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Chapter Contents
Chapter Introduction
NAG Toolbox

NAG Toolbox: nag_sparse_complex_herm_basic_solver (f11gs)

Purpose

nag_sparse_complex_herm_basic_solver (f11gs) is an iterative solver for a complex Hermitian system of simultaneous linear equations; nag_sparse_complex_herm_basic_solver (f11gs) is the second in a suite of three functions, where the first function, nag_sparse_complex_herm_basic_setup (f11gr), must be called prior to nag_sparse_complex_herm_basic_solver (f11gs) to set up the suite, and the third function in the suite, nag_sparse_complex_herm_basic_diag (f11gt), can be used to return additional information about the computation.
These three functions are suitable for the solution of large sparse complex Hermitian systems of equations.

Syntax

[irevcm, u, v, work, ifail] = f11gs(irevcm, u, v, wgt, work)
[irevcm, u, v, work, ifail] = nag_sparse_complex_herm_basic_solver(irevcm, u, v, wgt, work)
Note: the interface to this routine has changed since earlier releases of the toolbox:
Mark 22: lwork has been removed from the interface
.

Description

nag_sparse_complex_herm_basic_solver (f11gs) solves the complex Hermitian system of linear simultaneous equations Ax = bAx=b using either the preconditioned conjugate gradient method (see Hestenes and Stiefel (1952), Golub and Van Loan (1996), Barrett et al. (1994) and Dias da Cunha and Hopkins (1994)) or a preconditioned Lanczos method based upon the algorithm SYMMLQ (see Paige and Saunders (1975) and Barrett et al. (1994)).
For a general description of the methods employed you are referred to Section [Description] in (f11gr).
nag_sparse_complex_herm_basic_solver (f11gs) can solve the system after the first function in the suite, nag_sparse_complex_herm_basic_setup (f11gr), has been called to initialize the computation and specify the method of solution. The third function in the suite, nag_sparse_complex_herm_basic_diag (f11gt), can be used to return additional information generated by the computation during monitoring steps and after nag_sparse_complex_herm_basic_solver (f11gs) has completed its tasks.
nag_sparse_complex_herm_basic_solver (f11gs) uses reverse communication, i.e., nag_sparse_complex_herm_basic_solver (f11gs) returns repeatedly to the calling program with the parameter irevcm (see Section [Parameters]) set to specified values which require the calling program to carry out a specific task: either to compute the matrix-vector product v = Auv=Au; to solve the preconditioning equation Mv = uMv=u; to notify the completion of the computation; or, to allow the calling program to monitor the solution. Through the parameter irevcm the calling program can cause immediate or tidy termination of the execution. On final exit, the last iterates of the solution and of the residual vectors of the original system of equations are returned.
Reverse communication has the following advantages.
  1. Maximum flexibility in the representation and storage of sparse matrices. All matrix operations are performed outside the solver function, thereby avoiding the need for a complicated interface with enough flexibility to cope with all types of storage schemes and sparsity patterns. This applies also to preconditioners.
  2. Enhanced user interaction: you can closely monitor the progress of the solution and tidy or immediate termination can be requested. This is useful, for example, when alternative termination criteria are to be employed or in case of failure of the external functions used to perform matrix operations.

References

Barrett R, Berry M, Chan T F, Demmel J, Donato J, Dongarra J, Eijkhout V, Pozo R, Romine C and Van der Vorst H (1994) Templates for the Solution of Linear Systems: Building Blocks for Iterative Methods SIAM, Philadelphia
Dias da Cunha R and Hopkins T (1994) PIM 1.1 — the parallel iterative method package for systems of linear equations user's guide — Fortran 77 version Technical Report Computing Laboratory, University of Kent at Canterbury, Kent, UK
Golub G H and Van Loan C F (1996) Matrix Computations (3rd Edition) Johns Hopkins University Press, Baltimore
Hestenes M and Stiefel E (1952) Methods of conjugate gradients for solving linear systems J. Res. Nat. Bur. Stand. 49 409–436
Higham N J (1988) FORTRAN codes for estimating the one-norm of a real or complex matrix, with applications to condition estimation ACM Trans. Math. Software 14 381–396
Paige C C and Saunders M A (1975) Solution of sparse indefinite systems of linear equations SIAM J. Numer. Anal. 12 617–629

Parameters

Note: this function uses reverse communication. Its use involves an initial entry, intermediate exits and re-entries, and a final exit, as indicated by the parameter irevcm. Between intermediate exits and re-entries, all parameters other than irevcm and v must remain unchanged.

Compulsory Input Parameters

1:     irevcm – int64int32nag_int scalar
On initial entry: irevcm = 0irevcm=0, otherwise an error condition will be raised.
On intermediate re-entry: irevcm must either be unchanged from its previous exit value, or can have one of the following values.
irevcm = 5irevcm=5
Tidy termination: the computation will terminate at the end of the current iteration. Further reverse communication exits may occur depending on when the termination request is issued. nag_sparse_complex_herm_basic_solver (f11gs) will then return with the termination code irevcm = 4irevcm=4. Note that before calling nag_sparse_complex_herm_basic_solver (f11gs) with irevcm = 5irevcm=5 the calling program must have performed the tasks required by the value of irevcm returned by the previous call to nag_sparse_complex_herm_basic_solver (f11gs), otherwise subsequently returned values may be invalid.
irevcm = 6irevcm=6
Immediate termination: nag_sparse_complex_herm_basic_solver (f11gs) will return immediately with termination code irevcm = 4irevcm=4 and with any useful information available. This includes the last iterate of the solution and, for conjugate gradient only, the last iterate of the residual vector. The residual vector is generally not available when the Lanczos method (SYMMLQ) is used. nag_sparse_complex_herm_basic_solver (f11gs) will then return with the termination code irevcm = 4irevcm=4.
Immediate termination may be useful, for example, when errors are detected during matrix-vector multiplication or during the solution of the preconditioning equation.
Changing irevcm to any other value between calls will result in an error.
Constraint: on initial entry, irevcm = 0irevcm=0; on re-entry, either irevcm must remain unchanged or be reset to irevcm = 5irevcm=5 or 66.
2:     u( : :) – complex array
Note: the dimension of the array u must be at least nn.
On initial entry: an initial estimate, x0x0, of the solution of the system of equations Ax = bAx=b.
On intermediate re-entry: must remain unchanged.
3:     v( : :) – complex array
Note: the dimension of the array v must be at least nn.
On initial entry: the right-hand side bb of the system of equations Ax = bAx=b.
On intermediate re-entry: the returned value of irevcm determines the contents of v in the following way.
If irevcm = 1irevcm=1 or 22, v must store the vector vv, the result of the operation specified by the value of irevcm returned by the previous call to nag_sparse_complex_herm_basic_solver (f11gs)
If irevcm = 3irevcm=3, v must remain unchanged.
4:     wgt( : :) – double array
Note: the dimension of the array wgt must be at least max (1,n)max(1,n).
The user-supplied weights, if these are to be used in the computation of the vector norms in the termination criterion (see Sections [Description] and [Parameters] in (f11gr)).
Constraint: if weights are to be used, at least one element of wgt must be nonzero.
5:     work(lwork) – complex array
lwork, the dimension of the array, must satisfy the constraint lworklwreqlworklwreq, where lwreq is returned by nag_sparse_complex_herm_basic_setup (f11gr).
On initial entry: the array work as returned by nag_sparse_complex_herm_basic_setup (f11gr) (see also Section [Parameters] in (f11gr)).
lwork, the dimension of the array, must satisfy the constraint lworklwreqlworklwreq, where lwreq is returned by nag_sparse_complex_herm_basic_setup (f11gr).
On intermediate re-entry: must remain unchanged.

Optional Input Parameters

None.

Input Parameters Omitted from the MATLAB Interface

lwork

Output Parameters

1:     irevcm – int64int32nag_int scalar
On intermediate exit: has the following meanings.
irevcm = 1irevcm=1
The calling program must compute the matrix-vector product v = Auv=Au, where uu and vv are stored in u and v, respectively.
irevcm = 2irevcm=2
The calling program must solve the preconditioning equation Mv = uMv=u, where uu and vv are stored in u and v, respectively.
irevcm = 3irevcm=3
Monitoring step: the solution and residual at the current iteration are returned in the arrays u and v, respectively. No action by the calling program is required. To return additional information nag_sparse_complex_herm_basic_diag (f11gt) can be called at this step.
On final exit: if irevcm = 4irevcm=4, nag_sparse_complex_herm_basic_solver (f11gs) has completed its tasks. The value of ifail determines whether the iteration has been successfully completed, errors have been detected or the calling program has requested termination.
2:     u( : :) – complex array
Note: the dimension of the array u must be at least nn.
On intermediate exit: the returned value of irevcm determines the contents of u in the following way.
If irevcm = 1irevcm=1 or 22, u holds the vector uu on which the operation specified by irevcm is to be carried out.
If irevcm = 3irevcm=3, u holds the current iterate of the solution vector.
On final exit: if ifail = 3ifail=3 or i-i, the array u is unchanged from the initial entry to nag_sparse_complex_herm_basic_solver (f11gs). If ifail = 1ifail=1, the array u is unchanged from the last entry to nag_sparse_complex_herm_basic_solver (f11gs). Otherwise, u holds the last iterate of the solution of the system of equations, for all returned values of ifail.
3:     v( : :) – complex array
Note: the dimension of the array v must be at least nn.
On intermediate exit: if irevcm = 3irevcm=3, v holds the current iterate of the residual vector. Note that this is an approximation to the true residual vector. Otherwise, it does not contain any useful information.
On final exit: if ifail = 3ifail=3 or 00, the array v is unchanged from the last entry to nag_sparse_complex_herm_basic_solver (f11gs). If ifail = 1ifail=1, the array v is unchanged from the initial entry to nag_sparse_complex_herm_basic_solver (f11gs). If ifail = 0ifail=0 or 22, the array v contains the true residual vector of the system of equations (see also Section [Error Indicators and Warnings]). Otherwise, v stores the last iterate of the residual vector unless the Lanczos method (SYMMLQ) was used and ifail5ifail5, in which case v is set to 0.00.0.
4:     work(lwork) – complex array
5:     ifail – int64int32nag_int scalar
ifail = 0ifail=0 unless the function detects an error (see [Error Indicators and Warnings]).

Error Indicators and Warnings

Errors or warnings detected by the function:

Cases prefixed with W are classified as warnings and do not generate an error of type NAG:error_n. See nag_issue_warnings.

  ifail = iifail=-i
If ifail = iifail=-i, parameter ii had an illegal value on entry. The parameters are numbered as follows:
1: irevcm, 2: u, 3: v, 4: wgt, 5: work, 6: lwork, 7: ifail.
It is possible that ifail refers to a parameter that is omitted from the MATLAB interface. This usually indicates that an error in one of the other input parameters has caused an incorrect value to be inferred.
W ifail = 1ifail=1
nag_sparse_complex_herm_basic_solver (f11gs) has been called again after returning the termination code irevcm = 4irevcm=4. No further computation has been carried out and all input data and data stored for access by nag_sparse_complex_herm_basic_diag (f11gt) have remained unchanged.
W ifail = 2ifail=2
The required accuracy could not be obtained. However, nag_sparse_complex_herm_basic_solver (f11gs) has terminated with reasonable accuracy: the last iterate of the residual satisfied the termination criterion but the exact residual r = bAxr=b-Ax, did not. A small number of iterations have been carried out after the iterated residual satisfied the termination criterion, but were unable to improve on the accuracy. This error code usually implies that your problem has been fully and satisfactorily solved to within or close to the accuracy available on your system. Further iterations are unlikely to improve on this situation. You should call nag_sparse_complex_herm_basic_diag (f11gt) to check the values of the left- and right-hand side of the termination condition.
  ifail = 3ifail=3
nag_sparse_complex_herm_basic_setup (f11gr) was either not called before calling nag_sparse_complex_herm_basic_solver (f11gs) or it returned an error. The arrays u and v remain unchanged.
W ifail = 4ifail=4
The calling program requested a tidy termination before the solution had converged. The arrays u and v return the last iterates available of the solution and of the residual vector, respectively.
W ifail = 5ifail=5
The solution did not converge within the maximum number of iterations allowed. The arrays u and v return the last iterates available of the solution and of the residual vector, respectively.
  ifail = 6ifail=6
The preconditioner appears not to be positive definite. It is likely that your results are meaningless: both methods require a positive definite preconditioner (see also Section [Description]). However, the array u returns the last iterate of the solution, the array v returns the last iterate of the residual vector, for the conjugate gradient method only.
W ifail = 7ifail=7
The matrix of the coefficients appears not to be positive definite (conjugate gradient method only). The arrays u and v return the last iterates of the solution and residual vector, respectively. However, you should be warned that the results returned can be be in error.
W ifail = 8ifail=8
The calling program requested an immediate termination. However, the array u returns the last iterate of the solution, the array v returns the last iterate of the residual vector, for the conjugate gradient method only.
  ifail = 9ifail=9
The matrix appears to be singular.
  ifail = 10ifail=10
User-supplied weights are to be used, but all elements of the array wgt are zero.

Accuracy

On completion, i.e., irevcm = 4irevcm=4 on exit, the arrays u and v will return the solution and residual vectors, xkxk and rk = bAxkrk=b-Axk, respectively, at the kkth iteration, the last iteration performed, unless an immediate termination was requested and the Lanczos method (SYMMLQ) was used.
On successful completion, the termination criterion is satisfied to within the user-specified tolerance, as described in Section [Description] in (f11gr). The computed values of the left- and right-hand sides of the termination criterion selected can be obtained by a call to nag_sparse_complex_herm_basic_diag (f11gt).

Further Comments

The number of operations carried out by nag_sparse_complex_herm_basic_solver (f11gs) for each iteration is likely to be principally determined by the computation of the matrix-vector products v = Auv=Au and by the solution of the preconditioning equation Mv = uMv=u in the calling program. Each of these operations is carried out once every iteration.
The number of the remaining operations in nag_sparse_complex_herm_basic_solver (f11gs) for each iteration is approximately proportional to nn. Note that the Lanczos method (SYMMLQ) requires a slightly larger number of operations than the conjugate gradient method.
The number of iterations required to achieve a prescribed accuracy cannot be easily determined at the onset, as it can depend dramatically on the conditioning and spectrum of the preconditioned matrix of the coefficients A = E1AEHA-=E-1AE-H.
Additional matrix-vector products are required for the computation of A1 = AA1=A, when this has not been supplied to nag_sparse_complex_herm_basic_setup (f11gr) and is required by the termination criterion employed.
The number of operations required to compute σ1(A)σ1(A-) is negligible for reasonable values of sigtol and maxits (see Sections [Parameters] and [Further Comments] in (f11gr)).
If the termination criterion rkp τ (bp + Ap × xkp) rkp τ ( bp+Ap × xkp )  is used (see Section [Description] in (f11gr)) and x0xkx0xk, so that because of loss of significant digits the required accuracy could not be obtained, the iteration is restarted automatically at some suitable point: nag_sparse_complex_herm_basic_solver (f11gs) sets x0 = xkx0=xk and the computation begins again. For particularly badly scaled problems, more than one restart may be necessary. Naturally, restarting adds to computational costs: it is recommended that the iteration should start from a value x0x0 which is as close to the true solution x~ as can be estimated. Otherwise, the iteration should start from x0 = 0x0=0.

Example

function nag_sparse_complex_herm_basic_solver_example
nz = 23;
a = zeros(10000,1);
a(1:nz) = [ 6 + 0.i;
           -1 + 1.i;
            6 + 0.i;
            0 + 1.i;
            5 + 0.i;
            5 + 0.i;
            2 - 2.i;
            4 + 0.i;
            1 + 1.i;
            2 + 0.i;
            6 + 0.i;
           -4 + 3.i;
            0 + 1.i;
           -1 + 0.i;
            6 + 0.i;
           -1 - 1.i;
            0 - 1.i;
            9 + 0.i;
            1 + 3.i;
            1 + 2.i;
           -1 + 0.i;
            1 + 4.i;
            9 + 0.i];
irow = zeros(10000, 1, 'int64');
irow(1:nz) = [int64(1);2;2;3;3;4;5;5;6;6;6;7;7;7;7;8;8;8;9;9;9;9;9];
icol = zeros(10000, 1, 'int64');
icol(1:nz) = [int64(1);1;2;2;3;4;1;5;3;4;6;2;5;6;7;4;6;8;1;5;6;8;9];
lfill = int64(0);
dtol = 0;
mic = 'N';
dscale = 0;
ipiv = [int64(0);0;0;0;0;0;0;0;0];
method = 'CG    ';
precon = 'P';
n = 9;
tol = 1e-06;
maxitn = int64(20);
anorm = 0;
sigmax = 0;
maxits = int64(9);
monit = int64(2);

irevcm = int64(0);
u = [complex(0);
      0 + 0i;
      0 + 0i;
      0 + 0i;
      0 + 0i;
      0 + 0i;
      0 + 0i;
      0 + 0i;
      0 + 0i];
v = [ 8 + 54i;
      -10 - 92i;
      25 + 27i;
      26 - 28i;
      54 + 12i;
      26 - 22i;
      47 + 65i;
      71 - 57i;
      60 + 70i];
wgt = [0; 0; 0; 0; 0; 0; 0; 0; 0];


[a, irow, icol, ipiv, istr, nnzc, npivm, ifail] = ...
    nag_sparse_complex_herm_precon_ilu(int64(nz), a, irow, icol, lfill, ...
    dtol, mic, dscale, ipiv);

[lwreq, work, ifail] = ...
     nag_sparse_complex_herm_basic_setup(method, precon, int64(n), tol, ...
     maxitn, anorm, sigmax, maxits, monit, 'sigcmp', 's', 'norm_p', '1');

while (irevcm ~= 4)
  [irevcm, u, v, work, ifail] = ...
       nag_sparse_complex_herm_basic_solver(irevcm, u, v, wgt, work);

  if (irevcm == 1)
    [v, ifail] = ...
       nag_sparse_complex_herm_matvec(a(1:nz), irow(1:nz), icol(1:nz), 'N', u);
    if (ifail ~= 0)
      irecvm = 6;
    end
  elseif (irevcm == 2)
    [v, ifail] = ...
      nag_sparse_complex_herm_precon_ilu_solve(a, irow, icol, ipiv, istr, 'N', u);
    if (ifail ~= 0)
      irecvm = 6;
    end
  elseif (irevcm == 3)
    [itn, stplhs, stprhs, anorm, sigmax, its, sigerr, ifail] = ...
        nag_sparse_complex_herm_basic_diag(work);
    if (ifail ~= 0)
      irecvm = 6;
    end
    fprintf('\nMonitoring at iteration number %d\nresidual norm: %14.4e\n', ...
       itn, stplhs);
    for i = 1:n
      fprintf('%+16.4e + %+16.4eI\n', real(u(i)), imag(u(i)));
    end
    fprintf('\n   Residual Vector\n');
    for i = 1:n
      fprintf('%+16.4e + %+16.4eI\n', real(v(i)), imag(v(i)));
    end
  end
end

% Get information about the computation
[itn, stplhs, stprhs, anorm, sigmax, its, sigerr, ifail] = ...
     nag_sparse_complex_herm_basic_diag(work);
fprintf('\nNumber of iterations for convergence: %d\n', itn);
fprintf('Residual norm:                           %14.4e\n', stplhs);
fprintf('Right-hand side of termination criteria: %14.4e\n', stprhs);
fprintf('i-norm of matrix a:                      %14.4e\n', anorm);
fprintf('\n   Solution Vector\n');
for i = 1:n
  fprintf('%+16.4e + %+16.4eI\n', real(u(i)), imag(u(i)));
end
fprintf('\n   Residual Vector\n');
for i = 1:n
  fprintf('%+16.4e + %+16.4eI\n', real(v(i)), imag(v(i)));
end
 

Monitoring at iteration number 2
residual norm:     1.4937e+01
     +2.1423e-01 +      +4.5333e+00I
     -1.6589e+00 +      -1.2672e+01I
     +2.4101e+00 +      +7.4551e+00I
     +4.4400e+00 +      -6.4174e+00I
     +9.1135e+00 +      +3.7812e+00I
     +4.4419e+00 +      -4.0382e+00I
     +1.4757e+00 +      +1.2662e+00I
     +8.4872e+00 +      -3.5347e+00I
     +5.9948e+00 +      +9.6851e-01I

   Residual Vector
     -1.8370e+00 +      +3.6956e+00I
     -6.5005e-01 +      +2.5458e-01I
     -1.2616e-01 +      -1.3625e-01I
     -1.3120e-01 +      +1.4130e-01I
     -1.1471e+00 +      +7.3386e-01I
     -5.5054e-01 +      -1.0535e+00I
     +1.7165e+00 +      -1.4614e+00I
     -3.5829e-01 +      +2.8764e-01I
     -3.0278e-01 +      -3.5324e-01I

Monitoring at iteration number 4
residual norm:     1.4602e+00
     +1.0061e+00 +      +8.9847e+00I
     +1.9637e+00 +      -7.9768e+00I
     +3.0067e+00 +      +7.0285e+00I
     +3.9830e+00 +      -5.9636e+00I
     +5.0390e+00 +      +5.0432e+00I
     +6.0488e+00 +      -4.0771e+00I
     +6.9710e+00 +      +3.0168e+00I
     +8.0118e+00 +      -1.9806e+00I
     +9.0074e+00 +      +9.6458e-01I

   Residual Vector
     +1.1524e-02 +      -2.8188e-02I
     +1.3513e-02 +      -1.7345e-01I
     +1.8173e-02 +      +1.9627e-02I
     +1.8900e-02 +      -2.0354e-02I
     -9.0877e-02 +      -1.0895e-01I
     -2.3890e-01 +      +3.2440e-01I
     +1.9031e-01 +      -1.5499e-02I
     +5.1611e-02 +      -4.1435e-02I
     +4.3615e-02 +      +5.0884e-02I

Number of iterations for convergence: 5
Residual norm:                               7.1054e-14
Right-hand side of termination criteria:     2.7340e-03
i-norm of matrix a:                          2.2000e+01

   Solution Vector
     +1.0000e+00 +      +9.0000e+00I
     +2.0000e+00 +      -8.0000e+00I
     +3.0000e+00 +      +7.0000e+00I
     +4.0000e+00 +      -6.0000e+00I
     +5.0000e+00 +      +5.0000e+00I
     +6.0000e+00 +      -4.0000e+00I
     +7.0000e+00 +      +3.0000e+00I
     +8.0000e+00 +      -2.0000e+00I
     +9.0000e+00 +      +1.0000e+00I

   Residual Vector
     +1.0658e-14 +      +7.1054e-15I
     +0.0000e+00 +      +0.0000e+00I
     +0.0000e+00 +      -3.5527e-15I
     +3.5527e-15 +      +3.5527e-15I
     +0.0000e+00 +      +1.0658e-14I
     +0.0000e+00 +      -1.0658e-14I
     +1.4211e-14 +      +0.0000e+00I
     +0.0000e+00 +      +0.0000e+00I
     -7.1054e-15 +      +0.0000e+00I

function f11gs_example
nz = 23;
a = zeros(10000,1);
a(1:nz) = [ 6 + 0.i;
           -1 + 1.i;
            6 + 0.i;
            0 + 1.i;
            5 + 0.i;
            5 + 0.i;
            2 - 2.i;
            4 + 0.i;
            1 + 1.i;
            2 + 0.i;
            6 + 0.i;
           -4 + 3.i;
            0 + 1.i;
           -1 + 0.i;
            6 + 0.i;
           -1 - 1.i;
            0 - 1.i;
            9 + 0.i;
            1 + 3.i;
            1 + 2.i;
           -1 + 0.i;
            1 + 4.i;
            9 + 0.i];
irow = zeros(10000, 1, 'int64');
irow(1:nz) = [int64(1);2;2;3;3;4;5;5;6;6;6;7;7;7;7;8;8;8;9;9;9;9;9];
icol = zeros(10000, 1, 'int64');
icol(1:nz) = [int64(1);1;2;2;3;4;1;5;3;4;6;2;5;6;7;4;6;8;1;5;6;8;9];
lfill = int64(0);
dtol = 0;
mic = 'N';
dscale = 0;
ipiv = [int64(0);0;0;0;0;0;0;0;0];
method = 'CG    ';
precon = 'P';
n = 9;
tol = 1e-06;
maxitn = int64(20);
anorm = 0;
sigmax = 0;
maxits = int64(9);
monit = int64(2);

irevcm = int64(0);
u = [complex(0);
      0 + 0i;
      0 + 0i;
      0 + 0i;
      0 + 0i;
      0 + 0i;
      0 + 0i;
      0 + 0i;
      0 + 0i];
v = [ 8 + 54i;
      -10 - 92i;
      25 + 27i;
      26 - 28i;
      54 + 12i;
      26 - 22i;
      47 + 65i;
      71 - 57i;
      60 + 70i];
wgt = [0; 0; 0; 0; 0; 0; 0; 0; 0];


[a, irow, icol, ipiv, istr, nnzc, npivm, ifail] = ...
    f11jn(int64(nz), a, irow, icol, lfill, dtol, mic, dscale, ipiv);

[lwreq, work, ifail] = ...
     f11gr(method, precon, int64(n), tol, maxitn, anorm, sigmax, maxits, monit, ...
           'sigcmp', 's', 'norm_p', '1');

while (irevcm ~= 4)
  [irevcm, u, v, work, ifail] = f11gs(irevcm, u, v, wgt, work);

  if (irevcm == 1)
    [v, ifail] = f11xs(a(1:nz), irow(1:nz), icol(1:nz), 'N', u);
    if (ifail ~= 0)
      irecvm = 6;
    end
  elseif (irevcm == 2)
    [v, ifail] = f11jp(a, irow, icol, ipiv, istr, 'N', u);
    if (ifail ~= 0)
      irecvm = 6;
    end
  elseif (irevcm == 3)
    [itn, stplhs, stprhs, anorm, sigmax, its, sigerr, ifail] = f11gt(work);
    if (ifail ~= 0)
      irecvm = 6;
    end
    fprintf('\nMonitoring at iteration number %d\nresidual norm: %14.4e\n', ...
            itn, stplhs);
    for i = 1:n
      fprintf('%+16.4e + %+16.4eI\n', real(u(i)), imag(u(i)));
    end
    fprintf('\n   Residual Vector\n');
    for i = 1:n
      fprintf('%+16.4e + %+16.4eI\n', real(v(i)), imag(v(i)));
    end
  end
end

% Get information about the computation
[itn, stplhs, stprhs, anorm, sigmax, its, sigerr, ifail] = f11gt(work);
fprintf('\nNumber of iterations for convergence: %d\n', itn);
fprintf('Residual norm:                           %14.4e\n', stplhs);
fprintf('Right-hand side of termination criteria: %14.4e\n', stprhs);
fprintf('i-norm of matrix a:                      %14.4e\n', anorm);
fprintf('\n   Solution Vector\n');
for i = 1:n
  fprintf('%+16.4e + %+16.4eI\n', real(u(i)), imag(u(i)));
end
fprintf('\n   Residual Vector\n');
for i = 1:n
  fprintf('%+16.4e + %+16.4eI\n', real(v(i)), imag(v(i)));
end
 

Monitoring at iteration number 2
residual norm:     1.4937e+01
     +2.1423e-01 +      +4.5333e+00I
     -1.6589e+00 +      -1.2672e+01I
     +2.4101e+00 +      +7.4551e+00I
     +4.4400e+00 +      -6.4174e+00I
     +9.1135e+00 +      +3.7812e+00I
     +4.4419e+00 +      -4.0382e+00I
     +1.4757e+00 +      +1.2662e+00I
     +8.4872e+00 +      -3.5347e+00I
     +5.9948e+00 +      +9.6851e-01I

   Residual Vector
     -1.8370e+00 +      +3.6956e+00I
     -6.5005e-01 +      +2.5458e-01I
     -1.2616e-01 +      -1.3625e-01I
     -1.3120e-01 +      +1.4130e-01I
     -1.1471e+00 +      +7.3386e-01I
     -5.5054e-01 +      -1.0535e+00I
     +1.7165e+00 +      -1.4614e+00I
     -3.5829e-01 +      +2.8764e-01I
     -3.0278e-01 +      -3.5324e-01I

Monitoring at iteration number 4
residual norm:     1.4602e+00
     +1.0061e+00 +      +8.9847e+00I
     +1.9637e+00 +      -7.9768e+00I
     +3.0067e+00 +      +7.0285e+00I
     +3.9830e+00 +      -5.9636e+00I
     +5.0390e+00 +      +5.0432e+00I
     +6.0488e+00 +      -4.0771e+00I
     +6.9710e+00 +      +3.0168e+00I
     +8.0118e+00 +      -1.9806e+00I
     +9.0074e+00 +      +9.6458e-01I

   Residual Vector
     +1.1524e-02 +      -2.8188e-02I
     +1.3513e-02 +      -1.7345e-01I
     +1.8173e-02 +      +1.9627e-02I
     +1.8900e-02 +      -2.0354e-02I
     -9.0877e-02 +      -1.0895e-01I
     -2.3890e-01 +      +3.2440e-01I
     +1.9031e-01 +      -1.5499e-02I
     +5.1611e-02 +      -4.1435e-02I
     +4.3615e-02 +      +5.0884e-02I

Number of iterations for convergence: 5
Residual norm:                               7.0166e-14
Right-hand side of termination criteria:     2.7340e-03
i-norm of matrix a:                          2.2000e+01

   Solution Vector
     +1.0000e+00 +      +9.0000e+00I
     +2.0000e+00 +      -8.0000e+00I
     +3.0000e+00 +      +7.0000e+00I
     +4.0000e+00 +      -6.0000e+00I
     +5.0000e+00 +      +5.0000e+00I
     +6.0000e+00 +      -4.0000e+00I
     +7.0000e+00 +      +3.0000e+00I
     +8.0000e+00 +      -2.0000e+00I
     +9.0000e+00 +      +1.0000e+00I

   Residual Vector
     +1.5099e-14 +      +1.4211e-14I
     +1.7764e-15 +      +0.0000e+00I
     +0.0000e+00 +      +7.1054e-15I
     +3.5527e-15 +      +7.1054e-15I
     +7.1054e-15 +      +0.0000e+00I
     +0.0000e+00 +      -7.1054e-15I
     +0.0000e+00 +      +0.0000e+00I
     +0.0000e+00 +      -7.1054e-15I
     +0.0000e+00 +      +0.0000e+00I


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