NAG Library Routine Document
c05qcf (sys_func_expert)
1
Purpose
c05qcf is a comprehensive routine that finds a solution of a system of nonlinear equations by a modification of the Powell hybrid method.
2
Specification
Fortran Interface
Subroutine c05qcf ( 
fcn, n, x, fvec, xtol, maxfev, ml, mu, epsfcn, mode, diag, factor, nprint, nfev, fjac, r, qtf, iuser, ruser, ifail) 
Integer, Intent (In)  ::  n, maxfev, ml, mu, mode, nprint  Integer, Intent (Inout)  ::  iuser(*), ifail  Integer, Intent (Out)  ::  nfev  Real (Kind=nag_wp), Intent (In)  ::  xtol, epsfcn, factor  Real (Kind=nag_wp), Intent (Inout)  ::  x(n), diag(n), ruser(*)  Real (Kind=nag_wp), Intent (Out)  ::  fvec(n), fjac(n,n), r(n*(n+1)/2), qtf(n)  External  ::  fcn 

C Header Interface
#include <nagmk26.h>
void 
c05qcf_ ( void (NAG_CALL *fcn)(const Integer *n, const double x[], double fvec[], Integer iuser[], double ruser[], Integer *iflag), const Integer *n, double x[], double fvec[], const double *xtol, const Integer *maxfev, const Integer *ml, const Integer *mu, const double *epsfcn, const Integer *mode, double diag[], const double *factor, const Integer *nprint, Integer *nfev, double fjac[], double r[], double qtf[], Integer iuser[], double ruser[], Integer *ifail) 

3
Description
The system of equations is defined as:
c05qcf is based on the MINPACK routine HYBRD (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 rank1 method of Broyden. At the starting point, the Jacobian is approximated by forward differences, but these are not used again until the rank1 method fails to produce satisfactory progress. For more details see
Powell (1970).
4
References
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
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
$x$, unless
${\mathbf{iflag}}=0$ on entry to
fcn.
The specification of
fcn is:
Fortran Interface
Integer, Intent (In)  ::  n  Integer, Intent (Inout)  ::  iuser(*), iflag  Real (Kind=nag_wp), Intent (In)  ::  x(n)  Real (Kind=nag_wp), Intent (Inout)  ::  fvec(n), ruser(*) 

C Header Interface
#include <nagmk26.h>
void 
fcn (const Integer *n, const double x[], double fvec[], Integer iuser[], double ruser[], Integer *iflag) 

 1: $\mathbf{n}$ – IntegerInput

On entry: $n$, the number of equations.
 2: $\mathbf{x}\left({\mathbf{n}}\right)$ – Real (Kind=nag_wp) arrayInput

On entry: the components of the point $x$ at which the functions must be evaluated.
 3: $\mathbf{fvec}\left({\mathbf{n}}\right)$ – Real (Kind=nag_wp) arrayInput/Output

On entry: if
${\mathbf{iflag}}=0$,
fvec contains the function values
${f}_{i}\left(x\right)$ and must not be changed.
On exit: if
${\mathbf{iflag}}>0$ on entry,
fvec must contain the function values
${f}_{i}\left(x\right)$ (unless
iflag is set to a negative value by
fcn).
 4: $\mathbf{iuser}\left(*\right)$ – Integer arrayUser Workspace
 5: $\mathbf{ruser}\left(*\right)$ – Real (Kind=nag_wp) arrayUser Workspace

fcn is called with the arguments
iuser and
ruser as supplied to
c05qcf. You should use the arrays
iuser and
ruser to supply information to
fcn.
 6: $\mathbf{iflag}$ – IntegerInput/Output

On entry:
${\mathbf{iflag}}\ge 0$.
 ${\mathbf{iflag}}=0$
 x and fvec are available for printing (see nprint).
 ${\mathbf{iflag}}>0$
 fvec must be updated.
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
c05qcf 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
c05qcf. If your code inadvertently
does return any NaNs or infinities,
c05qcf is likely to produce unexpected results.
 2: $\mathbf{n}$ – IntegerInput

On entry: $n$, the number of equations.
Constraint:
${\mathbf{n}}>0$.
 3: $\mathbf{x}\left({\mathbf{n}}\right)$ – Real (Kind=nag_wp) arrayInput/Output

On entry: an initial guess at the solution vector.
On exit: the final estimate of the solution vector.
 4: $\mathbf{fvec}\left({\mathbf{n}}\right)$ – Real (Kind=nag_wp) arrayOutput

On exit: the function values at the final point returned in
x.
 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: $\mathbf{maxfev}$ – IntegerInput

On entry: the maximum number of calls to
fcn with
${\mathbf{iflag}}\ne 0$.
c05qcf will exit with
${\mathbf{ifail}}={\mathbf{2}}$, if, at the end of an iteration, the number of calls to
fcn exceeds
maxfev.
Suggested value:
${\mathbf{maxfev}}=200\times \left({\mathbf{n}}+1\right)$.
Constraint:
${\mathbf{maxfev}}>0$.
 7: $\mathbf{ml}$ – IntegerInput

On entry: the number of subdiagonals within the band of the Jacobian matrix. (If the Jacobian is not banded, or you are unsure, set ${\mathbf{ml}}={\mathbf{n}}1$.)
Constraint:
${\mathbf{ml}}\ge 0$.
 8: $\mathbf{mu}$ – IntegerInput

On entry: the number of superdiagonals within the band of the Jacobian matrix. (If the Jacobian is not banded, or you are unsure, set ${\mathbf{mu}}={\mathbf{n}}1$.)
Constraint:
${\mathbf{mu}}\ge 0$.
 9: $\mathbf{epsfcn}$ – Real (Kind=nag_wp)Input

On entry: a rough estimate of the largest relative error in the functions. It is used in determining a suitable step for a forward difference approximation to the Jacobian. If
epsfcn is less than
machine precision (returned by
x02ajf) then
machine precision is used. Consequently a value of
$0.0$ will often be suitable.
Suggested value:
${\mathbf{epsfcn}}=0.0$.
 10: $\mathbf{mode}$ – IntegerInput

On entry: indicates whether or not you have provided scaling factors in
diag.
If
${\mathbf{mode}}=2$, the scaling must have been specified in
diag.
Otherwise, if ${\mathbf{mode}}=1$, the variables will be scaled internally.
Constraint:
${\mathbf{mode}}=1$ or $2$.
 11: $\mathbf{diag}\left({\mathbf{n}}\right)$ – Real (Kind=nag_wp) arrayInput/Output

On entry: if
${\mathbf{mode}}=2$,
diag must contain multiplicative scale factors for the variables.
If
${\mathbf{mode}}=1$,
diag need not be set.
Constraint:
if ${\mathbf{mode}}=2$, ${\mathbf{diag}}\left(\mathit{i}\right)>0.0$, for $\mathit{i}=1,2,\dots ,n$.
On exit: the scale factors actually used (computed internally if ${\mathbf{mode}}=1$).
 12: $\mathbf{factor}$ – Real (Kind=nag_wp)Input

On entry: a quantity to be used in determining the initial step bound. In most cases,
factor should lie between
$0.1$ and
$100.0$. (The step bound is
${\mathbf{factor}}\times {\Vert {\mathbf{diag}}\times {\mathbf{x}}\Vert}_{2}$ if this is nonzero; otherwise the bound is
factor.)
Suggested value:
${\mathbf{factor}}=100.0$.
Constraint:
${\mathbf{factor}}>0.0$.
 13: $\mathbf{nprint}$ – IntegerInput

On entry: indicates whether (and how often) special calls to
fcn, with
iflag set to
$0$, are to be made for printing purposes.
 ${\mathbf{nprint}}\le 0$
 No calls are made.
 ${\mathbf{nprint}}>0$
 fcn is called at the beginning of the first iteration, every nprint iterations thereafter and immediately before the return from c05qcf.
 14: $\mathbf{nfev}$ – IntegerOutput

On exit: the number of calls made to
fcn with
${\mathbf{iflag}}>0$.
 15: $\mathbf{fjac}\left({\mathbf{n}},{\mathbf{n}}\right)$ – Real (Kind=nag_wp) arrayOutput

On exit: the orthogonal matrix $Q$ produced by the $QR$ factorization of the final approximate Jacobian.
 16: $\mathbf{r}\left({\mathbf{n}}\times \left({\mathbf{n}}+1\right)/2\right)$ – Real (Kind=nag_wp) arrayOutput

On exit: the upper triangular matrix $R$ produced by the $QR$ factorization of the final approximate Jacobian, stored rowwise.
 17: $\mathbf{qtf}\left({\mathbf{n}}\right)$ – Real (Kind=nag_wp) arrayOutput

On exit: the vector ${Q}^{\mathrm{T}}f$.
 18: $\mathbf{iuser}\left(*\right)$ – Integer arrayUser Workspace
 19: $\mathbf{ruser}\left(*\right)$ – Real (Kind=nag_wp) arrayUser Workspace

iuser and
ruser are not used by
c05qcf, but are passed directly to
fcn and may be used to pass information to this routine.
 20: $\mathbf{ifail}$ – IntegerInput/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 3.4 in How to Use the NAG Library and its Documentation 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
maxfev calls to
fcn:
${\mathbf{maxfev}}=\u2329\mathit{\text{value}}\u232a$. Consider restarting the calculation from the final 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, as measured by the improvement from the last $\u2329\mathit{\text{value}}\u232a$ Jacobian evaluations.
 ${\mathbf{ifail}}=5$

The iteration is not making good progress, as measured by the improvement from the last $\u2329\mathit{\text{value}}\u232a$ iterations.
 ${\mathbf{ifail}}=6$

iflag was set negative in
fcn.
${\mathbf{iflag}}=\u2329\mathit{\text{value}}\u232a$.
 ${\mathbf{ifail}}=11$

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: ${\mathbf{xtol}}\ge 0.0$.
 ${\mathbf{ifail}}=13$

On entry, ${\mathbf{mode}}=\u2329\mathit{\text{value}}\u232a$.
Constraint: ${\mathbf{mode}}=1$ or $2$.
 ${\mathbf{ifail}}=14$

On entry, ${\mathbf{factor}}=\u2329\mathit{\text{value}}\u232a$.
Constraint: ${\mathbf{factor}}>0.0$.
 ${\mathbf{ifail}}=15$

On entry,
${\mathbf{mode}}=2$ and
diag contained a nonpositive element.
 ${\mathbf{ifail}}=16$

On entry, ${\mathbf{ml}}=\u2329\mathit{\text{value}}\u232a$.
Constraint: ${\mathbf{ml}}\ge 0$.
 ${\mathbf{ifail}}=17$

On entry, ${\mathbf{mu}}=\u2329\mathit{\text{value}}\u232a$.
Constraint: ${\mathbf{mu}}\ge 0$.
 ${\mathbf{ifail}}=18$

On entry, ${\mathbf{maxfev}}=\u2329\mathit{\text{value}}\u232a$.
Constraint: ${\mathbf{maxfev}}>0$.
 ${\mathbf{ifail}}=99$
An unexpected error has been triggered by this routine. Please
contact
NAG.
See
Section 3.9 in How to Use the NAG Library and its Documentation for further information.
 ${\mathbf{ifail}}=399$
Your licence key may have expired or may not have been installed correctly.
See
Section 3.8 in How to Use the NAG Library and its Documentation for further information.
 ${\mathbf{ifail}}=999$
Dynamic memory allocation failed.
See
Section 3.7 in How to Use the NAG Library and its Documentation for further information.
A value of
${\mathbf{ifail}}={\mathbf{4}}$ or
${\mathbf{5}}$ 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
c05qcf from a different starting point may avoid the region of difficulty.
7
Accuracy
If
$\hat{x}$ is the true solution and
$D$ denotes the diagonal matrix whose entries are defined by the array
diag, then
c05qcf tries to ensure that
If this condition is satisfied with
${\mathbf{xtol}}={10}^{k}$, then the larger components of
$Dx$ have
$k$ significant decimal digits. There is a danger that the smaller components of
$Dx$ may have large relative errors, but the fast rate of convergence of
c05qcf 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
c05qcf may incorrectly indicate convergence. The validity of the answer can be checked, for example, by rerunning
c05qcf with a lower value for
xtol.
8
Parallelism and Performance
c05qcf is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
c05qcf 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 c05qcf. The total size of these arrays amounts to $4\times n$ real elements.
The time required by c05qcf 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 c05qcf to process each evaluation of the functions is approximately $11.5\times {n}^{2}$. The timing of c05qcf is strongly influenced by the time spent evaluating the functions.
Ideally the problem should be scaled so that, at the solution, the function values are of comparable magnitude.
The number of function evaluations required to evaluate the Jacobian may be reduced if you can specify
ml and
mu accurately.
10
Example
This example determines the values
${x}_{1},\dots ,{x}_{9}$ which satisfy the tridiagonal equations:
10.1
Program Text
Program Text (c05qcfe.f90)
10.2
Program Data
None.
10.3
Program Results
Program Results (c05qcfe.r)