NAG FL Interface
d02kaf (sl2_​reg_​finite)

1 Purpose

2 Specification

3 Description

4 References

5 Arguments

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

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

On entry: the left- and right-hand end points $a$ and $b$ respectively, of the interval of definition of the problem.

Constraint: $\mathbf{xl}<\mathbf{xr}$.

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

coeffn must compute the values of the coefficient functions $p\left(x\right)$ and $q\left(x;\lambda \right)$ for given values of $x$ and $\lambda$. Section 3 states the conditions which $p$ and $q$ must satisfy.

The specification of coeffn is:

Fortran Interface

Subroutine coeffn ( p, q, dqdl, x, elam, jint) Integer, Intent (In) :: jint Real (Kind=nag_wp), Intent (In) :: x, elam Real (Kind=nag_wp), Intent (Out) :: p, q, dqdl

C Header Interface

void  coeffn_ (double *p, double *q, double *dqdl, const double *x, const double *elam, const Integer *jint)

C++ Header Interface

#include <nag.h> extern "C" { void  coeffn_ (double &p, double &q, double &dqdl, const double &x, const double &elam, const Integer &jint) }

1: $\mathbf{p}$ – Real (Kind=nag_wp) Output

On exit: the value of $p\left(x\right)$ for the current value of $x$.

2: $\mathbf{q}$ – Real (Kind=nag_wp) Output

On exit: the value of $q\left(x;\lambda \right)$ for the current value of $x$ and the current trial value of $\lambda$.

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

On exit: the value of $\frac{\partial q}{\partial \lambda }\left(x;\lambda \right)$ for the current value of $x$ and the current trial value of $\lambda$. However dqdl is only used in error estimation and, in the rare cases where it may be difficult to evaluate, an approximation (say to within $20\%$) will suffice.

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

On entry: the current value of $x$.

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

On entry: the current trial value of the eigenvalue argument $\lambda$.

6: $\mathbf{jint}$ – Integer Input

This argument is included for compatibility with the more complex routine d02kdf (which is called by d02kaf).

On entry: need not be set.

coeffn must either be a module subprogram USEd by, or declared as EXTERNAL in, the (sub)program from which d02kaf is called. Arguments denoted as Input must not be changed by this procedure.

Note: coeffn should not return floating-point NaN (Not a Number) or infinity values, since these are not handled by d02kaf. If your code inadvertently does return any NaNs or infinities, d02kaf is likely to produce unexpected results.

4: $\mathbf{bcond}\left(3,2\right)$ – Real (Kind=nag_wp) array Input/Output

On entry: $\mathbf{bcond}\left(1,1\right)$ and $\mathbf{bcond}\left(2,1\right)$ must contain the numbers $a_1$, $a_2$ specifying the left-hand boundary condition in the form

$$a_{2}y\left(a\right)=a_{1}p\left(a\right)y^{\prime }\left(a\right)$$

where $\left|a_2\right|+\left|a_{1}p\left(a\right)\right|\ne 0$.

$\mathbf{bcond}\left(1,2\right)$ and $\mathbf{bcond}\left(2,2\right)$ must contain $b_1$, $b_2$ such that

$$b_{2}y\left(b\right)=b_{1}p\left(b\right)y^{\prime }\left(b\right)$$

where $\left|b_2\right|+\left|b_{1}p\left(b\right)\right|\ne 0$.

Note the occurrence of $p\left(a\right)$, $p\left(b\right)$ in these formulae.

On exit: $\mathbf{bcond}\left(3,1\right)$ and $\mathbf{bcond}\left(3,2\right)$ hold values ${\sigma }_l,{\sigma }_r$ estimating the sensitivity of the computed eigenvalue to changes in the boundary conditions. These values should only be of interest if the boundary conditions are, in some sense, an approximation to some ‘true’ boundary conditions. For example, if the range [xl, xr] should really be $\left[0,\infty \right]$ but instead xr has been given a large value and the boundary conditions at infinity applied at xr, the sensitivity argument ${\sigma }_r$ may be of interest. Refer to Section 9.5 in d02kdf, for the actual meaning of ${\sigma }_r$ and ${\sigma }_l$.

5: $\mathbf{k}$ – Integer Input

On entry: $k$, the index of the required eigenvalue when the eigenvalues are ordered

$${\lambda }_0<{\lambda }_1<{\lambda }_2<\cdots <{\lambda }_k<\cdots \text{.}$$

Constraint: $\mathbf{k}\ge 0$.

6: $\mathbf{tol}$ – Real (Kind=nag_wp) Input

On entry: the tolerance argument which determines the accuracy of the computed eigenvalue. The error estimate held in delam on exit satisfies the mixed absolute/relative error test

$$\mathbf{delam}\le \mathbf{tol}\times \max \left(1.0,\left|\mathbf{elam}\right|\right)\text{,}$$

(1)

where elam is the final estimate of the eigenvalue. delam is usually somewhat smaller than the right-hand side of (1) but not several orders of magnitude smaller.

Constraint: $\mathbf{tol}>0.0$.

7: $\mathbf{elam}$ – Real (Kind=nag_wp) Input/Output

On entry: an initial estimate of the eigenvalue $\tilde{\lambda }$.

On exit: the final computed estimate, whether or not an error occurred.

8: $\mathbf{delam}$ – Real (Kind=nag_wp) Input/Output

On entry: an indication of the scale of the problem in the $\lambda$-direction. delam holds the initial ‘search step’ (positive or negative). Its value is not critical, but the first two trial evaluations are made at elam and $\mathbf{elam}+\mathbf{delam}$, so the routine will work most efficiently if the eigenvalue lies between these values. A reasonable choice (if a closer bound is not known) is about half the distance between adjacent eigenvalues in the neighbourhood of the one sought. In practice, there will often be a problem, similar to the one in hand but with known eigenvalues, which will help one to choose initial values for elam and delam.

If $\mathbf{delam}=0.0$ on entry, it is given the default value of $0.25\times \max \left(1.0,\left|\mathbf{elam}\right|\right)$.

On exit: if $\mathbf{ifail}=\mathbf{0}$, delam holds an estimate of the absolute error in the computed eigenvalue, that is $\left|\tilde{\lambda }-\mathbf{elam}\right|\simeq \mathbf{delam}$, where $\tilde{\lambda }$ is the true eigenvalue.

If $\mathbf{ifail}\ne \mathbf{0}$, delam may hold an estimate of the error, or its initial value, depending on the value of ifail. See Section 6 for further details.

9: $\mathbf{monit}$ – Subroutine, supplied by the NAG Library or the user. External Procedure

monit is called by d02kaf at the end of each iteration for $\lambda$ and allows you to monitor the course of the computation by printing out the arguments (see Section 10 for an example).

If no monitoring is required, the dummy (sub)program d02kay may be used. (d02kay is included in the NAG Library.)

The specification of monit is:

Fortran Interface

Subroutine monit ( nit, iflag, elam, finfo) Integer, Intent (In) :: nit, iflag Real (Kind=nag_wp), Intent (In) :: elam, finfo(15)

C Header Interface

void  monit_ (const Integer *nit, const Integer *iflag, const double *elam, const double finfo[])

C++ Header Interface

#include <nag.h> extern "C" { void  monit_ (const Integer &nit, const Integer &iflag, const double &elam, const double finfo[]) }

1: $\mathbf{nit}$ – Integer Input

On entry: 15 minus the number of iterations used so far in the search for $\tilde{\lambda }$. (Up to $15$ iterations are permitted.)

2: $\mathbf{iflag}$ – Integer Input

On entry: describes what phase the computation is in.

$\mathbf{iflag}<0$

An error occurred in the computation at this iteration; an error exit from d02kaf will follow.

$\mathbf{iflag}=1$

The routine is trying to bracket the eigenvalue $\tilde{\lambda }$.

$\mathbf{iflag}=2$

The routine is converging to the eigenvalue $\tilde{\lambda }$ (having already bracketed it).

Normally, the iteration will terminate after a sequence of iterates with $\mathbf{iflag}=2$, but occasionally the bracket on $\tilde{\lambda }$ thus determined will not be sufficiently small and the iteration will be repeated with tighter accuracy control.

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

On entry: the current trial value of $\tilde{\lambda }$.

4: $\mathbf{finfo}\left(15\right)$ – Real (Kind=nag_wp) array Input

On entry: information about the behaviour of the shooting method, and diagnostic information in the case of errors. It should not normally be printed in full if no error has occurred (that is, if $\mathbf{iflag}\ge 0$), though the first few components may be of interest to you. In case of an error ($\mathbf{iflag}<0$) all the components of finfo should be printed.

The contents of finfo are as follows:

$\mathbf{finfo}\left(1\right)$

The current value of the ‘miss-distance’ or ‘residual’ function $f\left(\lambda \right)$ on which the shooting method is based. $f\left(\tilde{\lambda }\right)=0$ in theory. This is set to zero if $\mathbf{iflag}<0$.

$\mathbf{finfo}\left(2\right)$

An estimate of the quantity $\partial \lambda$ defined as follows. Consider the perturbation in the miss-distance $f\left(\lambda \right)$ that would result if the local error in the solution of the differential equation were always positive and equal to its maximum permitted value. Then $\partial \lambda$ is the perturbation in $\lambda$ that would have the same effect on $f\left(\lambda \right)$. Thus, at the zero of $f\left(\lambda \right),\left|\partial \lambda \right|$ is an approximate bound on the perturbation of the zero (that is the eigenvalue) caused by errors in numerical solution. If $\partial \lambda$ is very large then it is possible that there has been a programming error in coeffn such that $q$ is independent of $\lambda$. If this is the case, an error exit with $\mathbf{ifail}=\mathbf{5}$ should follow. $\mathbf{finfo}\left(2\right)$ is set to zero if $\mathbf{iflag}<0$.

$\mathbf{finfo}\left(3\right)$

The number of internal iterations, using the same value of $\lambda$ and tighter accuracy tolerances, needed to bring the accuracy (that is, the value of $\partial \lambda$) to an acceptable value. Its value should normally be $1.0$, and should almost never exceed $2.0$.

$\mathbf{finfo}\left(4\right)$

The number of calls to coeffn at this iteration.

$\mathbf{finfo}\left(5\right)$

The number of successful steps taken by the internal differential equation solver at this iteration. A step is successful if it is used to advance the integration.

$\mathbf{finfo}\left(6\right)$

The number of unsuccessful steps used by the internal integrator at this iteration.

$\mathbf{finfo}\left(7\right)$

The number of successful steps at the maximum step size taken by the internal integrator at this iteration.

$\mathbf{finfo}\left(8\right)$

Not used.

$\mathbf{finfo}\left(9\right)$ to $\mathbf{finfo}\left(15\right)$

Set to zero, unless $\mathbf{iflag}<0$ in which case they hold the following values describing the point of failure:

$\mathbf{finfo}\left(9\right)$

1 or $2$ depending on whether integration was in a forward or backward direction at the time of failure.

$\mathbf{finfo}\left(10\right)$

The value of the independent variable, $x$, the point at which the error occurred.

$\mathbf{finfo}\left(11\right)$, $\mathbf{finfo}\left(12\right)$, $\mathbf{finfo}\left(13\right)$

The current values of the Pruefer dependent variables $\beta$, $\varphi$ and $\rho$ respectively. See Section 3 in d02kef for a description of these variables.

$\mathbf{finfo}\left(14\right)$

The local-error tolerance being used by the internal integrator at the point of failure.

$\mathbf{finfo}\left(15\right)$

The last integration mesh point.

monit must either be a module subprogram USEd by, or declared as EXTERNAL in, the (sub)program from which d02kaf is called. Arguments denoted as Input must not be changed by this procedure.

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, 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

$\mathbf{ifail}=1$

On entry, $\mathbf{k}=〈\mathit{\text{value}}〉$.
Constraint: $\mathbf{k}\ge 0$.

On entry, $\mathbf{tol}=〈\mathit{\text{value}}〉$.
Constraint: $\mathbf{tol}>0.0$.

$\mathbf{ifail}=2$

The constraint on the left- or right-hand boundary condition has been violated.

$\mathbf{ifail}=3$

The function $p\left(x\right)$ became zero or changed sign in the interval $\left[a,b\right]$.

$\mathbf{ifail}=4$

After $15$ iterations the eigenvalue had not been found to the required accuracy.

$\mathbf{ifail}=5$

The bracketing phase failed to bracket the eigenvalue within ten iterations. This may be due to an error in formulating the problem (for example, $q$ is independent of $\lambda$), or by very poor initial estimates for the eigenvalue and search step.

On exit, $\mathbf{elam}$ and $\mathbf{elam}+\mathbf{delam}$ give the end points of the interval within which no eigenvalue was located by the routine.

$\mathbf{ifail}=6$

Too small a step size was required at the start of a sub-interval to obtain the desired accuracy.

$\mathbf{ifail}=7$

Too small a step size was required during solution in a sub-interval to obtain the desired accuracy.

At some point inside a sub-interval the step size in the differential equation solver was reduced to a value too small to make significant progress (for the same reasons as with $\mathbf{ifail}=\mathbf{7}$). This could be due to pathological behaviour of $p\left(x\right)$ and $q\left(x;\lambda \right)$ or to an unreasonable accuracy requirement or to the current value of $\lambda$ making the equations ‘stiff’. See the last call of monit for details.

$\mathbf{ifail}=8$

The tolerance set is too small for the problem being solved and the machine precision being used. The local eigenvalue estimate returned is likely to be a very good approximation.

$\mathbf{ifail}=9$

An internal error has occurred corresponding to a pole of the matching function. Try solving the problem again with a smaller tolerance.

$\mathbf{ifail}=-99$

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

8 Parallelism and Performance

9 Further Comments

10 Example

10.1 Program Text

10.2 Program Data

10.3 Program Results