matrix obtained * by reducing A to tridiagonal form. * * Eigenvalues will be computed most accurately when ABSTOL is * set to twice the underflow threshold 2*DLAMCH('S'), not zero. * If this routine returns with INFO>0, indicating that some * eigenvectors did not converge, try setting ABSTOL to * 2*DLAMCH('S'). * * M (output) INTEGER * The total number of eigenvalues found. 0 <= M <= N. * If RANGE = 'A', M = N, and if RANGE = 'I', M = IU-IL+1. * * W (output) DOUBLE PRECISION array, dimension (N) * On normal exit, the first M elements contain the selected * eigenvalues in ascending order. * * Z (output) DOUBLE PRECISION array, dimension (LDZ, max(1,M)) * If JOBZ = 'N', then Z is not referenced. * If JOBZ = 'V', then if INFO = 0, the first M columns of Z * contain the orthonormal eigenvectors of the matrix A * corresponding to the selected eigenvalues, with the i-th * column of Z holding the eigenvector associated with W(i). * The eigenvectors are normalized as follows: * if ITYPE = 1 or 2, Z**T*B*Z = I; * if ITYPE = 3, Z**T*inv(B)*Z = I. * * If an eigenvector fails to converge, then that column of Z * contains the latest approximation to the eigenvector, and the * index of the eigenvector is returned in IFAIL. * Note: the user must ensure that at least max(1,M) columns are * supplied in the array Z; if RANGE = 'V', the exact value of M * is not known in advance and an upper bound must be used. * * LDZ (input) INTEGER * The leading dimension of the array Z. LDZ >= 1, and if * JOBZ = 'V', LDZ >= max(1,N). * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The length of the array WORK. LWORK >= max(1,8*N). * For optimal efficiency, LWORK >= (NB+3)*N, * where NB is the blocksize for DSYTRD returned by ILAENV. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * IWORK (workspace) INTEGER array, dimension (5*N) * * IFAIL (output) INTEGER array, dimension (N) * If JOBZ = 'V', then if INFO = 0, the first M elements of * IFAIL are zero. If INFO > 0, then IFAIL contains the * indices of the eigenvectors that failed to converge. * If JOBZ = 'N', then IFAIL is not referenced. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: DPOTRF or DSYEVX returned an error code: * <= N: if INFO = i, DSYEVX failed to converge; * i eigenvectors failed to converge. Their indices * are stored in array IFAIL. * > N: if INFO = N + i, for 1 <= i <= N, then the leading * minor of order i of B is not positive definite. * The factorization of B could not be completed and * no eigenvalues or eigenvectors were computed. * * Further Details * =============== * * Based on contributions by * Mark Fahey, Department of Mathematics, Univ. of Kentucky, USA * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE PARAMETER ( ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL ALLEIG, INDEIG, LQUERY, UPPER, VALEIG, WANTZ CHARACTER TRANS INTEGER LOPT, LWKOPT, NB * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV EXTERNAL LSAME, ILAENV * .. * .. External Subroutines .. EXTERNAL DPOTRF, DSYEVX, DSYGST, DTRMM, DTRSM, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN * .. * .. Executable Statements .. * * Test the input parameters. * UPPER = LSAME( UPLO, 'U' ) WANTZ = LSAME( JOBZ, 'V' ) ALLEIG = LSAME( RANGE, 'A' ) VALEIG = LSAME( RANGE, 'V' ) INDEIG = LSAME( RANGE, 'I' ) LQUERY = ( LWORK.EQ.-1 ) * INFO = 0 IF( ITYPE.LT.0 .OR. ITYPE.GT.3 ) THEN INFO = -1 ELSE IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN INFO = -2 ELSE IF( .NOT.( ALLEIG .OR. VALEIG .OR. INDEIG ) ) THEN INFO = -3 ELSE IF( .NOT.( UPPER .OR. LSAME( UPLO, 'L' ) ) ) THEN INFO = -4 ELSE IF( N.LT.0 ) THEN INFO = -5 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -7 ELSE IF( LDB.LT.MAX( 1, N ) ) THEN INFO = -9 ELSE IF( VALEIG .AND. N.GT.0 ) THEN IF( VU.LE.VL ) $ INFO = -11 ELSE IF( INDEIG .AND. IL.LT.1 ) THEN INFO = -12 ELSE IF( INDEIG .AND. ( IU.LT.MIN( N, IL ) .OR. IU.GT.N ) ) THEN INFO = -13 ELSE IF( LDZ.LT.1 .OR. ( WANTZ .AND. LDZ.LT.N ) ) THEN INFO = -18 ELSE IF( LWORK.LT.MAX( 1, 8*N ) .AND. .NOT.LQUERY ) THEN INFO = -20 END IF * IF( INFO.EQ.0 ) THEN NB = ILAENV( 1, 'DSYTRD', UPLO, N, -1, -1, -1 ) LWKOPT = ( NB+3 )*N WORK( 1 ) = LWKOPT END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSYGVX', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * M = 0 IF( N.EQ.0 ) THEN WORK( 1 ) = 1 RETURN END IF * * Form a Cholesky factorization of B. * CALL DPOTRF( UPLO, N, B, LDB, INFO ) IF( INFO.NE.0 ) THEN INFO = N + INFO RETURN END IF * * Transform problem to standard eigenvalue problem and solve. * CALL DSYGST( ITYPE, UPLO, N, A, LDA, B, LDB, INFO ) CALL DSYEVX( JOBZ, RANGE, UPLO, N, A, LDA, VL, VU, IL, IU, ABSTOL, $ M, W, Z, LDZ, WORK, LWORK, IWORK, IFAIL, INFO ) LOPT = WORK( 1 ) * IF( WANTZ ) THEN * * Backtransform eigenvectors to the original problem. * IF( INFO.GT.0 ) $ M = INFO - 1 IF( ITYPE.EQ.1 .OR. ITYPE.EQ.2 ) THEN * * For A*x=(lambda)*B*x and A*B*x=(lambda)*x; * backtransform eigenvectors: x = inv(L)'*y or inv(U)*y * IF( UPPER ) THEN TRANS = 'N' ELSE TRANS = 'T' END IF * CALL DTRSM( 'Left', UPLO, TRANS, 'Non-unit', N, M, ONE, B, $ LDB, Z, LDZ ) * ELSE IF( ITYPE.EQ.3 ) THEN * * For B*A*x=(lambda)*x; * backtransform eigenvectors: x = L*y or U'*y * IF( UPPER ) THEN TRANS = 'T' ELSE TRANS = 'N' END IF * CALL DTRMM( 'Left', UPLO, TRANS, 'Non-unit', N, M, ONE, B, $ LDB, Z, LDZ ) END IF END IF * * Set WORK(1) to optimal workspace size. * WORK( 1 ) = LWKOPT * RETURN * * End of DSYGVX * END SUBROUTINE DSYSV( UPLO, N, NRHS, A, LDA, IPIV, B, LDB, WORK, $ LWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER UPLO INTEGER INFO, LDA, LDB, LWORK, N, NRHS * .. * .. Array Arguments .. INTEGER IPIV( * ) DOUBLE PRECISION A( LDA, * ), B( LDB, * ), WORK( * ) * .. * * Purpose * ======= * * DSYSV computes the solution to a real system of linear equations * A * X = B, * where A is an N-by-N symmetric matrix and X and B are N-by-NRHS * matrices. * * The diagonal pivoting method is used to factor A as * A = U * D * U**T, if UPLO = 'U', or * A = L * D * L**T, if UPLO = 'L', * where U (or L) is a product of permutation and unit upper (lower) * triangular matrices, and D is symmetric and block diagonal with * 1-by-1 and 2-by-2 diagonal blocks. The factored form of A is then * used to solve the system of equations A * X = B. * * Arguments * ========= * * UPLO (input) CHARACTER*1 * = 'U': Upper triangle of A is stored; * = 'L': Lower triangle of A is stored. * * N (input) INTEGER * The number of linear equations, i.e., the order of the * matrix A. N >= 0. * * NRHS (input) INTEGER * The number of right hand sides, i.e., the number of columns * of the matrix B. NRHS >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the symmetric matrix A. If UPLO = 'U', the leading * N-by-N upper triangular part of A contains the upper * triangular part of the matrix A, and the strictly lower * triangular part of A is not referenced. If UPLO = 'L', the * leading N-by-N lower triangular part of A contains the lower * triangular part of the matrix A, and the strictly upper * triangular part of A is not referenced. * * On exit, if INFO = 0, the block diagonal matrix D and the * multipliers used to obtain the factor U or L from the * factorization A = U*D*U**T or A = L*D*L**T as computed by * DSYTRF. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * IPIV (output) INTEGER array, dimension (N) * Details of the interchanges and the block structure of D, as * determined by DSYTRF. If IPIV(k) > 0, then rows and columns * k and IPIV(k) were interchanged, and D(k,k) is a 1-by-1 * diagonal block. If UPLO = 'U' and IPIV(k) = IPIV(k-1) < 0, * then rows and columns k-1 and -IPIV(k) were interchanged and * D(k-1:k,k-1:k) is a 2-by-2 diagonal block. If UPLO = 'L' and * IPIV(k) = IPIV(k+1) < 0, then rows and columns k+1 and * -IPIV(k) were interchanged and D(k:k+1,k:k+1) is a 2-by-2 * diagonal block. * * B (input/output) DOUBLE PRECISION array, dimension (LDB,NRHS) * On entry, the N-by-NRHS right hand side matrix B. * On exit, if INFO = 0, the N-by-NRHS solution matrix X. * * LDB (input) INTEGER * The leading dimension of the array B. LDB >= max(1,N). * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The length of WORK. LWORK >= 1, and for best performance * LWORK >= N*NB, where NB is the optimal blocksize for * DSYTRF. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = i, D(i,i) is exactly zero. The factorization * has been completed, but the block diagonal matrix D is * exactly singular, so the solution could not be computed. * * ===================================================================== * * .. Local Scalars .. LOGICAL LQUERY INTEGER LWKOPT, NB * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV EXTERNAL LSAME, ILAENV * .. * .. External Subroutines .. EXTERNAL DSYTRF, DSYTRS, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 LQUERY = ( LWORK.EQ.-1 ) IF( .NOT.LSAME( UPLO, 'U' ) .AND. .NOT.LSAME( UPLO, 'L' ) ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 ELSE IF( NRHS.LT.0 ) THEN INFO = -3 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -5 ELSE IF( LDB.LT.MAX( 1, N ) ) THEN INFO = -8 ELSE IF( LWORK.LT.1 .AND. .NOT.LQUERY ) THEN INFO = -10 END IF * IF( INFO.EQ.0 ) THEN NB = ILAENV( 1, 'DSYTRF', UPLO, N, -1, -1, -1 ) LWKOPT = N*NB WORK( 1 ) = LWKOPT END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSYSV ', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Compute the factorization A = U*D*U' or A = L*D*L'. * CALL DSYTRF( UPLO, N, A, LDA, IPIV, WORK, LWORK, INFO ) IF( INFO.EQ.0 ) THEN * * Solve the system A*X = B, overwriting B with X. * CALL DSYTRS( UPLO, N, NRHS, A, LDA, IPIV, B, LDB, INFO ) * END IF * WORK( 1 ) = LWKOPT * RETURN * * End of DSYSV * END SUBROUTINE DSYSVX( FACT, UPLO, N, NRHS, A, LDA, AF, LDAF, IPIV, B, $ LDB, X, LDX, RCOND, FERR, BERR, WORK, LWORK, $ IWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER FACT, UPLO INTEGER INFO, LDA, LDAF, LDB, LDX, LWORK, N, NRHS DOUBLE PRECISION RCOND * .. * .. Array Arguments .. INTEGER IPIV( * ), IWORK( * ) DOUBLE PRECISION A( LDA, * ), AF( LDAF, * ), B( LDB, * ), $ BERR( * ), FERR( * ), WORK( * ), X( LDX, * ) * .. * * Purpose * ======= * * DSYSVX uses the diagonal pivoting factorization to compute the * solution to a real system of linear equations A * X = B, * where A is an N-by-N symmetric matrix and X and B are N-by-NRHS * matrices. * * Error bounds on the solution and a condition estimate are also * provided. * * Description * =========== * * The following steps are performed: * * 1. If FACT = 'N', the diagonal pivoting method is used to factor A. * The form of the factorization is * A = U * D * U**T, if UPLO = 'U', or * A = L * D * L**T, if UPLO = 'L', * where U (or L) is a product of permutation and unit upper (lower) * triangular matrices, and D is symmetric and block diagonal with * 1-by-1 and 2-by-2 diagonal blocks. * * 2. If some D(i,i)=0, so that D is exactly singular, then the routine * returns with INFO = i. Otherwise, the factored form of A is used * to estimate the condition number of the matrix A. If the * reciprocal of the condition number is less than machine precision, * INFO = N+1 is returned as a warning, but the routine still goes on * to solve for X and compute error bounds as described below. * * 3. The system of equations is solved for X using the factored form * of A. * * 4. Iterative refinement is applied to improve the computed solution * matrix and calculate error bounds and backward error estimates * for it. * * Arguments * ========= * * FACT (input) CHARACTER*1 * Specifies whether or not the factored form of A has been * supplied on entry. * = 'F': On entry, AF and IPIV contain the factored form of * A. AF and IPIV will not be modified. * = 'N': The matrix A will be copied to AF and factored. * * UPLO (input) CHARACTER*1 * = 'U': Upper triangle of A is stored; * = 'L': Lower triangle of A is stored. * * N (input) INTEGER * The number of linear equations, i.e., the order of the * matrix A. N >= 0. * * NRHS (input) INTEGER * The number of right hand sides, i.e., the number of columns * of the matrices B and X. NRHS >= 0. * * A (input) DOUBLE PRECISION array, dimension (LDA,N) * The symmetric matrix A. If UPLO = 'U', the leading N-by-N * upper triangular part of A contains the upper triangular part * of the matrix A, and the strictly lower triangular part of A * is not referenced. If UPLO = 'L', the leading N-by-N lower * triangular part of A contains the lower triangular part of * the matrix A, and the strictly upper triangular part of A is * not referenced. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * AF (input or output) DOUBLE PRECISION array, dimension (LDAF,N) * If FACT = 'F', then AF is an input argument and on entry * contains the block diagonal matrix D and the multipliers used * to obtain the factor U or L from the factorization * A = U*D*U**T or A = L*D*L**T as computed by DSYTRF. * * If FACT = 'N', then AF is an output argument and on exit * returns the block diagonal matrix D and the multipliers used * to obtain the factor U or L from the factorization * A = U*D*U**T or A = L*D*L**T. * * LDAF (input) INTEGER * The leading dimension of the array AF. LDAF >= max(1,N). * * IPIV (input or output) INTEGER array, dimension (N) * If FACT = 'F', then IPIV is an input argument and on entry * contains details of the interchanges and the block structure * of D, as determined by DSYTRF. * If IPIV(k) > 0, then rows and columns k and IPIV(k) were * interchanged and D(k,k) is a 1-by-1 diagonal block. * If UPLO = 'U' and IPIV(k) = IPIV(k-1) < 0, then rows and * columns k-1 and -IPIV(k) were interchanged and D(k-1:k,k-1:k) * is a 2-by-2 diagonal block. If UPLO = 'L' and IPIV(k) = * IPIV(k+1) < 0, then rows and columns k+1 and -IPIV(k) were * interchanged and D(k:k+1,k:k+1) is a 2-by-2 diagonal block. * * If FACT = 'N', then IPIV is an output argument and on exit * contains details of the interchanges and the block structure * of D, as determined by DSYTRF. * * B (input) DOUBLE PRECISION array, dimension (LDB,NRHS) * The N-by-NRHS right hand side matrix B. * * LDB (input) INTEGER * The leading dimension of the array B. LDB >= max(1,N). * * X (output) DOUBLE PRECISION array, dimension (LDX,NRHS) * If INFO = 0 or INFO = N+1, the N-by-NRHS solution matrix X. * * LDX (input) INTEGER * The leading dimension of the array X. LDX >= max(1,N). * * RCOND (output) DOUBLE PRECISION * The estimate of the reciprocal condition number of the matrix * A. If RCOND is less than the machine precision (in * particular, if RCOND = 0), the matrix is singular to working * precision. This condition is indicated by a return code of * INFO > 0. * * FERR (output) DOUBLE PRECISION array, dimension (NRHS) * The estimated forward error bound for each solution vector * X(j) (the j-th column of the solution matrix X). * If XTRUE is the true solution corresponding to X(j), FERR(j) * is an estimated upper bound for the magnitude of the largest * element in (X(j) - XTRUE) divided by the magnitude of the * largest element in X(j). The estimate is as reliable as * the estimate for RCOND, and is almost always a slight * overestimate of the true error. * * BERR (output) DOUBLE PRECISION array, dimension (NRHS) * The componentwise relative backward error of each solution * vector X(j) (i.e., the smallest relative change in * any element of A or B that makes X(j) an exact solution). * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The length of WORK. LWORK >= 3*N, and for best performance * LWORK >= N*NB, where NB is the optimal blocksize for * DSYTRF. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * IWORK (workspace) INTEGER array, dimension (N) * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = i, and i is * <= N: D(i,i) is exactly zero. The factorization * has been completed but the factor D is exactly * singular, so the solution and error bounds could * not be computed. RCOND = 0 is returned. * = N+1: D is nonsingular, but RCOND is less than machine * precision, meaning that the matrix is singular * to working precision. Nevertheless, the * solution and error bounds are computed because * there are a number of situations where the * computed solution can be more accurate than the * value of RCOND would suggest. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO PARAMETER ( ZERO = 0.0D+0 ) * .. * .. Local Scalars .. LOGICAL LQUERY, NOFACT INTEGER LWKOPT, NB DOUBLE PRECISION ANORM * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANSY EXTERNAL LSAME, ILAENV, DLAMCH, DLANSY * .. * .. External Subroutines .. EXTERNAL DLACPY, DSYCON, DSYRFS, DSYTRF, DSYTRS, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 NOFACT = LSAME( FACT, 'N' ) LQUERY = ( LWORK.EQ.-1 ) IF( .NOT.NOFACT .AND. .NOT.LSAME( FACT, 'F' ) ) THEN INFO = -1 ELSE IF( .NOT.LSAME( UPLO, 'U' ) .AND. .NOT.LSAME( UPLO, 'L' ) ) $ THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( NRHS.LT.0 ) THEN INFO = -4 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -6 ELSE IF( LDAF.LT.MAX( 1, N ) ) THEN INFO = -8 ELSE IF( LDB.LT.MAX( 1, N ) ) THEN INFO = -11 ELSE IF( LDX.LT.MAX( 1, N ) ) THEN INFO = -13 ELSE IF( LWORK.LT.MAX( 1, 3*N ) .AND. .NOT.LQUERY ) THEN INFO = -18 END IF * IF( INFO.EQ.0 ) THEN NB = ILAENV( 1, 'DSYTRF', UPLO, N, -1, -1, -1 ) LWKOPT = N*NB WORK( 1 ) = LWKOPT END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSYSVX', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * IF( NOFACT ) THEN * * Compute the factorization A = U*D*U' or A = L*D*L'. * CALL DLACPY( UPLO, N, N, A, LDA, AF, LDAF ) CALL DSYTRF( UPLO, N, AF, LDAF, IPIV, WORK, LWORK, INFO ) * * Return if INFO is non-zero. * IF( INFO.NE.0 ) THEN IF( INFO.GT.0 ) $ RCOND = ZERO RETURN END IF END IF * * Compute the norm of the matrix A. * ANORM = DLANSY( 'I', UPLO, N, A, LDA, WORK ) * * Compute the reciprocal of the condition number of A. * CALL DSYCON( UPLO, N, AF, LDAF, IPIV, ANORM, RCOND, WORK, IWORK, $ INFO ) * * Set INFO = N+1 if the matrix is singular to working precision. * IF( RCOND.LT.DLAMCH( 'Epsilon' ) ) $ INFO = N + 1 * * Compute the solution vectors X. * CALL DLACPY( 'Full', N, NRHS, B, LDB, X, LDX ) CALL DSYTRS( UPLO, N, NRHS, AF, LDAF, IPIV, X, LDX, INFO ) * * Use iterative refinement to improve the computed solutions and * compute error bounds and backward error estimates for them. * CALL DSYRFS( UPLO, N, NRHS, A, LDA, AF, LDAF, IPIV, B, LDB, X, $ LDX, FERR, BERR, WORK, IWORK, INFO ) * RETURN * * End of DSYSVX * END