NAG CL Interface
c05qcc (sys_func_expert)
1
Purpose
c05qcc is a comprehensive function that finds a solution of a system of nonlinear equations by a modification of the Powell hybrid method.
2
Specification
void 
c05qcc (
Integer n,
double x[],
double fvec[],
double xtol,
Integer maxfev,
Integer ml,
Integer mu,
double epsfcn,
Nag_ScaleType scale_mode,
double diag[],
double factor,
Integer nprint,
Integer *nfev,
double fjac[],
double r[],
double qtf[],
Nag_Comm *comm,
NagError *fail) 

The function may be called by the names: c05qcc, nag_roots_sys_func_expert or nag_zero_nonlin_eqns_expert.
3
Description
The system of equations is defined as:
c05qcc 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:
$\mathbf{fcn}$ – function, supplied by the user
External Function

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:
void 
fcn (Integer n,
const double x[],
double fvec[],
Nag_Comm *comm, Integer *iflag)



1:
$\mathbf{n}$ – Integer
Input

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

2:
$\mathbf{x}\left[{\mathbf{n}}\right]$ – const double
Input

On entry: the components of the point $x$ at which the functions must be evaluated.

3:
$\mathbf{fvec}\left[{\mathbf{n}}\right]$ – double
Input/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:
$\mathbf{comm}$ – Nag_Comm *
Pointer to structure of type Nag_Comm; the following members are relevant to
fcn.
 user – double *
 iuser – Integer *
 p – Pointer
The type Pointer will be
void *. Before calling
c05qcc you may allocate memory and initialize these pointers with various quantities for use by
fcn when called from
c05qcc (see
Section 3.1.1 in the Introduction to the NAG Library CL Interface).

5:
$\mathbf{iflag}$ – Integer *
Input/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.
Note: fcn should not return floatingpoint NaN (Not a Number) or infinity values, since these are not handled by
c05qcc. If your code inadvertently
does return any NaNs or infinities,
c05qcc is likely to produce unexpected results.

2:
$\mathbf{n}$ – Integer
Input

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

3:
$\mathbf{x}\left[{\mathbf{n}}\right]$ – double
Input/Output

On entry: an initial guess at the solution vector.
On exit: the final estimate of the solution vector.

4:
$\mathbf{fvec}\left[{\mathbf{n}}\right]$ – double
Output

On exit: the function values at the final point returned in
x.

5:
$\mathbf{xtol}$ – double
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
X02AJC.
Constraint:
${\mathbf{xtol}}\ge 0.0$.

6:
$\mathbf{maxfev}$ – Integer
Input

On entry: the maximum number of calls to
fcn with
${\mathbf{iflag}}\ne 0$.
c05qcc will exit with
${\mathbf{fail}}\mathbf{.}\mathbf{code}=$ NE_TOO_MANY_FEVALS, 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:
$\mathbf{ml}$ – Integer
Input

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:
$\mathbf{mu}$ – Integer
Input

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:
$\mathbf{epsfcn}$ – double
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
X02AJC) then
machine precision is used. Consequently a value of
$0.0$ will often be suitable.
Suggested value:
${\mathbf{epsfcn}}=0.0$.

10:
$\mathbf{scale\_mode}$ – Nag_ScaleType
Input

On entry: indicates whether or not you have provided scaling factors in
diag.
If
${\mathbf{scale\_mode}}=\mathrm{Nag\_ScaleProvided}$, the scaling must have been specified in
diag.
Otherwise, if ${\mathbf{scale\_mode}}=\mathrm{Nag\_NoScaleProvided}$, the variables will be scaled internally.
Constraint:
${\mathbf{scale\_mode}}=\mathrm{Nag\_NoScaleProvided}$ or $\mathrm{Nag\_ScaleProvided}$.

11:
$\mathbf{diag}\left[{\mathbf{n}}\right]$ – double
Input/Output

On entry: if
${\mathbf{scale\_mode}}=\mathrm{Nag\_ScaleProvided}$,
diag must contain multiplicative scale factors for the variables.
If
${\mathbf{scale\_mode}}=\mathrm{Nag\_NoScaleProvided}$,
diag need not be set.
Constraint:
if ${\mathbf{scale\_mode}}=\mathrm{Nag\_ScaleProvided}$, ${\mathbf{diag}}\left[\mathit{i}1\right]>0.0$, for $\mathit{i}=1,2,\dots ,n$.
On exit: the scale factors actually used (computed internally if ${\mathbf{scale\_mode}}=\mathrm{Nag\_NoScaleProvided}$).

12:
$\mathbf{factor}$ – double
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:
$\mathbf{nprint}$ – Integer
Input

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 c05qcc.

14:
$\mathbf{nfev}$ – Integer *
Output

On exit: the number of calls made to
fcn with
${\mathbf{iflag}}>0$.

15:
$\mathbf{fjac}\left[{\mathbf{n}}\times {\mathbf{n}}\right]$ – double
Output

Note: the $\left(i,j\right)$th element of the matrix is stored in ${\mathbf{fjac}}\left[\left(j1\right)\times {\mathbf{n}}+i1\right]$.
On exit: the orthogonal matrix $Q$ produced by the $QR$ factorization of the final approximate Jacobian.

16:
$\mathbf{r}\left[{\mathbf{n}}\times \left({\mathbf{n}}+1\right)/2\right]$ – double
Output

On exit: the upper triangular matrix $R$ produced by the $QR$ factorization of the final approximate Jacobian, stored rowwise.

17:
$\mathbf{qtf}\left[{\mathbf{n}}\right]$ – double
Output

On exit: the vector ${Q}^{\mathrm{T}}f$.

18:
$\mathbf{comm}$ – Nag_Comm *

The NAG communication argument (see
Section 3.1.1 in the Introduction to the NAG Library CL Interface).

19:
$\mathbf{fail}$ – NagError *
Input/Output

The NAG error argument (see
Section 7 in the Introduction to the NAG Library CL Interface).
6
Error Indicators and Warnings
 NE_ALLOC_FAIL

Dynamic memory allocation failed.
See
Section 3.1.2 in the Introduction to the NAG Library CL Interface for further information.
 NE_BAD_PARAM

On entry, argument $\u2329\mathit{\text{value}}\u232a$ had an illegal value.
 NE_DIAG_ELEMENTS

On entry,
${\mathbf{scale\_mode}}=\mathrm{Nag\_ScaleProvided}$ and
diag contained a nonpositive element.
 NE_INT

On entry, ${\mathbf{maxfev}}=\u2329\mathit{\text{value}}\u232a$.
Constraint: ${\mathbf{maxfev}}>0$.
On entry, ${\mathbf{ml}}=\u2329\mathit{\text{value}}\u232a$.
Constraint: ${\mathbf{ml}}\ge 0$.
On entry, ${\mathbf{mu}}=\u2329\mathit{\text{value}}\u232a$.
Constraint: ${\mathbf{mu}}\ge 0$.
On entry, ${\mathbf{n}}=\u2329\mathit{\text{value}}\u232a$.
Constraint: ${\mathbf{n}}>0$.
 NE_INTERNAL_ERROR

An internal error has occurred in this function. Check the function call and any array sizes. If the call is correct then please contact
NAG for assistance.
See
Section 7.5 in the Introduction to the NAG Library CL Interface for further information.
 NE_NO_IMPROVEMENT

The iteration is not making good progress, as measured by the improvement from the last $\u2329\mathit{\text{value}}\u232a$ iterations.
The iteration is not making good progress, as measured by the improvement from the last $\u2329\mathit{\text{value}}\u232a$ Jacobian evaluations.
 NE_NO_LICENCE

Your licence key may have expired or may not have been installed correctly.
See
Section 8 in the Introduction to the NAG Library CL Interface for further information.
 NE_REAL

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

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.
 NE_TOO_SMALL

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

iflag was set negative in
fcn.
${\mathbf{iflag}}=\u2329\mathit{\text{value}}\u232a$.
7
Accuracy
If
$\hat{x}$ is the true solution and
$D$ denotes the diagonal matrix whose entries are defined by the array
diag, then
c05qcc 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
c05qcc 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 function exits with
${\mathbf{fail}}\mathbf{.}\mathbf{code}=$ NE_TOO_SMALL.
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
c05qcc may incorrectly indicate convergence. The validity of the answer can be checked, for example, by rerunning
c05qcc with a lower value for
xtol.
8
Parallelism and Performance
c05qcc is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
c05qcc 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 function. Please also consult the
Users' Note for your implementation for any additional implementationspecific information.
Local workspace arrays of fixed lengths are allocated internally by c05qcc. The total size of these arrays amounts to $4\times n$ double elements.
The time required by c05qcc 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 c05qcc to process each evaluation of the functions is approximately $11.5\times {n}^{2}$. The timing of c05qcc 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
10.2
Program Data
None.
10.3
Program Results