naginterfaces.library.specfun.bessel_​j0_​real_​vector

naginterfaces.library.specfun.bessel_j0_real_vector(x)

bessel_j0_real_vector returns an array of values of the Bessel function $J_0\left(x\right)$.

For full information please refer to the NAG Library document for s17as

https://support.nag.com/numeric/nl/nagdoc_30.3/flhtml/s/s17asf.html

Parameters

xfloat, array-like, shape $\left(n\right)$

The argument $x_{\text{i}}$ of the function, for $\text{i}=1,2,\dots ,n$.

Returns

ffloat, ndarray, shape $\left(n\right)$

$J_0\left(x_i\right)$, the function values.

ivalidint, ndarray, shape $\left(n\right)$

$ivalid[\text{i}-1]$ contains the error code for $x_{\text{i}}$, for $\text{i}=1,2,\dots ,n$.

$ivalid[i-1]=0$

No error.

$ivalid[i-1]=1$

On entry, $x_i$ is too large. $f[\text{i}-1]$ contains the amplitude of the $J_0$ oscillation, $\sqrt{\frac{2}{\pi \left|x_i\right|}}$.

Raises

NagValueError

(errno $2$)

On entry, $n=⟨value⟩$.

Constraint: $n\ge 0$.

Warns

NagAlgorithmicWarning

(errno $1$)

On entry, at least one value of $x$ was invalid.

Check $ivalid$ for more information.

Notes

bessel_j0_real_vector evaluates an approximation to the Bessel function of the first kind $J_0\left(x_i\right)$ for an array of arguments $x_{\text{i}}$, for $\text{i}=1,2,\dots ,n$.

Note: $J_0(-x)=J_0\left(x\right)$, so the approximation need only consider $x\ge 0$.

The function is based on three Chebyshev expansions:

For $0<x\le 8$,

$$J_0\left(x\right)={\sum ^{\prime }}_{r=0}{a}_r{T}_r\left(t\right)\text{, with}t=2{\left(\frac{x}{8}\right)}^2-1\text{.}$$

For $x>8$,

$$J_0\left(x\right)=\sqrt{\frac{2}{\pi x}}\{P_0\left(x\right)\cos (x-\frac{\pi }{4})-Q_0\left(x\right)\sin (x-\frac{\pi }{4})\}\text{,}$$

where $P_0\left(x\right)={{\sum }^{\prime }}_{r=0}{b}_r{T}_r\left(t\right)$,

and $Q_0\left(x\right)=\frac{8}{x}{{\sum }^{\prime }}_{r=0}{c}_r{T}_r\left(t\right)$,

with $t=2{\left(\frac{8}{x}\right)}^2-1$.

For $x$ near zero, $J_0\left(x\right)\simeq 1$. This approximation is used when $x$ is sufficiently small for the result to be correct to machine precision.

For very large $x$, it becomes impossible to provide results with any reasonable accuracy (see Accuracy), hence the function fails. Such arguments contain insufficient information to determine the phase of oscillation of $J_0\left(x\right)$; only the amplitude, $\sqrt{\frac{2}{\pi \left|x\right|}}$, 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 $\left|x\right|\gtrsim 1/\text{machine precision}$.

References

NIST Digital Library of Mathematical Functions

Clenshaw, C W, 1962, Chebyshev Series for Mathematical Functions, Mathematical tables, HMSO