NAG FL Interface
c05rdf (sys_deriv_rcomm)
1
Purpose
c05rdf is a comprehensive reverse communication routine that finds a solution of a system of nonlinear equations by a modification of the Powell hybrid method. You must provide the Jacobian.
2
Specification
Fortran Interface
Subroutine c05rdf ( 
irevcm, n, x, fvec, fjac, xtol, mode, diag, factor, r, qtf, iwsav, rwsav, ifail) 
Integer, Intent (In) 
:: 
n, mode 
Integer, Intent (Inout) 
:: 
irevcm, iwsav(17), ifail 
Real (Kind=nag_wp), Intent (In) 
:: 
xtol, factor 
Real (Kind=nag_wp), Intent (Inout) 
:: 
x(n), fvec(n), fjac(n,n), diag(n), r(n*(n+1)/2), qtf(n), rwsav(4*n+10) 

C Header Interface
#include <nag.h>
void 
c05rdf_ (Integer *irevcm, const Integer *n, double x[], double fvec[], double fjac[], const double *xtol, const Integer *mode, double diag[], const double *factor, double r[], double qtf[], Integer iwsav[], double rwsav[], Integer *ifail) 

C++ Header Interface
#include <nag.h> extern "C" {
void 
c05rdf_ (Integer &irevcm, const Integer &n, double x[], double fvec[], double fjac[], const double &xtol, const Integer &mode, double diag[], const double &factor, double r[], double qtf[], Integer iwsav[], double rwsav[], Integer &ifail) 
}

The routine may be called by the names c05rdf or nagf_roots_sys_deriv_rcomm.
3
Description
The system of equations is defined as:
c05rdf is based on the MINPACK routine HYBRJ (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. 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
Note: this routine uses
reverse communication. Its use involves an initial entry, intermediate exits and reentries, and a final exit, as indicated by the argument
irevcm. Between intermediate exits and reentries,
all arguments other than fvec and fjac must remain unchanged.

1:
$\mathbf{irevcm}$ – Integer
Input/Output

On initial entry: must have the value $0$.
On intermediate exit:
specifies what action you must take before reentering
c05rdf with
irevcm unchanged. The value of
irevcm should be interpreted as follows:
 ${\mathbf{irevcm}}=1$
 Indicates the start of a new iteration. No action is required by you, but x and fvec are available for printing.
 ${\mathbf{irevcm}}=2$
 Indicates that before reentry to c05rdf, fvec must contain the function values ${f}_{i}\left(x\right)$.
 ${\mathbf{irevcm}}=3$
 Indicates that before reentry to c05rdf,
${\mathbf{fjac}}\left(\mathit{i},\mathit{j}\right)$ must contain the value of $\frac{\partial {f}_{\mathit{i}}}{\partial {x}_{\mathit{j}}}$ at the point $x$, for $\mathit{i}=1,2,\dots ,n$ and $\mathit{j}=1,2,\dots ,n$.
On final exit: ${\mathbf{irevcm}}=0$ and the algorithm has terminated.
Constraint:
${\mathbf{irevcm}}=0$, $1$, $2$ or $3$.
Note: any values you return to c05rdf as part of the reverse communication procedure should not include floatingpoint NaN (Not a Number) or infinity values, since these are not handled by c05rdf. If your code does inadvertently return any NaNs or infinities, c05rdf 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 initial entry: an initial guess at the solution vector.
On intermediate exit:
contains the current point.
On final exit: the final estimate of the solution vector.

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

On initial entry: need not be set.
On intermediate reentry: if
${\mathbf{irevcm}}\ne 2$,
fvec must not be changed.
If
${\mathbf{irevcm}}=2$,
fvec must be set to the values of the functions computed at the current point
x.
On final exit: the function values at the final point,
x.

5:
$\mathbf{fjac}\left({\mathbf{n}},{\mathbf{n}}\right)$ – Real (Kind=nag_wp) array
Input/Output

On initial entry: need not be set.
On intermediate reentry: if
${\mathbf{irevcm}}\ne 3$,
fjac must not be changed.
If ${\mathbf{irevcm}}=3$,
${\mathbf{fjac}}\left(\mathit{i},\mathit{j}\right)$ must contain the value of $\frac{\partial {f}_{\mathit{i}}}{\partial {x}_{\mathit{j}}}$ at the point $x$, for $\mathit{i}=1,2,\dots ,n$ and $\mathit{j}=1,2,\dots ,n$.
On final exit: the orthogonal matrix $Q$ produced by the $QR$ factorization of the final approximate Jacobian.

6:
$\mathbf{xtol}$ – Real (Kind=nag_wp)
Input

On initial 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:
${\mathbf{xtol}}\ge 0.0$.

7:
$\mathbf{mode}$ – Integer
Input

On initial entry: indicates whether or not you have provided scaling factors in
diag.
If
${\mathbf{mode}}=2$, the scaling must have been supplied in
diag.
Otherwise, if ${\mathbf{mode}}=1$, the variables will be scaled internally.
Constraint:
${\mathbf{mode}}=1$ or $2$.

8:
$\mathbf{diag}\left({\mathbf{n}}\right)$ – Real (Kind=nag_wp) array
Input/Output

On initial 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 intermediate exit:
diag must not be changed.
On final exit: the scale factors actually used (computed internally if ${\mathbf{mode}}=1$).

9:
$\mathbf{factor}$ – Real (Kind=nag_wp)
Input

On initial 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:
${\mathbf{factor}}>0.0$.

10:
$\mathbf{r}\left({\mathbf{n}}\times \left({\mathbf{n}}+1\right)/2\right)$ – Real (Kind=nag_wp) array
Input/Output

On initial entry: need not be set.
On intermediate exit:
must not be changed.
On final exit: the upper triangular matrix $R$ produced by the $QR$ factorization of the final approximate Jacobian, stored rowwise.

11:
$\mathbf{qtf}\left({\mathbf{n}}\right)$ – Real (Kind=nag_wp) array
Input/Output

On initial entry: need not be set.
On intermediate exit:
must not be changed.
On final exit: the vector ${Q}^{\mathrm{T}}f$.

12:
$\mathbf{iwsav}\left(17\right)$ – Integer array
Communication Array

13:
$\mathbf{rwsav}\left(4\times {\mathbf{n}}+10\right)$ – Real (Kind=nag_wp) array
Communication Array

The arrays
iwsav and
rwsav must not be altered between calls to
c05rdf.

14:
$\mathbf{ifail}$ – Integer
Input/Output

On initial entry:
ifail must be set to
$0$,
$1$ or
$1$ to set behaviour on detection of an error; these values have no effect when no error is detected.
A value of $0$ causes the printing of an error message and program execution will be halted; otherwise program execution continues. A value of $1$ means that an error message is printed while a value of $1$ means that it is not.
If halting is not appropriate, the value
$1$ or
$1$ is recommended. If message printing is undesirable, then the value
$1$ is recommended. Otherwise, the value
$1$ is recommended since useful values can be provided in some output arguments even when
${\mathbf{ifail}}\ne {\mathbf{0}}$ on exit.
When the value $\mathbf{1}$ or $\mathbf{1}$ is used it is essential to test the value of ifail on exit.
On final 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:
 ${\mathbf{ifail}}=2$

On entry, ${\mathbf{irevcm}}=\u2329\mathit{\text{value}}\u232a$.
Constraint: ${\mathbf{irevcm}}=0$, $1$, $2$ or $3$.
 ${\mathbf{ifail}}=3$

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. 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
c05rdf from a different starting point may avoid the region of difficulty.
 ${\mathbf{ifail}}=5$

The iteration is not making good progress, as measured by the improvement from the last
$\u2329\mathit{\text{value}}\u232a$ iterations. 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
c05rdf from a different starting point may avoid the region of difficulty.
 ${\mathbf{ifail}}=11$

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.
 ${\mathbf{ifail}}=99$
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 and
$D$ denotes the diagonal matrix whose entries are defined by the array
diag, then
c05rdf 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
c05rdf 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 and the Jacobian are coded consistently and that the functions are reasonably well behaved. If these conditions are not satisfied, then
c05rdf may incorrectly indicate convergence. The coding of the Jacobian can be checked using
c05zdf. If the Jacobian is coded correctly, then the validity of the answer can be checked by rerunning
c05rdf with a lower value for
xtol.
8
Parallelism and Performance
c05rdf is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
c05rdf 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.
The time required by c05rdf 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 c05rdf is approximately $11.5\times {n}^{2}$ to process each evaluation of the functions and approximately $1.3\times {n}^{3}$ to process each evaluation of the Jacobian. The timing of c05rdf 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.
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