# NAG Library Routine Document

## 1Purpose

d03pkf integrates a system of linear or nonlinear, first-order, time-dependent partial differential equations (PDEs) in one space variable, with scope for coupled ordinary differential equations (ODEs). The spatial discretization is performed using the Keller box scheme and the method of lines is employed to reduce the PDEs to a system of ODEs. The resulting system is solved using a Backward Differentiation Formula (BDF) method or a Theta method (switching between Newton's method and functional iteration).

## 2Specification

Fortran Interface
 Subroutine d03pkf ( npde, ts, tout, u, npts, x, nv, nxi, xi, neqn, rtol, atol, itol, norm, ind,
 Integer, Intent (In) :: npde, npts, nleft, nv, nxi, neqn, itol, lrsave, lisave, itask, itrace Integer, Intent (Inout) :: isave(lisave), ind, ifail Real (Kind=nag_wp), Intent (In) :: tout, x(npts), xi(nxi), rtol(*), atol(*), algopt(30) Real (Kind=nag_wp), Intent (Inout) :: ts, u(neqn), rsave(lrsave) Character (1), Intent (In) :: norm, laopt External :: pdedef, bndary, odedef
#include <nagmk26.h>
 void d03pkf_ (const Integer *npde, double *ts, const double *tout, void (NAG_CALL *pdedef)(const Integer *npde, const double *t, const double *x, const double u[], const double ut[], const double ux[], const Integer *nv, const double v[], const double vdot[], double res[], Integer *ires),void (NAG_CALL *bndary)(const Integer *npde, const double *t, const Integer *ibnd, const Integer *nobc, const double u[], const double ut[], const Integer *nv, const double v[], const double vdot[], double res[], Integer *ires),double u[], const Integer *npts, const double x[], const Integer *nleft, const Integer *nv, void (NAG_CALL *odedef)(const Integer *npde, const double *t, const Integer *nv, const double v[], const double vdot[], const Integer *nxi, const double xi[], const double ucp[], const double ucpx[], const double ucpt[], double r[], Integer *ires),const Integer *nxi, const double xi[], const Integer *neqn, const double rtol[], const double atol[], const Integer *itol, const char *norm, const char *laopt, const double algopt[], double rsave[], const Integer *lrsave, Integer isave[], const Integer *lisave, const Integer *itask, const Integer *itrace, Integer *ind, Integer *ifail, const Charlen length_norm, const Charlen length_laopt)

## 3Description

d03pkf integrates the system of first-order PDEs and coupled ODEs
 $Gi x,t,U,Ux,Ut,V,V. = 0 , i=1,2,…,npde , a≤x≤b,t≥t0 ,$ (1)
 $Ri t,V,V.,ξ,U*,Ux*,Ut* = 0 , i=1,2,…,nv .$ (2)
In the PDE part of the problem given by (1), the functions ${G}_{i}$ must have the general form
 $Gi = ∑ j=1 npde Pi,j ∂Uj ∂t + ∑ j=1 nv Qi,j V.j + Si = 0 , i=1,2,…,npde ,$ (3)
where ${P}_{i,j}$, ${Q}_{i,j}$ and ${S}_{i}$ depend on $x,t,U,{U}_{x}$ and $V$.
The vector $U$ is the set of PDE solution values
 $U x,t = U 1 x,t ,…, U npde x,t T ,$
and the vector ${U}_{x}$ is the partial derivative with respect to $x$. The vector $V$ is the set of ODE solution values
 $Vt=V1t,…,VnvtT,$
and $\stackrel{.}{V}$ denotes its derivative with respect to time.
In the ODE part given by (2), $\xi$ represents a vector of ${n}_{\xi }$ spatial coupling points at which the ODEs are coupled to the PDEs. These points may or may not be equal to some of the PDE spatial mesh points. ${U}^{*}$, ${U}_{x}^{*}$ and ${U}_{t}^{*}$ are the functions $U$, ${U}_{x}$ and ${U}_{t}$ evaluated at these coupling points. Each ${R}_{i}$ may only depend linearly on time derivatives. Hence equation (2) may be written more precisely as
 $R=A-BV.-CUt*,$ (4)
where $R={\left[{R}_{1},\dots ,{R}_{{\mathbf{nv}}}\right]}^{\mathrm{T}}$, $A$ is a vector of length nv, $B$ is an nv by nv matrix, $C$ is an nv by $\left({n}_{\xi }×{\mathbf{npde}}\right)$ matrix. The entries in $A$, $B$ and $C$ may depend on $t$, $\xi$, ${U}^{*}$, ${U}_{x}^{*}$ and $V$. In practice you only need to supply a vector of information to define the ODEs and not the matrices $B$ and $C$. (See Section 5 for the specification of odedef.)
The integration in time is from ${t}_{0}$ to ${t}_{\mathrm{out}}$, over the space interval $a\le x\le b$, where $a={x}_{1}$ and $b={x}_{{\mathbf{npts}}}$ are the leftmost and rightmost points of a user-defined mesh ${x}_{1},{x}_{2},\dots ,{x}_{{\mathbf{npts}}}$.
The PDE system which is defined by the functions ${G}_{i}$ must be specified in pdedef.
The initial values of the functions $U\left(x,t\right)$ and $V\left(t\right)$ must be given at $t={t}_{0}$.
For a first-order system of PDEs, only one boundary condition is required for each PDE component ${U}_{i}$. The npde boundary conditions are separated into ${n}_{a}$ at the left-hand boundary $x=a$, and ${n}_{b}$ at the right-hand boundary $x=b$, such that ${n}_{a}+{n}_{b}={\mathbf{npde}}$. The position of the boundary condition for each component should be chosen with care; the general rule is that if the characteristic direction of ${U}_{i}$ at the left-hand boundary (say) points into the interior of the solution domain, then the boundary condition for ${U}_{i}$ should be specified at the left-hand boundary. Incorrect positioning of boundary conditions generally results in initialization or integration difficulties in the underlying time integration routines.
The boundary conditions have the form:
 $G i L x,t,U, U t ,V, V . = 0 at ​ x = a , i=1,2,…,na ,$ (5)
at the left-hand boundary, and
 $G i R x,t,U, U t ,V, V . = 0 at ​ x = b, i=1,2,…,nb,$ (6)
at the right-hand boundary.
Note that the functions ${G}_{i}^{L}$ and ${G}_{i}^{R}$ must not depend on ${U}_{x}$, since spatial derivatives are not determined explicitly in the Keller box scheme. If the problem involves derivative (Neumann) boundary conditions then it is generally possible to restate such boundary conditions in terms of permissible variables. Also note that ${G}_{i}^{L}$ and ${G}_{i}^{R}$ must be linear with respect to time derivatives, so that the boundary conditions have the general form:
 $∑j=1npdeEi,jL ∂Uj ∂t +∑j=1nvHi,jLV.j+KiL=0, i=1,2,…,na,$ (7)
at the left-hand boundary, and
 $∑j=1npdeEi,jR ∂Uj ∂t +∑j=1nvHi,jRV.j+KiR=0, i=1,2,…,nb,$ (8)
at the right-hand boundary, where ${E}_{i,j}^{L}$, ${E}_{i,j}^{R}$, ${H}_{i,j}^{L}$, ${H}_{i,j}^{R}$, ${K}_{i}^{L}$ and ${K}_{i}^{R}$ depend on $x,t,U$ and $V$ only.
The boundary conditions must be specified in bndary.
The problem is subject to the following restrictions:
 (i) ${P}_{i,j}$, ${Q}_{i,j}$ and ${S}_{i}$ must not depend on any time derivatives; (ii) ${t}_{0}<{t}_{\mathrm{out}}$, so that integration is in the forward direction; (iii) The evaluation of the function ${G}_{i}$ is done approximately at the mid-points of the mesh ${\mathbf{x}}\left(\mathit{i}\right)$, for $\mathit{i}=1,2,\dots ,{\mathbf{npts}}$, by calling the pdedef for each mid-point in turn. Any discontinuities in the function must therefore be at one or more of the mesh points ${x}_{1},{x}_{2},\dots ,{x}_{{\mathbf{npts}}}$; (iv) At least one of the functions ${P}_{i,j}$ must be nonzero so that there is a time derivative present in the PDE problem.
The algebraic-differential equation system which is defined by the functions ${R}_{i}$ must be specified in odedef. You must also specify the coupling points $\xi$ in the array xi.
The parabolic equations are approximated by a system of ODEs in time for the values of ${U}_{i}$ at mesh points. In this method of lines approach the Keller box scheme (see Keller (1970)) is applied to each PDE in the space variable only, resulting in a system of ODEs in time for the values of ${U}_{i}$ at each mesh point. In total there are ${\mathbf{npde}}×{\mathbf{npts}}+{\mathbf{nv}}$ ODEs in time direction. This system is then integrated forwards in time using a Backward Differentiation Formula (BDF) or a Theta method.

## 4References

Berzins M (1990) Developments in the NAG Library software for parabolic equations Scientific Software Systems (eds J C Mason and M G Cox) 59–72 Chapman and Hall
Berzins M, Dew P M and Furzeland R M (1989) Developing software for time-dependent problems using the method of lines and differential-algebraic integrators Appl. Numer. Math. 5 375–397
Berzins M and Furzeland R M (1992) An adaptive theta method for the solution of stiff and nonstiff differential equations Appl. Numer. Math. 9 1–19
Keller H B (1970) A new difference scheme for parabolic problems Numerical Solutions of Partial Differential Equations (ed J Bramble) 2 327–350 Academic Press
Pennington S V and Berzins M (1994) New NAG Library software for first-order partial differential equations ACM Trans. Math. Softw. 20 63–99

## 5Arguments

1:     $\mathbf{npde}$ – IntegerInput
On entry: the number of PDEs to be solved.
Constraint: ${\mathbf{npde}}\ge 1$.
2:     $\mathbf{ts}$ – Real (Kind=nag_wp)Input/Output
On entry: the initial value of the independent variable $t$.
Constraint: ${\mathbf{ts}}<{\mathbf{tout}}$.
On exit: the value of $t$ corresponding to the solution in u. Normally ${\mathbf{ts}}={\mathbf{tout}}$.
3:     $\mathbf{tout}$ – Real (Kind=nag_wp)Input
On entry: the final value of $t$ to which the integration is to be carried out.
4:     $\mathbf{pdedef}$ – Subroutine, supplied by the user.External Procedure
pdedef must evaluate the functions ${G}_{i}$ which define the system of PDEs. pdedef is called approximately midway between each pair of mesh points in turn by d03pkf.
The specification of pdedef is:
Fortran Interface
 Subroutine pdedef ( npde, t, x, u, ut, ux, nv, v, vdot, res, ires)
 Integer, Intent (In) :: npde, nv Integer, Intent (Inout) :: ires Real (Kind=nag_wp), Intent (In) :: t, x, u(npde), ut(npde), ux(npde), v(nv), vdot(nv) Real (Kind=nag_wp), Intent (Out) :: res(npde)
#include <nagmk26.h>
 void pdedef (const Integer *npde, const double *t, const double *x, const double u[], const double ut[], const double ux[], const Integer *nv, const double v[], const double vdot[], double res[], Integer *ires)
1:     $\mathbf{npde}$ – IntegerInput
On entry: the number of PDEs in the system.
2:     $\mathbf{t}$ – Real (Kind=nag_wp)Input
On entry: the current value of the independent variable $t$.
3:     $\mathbf{x}$ – Real (Kind=nag_wp)Input
On entry: the current value of the space variable $x$.
4:     $\mathbf{u}\left({\mathbf{npde}}\right)$ – Real (Kind=nag_wp) arrayInput
On entry: ${\mathbf{u}}\left(\mathit{i}\right)$ contains the value of the component ${U}_{\mathit{i}}\left(x,t\right)$, for $\mathit{i}=1,2,\dots ,{\mathbf{npde}}$.
5:     $\mathbf{ut}\left({\mathbf{npde}}\right)$ – Real (Kind=nag_wp) arrayInput
On entry: ${\mathbf{ut}}\left(\mathit{i}\right)$ contains the value of the component $\frac{\partial {U}_{\mathit{i}}\left(x,t\right)}{\partial t}$, for $\mathit{i}=1,2,\dots ,{\mathbf{npde}}$.
6:     $\mathbf{ux}\left({\mathbf{npde}}\right)$ – Real (Kind=nag_wp) arrayInput
On entry: ${\mathbf{ux}}\left(\mathit{i}\right)$ contains the value of the component $\frac{\partial {U}_{\mathit{i}}\left(x,t\right)}{\partial x}$, for $\mathit{i}=1,2,\dots ,{\mathbf{npde}}$.
7:     $\mathbf{nv}$ – IntegerInput
On entry: the number of coupled ODEs in the system.
8:     $\mathbf{v}\left({\mathbf{nv}}\right)$ – Real (Kind=nag_wp) arrayInput
On entry: if ${\mathbf{nv}}>0$, ${\mathbf{v}}\left(\mathit{i}\right)$ contains the value of the component ${V}_{\mathit{i}}\left(t\right)$, for $\mathit{i}=1,2,\dots ,{\mathbf{nv}}$.
9:     $\mathbf{vdot}\left({\mathbf{nv}}\right)$ – Real (Kind=nag_wp) arrayInput
On entry: if ${\mathbf{nv}}>0$, ${\mathbf{vdot}}\left(\mathit{i}\right)$ contains the value of component ${\stackrel{.}{V}}_{\mathit{i}}\left(t\right)$, for $\mathit{i}=1,2,\dots ,{\mathbf{nv}}$.
10:   $\mathbf{res}\left({\mathbf{npde}}\right)$ – Real (Kind=nag_wp) arrayOutput
On exit: ${\mathbf{res}}\left(\mathit{i}\right)$ must contain the $\mathit{i}$th component of $G$, for $\mathit{i}=1,2,\dots ,{\mathbf{npde}}$, where $G$ is defined as
 $Gi=∑j=1npdePi,j ∂Uj ∂t +∑j=1nvQi,jV.j,$ (9)
i.e., only terms depending explicitly on time derivatives, or
 $Gi=∑j=1npdePi,j ∂Uj ∂t +∑j=1nvQi,jV.j+Si,$ (10)
i.e., all terms in equation (3).
The definition of $G$ is determined by the input value of ires.
11:   $\mathbf{ires}$ – IntegerInput/Output
On entry: the form of ${G}_{i}$ that must be returned in the array res.
${\mathbf{ires}}=-1$
Equation (9) must be used.
${\mathbf{ires}}=1$
Equation (10) must be used.
On exit: should usually remain unchanged. However, you may set ires to force the integration routine to take certain actions, as described below:
${\mathbf{ires}}=2$
Indicates to the integrator that control should be passed back immediately to the calling (sub)routine with the error indicator set to ${\mathbf{ifail}}={\mathbf{6}}$.
${\mathbf{ires}}=3$
Indicates to the integrator that the current time step should be abandoned and a smaller time step used instead. You may wish to set ${\mathbf{ires}}=3$ when a physically meaningless input or output value has been generated. If you consecutively set ${\mathbf{ires}}=3$, d03pkf returns to the calling subroutine with the error indicator set to ${\mathbf{ifail}}={\mathbf{4}}$.
pdedef must either be a module subprogram USEd by, or declared as EXTERNAL in, the (sub)program from which d03pkf is called. Arguments denoted as Input must not be changed by this procedure.
Note: pdedef should not return floating-point NaN (Not a Number) or infinity values, since these are not handled by d03pkf. If your code inadvertently does return any NaNs or infinities, d03pkf is likely to produce unexpected results.
5:     $\mathbf{bndary}$ – Subroutine, supplied by the user.External Procedure
bndary must evaluate the functions ${G}_{i}^{L}$ and ${G}_{i}^{R}$ which describe the boundary conditions, as given in (5) and (6).
The specification of bndary is:
Fortran Interface
 Subroutine bndary ( npde, t, ibnd, nobc, u, ut, nv, v, vdot, res, ires)
 Integer, Intent (In) :: npde, ibnd, nobc, nv Integer, Intent (Inout) :: ires Real (Kind=nag_wp), Intent (In) :: t, u(npde), ut(npde), v(nv), vdot(nv) Real (Kind=nag_wp), Intent (Out) :: res(nobc)
#include <nagmk26.h>
 void bndary (const Integer *npde, const double *t, const Integer *ibnd, const Integer *nobc, const double u[], const double ut[], const Integer *nv, const double v[], const double vdot[], double res[], Integer *ires)
1:     $\mathbf{npde}$ – IntegerInput
On entry: the number of PDEs in the system.
2:     $\mathbf{t}$ – Real (Kind=nag_wp)Input
On entry: the current value of the independent variable $t$.
3:     $\mathbf{ibnd}$ – IntegerInput
On entry: specifies which boundary conditions are to be evaluated.
${\mathbf{ibnd}}=0$
bndary must compute the left-hand boundary condition at $x=a$.
${\mathbf{ibnd}}\ne 0$
bndary must compute the right-hand boundary condition at $x=b$.
4:     $\mathbf{nobc}$ – IntegerInput
On entry: specifies the number of boundary conditions at the boundary specified by ibnd.
5:     $\mathbf{u}\left({\mathbf{npde}}\right)$ – Real (Kind=nag_wp) arrayInput
On entry: ${\mathbf{u}}\left(\mathit{i}\right)$ contains the value of the component ${U}_{\mathit{i}}\left(x,t\right)$ at the boundary specified by ibnd, for $\mathit{i}=1,2,\dots ,{\mathbf{npde}}$.
6:     $\mathbf{ut}\left({\mathbf{npde}}\right)$ – Real (Kind=nag_wp) arrayInput
On entry: ${\mathbf{ut}}\left(\mathit{i}\right)$ contains the value of the component $\frac{\partial {U}_{\mathit{i}}\left(x,t\right)}{\partial t}$ at the boundary specified by ibnd, for $\mathit{i}=1,2,\dots ,{\mathbf{npde}}$.
7:     $\mathbf{nv}$ – IntegerInput
On entry: the number of coupled ODEs in the system.
8:     $\mathbf{v}\left({\mathbf{nv}}\right)$ – Real (Kind=nag_wp) arrayInput
On entry: if ${\mathbf{nv}}>0$, ${\mathbf{v}}\left(\mathit{i}\right)$ contains the value of the component ${V}_{\mathit{i}}\left(t\right)$, for $\mathit{i}=1,2,\dots ,{\mathbf{nv}}$.
9:     $\mathbf{vdot}\left({\mathbf{nv}}\right)$ – Real (Kind=nag_wp) arrayInput
On entry: if ${\mathbf{nv}}>0$, ${\mathbf{vdot}}\left(\mathit{i}\right)$ contains the value of component ${\stackrel{.}{V}}_{\mathit{i}}\left(t\right)$, for $\mathit{i}=1,2,\dots ,{\mathbf{nv}}$.
Note: ${\mathbf{vdot}}\left(\mathit{i}\right)$, for $\mathit{i}=1,2,\dots ,{\mathbf{nv}}$, may only appear linearly as in (7) and (8).
10:   $\mathbf{res}\left({\mathbf{nobc}}\right)$ – Real (Kind=nag_wp) arrayOutput
On exit: ${\mathbf{res}}\left(\mathit{i}\right)$ must contain the $\mathit{i}$th component of ${G}^{L}$ or ${G}^{R}$, depending on the value of ibnd, for $\mathit{i}=1,2,\dots ,{\mathbf{nobc}}$, where ${G}^{L}$ is defined as
 $GiL=∑j=1npdeEi,jL ∂Uj ∂t +∑j=1nvHi,jLV.j,$ (11)
i.e., only terms depending explicitly on time derivatives, or
 $GiL=∑j=1npdeEi,jL ∂Uj ∂t +∑j=1nvHi,jLV.j+KiL,$ (12)
i.e., all terms in equation (7), and similarly for ${G}_{\mathit{i}}^{R}$.
The definitions of ${G}^{L}$ and ${G}^{R}$ are determined by the input value of ires.
11:   $\mathbf{ires}$ – IntegerInput/Output
On entry: the form of ${G}_{i}^{L}$ (or ${G}_{i}^{R}$) that must be returned in the array res.
${\mathbf{ires}}=-1$
Equation (11) must be used.
${\mathbf{ires}}=1$
Equation (12) must be used.
On exit: should usually remain unchanged. However, you may set ires to force the integration routine to take certain actions as described below:
${\mathbf{ires}}=2$
Indicates to the integrator that control should be passed back immediately to the calling (sub)routine with the error indicator set to ${\mathbf{ifail}}={\mathbf{6}}$.
${\mathbf{ires}}=3$
Indicates to the integrator that the current time step should be abandoned and a smaller time step used instead. You may wish to set ${\mathbf{ires}}=3$ when a physically meaningless input or output value has been generated. If you consecutively set ${\mathbf{ires}}=3$, d03pkf returns to the calling subroutine with the error indicator set to ${\mathbf{ifail}}={\mathbf{4}}$.
bndary must either be a module subprogram USEd by, or declared as EXTERNAL in, the (sub)program from which d03pkf is called. Arguments denoted as Input must not be changed by this procedure.
Note: bndary should not return floating-point NaN (Not a Number) or infinity values, since these are not handled by d03pkf. If your code inadvertently does return any NaNs or infinities, d03pkf is likely to produce unexpected results.
6:     $\mathbf{u}\left({\mathbf{neqn}}\right)$ – Real (Kind=nag_wp) arrayInput/Output
On entry: the initial values of the dependent variables defined as follows:
• ${\mathbf{u}}\left({\mathbf{npde}}×\left(\mathit{j}-1\right)+\mathit{i}\right)$ contain ${U}_{\mathit{i}}\left({x}_{\mathit{j}},{t}_{0}\right)$, for $\mathit{i}=1,2,\dots ,{\mathbf{npde}}$ and $\mathit{j}=1,2,\dots ,{\mathbf{npts}}$, and
• ${\mathbf{u}}\left({\mathbf{npts}}×{\mathbf{npde}}+\mathit{i}\right)$ contain ${V}_{\mathit{i}}\left({t}_{0}\right)$, for $\mathit{i}=1,2,\dots ,{\mathbf{nv}}$.
On exit: the computed solution ${U}_{\mathit{i}}\left({x}_{\mathit{j}},t\right)$, for $\mathit{i}=1,2,\dots ,{\mathbf{npde}}$ and $\mathit{j}=1,2,\dots ,{\mathbf{npts}}$, and ${V}_{\mathit{k}}\left(t\right)$, for $\mathit{k}=1,2,\dots ,{\mathbf{nv}}$, evaluated at $t={\mathbf{ts}}$.
7:     $\mathbf{npts}$ – IntegerInput
On entry: the number of mesh points in the interval $\left[a,b\right]$.
Constraint: ${\mathbf{npts}}\ge 3$.
8:     $\mathbf{x}\left({\mathbf{npts}}\right)$ – Real (Kind=nag_wp) arrayInput
On entry: the mesh points in the space direction. ${\mathbf{x}}\left(1\right)$ must specify the left-hand boundary, $a$, and ${\mathbf{x}}\left({\mathbf{npts}}\right)$ must specify the right-hand boundary, $b$.
Constraint: ${\mathbf{x}}\left(1\right)<{\mathbf{x}}\left(2\right)<\cdots <{\mathbf{x}}\left({\mathbf{npts}}\right)$.
9:     $\mathbf{nleft}$ – IntegerInput
On entry: the number ${n}_{a}$ of boundary conditions at the left-hand mesh point ${\mathbf{x}}\left(1\right)$.
Constraint: $0\le {\mathbf{nleft}}\le {\mathbf{npde}}$.
10:   $\mathbf{nv}$ – IntegerInput
On entry: the number of coupled ODE components.
Constraint: ${\mathbf{nv}}\ge 0$.
11:   $\mathbf{odedef}$ – Subroutine, supplied by the NAG Library or the user.External Procedure
odedef must evaluate the functions $R$, which define the system of ODEs, as given in (4).
If you wish to compute the solution of a system of PDEs only (i.e., ${\mathbf{nv}}=0$), odedef must be the dummy routine d03pek. (d03pek is included in the NAG Library.)
The specification of odedef is:
Fortran Interface
 Subroutine odedef ( npde, t, nv, v, vdot, nxi, xi, ucp, ucpx, ucpt, r, ires)
 Integer, Intent (In) :: npde, nv, nxi Integer, Intent (Inout) :: ires Real (Kind=nag_wp), Intent (In) :: t, v(nv), vdot(nv), xi(nxi), ucp(npde,nxi), ucpx(npde,nxi), ucpt(npde,nxi) Real (Kind=nag_wp), Intent (Out) :: r(nv)
#include <nagmk26.h>
 void odedef (const Integer *npde, const double *t, const Integer *nv, const double v[], const double vdot[], const Integer *nxi, const double xi[], const double ucp[], const double ucpx[], const double ucpt[], double r[], Integer *ires)
1:     $\mathbf{npde}$ – IntegerInput
On entry: the number of PDEs in the system.
2:     $\mathbf{t}$ – Real (Kind=nag_wp)Input
On entry: the current value of the independent variable $t$.
3:     $\mathbf{nv}$ – IntegerInput
On entry: the number of coupled ODEs in the system.
4:     $\mathbf{v}\left({\mathbf{nv}}\right)$ – Real (Kind=nag_wp) arrayInput
On entry: if ${\mathbf{nv}}>0$, ${\mathbf{v}}\left(\mathit{i}\right)$ contains the value of the component ${V}_{\mathit{i}}\left(t\right)$, for $\mathit{i}=1,2,\dots ,{\mathbf{nv}}$.
5:     $\mathbf{vdot}\left({\mathbf{nv}}\right)$ – Real (Kind=nag_wp) arrayInput
On entry: if ${\mathbf{nv}}>0$, ${\mathbf{vdot}}\left(\mathit{i}\right)$ contains the value of component ${\stackrel{.}{V}}_{\mathit{i}}\left(t\right)$, for $\mathit{i}=1,2,\dots ,{\mathbf{nv}}$.
6:     $\mathbf{nxi}$ – IntegerInput
On entry: the number of ODE/PDE coupling points.
7:     $\mathbf{xi}\left({\mathbf{nxi}}\right)$ – Real (Kind=nag_wp) arrayInput
On entry: if ${\mathbf{nxi}}>0$, ${\mathbf{xi}}\left(\mathit{i}\right)$ contains the ODE/PDE coupling points, ${\xi }_{\mathit{i}}$, for $\mathit{i}=1,2,\dots ,{\mathbf{nxi}}$.
8:     $\mathbf{ucp}\left({\mathbf{npde}},{\mathbf{nxi}}\right)$ – Real (Kind=nag_wp) arrayInput
On entry: if ${\mathbf{nxi}}>0$, ${\mathbf{ucp}}\left(\mathit{i},\mathit{j}\right)$ contains the value of ${U}_{\mathit{i}}\left(x,t\right)$ at the coupling point $x={\xi }_{\mathit{j}}$, for $\mathit{i}=1,2,\dots ,{\mathbf{npde}}$ and $\mathit{j}=1,2,\dots ,{\mathbf{nxi}}$.
9:     $\mathbf{ucpx}\left({\mathbf{npde}},{\mathbf{nxi}}\right)$ – Real (Kind=nag_wp) arrayInput
On entry: if ${\mathbf{nxi}}>0$, ${\mathbf{ucpx}}\left(\mathit{i},\mathit{j}\right)$ contains the value of $\frac{\partial {U}_{\mathit{i}}\left(x,t\right)}{\partial x}$ at the coupling point $x={\xi }_{\mathit{j}}$, for $\mathit{i}=1,2,\dots ,{\mathbf{npde}}$ and $\mathit{j}=1,2,\dots ,{\mathbf{nxi}}$.
10:   $\mathbf{ucpt}\left({\mathbf{npde}},{\mathbf{nxi}}\right)$ – Real (Kind=nag_wp) arrayInput
On entry: if ${\mathbf{nxi}}>0$, ${\mathbf{ucpt}}\left(\mathit{i},\mathit{j}\right)$ contains the value of $\frac{\partial {U}_{\mathit{i}}}{\partial t}$ at the coupling point $x={\xi }_{\mathit{j}}$, for $\mathit{i}=1,2,\dots ,{\mathbf{npde}}$ and $\mathit{j}=1,2,\dots ,{\mathbf{nxi}}$.
11:   $\mathbf{r}\left({\mathbf{nv}}\right)$ – Real (Kind=nag_wp) arrayOutput
On exit: if ${\mathbf{nv}}>0$, ${\mathbf{r}}\left(\mathit{i}\right)$ must contain the $\mathit{i}$th component of $R$, for $\mathit{i}=1,2,\dots ,{\mathbf{nv}}$, where $R$ is defined as
 $R=-BV.-CUt*,$ (13)
i.e., only terms depending explicitly on time derivatives, or
 $R=A-BV.-CUt*,$ (14)
i.e., all terms in equation (4). The definition of $R$ is determined by the input value of ires.
12:   $\mathbf{ires}$ – IntegerInput/Output
On entry: the form of $R$ that must be returned in the array r.
${\mathbf{ires}}=-1$
Equation (13) must be used.
${\mathbf{ires}}=1$
Equation (14) must be used.
On exit: should usually remain unchanged. However, you may reset ires to force the integration routine to take certain actions, as described below:
${\mathbf{ires}}=2$
Indicates to the integrator that control should be passed back immediately to the calling (sub)routine with the error indicator set to ${\mathbf{ifail}}={\mathbf{6}}$.
${\mathbf{ires}}=3$
Indicates to the integrator that the current time step should be abandoned and a smaller time step used instead. You may wish to set ${\mathbf{ires}}=3$ when a physically meaningless input or output value has been generated. If you consecutively set ${\mathbf{ires}}=3$, d03pkf returns to the calling subroutine with the error indicator set to ${\mathbf{ifail}}={\mathbf{4}}$.
odedef must either be a module subprogram USEd by, or declared as EXTERNAL in, the (sub)program from which d03pkf is called. Arguments denoted as Input must not be changed by this procedure.
Note: odedef should not return floating-point NaN (Not a Number) or infinity values, since these are not handled by d03pkf. If your code inadvertently does return any NaNs or infinities, d03pkf is likely to produce unexpected results.
12:   $\mathbf{nxi}$ – IntegerInput
On entry: the number of ODE/PDE coupling points.
Constraints:
• if ${\mathbf{nv}}=0$, ${\mathbf{nxi}}=0$;
• if ${\mathbf{nv}}>0$, ${\mathbf{nxi}}\ge 0$.
13:   $\mathbf{xi}\left({\mathbf{nxi}}\right)$ – Real (Kind=nag_wp) arrayInput
On entry: ${\mathbf{xi}}\left(\mathit{i}\right)$, for $\mathit{i}=1,2,\dots ,{\mathbf{nxi}}$, must be set to the ODE/PDE coupling points, ${\xi }_{\mathit{i}}$.
Constraint: ${\mathbf{x}}\left(1\right)\le {\mathbf{xi}}\left(1\right)<{\mathbf{xi}}\left(2\right)<\cdots <{\mathbf{xi}}\left({\mathbf{nxi}}\right)\le {\mathbf{x}}\left({\mathbf{npts}}\right)$.
14:   $\mathbf{neqn}$ – IntegerInput
On entry: the number of ODEs in the time direction.
Constraint: ${\mathbf{neqn}}={\mathbf{npde}}×{\mathbf{npts}}+{\mathbf{nv}}$.
15:   $\mathbf{rtol}\left(*\right)$ – Real (Kind=nag_wp) arrayInput
Note: the dimension of the array rtol must be at least $1$ if ${\mathbf{itol}}=1$ or $2$ and at least ${\mathbf{neqn}}$ if ${\mathbf{itol}}=3$ or $4$.
On entry: the relative local error tolerance.
Constraint: ${\mathbf{rtol}}\left(i\right)\ge 0.0$ for all relevant $i$.
16:   $\mathbf{atol}\left(*\right)$ – Real (Kind=nag_wp) arrayInput
Note: the dimension of the array atol must be at least $1$ if ${\mathbf{itol}}=1$ or $3$ and at least ${\mathbf{neqn}}$ if ${\mathbf{itol}}=2$ or $4$.
On entry: the absolute local error tolerance.
Constraint: ${\mathbf{atol}}\left(i\right)\ge 0.0$ for all relevant $i$.
Note: corresponding elements of rtol and atol cannot both be $0.0$.
17:   $\mathbf{itol}$ – IntegerInput
On entry: a value to indicate the form of the local error test. itol indicates to d03pkf whether to interpret either or both of rtol or atol as a vector or scalar. The error test to be satisfied is $‖{e}_{i}/{w}_{i}‖<1.0$, where ${w}_{i}$ is defined as follows:
 itol rtol atol ${w}_{i}$ 1 scalar scalar ${\mathbf{rtol}}\left(1\right)×\left|{\mathbf{u}}\left(i\right)\right|+{\mathbf{atol}}\left(1\right)$ 2 scalar vector ${\mathbf{rtol}}\left(1\right)×\left|{\mathbf{u}}\left(i\right)\right|+{\mathbf{atol}}\left(i\right)$ 3 vector scalar ${\mathbf{rtol}}\left(i\right)×\left|{\mathbf{u}}\left(i\right)\right|+{\mathbf{atol}}\left(1\right)$ 4 vector vector ${\mathbf{rtol}}\left(i\right)×\left|{\mathbf{u}}\left(i\right)\right|+{\mathbf{atol}}\left(i\right)$
In the above, ${e}_{\mathit{i}}$ denotes the estimated local error for the $\mathit{i}$th component of the coupled PDE/ODE system in time, ${\mathbf{u}}\left(\mathit{i}\right)$, for $\mathit{i}=1,2,\dots ,{\mathbf{neqn}}$.
The choice of norm used is defined by the argument norm.
Constraint: $1\le {\mathbf{itol}}\le 4$.
18:   $\mathbf{norm}$ – Character(1)Input
On entry: the type of norm to be used.
${\mathbf{norm}}=\text{'M'}$
Maximum norm.
${\mathbf{norm}}=\text{'A'}$
Averaged ${L}_{2}$ norm.
If ${{\mathbf{u}}}_{\mathrm{norm}}$ denotes the norm of the vector u of length neqn, then for the averaged ${L}_{2}$ norm
 $unorm=1neqn∑i=1neqnui/wi2,$
while for the maximum norm
 $u norm = maxi ui / wi .$
See the description of itol for the formulation of the weight vector $w$.
Constraint: ${\mathbf{norm}}=\text{'M'}$ or $\text{'A'}$.
19:   $\mathbf{laopt}$ – Character(1)Input
On entry: the type of matrix algebra required.
${\mathbf{laopt}}=\text{'F'}$
Full matrix methods to be used.
${\mathbf{laopt}}=\text{'B'}$
Banded matrix methods to be used.
${\mathbf{laopt}}=\text{'S'}$
Sparse matrix methods to be used.
Constraint: ${\mathbf{laopt}}=\text{'F'}$, $\text{'B'}$ or $\text{'S'}$.
Note: you are recommended to use the banded option when no coupled ODEs are present (i.e., ${\mathbf{nv}}=0$).
20:   $\mathbf{algopt}\left(30\right)$ – Real (Kind=nag_wp) arrayInput
On entry: may be set to control various options available in the integrator. If you wish to employ all the default options, ${\mathbf{algopt}}\left(1\right)$ should be set to $0.0$. Default values will also be used for any other elements of algopt set to zero. The permissible values, default values, and meanings are as follows:
${\mathbf{algopt}}\left(1\right)$
Selects the ODE integration method to be used. If ${\mathbf{algopt}}\left(1\right)=1.0$, a BDF method is used and if ${\mathbf{algopt}}\left(1\right)=2.0$, a Theta method is used. The default value is ${\mathbf{algopt}}\left(1\right)=1.0$.
If ${\mathbf{algopt}}\left(1\right)=2.0$, then ${\mathbf{algopt}}\left(\mathit{i}\right)$, for $\mathit{i}=2,3,4$, are not used.
${\mathbf{algopt}}\left(2\right)$
Specifies the maximum order of the BDF integration formula to be used. ${\mathbf{algopt}}\left(2\right)$ may be $1.0$, $2.0$, $3.0$, $4.0$ or $5.0$. The default value is ${\mathbf{algopt}}\left(2\right)=5.0$.
${\mathbf{algopt}}\left(3\right)$
Specifies what method is to be used to solve the system of nonlinear equations arising on each step of the BDF method. If ${\mathbf{algopt}}\left(3\right)=1.0$ a modified Newton iteration is used and if ${\mathbf{algopt}}\left(3\right)=2.0$ a functional iteration method is used. If functional iteration is selected and the integrator encounters difficulty, there is an automatic switch to the modified Newton iteration. The default value is ${\mathbf{algopt}}\left(3\right)=1.0$.
${\mathbf{algopt}}\left(4\right)$
Specifies whether or not the Petzold error test is to be employed. The Petzold error test results in extra overhead but is more suitable when algebraic equations are present, such as ${P}_{i,\mathit{j}}=0.0$, for $\mathit{j}=1,2,\dots ,{\mathbf{npde}}$, for some $i$ or when there is no ${\stackrel{.}{V}}_{i}\left(t\right)$ dependence in the coupled ODE system. If ${\mathbf{algopt}}\left(4\right)=1.0$, the Petzold test is used. If ${\mathbf{algopt}}\left(4\right)=2.0$, the Petzold test is not used. The default value is ${\mathbf{algopt}}\left(4\right)=1.0$.
If ${\mathbf{algopt}}\left(1\right)=1.0$, ${\mathbf{algopt}}\left(\mathit{i}\right)$, for $\mathit{i}=5,6,7$, are not used.
${\mathbf{algopt}}\left(5\right)$
Specifies the value of Theta to be used in the Theta integration method. $0.51\le {\mathbf{algopt}}\left(5\right)\le 0.99$. The default value is ${\mathbf{algopt}}\left(5\right)=0.55$.
${\mathbf{algopt}}\left(6\right)$
Specifies what method is to be used to solve the system of nonlinear equations arising on each step of the Theta method. If ${\mathbf{algopt}}\left(6\right)=1.0$, a modified Newton iteration is used and if ${\mathbf{algopt}}\left(6\right)=2.0$, a functional iteration method is used. The default value is ${\mathbf{algopt}}\left(6\right)=1.0$.
${\mathbf{algopt}}\left(7\right)$
Specifies whether or not the integrator is allowed to switch automatically between modified Newton and functional iteration methods in order to be more efficient. If ${\mathbf{algopt}}\left(7\right)=1.0$, switching is allowed and if ${\mathbf{algopt}}\left(7\right)=2.0$, switching is not allowed. The default value is ${\mathbf{algopt}}\left(7\right)=1.0$.
${\mathbf{algopt}}\left(11\right)$
Specifies a point in the time direction, ${t}_{\mathrm{crit}}$, beyond which integration must not be attempted. The use of ${t}_{\mathrm{crit}}$ is described under the argument itask. If ${\mathbf{algopt}}\left(1\right)\ne 0.0$, a value of $0.0$, for ${\mathbf{algopt}}\left(11\right)$, say, should be specified even if itask subsequently specifies that ${t}_{\mathrm{crit}}$ will not be used.
${\mathbf{algopt}}\left(12\right)$
Specifies the minimum absolute step size to be allowed in the time integration. If this option is not required, ${\mathbf{algopt}}\left(12\right)$ should be set to $0.0$.
${\mathbf{algopt}}\left(13\right)$
Specifies the maximum absolute step size to be allowed in the time integration. If this option is not required, ${\mathbf{algopt}}\left(13\right)$ should be set to $0.0$.
${\mathbf{algopt}}\left(14\right)$
Specifies the initial step size to be attempted by the integrator. If ${\mathbf{algopt}}\left(14\right)=0.0$, the initial step size is calculated internally.
${\mathbf{algopt}}\left(15\right)$
Specifies the maximum number of steps to be attempted by the integrator in any one call. If ${\mathbf{algopt}}\left(15\right)=0.0$, no limit is imposed.
${\mathbf{algopt}}\left(23\right)$
Specifies what method is to be used to solve the nonlinear equations at the initial point to initialize the values of $U$, ${U}_{t}$, $V$ and $\stackrel{.}{V}$. If ${\mathbf{algopt}}\left(23\right)=1.0$, a modified Newton iteration is used and if ${\mathbf{algopt}}\left(23\right)=2.0$, functional iteration is used. The default value is ${\mathbf{algopt}}\left(23\right)=1.0$.
${\mathbf{algopt}}\left(29\right)$ and ${\mathbf{algopt}}\left(30\right)$ are used only for the sparse matrix algebra option, i.e., ${\mathbf{laopt}}=\text{'S'}$.
${\mathbf{algopt}}\left(29\right)$
Governs the choice of pivots during the decomposition of the first Jacobian matrix. It should lie in the range $0.0<{\mathbf{algopt}}\left(29\right)<1.0$, with smaller values biasing the algorithm towards maintaining sparsity at the expense of numerical stability. If ${\mathbf{algopt}}\left(29\right)$ lies outside this range then the default value is used. If the routines regard the Jacobian matrix as numerically singular then increasing ${\mathbf{algopt}}\left(29\right)$ towards $1.0$ may help, but at the cost of increased fill-in. The default value is ${\mathbf{algopt}}\left(29\right)=0.1$.
${\mathbf{algopt}}\left(30\right)$
Used as a relative pivot threshold during subsequent Jacobian decompositions (see ${\mathbf{algopt}}\left(29\right)$) below which an internal error is invoked. ${\mathbf{algopt}}\left(30\right)$ must be greater than zero, otherwise the default value is used. If ${\mathbf{algopt}}\left(30\right)$ is greater than $1.0$ no check is made on the pivot size, and this may be a necessary option if the Jacobian is found to be numerically singular (see ${\mathbf{algopt}}\left(29\right)$). The default value is ${\mathbf{algopt}}\left(30\right)=0.0001$.
21:   $\mathbf{rsave}\left({\mathbf{lrsave}}\right)$ – Real (Kind=nag_wp) arrayCommunication Array
If ${\mathbf{ind}}=0$, rsave need not be set on entry.
If ${\mathbf{ind}}=1$, rsave must be unchanged from the previous call to the routine because it contains required information about the iteration.
22:   $\mathbf{lrsave}$ – IntegerInput
On entry: the dimension of the array rsave as declared in the (sub)program from which d03pkf is called. Its size depends on the type of matrix algebra selected.
If ${\mathbf{laopt}}=\text{'F'}$, ${\mathbf{lrsave}}\ge {\mathbf{neqn}}×{\mathbf{neqn}}+{\mathbf{neqn}}+\mathit{nwkres}+\mathit{lenode}$.
If ${\mathbf{laopt}}=\text{'B'}$, ${\mathbf{lrsave}}\ge \left(2×\mathit{ml}+\mathit{mu}+2\right)×{\mathbf{neqn}}+\mathit{nwkres}+\mathit{lenode}$.
If ${\mathbf{laopt}}=\text{'S'}$, ${\mathbf{lrsave}}\ge 4×{\mathbf{neqn}}+11×{\mathbf{neqn}}/2+1+\mathit{nwkres}+\mathit{lenode}$.
Where
 $\mathit{ml}$ and $\mathit{mu}$ are the lower and upper half bandwidths given by $\mathit{ml}={\mathbf{npde}}+{\mathbf{nleft}}-1$ such that $\mathit{mu}=2×{\mathbf{npde}}-{\mathbf{nleft}}-1$, for problems involving PDEs only; or $\mathit{ml}=\mathit{mu}={\mathbf{neqn}}-1$, for coupled PDE/ODE problems. $\mathit{nwkres}=\left\{\begin{array}{ll}{\mathbf{npde}}×\left(3×{\mathbf{npde}}+6×{\mathbf{nxi}}+{\mathbf{npts}}+15\right)+{\mathbf{nxi}}+{\mathbf{nv}}+7×{\mathbf{npts}}+2\text{,}& \text{when ​}{\mathbf{nv}}>0\text{​ and ​}{\mathbf{nxi}}>0\text{; or}\\ {\mathbf{npde}}×\left(3×{\mathbf{npde}}+{\mathbf{npts}}+21\right)+{\mathbf{nv}}+7×{\mathbf{npts}}+3\text{,}& \text{when ​}{\mathbf{nv}}>0\text{​ and ​}{\mathbf{nxi}}=0\text{; or}\\ {\mathbf{npde}}×\left(3×{\mathbf{npde}}+{\mathbf{npts}}+21\right)+7×{\mathbf{npts}}+4\text{,}& \text{when ​}{\mathbf{nv}}=0\text{.}\end{array}\right\$ $\mathit{lenode}=\left\{\begin{array}{ll}\left(6+\mathrm{int}\left({\mathbf{algopt}}\left(2\right)\right)\right)×{\mathbf{neqn}}+50\text{,}& \text{when the BDF method is used; or}\\ 9×{\mathbf{neqn}}+50\text{,}& \text{when the Theta method is used.}\end{array}\right\$
Note: when using the sparse option, the value of lrsave may be too small when supplied to the integrator. An estimate of the minimum size of lrsave is printed on the current error message unit if ${\mathbf{itrace}}>0$ and the routine returns with ${\mathbf{ifail}}={\mathbf{15}}$.
23:   $\mathbf{isave}\left({\mathbf{lisave}}\right)$ – Integer arrayCommunication Array
If ${\mathbf{ind}}=0$, isave need not be set.
If ${\mathbf{ind}}=1$, isave must be unchanged from the previous call to the routine because it contains required information about the iteration. In particular the following components of the array isave concern the efficiency of the integration:
${\mathbf{isave}}\left(1\right)$
Contains the number of steps taken in time.
${\mathbf{isave}}\left(2\right)$
Contains the number of residual evaluations of the resulting ODE system used. One such evaluation involves evaluating the PDE functions at all the mesh points, as well as one evaluation of the functions in the boundary conditions.
${\mathbf{isave}}\left(3\right)$
Contains the number of Jacobian evaluations performed by the time integrator.
${\mathbf{isave}}\left(4\right)$
Contains the order of the ODE method last used in the time integration.
${\mathbf{isave}}\left(5\right)$
Contains the number of Newton iterations performed by the time integrator. Each iteration involves residual evaluation of the resulting ODE system followed by a back-substitution using the $LU$ decomposition of the Jacobian matrix.
24:   $\mathbf{lisave}$ – IntegerInput
On entry: the dimension of the array isave as declared in the (sub)program from which d03pkf is called. Its size depends on the type of matrix algebra selected:
• if ${\mathbf{laopt}}=\text{'F'}$, ${\mathbf{lisave}}\ge 24$;
• if ${\mathbf{laopt}}=\text{'B'}$, ${\mathbf{lisave}}\ge {\mathbf{neqn}}+24$;
• if ${\mathbf{laopt}}=\text{'S'}$, ${\mathbf{lisave}}\ge 25×{\mathbf{neqn}}+24$.
Note: when using the sparse option, the value of lisave may be too small when supplied to the integrator. An estimate of the minimum size of lisave is printed on the current error message unit if ${\mathbf{itrace}}>0$ and the routine returns with ${\mathbf{ifail}}={\mathbf{15}}$.
25:   $\mathbf{itask}$ – IntegerInput
On entry: the task to be performed by the ODE integrator.
${\mathbf{itask}}=1$
Normal computation of output values u at $t={\mathbf{tout}}$ (by overshooting and interpolating).
${\mathbf{itask}}=2$
Take one step in the time direction and return.
${\mathbf{itask}}=3$
Stop at first internal integration point at or beyond $t={\mathbf{tout}}$.
${\mathbf{itask}}=4$
Normal computation of output values u at $t={\mathbf{tout}}$ but without overshooting $t={t}_{\mathrm{crit}}$ where ${t}_{\mathrm{crit}}$ is described under the argument algopt.
${\mathbf{itask}}=5$
Take one step in the time direction and return, without passing ${t}_{\mathrm{crit}}$, where ${t}_{\mathrm{crit}}$ is described under the argument algopt.
Constraint: ${\mathbf{itask}}=1$, $2$, $3$, $4$ or $5$.
26:   $\mathbf{itrace}$ – IntegerInput
On entry: the level of trace information required from d03pkf and the underlying ODE solver as follows:
${\mathbf{itrace}}\le -1$
No output is generated.
${\mathbf{itrace}}=0$
Only warning messages from the PDE solver are printed on the current error message unit (see x04aaf).
${\mathbf{itrace}}=1$
Output from the underlying ODE solver is printed on the current advisory message unit (see x04abf). This output contains details of Jacobian entries, the nonlinear iteration and the time integration during the computation of the ODE system.
${\mathbf{itrace}}=2$
Output from the underlying ODE solver is similar to that produced when ${\mathbf{itrace}}=1$, except that the advisory messages are given in greater detail.
${\mathbf{itrace}}\ge 3$
Output from the underlying ODE solver is similar to that produced when ${\mathbf{itrace}}=2$, except that the advisory messages are given in greater detail.
You advised to set ${\mathbf{itrace}}=0$, unless you are experienced with Sub-chapter D02M–N.
27:   $\mathbf{ind}$ – IntegerInput/Output
On entry: indicates whether this is a continuation call or a new integration.
${\mathbf{ind}}=0$
Starts or restarts the integration in time.
${\mathbf{ind}}=1$
Continues the integration after an earlier exit from the routine. In this case, only the arguments tout and ifail should be reset between calls to d03pkf.
Constraint: ${\mathbf{ind}}=0$ or $1$.
On exit: ${\mathbf{ind}}=1$.
28:   $\mathbf{ifail}$ – IntegerInput/Output
On entry: ifail must be set to $0$, . 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  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  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).
Errors or warnings detected by the routine:
${\mathbf{ifail}}=1$
On entry, at least one point in xi lies outside $\left[{\mathbf{x}}\left(1\right),{\mathbf{x}}\left({\mathbf{npts}}\right)\right]$: ${\mathbf{x}}\left(1\right)=〈\mathit{\text{value}}〉$ and ${\mathbf{x}}\left({\mathbf{npts}}\right)=〈\mathit{\text{value}}〉$.
On entry, $\mathit{i}=〈\mathit{\text{value}}〉$, ${\mathbf{x}}\left(\mathit{i}\right)=〈\mathit{\text{value}}〉$, $\mathit{j}=〈\mathit{\text{value}}〉$ and ${\mathbf{x}}\left(\mathit{j}\right)=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{x}}\left(1\right)<{\mathbf{x}}\left(2\right)<\cdots <{\mathbf{x}}\left({\mathbf{npts}}\right)$.
On entry, $\mathit{i}=〈\mathit{\text{value}}〉$, ${\mathbf{xi}}\left(\mathit{i}+1\right)=〈\mathit{\text{value}}〉$ and ${\mathbf{xi}}\left(\mathit{i}\right)=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{xi}}\left(\mathit{i}+1\right)>{\mathbf{xi}}\left(\mathit{i}\right)$.
On entry, $\mathit{i}=〈\mathit{\text{value}}〉$ and ${\mathbf{atol}}\left(\mathit{i}\right)=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{atol}}\left(\mathit{i}\right)\ge 0.0$.
On entry, $\mathit{i}=〈\mathit{\text{value}}〉$ and $\mathit{j}=〈\mathit{\text{value}}〉$.
Constraint: corresponding elements ${\mathbf{atol}}\left(\mathit{i}\right)$ and ${\mathbf{rtol}}\left(\mathit{j}\right)$ cannot both be $0.0$.
On entry, $\mathit{i}=〈\mathit{\text{value}}〉$ and ${\mathbf{rtol}}\left(\mathit{i}\right)=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{rtol}}\left(\mathit{i}\right)\ge 0.0$.
On entry, ${\mathbf{ind}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{ind}}=0$ or $1$.
On entry, ${\mathbf{itask}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{itask}}=1$, $2$, $3$, $4$ or $5$.
On entry, ${\mathbf{itol}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{itol}}=1$, $2$, $3$ or $4$.
On entry, ${\mathbf{laopt}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{laopt}}=\text{'F'}$, $\text{'B'}$ or $\text{'S'}$.
On entry, ${\mathbf{lisave}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{lisave}}\ge 〈\mathit{\text{value}}〉$.
On entry, ${\mathbf{lrsave}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{lrsave}}\ge 〈\mathit{\text{value}}〉$.
On entry, ${\mathbf{neqn}}=〈\mathit{\text{value}}〉$, ${\mathbf{npde}}=〈\mathit{\text{value}}〉$, ${\mathbf{npts}}=〈\mathit{\text{value}}〉$ and ${\mathbf{nv}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{neqn}}={\mathbf{npde}}×{\mathbf{npts}}+{\mathbf{nv}}$.
On entry, ${\mathbf{nleft}}=〈\mathit{\text{value}}〉$, ${\mathbf{npde}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{nleft}}\le {\mathbf{npde}}$.
On entry, ${\mathbf{nleft}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{nleft}}\ge 0$.
On entry, ${\mathbf{norm}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{norm}}=\text{'A'}$ or $\text{'M'}$.
On entry, ${\mathbf{npde}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{npde}}\ge 1$.
On entry, ${\mathbf{npts}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{npts}}\ge 3$.
On entry, ${\mathbf{nv}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{nv}}\ge 0$.
On entry, ${\mathbf{nv}}=〈\mathit{\text{value}}〉$ and ${\mathbf{nxi}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{nxi}}=0$ when ${\mathbf{nv}}=0$.
On entry, ${\mathbf{nv}}=〈\mathit{\text{value}}〉$ and ${\mathbf{nxi}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{nxi}}\ge 0$ when ${\mathbf{nv}}>0$.
On entry, on initial entry ${\mathbf{ind}}=1$.
Constraint: on initial entry ${\mathbf{ind}}=0$.
On entry, ${\mathbf{tout}}=〈\mathit{\text{value}}〉$ and ${\mathbf{ts}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{tout}}>{\mathbf{ts}}$.
On entry, ${\mathbf{tout}}-{\mathbf{ts}}$ is too small: ${\mathbf{tout}}=〈\mathit{\text{value}}〉$ and ${\mathbf{ts}}=〈\mathit{\text{value}}〉$.
${\mathbf{ifail}}=2$
Underlying ODE solver cannot make further progress from the point ts with the supplied values of atol and rtol. ${\mathbf{ts}}=〈\mathit{\text{value}}〉$.
${\mathbf{ifail}}=3$
Repeated errors in an attempted step of underlying ODE solver. Integration was successful as far as ts: ${\mathbf{ts}}=〈\mathit{\text{value}}〉$.
In the underlying ODE solver, there were repeated error test failures on an attempted step, before completing the requested task, but the integration was successful as far as $t={\mathbf{ts}}$. The problem may have a singularity, or the error requirement may be inappropriate. Incorrect positioning of boundary conditions may also result in this error.
${\mathbf{ifail}}=4$
In setting up the ODE system an internal auxiliary was unable to initialize the derivative. This could be due to your setting ${\mathbf{ires}}=3$ in pdedef or bndary.
${\mathbf{ifail}}=5$
Singular Jacobian of ODE system. Check problem formulation.
${\mathbf{ifail}}=6$
In evaluating residual of ODE system, ${\mathbf{ires}}=2$ has been set in pdedef, bndary, or odedef. Integration is successful as far as ts: ${\mathbf{ts}}=〈\mathit{\text{value}}〉$.
${\mathbf{ifail}}=7$
atol and rtol were too small to start integration.
${\mathbf{ifail}}=8$
ires set to an invalid value in call to pdedef, bndary, or odedef.
${\mathbf{ifail}}=9$
Serious error in internal call to an auxiliary. Increase itrace for further details.
${\mathbf{ifail}}=10$
Integration completed, but small changes in atol or rtol are unlikely to result in a changed solution.
The required task has been completed, but it is estimated that a small change in atol and rtol is unlikely to produce any change in the computed solution. (Only applies when you are not operating in one step mode, that is when ${\mathbf{itask}}\ne 2$ or $5$.)
${\mathbf{ifail}}=11$
Error during Jacobian formulation for ODE system. Increase itrace for further details.
${\mathbf{ifail}}=12$
In solving ODE system, the maximum number of steps ${\mathbf{algopt}}\left(15\right)$ has been exceeded. ${\mathbf{algopt}}\left(15\right)=〈\mathit{\text{value}}〉$.
${\mathbf{ifail}}=13$
Zero error weights encountered during time integration.
Some error weights ${w}_{i}$ became zero during the time integration (see the description of itol). Pure relative error control $\left({\mathbf{atol}}\left(i\right)=0.0\right)$ was requested on a variable (the $i$th) which has become zero. The integration was successful as far as $t={\mathbf{ts}}$.
${\mathbf{ifail}}=15$
When using the sparse option lisave or lrsave is too small: ${\mathbf{lisave}}=〈\mathit{\text{value}}〉$, ${\mathbf{lrsave}}=〈\mathit{\text{value}}〉$.
${\mathbf{ifail}}=-99$
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

d03pkf controls the accuracy of the integration in the time direction but not the accuracy of the approximation in space. The spatial accuracy depends on both the number of mesh points and on their distribution in space. In the time integration only the local error over a single step is controlled and so the accuracy over a number of steps cannot be guaranteed. You should therefore test the effect of varying the accuracy arguments, atol and rtol.

## 8Parallelism and Performance

d03pkf is not thread safe and should not be called from a multithreaded user program. Please see Section 3.12.1 in How to Use the NAG Library and its Documentation for more information on thread safety.
d03pkf is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
d03pkf 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 implementation-specific information.

The Keller box scheme can be used to solve higher-order problems which have been reduced to first-order by the introduction of new variables (see the example in Section 10). In general, a second-order problem can be solved with slightly greater accuracy using the Keller box scheme instead of a finite difference scheme (see d03pcf/d03pca or d03phf/d03pha for example), but at the expense of increased CPU time due to the larger number of function evaluations required.
It should be noted that the Keller box scheme, in common with other central-difference schemes, may be unsuitable for some hyperbolic first-order problems such as the apparently simple linear advection equation ${U}_{t}+a{U}_{x}=0$, where $a$ is a constant, resulting in spurious oscillations due to the lack of dissipation. This type of problem requires a discretization scheme with upwind weighting (d03plf for example), or the addition of a second-order artificial dissipation term.
The time taken depends on the complexity of the system and on the accuracy requested. For a given system and a fixed accuracy it is approximately proportional to neqn.

## 10Example

This example provides a simple coupled system of two PDEs and one ODE.
 $V1 2 ∂U1 ∂t -xV1V.1U2- ∂U2 ∂x =0, U2- ∂U1 ∂x =0, V.1-V1U1-U2-1-t=0,$
for $t\in \left[{10}^{-4},0.1×{2}^{i}\right]$, for $i=1,2,\dots ,5,x\in \left[0,1\right]$. The left boundary condition at $x=0$ is
 $U2=-V1exp⁡t,$
and the right boundary condition at $x=1$ is
 $U2=-V1V.1.$
The initial conditions at $t={10}^{-4}$ are defined by the exact solution:
 $V1 = t , U1 x,t = exp t 1-x - 1.0 and U2 x,t = - t exp t 1-x , ​ x ∈ 0,1 ,$
and the coupling point is at ${\xi }_{1}=1.0$.
This problem is exactly the same as the d03phf/d03pha example problem, but reduced to first-order by the introduction of a second PDE variable (as mentioned in Section 9).

### 10.1Program Text

Program Text (d03pkfe.f90)

### 10.2Program Data

Program Data (d03pkfe.d)

### 10.3Program Results

Program Results (d03pkfe.r)