NAG FL Interface
d02pff (ivp_rkts_onestep)
1
Purpose
d02pff is a onestep routine for solving an initial value problem for a firstorder system of ordinary differential equations using Runge–Kutta methods.
2
Specification
Fortran Interface
Integer, Intent (In) 
:: 
n 
Integer, Intent (Inout) 
:: 
iuser(*), iwsav(130), ifail 
Real (Kind=nag_wp), Intent (Inout) 
:: 
ruser(*), rwsav(32*n+350) 
Real (Kind=nag_wp), Intent (Out) 
:: 
tnow, ynow(n), ypnow(n) 
External 
:: 
f 

C Header Interface
#include <nag.h>
void 
d02pff_ ( void (NAG_CALL *f)(const double *t, const Integer *n, const double y[], double yp[], Integer iuser[], double ruser[]), const Integer *n, double *tnow, double ynow[], double ypnow[], Integer iuser[], double ruser[], Integer iwsav[], double rwsav[], Integer *ifail) 

C++ Header Interface
#include <nag.h> extern "C" {
void 
d02pff_ ( void (NAG_CALL *f)(const double &t, const Integer &n, const double y[], double yp[], Integer iuser[], double ruser[]), const Integer &n, double &tnow, double ynow[], double ypnow[], Integer iuser[], double ruser[], Integer iwsav[], double rwsav[], Integer &ifail) 
}

The routine may be called by the names d02pff or nagf_ode_ivp_rkts_onestep.
3
Description
d02pff and its associated routines
(
d02pqf,
d02prf,
d02psf,
d02ptf and
d02puf) solve an initial value problem for a firstorder system of ordinary differential equations. The routines, based on Runge–Kutta methods and derived from RKSUITE (see
Brankin et al. (1991)), integrate
where
$y$ is the vector of
$\mathit{n}$ solution components and
$t$ is the independent variable.
d02pff is designed to be used in complicated tasks when solving systems of ordinary differential equations. You must first call
d02pqf to specify the problem and how it is to be solved. Thereafter you (repeatedly) call
d02pff to take one integration step at a time from
tstart in the direction of
tend (as specified in
d02pqf). In this manner
d02pff returns an approximation to the solution
ynow and its derivative
ypnow at successive points
tnow. If
d02pff encounters some difficulty in taking a step, the integration is not advanced and the routine returns with the same values of
tnow,
ynow and
ypnow as returned on the previous successful step.
d02pff tries to advance the integration as far as possible subject to passing the test on the local error and not going past
tend.
In the call to
d02pqf you can specify either the first step size for
d02pff to attempt or that it computes automatically an appropriate value. Thereafter
d02pff estimates an appropriate step size for its next step. This value and other details of the integration can be obtained after any call to
d02pff by a call to
d02ptf. The local error is controlled at every step as specified in
d02pqf. If you wish to assess the true error, you must set
method to a positive value
in the call to
d02pqf. This assessment can be obtained after any call to
d02pff by a call to
d02puf.
If you want answers at specific points there are two ways to proceed:

(i)The more efficient way is to step past the point where a solution is desired, and then call d02psf to get an answer there. Within the span of the current step, you can get all the answers you want at very little cost by repeated calls to d02psf. This is very valuable when you want to find where something happens, e.g., where a particular solution component vanishes. You cannot proceed in this way with
${\mathbf{method}}=3$ or $3$.

(ii)The other way to get an answer at a specific point is to set tend to this value and integrate to tend. d02pff will not step past tend, so when a step would carry it past, it will reduce the step size so as to produce an answer at tend exactly. After getting an answer there (${\mathbf{tnow}}={\mathbf{tend}}$), you can reset tend to the next point where you want an answer, and repeat. tend could be reset by a call to d02pqf, but you should not do this. You should use d02prf instead because it is both easier to use and much more efficient. This way of getting answers at specific points can be used with any of the available methods, but it is the only way with ${\mathbf{method}}=3$ or $3$. It can be inefficient. Should this be the case, the code will bring the matter to your attention.
4
References
Brankin R W, Gladwell I and Shampine L F (1991) RKSUITE: A suite of Runge–Kutta codes for the initial value problems for ODEs SoftReport 91S1 Southern Methodist University
5
Arguments

1:
$\mathbf{f}$ – Subroutine, supplied by the user.
External Procedure

f must evaluate the functions
${f}_{i}$ (that is the first derivatives
${y}_{i}^{\prime}$) for given values of the arguments
$t$,
${y}_{i}$.
The specification of
f is:
Fortran Interface
Integer, Intent (In) 
:: 
n 
Integer, Intent (Inout) 
:: 
iuser(*) 
Real (Kind=nag_wp), Intent (In) 
:: 
t, y(n) 
Real (Kind=nag_wp), Intent (Inout) 
:: 
ruser(*) 
Real (Kind=nag_wp), Intent (Out) 
:: 
yp(n) 

C Header Interface
void 
f_ (const double *t, const Integer *n, const double y[], double yp[], Integer iuser[], double ruser[]) 

C++ Header Interface
#include <nag.h> extern "C" {
void 
f_ (const double &t, const Integer &n, const double y[], double yp[], Integer iuser[], double ruser[]) 
}


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

On entry: $t$, the current value of the independent variable.

2:
$\mathbf{n}$ – Integer
Input

On entry: $\mathit{n}$, the number of ordinary differential equations in the system to be solved.

3:
$\mathbf{y}\left({\mathbf{n}}\right)$ – Real (Kind=nag_wp) array
Input

On entry: the current values of the dependent variables,
${y}_{\mathit{i}}$, for $\mathit{i}=1,2,\dots ,\mathit{n}$.

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

On exit: the values of
${f}_{\mathit{i}}$, for $\mathit{i}=1,2,\dots ,\mathit{n}$.

5:
$\mathbf{iuser}\left(*\right)$ – Integer array
User Workspace

6:
$\mathbf{ruser}\left(*\right)$ – Real (Kind=nag_wp) array
User Workspace

f is called with the arguments
iuser and
ruser as supplied to
d02pff. You should use the arrays
iuser and
ruser to supply information to
f.
f must either be a module subprogram USEd by, or declared as EXTERNAL in, the (sub)program from which
d02pff 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
d02pff. If your code inadvertently
does return any NaNs or infinities,
d02pff is likely to produce unexpected results.

2:
$\mathbf{n}$ – Integer
Input

On entry: $n$, the number of ordinary differential equations in the system to be solved.
Constraint:
${\mathbf{n}}\ge 1$.

3:
$\mathbf{tnow}$ – Real (Kind=nag_wp)
Output

On exit: $t$, the value of the independent variable at which a solution has been computed.

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

On exit: an approximation to the solution at
tnow. The local error of the step to
tnow was no greater than permitted by the specified tolerances (see
d02pqf).

5:
$\mathbf{ypnow}\left({\mathbf{n}}\right)$ – Real (Kind=nag_wp) array
Output

On exit: an approximation to the first derivative of the solution at
tnow.

6:
$\mathbf{iuser}\left(*\right)$ – Integer array
User Workspace

7:
$\mathbf{ruser}\left(*\right)$ – Real (Kind=nag_wp) array
User Workspace

iuser and
ruser are not used by
d02pff, but are passed directly to
f and may be used to pass information to this routine.

8:
$\mathbf{iwsav}\left(130\right)$ – Integer array
Communication Array

9:
$\mathbf{rwsav}\left(32\times {\mathbf{n}}+350\right)$ – Real (Kind=nag_wp) array
Communication Array

On entry: these must be the same arrays supplied in a previous call to
d02pqf. They must remain unchanged between calls.
On exit: information about the integration for use on subsequent calls to d02pff or other associated routines.

10:
$\mathbf{ifail}$ – Integer
Input/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 4 in the Introduction to the NAG Library FL Interface 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).
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:
 ${\mathbf{ifail}}=1$

A call to this routine cannot be made after it has returned an error.
The setup routine must be called to start another problem.
On entry, ${\mathbf{n}}=\u2329\mathit{\text{value}}\u232a$, but the value passed to the setup routine was ${\mathbf{n}}=\u2329\mathit{\text{value}}\u232a$.
On entry, the communication arrays have become corrupted, or a catastrophic error has already been detected elsewhere. You cannot continue integrating the problem.
tend, as specified in the setup routine, has already been reached. To start a new problem, you will need to call the setup routine. To continue integration beyond
tend then
d02prf must first be called to reset
tend to a new end value.
 ${\mathbf{ifail}}=2$

More than
$100$ output points have been obtained by integrating to
tend (as specified in the setup routine). They have been so clustered that it would probably be (much) more efficient to use the interpolation routine
(if
$\left{\mathbf{method}}\right=3$,
switch to
$\left{\mathbf{method}}\right=2$ at setup).
However, you can continue integrating the problem.
 ${\mathbf{ifail}}=3$

Approximately $\u2329\mathit{\text{value}}\u232a$ function evaluations have been used to compute the solution since the integration started or since this message was last printed. However, you can continue integrating the problem.
 ${\mathbf{ifail}}=4$

Approximately
$\u2329\mathit{\text{value}}\u232a$ function evaluations have been used to compute the solution since the integration started or since this message was last printed. Your problem has been diagnosed as stiff. If the situation persists, it will cost roughly
$\u2329\mathit{\text{value}}\u232a$ times as much to reach
tend (setup) as it has cost to reach the current time. You should probably call routines intended for stiff problems. However, you can continue integrating the problem.
 ${\mathbf{ifail}}=5$

In order to satisfy your error requirements the solver has to use a step size of $\u2329\mathit{\text{value}}\u232a$ at the current time, $\u2329\mathit{\text{value}}\u232a$. This step size is too small for the machine precision, and is smaller than $\u2329\mathit{\text{value}}\u232a$.
 ${\mathbf{ifail}}=6$

The global error assessment algorithm failed at start of integration.
The integration is being terminated.
The global error assessment may not be reliable for times beyond $\u2329\mathit{\text{value}}\u232a$.
The integration is being terminated.
 ${\mathbf{ifail}}=99$
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
The accuracy of integration is determined by the arguments
tol and
thresh in a prior call to
d02pqf (see the routine document for
d02pqf for further details and advice). Note that only the local error at each step is controlled by these arguments. The error estimates obtained are not strict bounds but are usually reliable over one step. Over a number of steps the overall error may accumulate in various ways, depending on the properties of the differential system.
8
Parallelism and Performance
d02pff 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.
If
d02pff returns with
${\mathbf{ifail}}={\mathbf{5}}$ and the accuracy specified by
tol and
thresh is really required then you should consider whether there is a more fundamental difficulty. For example, the solution may contain a singularity. In such a region the solution components will usually be large in magnitude. Successive output values of
ynow should be monitored with the aim of trapping the solution before the singularity. In any case numerical integration cannot be continued through a singularity, and analytical treatment may be necessary.
Performance statistics are available after any return from
d02pff (except when
${\mathbf{ifail}}={\mathbf{1}}$) by a call to
d02ptf. If
${\mathbf{method}}>0$
in the call to
d02pqf, global error assessment is available after any return from
d02pff (except when
${\mathbf{ifail}}={\mathbf{1}}$) by a call to
d02puf.
After a failure with
${\mathbf{ifail}}={\mathbf{5}}$ or
${\mathbf{6}}$ each of the diagnostic routines
d02ptf and
d02puf
may be called only once.
If d02pff returns with ${\mathbf{ifail}}={\mathbf{4}}$ then it is advisable to change to another code more suited to the solution of stiff problems. d02pff will not return with ${\mathbf{ifail}}={\mathbf{4}}$ if the problem is actually stiff but it is estimated that integration can be completed using less function evaluations than already computed.
10
Example
This example solves the equation
reposed as
over the range
$\left[0,2\pi \right]$ with initial conditions
${y}_{1}=0.0$ and
${y}_{2}=1.0$. We use relative error control with threshold values of
$\text{1.0E\u22128}$ for each solution component and print the solution at each integration step across the range. We use a medium order Runge–Kutta method
(
${\mathbf{method}}=2$) with tolerances
${\mathbf{tol}}=\text{1.0E\u22124}$ and
${\mathbf{tol}}=\text{1.0E\u22125}$
in turn so that we may compare the solutions.
10.1
Program Text
10.2
Program Data
10.3
Program Results