The function may be called by the names: s17asc, nag_specfun_bessel_j0_real_vector or nag_bessel_j0_vector.
s17asc evaluates an approximation to the Bessel function of the first kind for an array of arguments , for .
Note: , so the approximation need only consider .
The function is based on three Chebyshev expansions:
For near zero, . This approximation is used when is sufficiently small for the result to be correct to machine precision.
For very large , it becomes impossible to provide results with any reasonable accuracy (see Section 7), hence the function fails. Such arguments contain insufficient information to determine the phase of oscillation of ; only the amplitude, , can be determined and this is returned on failure. The range for which this occurs is roughly related to machine precision; the function will fail if
(see the Users' Note for your implementation for details).
Clenshaw C W (1962) Chebyshev Series for Mathematical Functions Mathematical tables HMSO
1: – IntegerInput
On entry: , the number of points.
2: – const doubleInput
On entry: the argument of the function, for .
3: – doubleOutput
On exit: , the function values.
4: – IntegerOutput
On exit: contains the error code for , for .
On entry, is too large. contains the amplitude of the oscillation, .
5: – NagError *Input/Output
The NAG error argument (see Section 7 in the Introduction to the NAG Library CL Interface).
6Error Indicators and Warnings
Dynamic memory allocation failed.
See Section 3.1.2 in the Introduction to the NAG Library CL Interface for further information.
On entry, argument had an illegal value.
On entry, .
An internal error has occurred in this function. Check the function call and any array sizes. If the call is correct then please contact NAG for assistance.
See Section 7.5 in the Introduction to the NAG Library CL Interface for further information.
Your licence key may have expired or may not have been installed correctly.
See Section 8 in the Introduction to the NAG Library CL Interface for further information.
On entry, at least one value of x was invalid.
Check ivalid for more information.
Let be the relative error in the argument and be the absolute error in the result. (Since oscillates about zero, absolute error and not relative error is significant.)
If is somewhat larger than the machine precision (e.g., if is due to data errors etc.), then and are approximately related by:
(provided is also within machine bounds). Figure 1 displays the behaviour of the amplification factor .
However, if is of the same order as machine precision, then rounding errors could make slightly larger than the above relation predicts.
For very large , the above relation ceases to apply. In this region, . The amplitude can be calculated with reasonable accuracy for all , but cannot. If is written as where is an integer and , then is determined by only. If , cannot be determined with any accuracy at all. Thus if is greater than, or of the order of, the inverse of the machine precision, it is impossible to calculate the phase of and the function must fail.
8Parallelism and Performance
s17asc is not threaded in any implementation.
This example reads values of x from a file, evaluates the function at each value of and prints the results.