NAG Library Routine Document
d01akf (dim1_fin_osc)
1
Purpose
d01akf is an adaptive integrator, especially suited to oscillating, nonsingular integrands, 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 d01akf ( 
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 nagmk26.h
void 
d01akf_ ( 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) 

3
Description
d01akf is based on the QUADPACK routine QAG (see
Piessens et al. (1983)). It is an adaptive routine, using the Gauss
$30$point and Kronrod
$61$point rules. A ‘global’ acceptance criterion (as defined by
Malcolm and Simpson (1976)) is used. The local error estimation is described in
Piessens et al. (1983).
Because d01akf is based on integration rules of high order, it is especially suitable for nonsingular oscillating integrands.
d01akf requires you to supply a function to evaluate the integrand at a single point.
The routine
d01auf uses an identical algorithm but requires you to supply a subroutine to evaluate the integrand at an array of points. Therefore
d01auf will be more efficient if the evaluation can be performed in vector mode on a vectorprocessing machine.
4
References
Malcolm M A and Simpson R B (1976) Local versus global strategies for adaptive quadrature ACM Trans. Math. Software 1 129–146
Piessens R (1973) An algorithm for automatic integration Angew. Inf. 15 399–401
Piessens R, de Doncker–Kapenga E, Überhuber C and Kahaner D (1983) QUADPACK, A Subroutine Package for Automatic Integration Springer–Verlag
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
#include nagmk26.h
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
d01akf 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
d01akf. If your code inadvertently
does return any NaNs or infinities,
d01akf 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) 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
d01akf 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 arrayOutput

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

On entry: the dimension of the array
iw as declared in the (sub)program from which
d01akf 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: $\mathbf{ifail}$ – 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:
 ${\mathbf{ifail}}=1$

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 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. 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 ${\mathbf{ifail}}={\mathbf{1}}$.
 ${\mathbf{ifail}}=4$

On entry,  ${\mathbf{lw}}<4$, 
or  ${\mathbf{liw}}<1$. 
 ${\mathbf{ifail}}=99$
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.
7
Accuracy
d01akf 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
d01akf is not threaded in any implementation.
The time taken by d01akf 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
d01akf along with the integral contributions and error estimates over these 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
${\mathbf{result}}={\displaystyle \sum _{i=1}^{n}}{r}_{i}$. 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
Program Text (d01akfe.f90)
10.2
Program Data
None.
10.3
Program Results
Program Results (d01akfe.r)