NAG FL Interface
c05qsf (sparsys_func_easy)
1
Purpose
c05qsf is an easytouse routine that finds a solution of a sparse system of nonlinear equations by a modification of the Powell hybrid method.
2
Specification
Fortran Interface
Subroutine c05qsf ( 
fcn, n, x, fvec, xtol, init, rcomm, lrcomm, icomm, licomm, iuser, ruser, ifail) 
Integer, Intent (In) 
:: 
n, lrcomm, licomm 
Integer, Intent (Inout) 
:: 
icomm(licomm), iuser(*), ifail 
Real (Kind=nag_wp), Intent (In) 
:: 
xtol 
Real (Kind=nag_wp), Intent (Inout) 
:: 
x(n), rcomm(lrcomm), ruser(*) 
Real (Kind=nag_wp), Intent (Out) 
:: 
fvec(n) 
Logical, Intent (In) 
:: 
init 
External 
:: 
fcn 

C Header Interface
#include <nag.h>
void 
c05qsf_ ( void (NAG_CALL *fcn)(const Integer *n, const Integer *lindf, const Integer indf[], const double x[], double fvec[], Integer iuser[], double ruser[], Integer *iflag), const Integer *n, double x[], double fvec[], const double *xtol, const logical *init, double rcomm[], const Integer *lrcomm, Integer icomm[], const Integer *licomm, Integer iuser[], double ruser[], Integer *ifail) 

C++ Header Interface
#include <nag.h> extern "C" {
void 
c05qsf_ ( void (NAG_CALL *fcn)(const Integer &n, const Integer &lindf, const Integer indf[], const double x[], double fvec[], Integer iuser[], double ruser[], Integer &iflag), const Integer &n, double x[], double fvec[], const double &xtol, const logical &init, double rcomm[], const Integer &lrcomm, Integer icomm[], const Integer &licomm, Integer iuser[], double ruser[], Integer &ifail) 
}

The routine may be called by the names c05qsf or nagf_roots_sparsys_func_easy.
3
Description
The system of equations is defined as:
c05qsf is based on the MINPACK routine HYBRD1 (see
Moré et al. (1980)). It chooses the correction at each step as a convex combination of the Newton and scaled gradient directions. The Jacobian is updated by the sparse rank1 method of Schubert (see
Schubert (1970)). At the starting point, the sparsity pattern is determined and the Jacobian is approximated by forward differences, but these are not used again until the rank1 method fails to produce satisfactory progress. Then, the sparsity structure is used to recompute an approximation to the Jacobian by forward differences with the least number of function evaluations. The subroutine you supply must be able to compute only the requested subset of the function values. The sparse Jacobian linear system is solved at each iteration with
f11mef computing the Newton step. For more details see
Powell (1970) and
Broyden (1965).
4
References
Broyden C G (1965) A class of methods for solving nonlinear simultaneous equations Mathematics of Computation 19(92) 577–593
Moré J J, Garbow B S and Hillstrom K E (1980) User guide for MINPACK1 Technical Report ANL8074 Argonne National Laboratory
Powell M J D (1970) A hybrid method for nonlinear algebraic equations Numerical Methods for Nonlinear Algebraic Equations (ed P Rabinowitz) Gordon and Breach
Schubert L K (1970) Modification of a quasiNewton method for nonlinear equations with a sparse Jacobian Mathematics of Computation 24(109) 27–30
5
Arguments

1:
$\mathbf{fcn}$ – Subroutine, supplied by the user.
External Procedure

fcn must return the values of the functions
${f}_{i}$ at a point
$x$.
The specification of
fcn is:
Fortran Interface
Integer, Intent (In) 
:: 
n, lindf, indf(lindf) 
Integer, Intent (Inout) 
:: 
iuser(*), iflag 
Real (Kind=nag_wp), Intent (In) 
:: 
x(n) 
Real (Kind=nag_wp), Intent (Inout) 
:: 
ruser(*) 
Real (Kind=nag_wp), Intent (Out) 
:: 
fvec(n) 

C Header Interface
void 
fcn_ (const Integer *n, const Integer *lindf, const Integer indf[], const double x[], double fvec[], Integer iuser[], double ruser[], Integer *iflag) 

C++ Header Interface
#include <nag.h> extern "C" {
void 
fcn_ (const Integer &n, const Integer &lindf, const Integer indf[], const double x[], double fvec[], Integer iuser[], double ruser[], Integer &iflag) 
}


1:
$\mathbf{n}$ – Integer
Input

On entry: $n$, the number of equations.

2:
$\mathbf{lindf}$ – Integer
Input

On entry:
lindf specifies the number of indices
$i$ for which values of
${f}_{i}\left(x\right)$ must be computed.

3:
$\mathbf{indf}\left({\mathbf{lindf}}\right)$ – Integer array
Input

On entry:
indf specifies the indices
$i$ for which values of
${f}_{i}\left(x\right)$ must be computed. The indices are specified in strictly ascending order.

4:
$\mathbf{x}\left({\mathbf{n}}\right)$ – Real (Kind=nag_wp) array
Input

On entry: the components of the point $x$ at which the functions must be evaluated. ${\mathbf{x}}\left(i\right)$ contains the coordinate ${x}_{i}$.

5:
$\mathbf{fvec}\left({\mathbf{n}}\right)$ – Real (Kind=nag_wp) array
Output

On exit:
${\mathbf{fvec}}\left(i\right)$ must contain the function values
${f}_{i}\left(x\right)$, for all indices
$i$ in
indf.

6:
$\mathbf{iuser}\left(*\right)$ – Integer array
User Workspace

7:
$\mathbf{ruser}\left(*\right)$ – Real (Kind=nag_wp) array
User Workspace

fcn is called with the arguments
iuser and
ruser as supplied to
c05qsf. You should use the arrays
iuser and
ruser to supply information to
fcn.

8:
$\mathbf{iflag}$ – Integer
Input/Output

On entry: ${\mathbf{iflag}}>0$.
On exit: in general,
iflag should not be reset by
fcn. If, however, you wish to terminate execution (perhaps because some illegal point
x has been reached),
iflag should be set to a negative integer.
fcn must either be a module subprogram USEd by, or declared as EXTERNAL in, the (sub)program from which
c05qsf is called. Arguments denoted as
Input must
not be changed by this procedure.
Note: fcn should not return floatingpoint NaN (Not a Number) or infinity values, since these are not handled by
c05qsf. If your code inadvertently
does return any NaNs or infinities,
c05qsf is likely to produce unexpected results.

2:
$\mathbf{n}$ – Integer
Input

On entry: $n$, the number of equations.
Constraint:
${\mathbf{n}}>0$.

3:
$\mathbf{x}\left({\mathbf{n}}\right)$ – Real (Kind=nag_wp) array
Input/Output

On entry: an initial guess at the solution vector. ${\mathbf{x}}\left(i\right)$ must contain the coordinate ${x}_{i}$.
On exit: the final estimate of the solution vector.

4:
$\mathbf{fvec}\left({\mathbf{n}}\right)$ – Real (Kind=nag_wp) array
Output

On exit: the function values at the final point returned in
x.
${\mathbf{fvec}}\left(i\right)$ contains the function values
${f}_{i}$.

5:
$\mathbf{xtol}$ – Real (Kind=nag_wp)
Input

On entry: the accuracy in
x to which the solution is required.
Suggested value:
$\sqrt{\epsilon}$, where
$\epsilon $ is the
machine precision returned by
x02ajf.
Constraint:
${\mathbf{xtol}}\ge 0.0$.

6:
$\mathbf{init}$ – Logical
Input

On entry:
init must be set to .TRUE. to indicate that this is the first time
c05qsf is called for this specific problem.
c05qsf then computes the dense Jacobian and detects and stores its sparsity pattern (in
rcomm and
icomm) before proceeding with the iterations. This is noticeably time consuming when
n is large. If not enough storage has been provided for
rcomm or
icomm,
c05qsf will fail. On exit with
${\mathbf{ifail}}={\mathbf{0}}$,
${\mathbf{2}}$,
${\mathbf{3}}$ or
${\mathbf{4}}$,
${\mathbf{icomm}}\left(1\right)$ contains
$\mathit{nnz}$, the number of nonzero entries found in the Jacobian. On subsequent calls,
init can be set to .FALSE. if the problem has a Jacobian of the same sparsity pattern. In that case, the computation time required for the detection of the sparsity pattern will be smaller.

7:
$\mathbf{rcomm}\left({\mathbf{lrcomm}}\right)$ – Real (Kind=nag_wp) array
Communication Array

rcomm must not be altered between successive calls to
c05qsf.

8:
$\mathbf{lrcomm}$ – Integer
Input

On entry: the dimension of the array
rcomm as declared in the (sub)program from which
c05qsf is called.
Constraint:
${\mathbf{lrcomm}}\ge 12+\mathit{nnz}$ where $\mathit{nnz}$ is the number of nonzero entries in the Jacobian, as computed by c05qsf.

9:
$\mathbf{icomm}\left({\mathbf{licomm}}\right)$ – Integer array
Communication Array

If ${\mathbf{ifail}}={\mathbf{0}}$, ${\mathbf{2}}$, ${\mathbf{3}}$ or ${\mathbf{4}}$ on exit, ${\mathbf{icomm}}\left(1\right)$ contains $\mathit{nnz}$ where $\mathit{nnz}$ is the number of nonzero entries in the Jacobian.
icomm must not be altered between successive calls to
c05qsf.

10:
$\mathbf{licomm}$ – Integer
Input

On entry: the dimension of the array
icomm as declared in the (sub)program from which
c05qsf is called.
Constraint:
${\mathbf{licomm}}\ge 8\times {\mathbf{n}}+19+\mathit{nnz}$ where $\mathit{nnz}$ is the number of nonzero entries in the Jacobian, as computed by c05qsf.

11:
$\mathbf{iuser}\left(*\right)$ – Integer array
User Workspace

12:
$\mathbf{ruser}\left(*\right)$ – Real (Kind=nag_wp) array
User Workspace

iuser and
ruser are not used by
c05qsf, but are passed directly to
fcn and may be used to pass information to this routine.

13:
$\mathbf{ifail}$ – Integer
Input/Output

On entry:
ifail must be set to
$0$,
$1\text{or}1$. If you are unfamiliar with this argument you should refer to
Section 4 in the Introduction to the NAG Library FL Interface for details.
For environments where it might be inappropriate to halt program execution when an error is detected, the value
$1\text{or}1$ is recommended. If the output of error messages is undesirable, then the value
$1$ is recommended. Otherwise, if you are not familiar with this argument, the recommended value is
$0$.
When the value $\mathbf{1}\text{or}\mathbf{1}$ is used it is essential to test the value of ifail on exit.
On exit:
${\mathbf{ifail}}={\mathbf{0}}$ unless the routine detects an error or a warning has been flagged (see
Section 6).
6
Error Indicators and Warnings
If on entry
${\mathbf{ifail}}=0$ or
$1$, explanatory error messages are output on the current error message unit (as defined by
x04aaf).
Errors or warnings detected by the routine:
 ${\mathbf{ifail}}=2$

There have been at least
$200\times \left({\mathbf{n}}+1\right)$ calls to
fcn. Consider setting
${\mathbf{init}}=\mathrm{.FALSE.}$ and restarting the calculation from the point held in
x.
 ${\mathbf{ifail}}=3$

No further improvement in the solution is possible.
xtol is too small:
${\mathbf{xtol}}=\u2329\mathit{\text{value}}\u232a$.
 ${\mathbf{ifail}}=4$

The iteration is not making good progress. This failure exit may indicate that the system does not have a zero, or that the solution is very close to the origin (see
Section 7). Otherwise, rerunning
c05qsf from a different starting point may avoid the region of difficulty. The condition number of the Jacobian is
$\u2329\mathit{\text{value}}\u232a$.
 ${\mathbf{ifail}}=5$

iflag was set negative in
fcn.
${\mathbf{iflag}}=\u2329\mathit{\text{value}}\u232a$.
 ${\mathbf{ifail}}=6$

On entry, ${\mathbf{lrcomm}}=\u2329\mathit{\text{value}}\u232a$.
Constraint: ${\mathbf{lrcomm}}\ge \u2329\mathit{\text{value}}\u232a$.
 ${\mathbf{ifail}}=7$

On entry, ${\mathbf{licomm}}=\u2329\mathit{\text{value}}\u232a$.
Constraint: ${\mathbf{licomm}}\ge \u2329\mathit{\text{value}}\u232a$.
 ${\mathbf{ifail}}=9$

An internal error has occurred. Code $=\u2329\mathit{\text{value}}\u232a$.
 ${\mathbf{ifail}}=11$

On entry, ${\mathbf{n}}=\u2329\mathit{\text{value}}\u232a$.
Constraint: ${\mathbf{n}}>0$.
 ${\mathbf{ifail}}=12$

On entry, ${\mathbf{xtol}}=\u2329\mathit{\text{value}}\u232a$.
Constraint: ${\mathbf{xtol}}\ge 0.0$.
 ${\mathbf{ifail}}=99$
An unexpected error has been triggered by this routine. Please
contact
NAG.
See
Section 7 in the Introduction to the NAG Library FL Interface for further information.
 ${\mathbf{ifail}}=399$
Your licence key may have expired or may not have been installed correctly.
See
Section 8 in the Introduction to the NAG Library FL Interface for further information.
 ${\mathbf{ifail}}=999$
Dynamic memory allocation failed.
See
Section 9 in the Introduction to the NAG Library FL Interface for further information.
7
Accuracy
If
$\hat{x}$ is the true solution,
c05qsf tries to ensure that
If this condition is satisfied with
${\mathbf{xtol}}={10}^{k}$, then the larger components of
$x$ have
$k$ significant decimal digits. There is a danger that the smaller components of
$x$ may have large relative errors, but the fast rate of convergence of
c05qsf usually obviates this possibility.
If
xtol is less than
machine precision and the above test is satisfied with the
machine precision in place of
xtol, then the routine exits with
${\mathbf{ifail}}={\mathbf{3}}$.
Note: this convergence test is based purely on relative error, and may not indicate convergence if the solution is very close to the origin.
The convergence test assumes that the functions are reasonably well behaved. If this condition is not satisfied, then
c05qsf may incorrectly indicate convergence. The validity of the answer can be checked, for example, by rerunning
c05qsf with a lower value for
xtol.
8
Parallelism and Performance
c05qsf is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
c05qsf makes calls to BLAS and/or LAPACK routines, which may be threaded within the vendor library used by this implementation. Consult the documentation for the vendor library for further information.
Please consult the
X06 Chapter Introduction for information on how to control and interrogate the OpenMP environment used within this routine. Please also consult the
Users' Note for your implementation for any additional implementationspecific information.
Local workspace arrays of fixed lengths are allocated internally by c05qsf. The total size of these arrays amounts to $8\times n+2\times q$ real elements and $10\times n+2\times q+5$ integer elements where the integer $q$ is bounded by $8\times \mathit{nnz}$ and ${n}^{2}$ and depends on the sparsity pattern of the Jacobian.
The time required by c05qsf to solve a given problem depends on $n$, the behaviour of the functions, the accuracy requested and the starting point. The number of arithmetic operations executed by c05qsf to process each evaluation of the functions depends on the number of nonzero entries in the Jacobian. The timing of c05qsf is strongly influenced by the time spent evaluating the functions.
When
init is .TRUE., the dense Jacobian is first evaluated and that will take time proportional to
${n}^{2}$.
Ideally the problem should be scaled so that, at the solution, the function values are of comparable magnitude.
10
Example
This example determines the values
${x}_{1},\dots ,{x}_{9}$ which satisfy the tridiagonal equations:
It then perturbs the equations by a small amount and solves the new system.
10.1
Program Text
10.2
Program Data
None.
10.3
Program Results