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ZGEEVX - compute for an N-by-N complex nonsymmetric matrix A, the eigenvalues and, optionally, the left and/or right eigenvectors
SUBROUTINE ZGEEVX( BALANC, JOBVL, JOBVR, SENSE, N, A, LDA, W, VL, LDVL, VR, LDVR, ILO, IHI, SCALE, ABNRM, RCONDE, RCONDV, WORK, LWORK, RWORK, INFO ) CHARACTER BALANC, JOBVL, JOBVR, SENSE INTEGER IHI, ILO, INFO, LDA, LDVL, LDVR, LWORK, N DOUBLE PRECISION ABNRM DOUBLE PRECISION RCONDE( * ), RCONDV( * ), RWORK( * ), SCALE( * ) COMPLEX*16 A( LDA, * ), VL( LDVL, * ), VR( LDVR, * ), W( * ), WORK( * )
ZGEEVX computes for an N-by-N complex nonsymmetric matrix A, the eigen‐ values and, optionally, the left and/or right eigenvectors. Optionally also, it computes a balancing transformation to improve the condition‐ ing of the eigenvalues and eigenvectors (ILO, IHI, SCALE, and ABNRM), reciprocal condition numbers for the eigenvalues (RCONDE), and recipro‐ cal 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 transforma‐ tion 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.
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, ie. 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) COMPLEX*16 array, dimension (LDA,N) On entry, the N-by-N matrix A. On exit, A has been overwrit‐ ten. If JOBVL = ’V’ or JOBVR = ’V’, A contains the Schur form of the balanced version of the matrix A. LDA (input) INTEGER The leading dimension of the array A. LDA >= max(1,N). W (output) COMPLEX*16 array, dimension (N) W contains the computed eigenvalues. VL (output) COMPLEX*16 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 eigen‐ values. If JOBVL = ’N’, VL is not referenced. u(j) = VL(:,j), the j-th column of VL. LDVL (input) INTEGER The leading dimension of the array VL. LDVL >= 1; if JOBVL = ’V’, LDVL >= N. VR (output) COMPLEX*16 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. v(j) = VR(:,j), the j-th column of VR. LDVR (input) INTEGER The leading dimension of the array VR. LDVR >= 1; if JOBVR = ’V’, LDVR >= N. ILO,IHI (output) INTEGER ILO and IHI are integer values deter‐ mined 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 eigen‐ value. RCONDV (output) DOUBLE PRECISION array, dimension (N) RCONDV(j) is the reciprocal condition number of the j-th right eigenvector. WORK (workspace/output) COMPLEX*16 array, dimension (LWORK) 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 SENSE = ’V’ or ’B’, LWORK >= N*N+2*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. RWORK (workspace) DOUBLE PRECISION array, dimension (2*N) 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 W contain eigenvalues which have converged.