F08NBF (DGEEVX) (PDF version)
F08 Chapter Contents
F08 Chapter Introduction
NAG Library Manual

NAG Library Routine Document

F08NBF (DGEEVX)

Note:  before using this routine, please read the Users' Note for your implementation to check the interpretation of bold italicised terms and other implementation-dependent details.

+ Contents

    1  Purpose
    7  Accuracy

1  Purpose

F08NBF (DGEEVX) computes the eigenvalues and, optionally, the left and/or right eigenvectors for an n by n real nonsymmetric matrix A.
Optionally, it also computes a balancing transformation to improve the conditioning of the eigenvalues and eigenvectors, reciprocal condition numbers for the eigenvalues, and reciprocal condition numbers for the right eigenvectors.

2  Specification

SUBROUTINE F08NBF ( BALANC, JOBVL, JOBVR, SENSE, N, A, LDA, WR, WI, VL, LDVL, VR, LDVR, ILO, IHI, SCALE, ABNRM, RCONDE, RCONDV, WORK, LWORK, IWORK, INFO)
INTEGER  N, LDA, LDVL, LDVR, ILO, IHI, LWORK, IWORK(*), INFO
REAL (KIND=nag_wp)  A(LDA,*), WR(*), WI(*), VL(LDVL,*), VR(LDVR,*), SCALE(*), ABNRM, RCONDE(*), RCONDV(*), WORK(max(1,LWORK))
CHARACTER(1)  BALANC, JOBVL, JOBVR, SENSE
The routine may be called by its LAPACK name dgeevx.

3  Description

The right eigenvector vj of A satisfies
A vj = λj vj
where λj is the jth eigenvalue of A. The left eigenvector uj of A satisfies
ujH A = λj ujH
where ujH denotes the conjugate transpose of uj.
Balancing a matrix A comprises two operations. The first is to permute the rows and columns of A to make it ‘more nearly’ upper triangular (closer to Schur form): A = PAPT , where P is a permutation matrix. The second operation is applying a diagonal similarity transformation DAD-1, where D is a diagonal matrix, with the aim of making 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 4.8.1.2 of Anderson et al. (1999).
Following the optional balancing, the matrix A is first reduced to upper Hessenberg form by means of orthogonal similarity transformations, and the QR algorithm is then used to further reduce the matrix to upper quasi-triangular Schur form, T, with 1 by 1 and 2 by 2 blocks on the main diagonal. The eigenvalues are computed from T, the 2 by 2 blocks corresponding to complex conjugate pairs and, optionally, the eigenvectors of T are computed and backtransformed to the eigenvectors of A.

4  References

Anderson E, Bai Z, Bischof C, Blackford S, Demmel J, Dongarra J J, Du Croz J J, Greenbaum A, Hammarling S, McKenney A and Sorensen D (1999) LAPACK Users' Guide (3rd Edition) SIAM, Philadelphia http://www.netlib.org/lapack/lug
Golub G H and Van Loan C F (1996) Matrix Computations (3rd Edition) Johns Hopkins University Press, Baltimore

5  Parameters

1:     BALANC – CHARACTER(1)Input
On entry: indicates how the input matrix should be diagonally scaled and/or permuted to improve the conditioning of its eigenvalues.
BALANC='N'
Do not diagonally scale or permute.
BALANC='P'
Perform permutations to make the matrix more nearly upper triangular. Do not diagonally scale.
BALANC='S'
Diagonally scale the matrix, i.e., replace A by DAD-1, where D is a diagonal matrix chosen to make the rows and columns of A more equal in norm. Do not permute.
BALANC='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.
Constraint: BALANC='N', 'P', 'S' or 'B'.
2:     JOBVL – CHARACTER(1)Input
Constraint: JOBVL='N' or 'V'.
3:     JOBVR – CHARACTER(1)Input
Constraint: JOBVR='N' or 'V'.
4:     SENSE – CHARACTER(1)Input
On entry: determines which reciprocal condition numbers are computed.
SENSE='N'
None are computed.
SENSE='E'
Computed for eigenvalues only.
SENSE='V'
Computed for right eigenvectors only.
SENSE='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').
Constraint: SENSE='N', 'E', 'V' or 'B'.
5:     N – INTEGERInput
On entry: n, the order of the matrix A.
Constraint: N0.
6:     A(LDA,*) – REAL (KIND=nag_wp) arrayInput/Output
Note: the second dimension of the array A must be at least max1,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.
7:     LDA – INTEGERInput
On entry: the first dimension of the array A as declared in the (sub)program from which F08NBF (DGEEVX) is called.
Constraint: LDAmax1,N.
8:     WR(*) – REAL (KIND=nag_wp) arrayOutput
9:     WI(*) – REAL (KIND=nag_wp) arrayOutput
Note: the dimension of the arrays WR and WI must be at least max1,N.
On exit: 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.
10:   VL(LDVL,*) – REAL (KIND=nag_wp) arrayOutput
Note: the second dimension of the array VL must be at least max1,N if JOBVL='V', and at least 1 otherwise.
On exit: if JOBVL='V', the left eigenvectors uj are stored one after another in the columns of VL, in the same order as their corresponding eigenvalues.
If JOBVL='N', VL is not referenced.
If the jth eigenvalue is real, then uj=VL:,j, the jth column of VL.
If the jth and j+1st eigenvalues form a complex conjugate pair, then uj=VL:,j+i×VL:,j+1 and uj+1=VL:,j-i×VL:,j+1.
11:   LDVL – INTEGERInput
On entry: the first dimension of the array VL as declared in the (sub)program from which F08NBF (DGEEVX) is called.
Constraints:
  • if JOBVL='V', LDVLmax1,N;
  • otherwise LDVL1.
12:   VR(LDVR,*) – REAL (KIND=nag_wp) arrayOutput
Note: the second dimension of the array VR must be at least max1,N if JOBVR='V', and at least 1 otherwise.
On exit: if JOBVR='V', the right eigenvectors vj are stored one after another in the columns of VR, in the same order as their corresponding eigenvalues.
If JOBVR='N', VR is not referenced.
If the jth eigenvalue is real, then vj=VR:,j, the jth column of VR.
If the jth and j+1st eigenvalues form a complex conjugate pair, then vj=VR:,j+i×VR:,j+1 and vj+1=VR:,j-i×VR:,j+1.
13:   LDVR – INTEGERInput
On entry: the first dimension of the array VR as declared in the (sub)program from which F08NBF (DGEEVX) is called.
Constraints:
  • if JOBVR='V', LDVRmax1,N;
  • otherwise LDVR1.
14:   ILO – INTEGEROutput
15:   IHI – INTEGEROutput
On exit: ILO and IHI are integer values determined when A was balanced. The balanced A has aij=0 if i>j and j=1,2,,ILO-1 or i=IHI+1,,N.
16:   SCALE(*) – REAL (KIND=nag_wp) arrayOutput
On exit: details of the permutations and scaling factors applied when balancing A.
If pj is the index of the row and column interchanged with row and column j, and dj is the scaling factor applied to row and column j, then
  • SCALEj=pj, for j=1,2,,ILO-1;
  • SCALEj=dj, for j=ILO,,IHI;
  • SCALEj=pj, for j=IHI+1,,N.
The order in which the interchanges are made is N to IHI+1, then 1 to ILO-1.
17:   ABNRM – REAL (KIND=nag_wp)Output
On exit: the 1-norm of the balanced matrix (the maximum of the sum of absolute values of elements of any column).
18:   RCONDE(*) – REAL (KIND=nag_wp) arrayOutput
On exit: RCONDEj is the reciprocal condition number of the jth eigenvalue.
19:   RCONDV(*) – REAL (KIND=nag_wp) arrayOutput
On exit: RCONDVj is the reciprocal condition number of the jth right eigenvector.
20:   WORK(max1,LWORK) – REAL (KIND=nag_wp) arrayWorkspace
21:   LWORK – INTEGERInput
On entry: the dimension of the array WORK as declared in the (sub)program from which F08NBF (DGEEVX) is called.
If LWORK=-1, 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.
Suggested value: for optimal performance, LWORK must generally be larger than the minimum, increase LWORK by, say, N×nb , where nb  is the optimal block size for F08NEF (DGEHRD).
Constraints:
  • if JOBVL='N' and JOBVR='N',
    • if SENSE='N', LWORKmax1,2×N;
    • otherwise LWORKmax1,N2+6×N;
  • if JOBVL='V' or JOBVR='V',
    • if SENSE='N' or 'E', LWORKmax1,3×N;
    • otherwise LWORKmax1,N2+6×N.
22:   IWORK(*) – INTEGER arrayWorkspace
Note: the dimension of the array IWORK must be at least max1,2×N-1.
If SENSE='N' or 'E', IWORK is not referenced.
23:   INFO – INTEGEROutput

6  Error Indicators and Warnings

Errors or warnings detected by the routine:
INFO<0
If INFO=-i, argument i had an illegal value. An explanatory message is output, and execution of the program is terminated.
INFO>0

7  Accuracy

The computed eigenvalues and eigenvectors are exact for a nearby matrix A+E, where
E2 = Oε A2 ,
and ε is the machine precision. See Section 4.8 of
Anderson et al. (1999) for further details.

8  Further Comments

Each eigenvector is normalized to have Euclidean norm equal to unity and the element of largest absolute value real and positive.
The total number of floating point operations is proportional to n3.
The complex analogue of this routine is F08NPF (ZGEEVX).

9  Example

This example finds all the eigenvalues and right eigenvectors of the matrix
A = 0.35 0.45 -0.14 -0.17 0.09 0.07 -0.54 0.35 -0.44 -0.33 -0.03 0.17 0.25 -0.32 -0.13 0.11 ,
together with estimates of the condition number and forward error bounds for each eigenvalue and eigenvector. The option to balance the matrix is used. In order to compute the condition numbers of the eigenvalues, the left eigenvectors also have to be computed, but they are not printed out in this example.
Note that the block size (NB) of 64 assumed in this example is not realistic for such a small problem, but should be suitable for large problems.

9.1  Program Text

Program Text (f08nbfe.f90)

9.2  Program Data

Program Data (f08nbfe.d)

9.3  Program Results

Program Results (f08nbfe.r)


F08NBF (DGEEVX) (PDF version)
F08 Chapter Contents
F08 Chapter Introduction
NAG Library Manual

© The Numerical Algorithms Group Ltd, Oxford, UK. 2011