Interface for the Implicitly Restarted Arnoldi Iteration, to compute the converged approximations to eigenvalues of A * z = lambda * B * z approximations to a few eigenpairs of a real linear operator
[Dr, Di, Z, RESID, V, IPARAM, IPNTR, WORKD, WORKL, INFO] = dneupd(RVEC, HOWMANY, SELECT, Dr, Di, Z, SIGMAr, SIGMAi, WORKev,
BMAT, N, WHICH, NEV, TOL, RESID, NCV, V, IPARAM, IPNTR, WORKD, WORKL, INFO)
:RVEC Integer. (INPUT) Specifies whether a basis for the invariant subspace corresponding to the converged Ritz value approximations for the eigenproblem A * z = lambda * B * z is computed.
- RVEC = 0 Compute Ritz values only.
- RVEC = 1 Compute the Ritz vectors or Schur vectors.
See Remarks below. : :HOWMANY Character. (INPUT) Specifies the form of the basis for the invariant subspace corresponding to the converged Ritz values that is to be computed.
- ‘A’: Compute NEV Ritz vectors;
- ‘P’: Compute NEV Schur vectors;
- ‘S’: compute some of the Ritz vectors, specified by the integer array SELECT.
:
NOTE: The remaining arguments BMAT, N, WHICH, NEV, TOL, RESID, NCV, V, IPARAM, IPNTR, WORKD, WORKL, LWORKL, INFO must be passed directly to DNEUPD following the last call to DNAUPD .
These arguments MUST NOT BE MODIFIED between the last call to DNAUPD and the call to DNEUPD .
Three of these parameters (V, WORKL, INFO) are also output parameters.
V Double precision N by NCV array. (INPUT/OUTPUT) Upon INPUT: | |
---|---|
the NCV columns of V contain the Arnoldi basis vectors for OP as constructed by DNAUPD. Upon OUTPUT: If RVEC = 1 the first NCONV = IPARAM(5) columns contain approximate Schur vectors that span the desired invariant subspace. See Remark 2 below. NOTE: If the array Z has been set equal to first NEV+1 columns of the array V and RVEC = 1 and HOWMANY= ‘A’, then the Arnoldi basis held by V has been overwritten by the desired Ritz vectors. If a separate array Z has been passed then the first NCONV = IPARAM(5) columns of V will contain approximate Schur vectors that span the desired invariant subspace. |
: :WORKL Double precision work array of length LWORKL. (OUTPUT/WORKSPACE) WORKL(1:ncv*ncv+3*ncv) contains information obtained in dnaupd . They are not changed by dneupd . WORKL(ncv*ncv+3*ncv+1:3*ncv*ncv+6*ncv) holds the real and imaginary part of the untransformed Ritz values, the upper quasi-triangular matrix for H, and the associated matrix representation of the invariant subspace for H. Note: IPNTR(9:13) contains the pointer into WORKL for addresses of the above information computed by dneupd .
- IPNTR(9): pointer to the real part of the NCV RITZ values of the original system.
- IPNTR(10): pointer to the imaginary part of the NCV RITZ values of the original system.
- IPNTR(11): pointer to the NCV corresponding error bounds.
- IPNTR(12): pointer to the NCV by NCV upper quasi-triangular Schur matrix for H.
- IPNTR(13): pointer to the NCV by NCV matrix of eigenvectors of the upper Hessenberg matrix H. Only referenced by dneupd if RVEC = 1 See Remark 2 below.
: :INFO Integer. (OUTPUT). Error flag on output.
- 0: Normal exit.
- 1: The Schur form computed by LAPACK routine dlahqr could not be reordered by LAPACK routine dtrsen . Re-enter subroutine dneupd with IPARAM(5)=NCV and increase the size of the arrays DR and DI to have dimension at least dimension NCV and allocate at least NCV columns for Z. NOTE: Not necessary if Z and V share the same space. Please notify the authors if this error occurs.
- -1: N must be positive.
- -2: NEV must be positive.
- -3: NCV-NEV >= 2 and less than or equal to N.
- -5: WHICH must be one of ‘LM’, ‘SM’, ‘LR’, ‘SR’, ‘LI’, ‘SI’.
- -6: BMAT must be one of ‘I’ or ‘G’.
- -7: Length of private work WORKL array is not sufficient.
- -8: Error return from calculation of a real Schur form. Informational error from LAPACK routine dlahqr.
- -9: Error return from calculation of eigenvectors. Informational error from LAPACK routine dtrevc.
- -10: IPARAM(7) must be 1, 2, 3, 4.
- -11: IPARAM(7) = 1 and BMAT = ‘G’ are incompatible.
- -12: HOWMANY = ‘S’ not yet implemented.
- -13: HOWMANY must be one of ‘A’ or ‘P’ if RVEC = 1.
- -14: DNAUPD did not find any eigenvalues to sufficient accuracy.
- -15: DNEUPD got a different count of the number of converged Ritz values than DNAUPD got. This indicates the user probably made an error in passing data from DNAUPD to DNEUPD or that the data was modified before entering DNEUPD.
:
This subroutine returns the converged approximations to eigenvalues of A * z = lambda * B * z and (optionally):
There is negligible additional cost to obtain eigenvectors. An orthonormal basis is always computed.
There is an additional storage cost of n*nev if both are requested (in this case a separate array Z must be supplied).
The approximate eigenvalues and eigenvectors of A * z = lambda * B * z are derived from approximate eigenvalues and eigenvectors of of the linear operator OP prescribed by the MODE selection in the call to DNAUPD. DNAUPD must be called before this routine is called.
These approximate eigenvalues and vectors are commonly called Ritz values and Ritz vectors respectively. They are referred to as such in the comments that follow.
The computed orthonormal basis for the invariant subspace corresponding to these Ritz values is referred to as a Schur basis.
See documentation in the header of the subroutine DNAUPD for definition of OP as well as other terms and the relation of computed Ritz values and Ritz vectors of OP with respect to the given problem A * z = lambda * B * z.
For a brief description, see definitions of IPARAM(7), MODE and WHICH in the documentation of DNAUPD .
// The following sets dimensions for this problem.
nx = 10;
nev = 3;
ncv = 6;
bmat = 'I';
which = 'LM';
// Local Arrays
iparam = `zeros`_(11, 1);
ipntr = `zeros`_(14, 1);
_select = `zeros`_(ncv, 1);
dr = `zeros`_(nev + 1, 1);
di = `zeros`_(nev + 1, 1);
z = `zeros`_(nx, nev + 1);
resid = `zeros`_(nx, 1);
v = `zeros`_(nx, ncv);
workd = `zeros`_(3 * nx, 1);
workev = `zeros`_(3 * ncv, 1);
workl = `zeros`_(3 * ncv * ncv + 6 * ncv, 1);
// Build the test matrix
A = `diag`_(10 * `ones`_(nx, 1));
A(1:$-1,2:$) = A(1:$-1,2:$) + `diag`_(6 * `ones`_(nx-1,1));
A(2:$,1:$-1) = A(2:$,1:$-1) + `diag`_(-6 * `ones`_(nx-1,1));
tol = 0;
ido = 0;
ishfts = 1;
maxitr = 300;
mode1 = 1;
iparam(1) = ishfts;
iparam(3) = maxitr;
iparam(7) = mode1;
sigmar = 0; // the real part of the shift
sigmai = 0; // the imaginary part of the shift
info_dnaupd = 0;
// M A I N L O O P (Reverse communication)
while(ido <> 99)
// Repeatedly call the routine DNAUPD and take actions indicated by parameter IDO until
// either convergence is indicated or maxitr has been exceeded.
[ido, resid, v, iparam, ipntr, workd, workl, info_dnaupd] = `dnaupd`_(ido, bmat, nx, which, nev, tol, resid, ncv, v, iparam, ipntr, workd, workl, info_dnaupd);
if(info_dnaupd < 0)
printf('\nError with dnaupd, info = %d\n',info_dnaupd);
printf('Check the documentation of dnaupd\n\n');
end
if(ido == -1 | ido == 1)
// Perform matrix vector multiplication
workd(ipntr(2):ipntr(2) + nx -1) = A * workd(ipntr(1):ipntr(1) + nx - 1);
end
end
// Post-Process using DNEUPD.
rvec = 1;
howmany = 'A';
info_dneupd = 0;
[dr, di, z, resid, v, iparam, ipntr, workd, workl, info_dneupd] = dneupd(rvec, howmany, _select, dr, di, z, sigmar, sigmai, workev, ...
bmat, nx, which, nev, tol, resid, ncv, v, ...
iparam, ipntr, workd, workl, info_dneupd);
if(info_dneupd < 0)
printf('\nError with dneupd, info = %d\n', info_dneupd);
printf('Check the documentation of dneupd.\n\n');
end
printf('\nDNSIMP\n');
printf('======\n');
printf('\n');
printf('Size of the matrix is %d\n', nx);
printf('The number of Ritz values requested is %d\n', nev);
printf('The number of Arnoldi vectors generated (NCV) is %d\n', ncv);
printf('What portion of the spectrum: %s\n', which);
printf('The number of Implicit Arnoldi update iterations taken is %d\n', iparam(3));
printf('The number of OP*x is %d\n', iparam(9));
printf('The convergence criterion is %d\n', tol);
1. D.C. Sorensen, “Implicit Application of Polynomial Filters in a k-Step Arnoldi Method”, SIAM J. Matr. Anal. Apps., 13 (1992), pp 357-385.
2. R.B. Lehoucq, “Analysis and Implementation of an Implicitly Restarted Arnoldi Iteration”, Rice University Technical Report TR95-13, Department of Computational and Applied Mathematics.
3. B.N. Parlett, “The Symmetric Eigenvalue Problem”. Prentice-Hall, 1980.
4. B.N. Parlett, B. Nour-Omid, “Towards a Black Box Lanczos Program”, Computer Physics Communications, 53 (1989), pp 169-179.
5. B. Nour-Omid, B.N. Parlett, T. Ericson, P.S. Jensen, “How to Implement the Spectral Transformation”, Math. Comp., 48 (1987), pp 663-673.
6. R.G. Grimes, J.G. Lewis and H.D. Simon, “A Shifted Block Lanczos Algorithm for Solving Sparse Symmetric Generalized Eigenproblems”, SIAM J. Matr. Anal. Apps., January (1993).
7. L. Reichel, W.B. Gragg, “Algorithm 686: FORTRAN Subroutines for Updating the QR decomposition”, ACM TOMS, December 1990, Volume 16 Number 4, pp 369-377.
8. R.B. Lehoucq, D.C. Sorensen, “Implementation of Some Spectral Transformations in a k-Step Arnoldi Method”. In Preparation.
Based on ARPACK routine dneupd