# NAG Library Routine Document

## 1Purpose

d01atf is a general purpose integrator which calculates an approximation to the integral of a function $f\left(x\right)$ over a finite interval $\left[a,b\right]$:
 $I= ∫ab fx dx .$

## 2Specification

Fortran Interface
 Subroutine d01atf ( f, a, b, w, lw, iw, liw,
 Integer, Intent (In) :: lw, liw Integer, Intent (Inout) :: ifail Integer, Intent (Out) :: iw(liw) Real (Kind=nag_wp), Intent (In) :: a, b, epsabs, epsrel Real (Kind=nag_wp), Intent (Out) :: result, abserr, w(lw) External :: f
#include nagmk26.h
 void d01atf_ (void (NAG_CALL *f)(const double x[], double fv[], const Integer *n),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)

## 3Description

d01atf 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.
d01atf requires a subroutine to evaluate the integrand at an array of different points and is therefore amenable to parallel execution. Otherwise the algorithm is identical to that used by d01ajf.

## 4References

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

## 5Arguments

1:     $\mathbf{f}$ – Subroutine, supplied by the user.External Procedure
f must return the values of the integrand $f$ at a set of points.
The specification of f is:
Fortran Interface
 Subroutine f ( x, fv, n)
 Integer, Intent (In) :: n Real (Kind=nag_wp), Intent (In) :: x(n) Real (Kind=nag_wp), Intent (Out) :: fv(n)
#include nagmk26.h
 void f (const double x[], double fv[], const Integer *n)
1:     $\mathbf{x}\left({\mathbf{n}}\right)$ – Real (Kind=nag_wp) arrayInput
On entry: the points at which the integrand $f$ must be evaluated.
2:     $\mathbf{fv}\left({\mathbf{n}}\right)$ – Real (Kind=nag_wp) arrayOutput
On exit: ${\mathbf{fv}}\left(\mathit{j}\right)$ must contain the value of $f$ at the point ${\mathbf{x}}\left(\mathit{j}\right)$, for $\mathit{j}=1,2,\dots ,{\mathbf{n}}$.
3:     $\mathbf{n}$ – IntegerInput
On entry: the number of points at which the integrand is to be evaluated. The actual value of n is always $21$.
f must either be a module subprogram USEd by, or declared as EXTERNAL in, the (sub)program from which d01atf is called. Arguments denoted as Input must not be changed by this procedure.
Note: f should not return floating-point NaN (Not a Number) or infinity values, since these are not handled by d01atf. If your code inadvertently does return any NaNs or infinities, d01atf 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.
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 $\left|I-{\mathbf{result}}\right|$.
8:     $\mathbf{w}\left({\mathbf{lw}}\right)$ – Real (Kind=nag_wp) arrayOutput
On exit: details of the computation see Section 9 for more information.
9:     $\mathbf{lw}$ – IntegerInput
On entry: the dimension of the array w as declared in the (sub)program from which d01atf is called. The value of lw (together with that of liw) imposes a bound on the number of sub-intervals into which the interval of integration may be divided by the routine. The number of sub-intervals 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 arrayOutput
On exit: ${\mathbf{iw}}\left(1\right)$ contains the actual number of sub-intervals used. The rest of the array is used as workspace.
11:   $\mathbf{liw}$ – IntegerInput
On entry: the dimension of the array iw as declared in the (sub)program from which d01atf is called. The number of sub-intervals 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:   $\mathbf{ifail}$ – 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, because for this routine the values of the output arguments may be useful even if ${\mathbf{ifail}}\ne {\mathbf{0}}$ on exit, the recommended value is $-1$. When the value $-\mathbf{1}\text{​ or ​}1$ 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).

## 6Error 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).
Note: d01atf may return useful information for one or more of the following detected errors or warnings.
Errors or warnings detected by the routine:
${\mathbf{ifail}}=1$
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.
${\mathbf{ifail}}=2$
Round-off error prevents the requested tolerance from being achieved. Consider requesting less accuracy.
${\mathbf{ifail}}=3$
Extremely bad local integrand behaviour causes a very strong subdivision around one (or more) points of the interval. The same advice applies as in the case of ${\mathbf{ifail}}={\mathbf{1}}$.
${\mathbf{ifail}}=4$
The requested tolerance cannot be achieved because the extrapolation does not increase the accuracy satisfactorily; the returned result is the best which 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. Please note that divergence can occur with any nonzero value of ifail.
${\mathbf{ifail}}=6$
 On entry, ${\mathbf{lw}}<4$, or ${\mathbf{liw}}<1$.
${\mathbf{ifail}}=-99$
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.

## 7Accuracy

d01atf cannot guarantee, but in practice usually achieves, the following accuracy:
 $I-result ≤ tol ,$
where
 $tol = max epsabs , epsrel × I ,$
and epsabs and epsrel are user-specified absolute and relative error tolerances. Moreover, it returns the quantity abserr which, in normal circumstances, satisfies
 $I-result ≤ abserr ≤ tol .$

## 8Parallelism and Performance

d01atf is not threaded in any implementation.

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 sub-intervals used by d01atf along with the integral contributions and error estimates over the sub-intervals.
Specifically, for $i=1,2,\dots ,n$, let ${r}_{i}$ denote the approximation to the value of the integral over the sub-interval $\left[{a}_{i},{b}_{i}\right]$ 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 ${\mathbf{result}}=\sum _{i=1}^{n}{r}_{i}$, unless d01atf 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
• ${r}_{i}={\mathbf{w}}\left(3n+i\right)$.

## 10Example

This example computes
 $∫ 0 2π x sin30x 1 - x/2π 2 dx .$

### 10.1Program Text

Program Text (d01atfe.f90)

None.

### 10.3Program Results

Program Results (d01atfe.r)

© The Numerical Algorithms Group Ltd, Oxford, UK. 2017