c Che 515: Driver program for LAPACK routine DGEEV c for solving real eigenvalue problem A x = lambda x c September 16, 1998 c implicit double precision (a-h,o-z) parameter(ndim = 20, lwork = 6*ndim) dimension a(ndim,ndim) double precision lambdar(ndim), lambdai(ndim) double precision evecl(ndim,ndim), evecr(ndim,ndim) double precision work(lwork) c c Construct your matrix here. c do i=1,ndim do j=i,ndim a(i,j) = 0.d0 enddo a(i,i) = 1.d0 enddo c c Call DGEEV c call dgeev('N','N',ndim,a,ndim,lambdar,lambdai,evecl,ndim, & evecr,ndim,work,lwork,info) c do i=1,ndim write(40,*) lambdar(i), lambdai(i) enddo c stop end c SUBROUTINE DGEEV( JOBVL, JOBVR, N, A, LDA, WR, WI, VL, LDVL, VR, $ LDVR, WORK, LWORK, INFO ) * * -- LAPACK driver routine (version 2.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * September 30, 1994 * * .. 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. * * 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. * * =====================================================================