NAG FL Interface
d01ajf (dim1_fin_bad)
1
Purpose
d01ajf is a general purpose integrator which calculates an approximation to the integral of a function
$f\left(x\right)$ over a finite interval
$\left[a,b\right]$:
2
Specification
Fortran Interface
Subroutine d01ajf ( 
f, a, b, epsabs, epsrel, result, abserr, w, lw, iw, liw, ifail) 
Integer, Intent (In) 
:: 
lw, liw 
Integer, Intent (Inout) 
:: 
ifail 
Integer, Intent (Out) 
:: 
iw(liw) 
Real (Kind=nag_wp), External 
:: 
f 
Real (Kind=nag_wp), Intent (In) 
:: 
a, b, epsabs, epsrel 
Real (Kind=nag_wp), Intent (Out) 
:: 
result, abserr, w(lw) 

C Header Interface
#include <nag.h>
void 
d01ajf_ ( double (NAG_CALL *f)(const double *x), const double *a, const double *b, const double *epsabs, const double *epsrel, double *result, double *abserr, double w[], const Integer *lw, Integer iw[], const Integer *liw, Integer *ifail) 

C++ Header Interface
#include <nag.h> extern "C" {
void 
d01ajf_ ( double (NAG_CALL *f)(const double &x), const double &a, const double &b, const double &epsabs, const double &epsrel, double &result, double &abserr, double w[], const Integer &lw, Integer iw[], const Integer &liw, Integer &ifail) 
}

The routine may be called by the names d01ajf or nagf_quad_dim1_fin_bad.
3
Description
d01ajf is based on the QUADPACK routine QAGS (see
Piessens et al. (1983)). It is an adaptive routine, using the Gauss
$10$point and Kronrod
$21$point rules. The algorithm, described in
de Doncker (1978), incorporates a global acceptance criterion (as defined by
Malcolm and Simpson (1976)) together with the
$\epsilon $algorithm (see
Wynn (1956)) to perform extrapolation. The local error estimation is described in
Piessens et al. (1983).
The routine is suitable as a general purpose integrator, and can be used when the integrand has singularities, especially when these are of algebraic or logarithmic type.
d01ajf requires you to supply a function to evaluate the integrand at a single point.
The routine
d01atf uses an identical algorithm but requires you to supply a subroutine to evaluate the integrand at an array of points. Therefore
d01atf may be more efficient for some problem types and some machine architectures.
4
References
de Doncker E (1978) An adaptive extrapolation algorithm for automatic integration ACM SIGNUM Newsl. 13(2) 12–18
Malcolm M A and Simpson R B (1976) Local versus global strategies for adaptive quadrature ACM Trans. Math. Software 1 129–146
Piessens R, de Doncker–Kapenga E, Überhuber C and Kahaner D (1983) QUADPACK, A Subroutine Package for Automatic Integration Springer–Verlag
Wynn P (1956) On a device for computing the ${e}_{m}\left({S}_{n}\right)$ transformation Math. Tables Aids Comput. 10 91–96
5
Arguments

1:
$\mathbf{f}$ – real (Kind=nag_wp) Function, supplied by the user.
External Procedure

f must return the value of the integrand
$f$ at a given point.
The specification of
f is:
Fortran Interface
Real (Kind=nag_wp) 
:: 
f 
Real (Kind=nag_wp), Intent (In) 
:: 
x 

C Header Interface
double 
f_ (const double *x) 

C++ Header Interface
#include <nag.h> extern "C" {
double 
f_ (const double &x) 
}


1:
$\mathbf{x}$ – Real (Kind=nag_wp)
Input

On entry: the point at which the integrand $f$ must be evaluated.
f must either be a module subprogram USEd by, or declared as EXTERNAL in, the (sub)program from which
d01ajf is called. Arguments denoted as
Input must
not be changed by this procedure.
Note: f should not return floatingpoint NaN (Not a Number) or infinity values, since these are not handled by
d01ajf. If your code inadvertently
does return any NaNs or infinities,
d01ajf is likely to produce unexpected results.

2:
$\mathbf{a}$ – Real (Kind=nag_wp)
Input

On entry: $a$, the lower limit of integration.

3:
$\mathbf{b}$ – Real (Kind=nag_wp)
Input

On entry: $b$, the upper limit of integration. It is not necessary that $a<b$.

4:
$\mathbf{epsabs}$ – Real (Kind=nag_wp)
Input

On entry: the absolute accuracy required. If
epsabs is negative, the absolute value is used. See
Section 7.

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

On entry: the relative accuracy required. If
epsrel is negative, the absolute value is used. See
Section 7.

6:
$\mathbf{result}$ – Real (Kind=nag_wp)
Output

On exit: the approximation to the integral $I$.

7:
$\mathbf{abserr}$ – Real (Kind=nag_wp)
Output

On exit: an estimate of the modulus of the absolute error, which should be an upper bound for $\leftI{\mathbf{result}}\right$.

8:
$\mathbf{w}\left({\mathbf{lw}}\right)$ – Real (Kind=nag_wp) array
Output

On exit: details of the computation see
Section 9 for more information.

9:
$\mathbf{lw}$ – Integer
Input

On entry: the dimension of the array
w as declared in the (sub)program from which
d01ajf is called. The value of
lw (together with that of
liw) imposes a bound on the number of subintervals into which the interval of integration may be divided by the routine. The number of subintervals cannot exceed
${\mathbf{lw}}/4$. The more difficult the integrand, the larger
lw should be.
Suggested value:
${\mathbf{lw}}=800$ to $2000$ is adequate for most problems.
Constraint:
${\mathbf{lw}}\ge 4$.

10:
$\mathbf{iw}\left({\mathbf{liw}}\right)$ – Integer array
Output

On exit: ${\mathbf{iw}}\left(1\right)$ contains the actual number of subintervals used. The rest of the array is used as workspace.

11:
$\mathbf{liw}$ – Integer
Input

On entry: the dimension of the array
iw as declared in the (sub)program from which
d01ajf is called. The number of subintervals into which the interval of integration may be divided cannot exceed
liw.
Suggested value:
${\mathbf{liw}}={\mathbf{lw}}/4$.
Constraint:
${\mathbf{liw}}\ge 1$.

12:
$\mathbf{ifail}$ – Integer
Input/Output

On 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 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:
Note: in some cases d01ajf may return useful information.
 ${\mathbf{ifail}}=1$

The maximum number of subdivisions allowed with the given workspace has been reached without the accuracy requirements being achieved. Look at the integrand in order to determine the integration difficulties. If the position of a local difficulty within the interval can be determined (e.g., a singularity of the integrand or its derivative, a peak, a discontinuity, etc.) you will probably gain from splitting up the interval at this point and calling the integrator on the subranges. If necessary, another integrator, which is designed for handling the type of difficulty involved, must be used. Alternatively, consider relaxing the accuracy requirements specified by
epsabs and
epsrel, or increasing the amount of workspace.
 ${\mathbf{ifail}}=2$

Roundoff error prevents the requested tolerance from being achieved: ${\mathbf{epsabs}}=\u2329\mathit{\text{value}}\u232a$ and ${\mathbf{epsrel}}=\u2329\mathit{\text{value}}\u232a$.
 ${\mathbf{ifail}}=3$

Extremely bad integrand behaviour occurs around the subinterval $\left(\u2329\mathit{\text{value}}\u232a,\u2329\mathit{\text{value}}\u232a\right)$. The same advice applies as in the case of ${\mathbf{ifail}}={\mathbf{1}}$.
 ${\mathbf{ifail}}=4$

Roundoff error is detected in the extrapolation table. The requested tolerance cannot be achieved because the extrapolation does not increase the accuracy satisfactorily; the returned result is the best that can be obtained. The same advice applies as in the case of ${\mathbf{ifail}}={\mathbf{1}}$.
 ${\mathbf{ifail}}=5$

The integral is probably divergent or slowly convergent.
 ${\mathbf{ifail}}=6$

On entry, ${\mathbf{liw}}=\u2329\mathit{\text{value}}\u232a$.
Constraint: ${\mathbf{liw}}\ge 1$.
On entry, ${\mathbf{lw}}=\u2329\mathit{\text{value}}\u232a$.
Constraint: ${\mathbf{lw}}\ge 4$.
 ${\mathbf{ifail}}=99$
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
d01ajf cannot guarantee, but in practice usually achieves, the following accuracy:
where
and
epsabs and
epsrel are userspecified absolute and relative error tolerances. Moreover, it returns the quantity
abserr which, in normal circumstances, satisfies
8
Parallelism and Performance
d01ajf is not threaded in any implementation.
The time taken by d01ajf depends on the integrand and the accuracy required.
If
${\mathbf{ifail}}\ne {\mathbf{0}}$
on exit, then you may wish to examine the contents of the
array
w,
which contains the end points of the subintervals used by
d01ajf along with the integral contributions and error estimates over the subintervals.
Specifically, for
$i=1,2,\dots ,n$, let
${r}_{i}$ denote the approximation to the value of the integral over the subinterval
$\left[{a}_{i},{b}_{i}\right]$ in the partition of
$\left[a,b\right]$ and
${e}_{i}$ be the corresponding absolute error estimate. Then,
$\underset{{a}_{i}}{\overset{{b}_{i}}{\int}}}f\left(x\right)dx\simeq {r}_{i$ and
${\mathbf{result}}={\displaystyle \sum _{i=1}^{n}}{r}_{i}$, unless
d01ajf terminates while testing for divergence of the integral (see Section 3.4.3 of
Piessens et al. (1983)). In this case,
result (and
abserr) are taken to be the values returned from the extrapolation process. The value of
$n$ is returned in
${\mathbf{iw}}\left(1\right)$, and the
values
${a}_{i}$,
${b}_{i}$,
${e}_{i}$ and
${r}_{i}$ are stored consecutively in the
array
w,
that is:
 ${a}_{i}={\mathbf{w}}\left(i\right)$,
 ${b}_{i}={\mathbf{w}}\left(n+i\right)$,
 ${e}_{i}={\mathbf{w}}\left(2n+i\right)$ and
 ${r}_{i}={\mathbf{w}}\left(3n+i\right)$.
10
Example
10.1
Program Text
10.2
Program Data
None.
10.3
Program Results