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bundles / scipy latest / scipy / special / _basic / jvp

function

scipy.special._basic:jvp

source: /scipy/special/_basic.py :817

Signature

def   jvp ( v z n = 1 )

Summary

Compute derivatives of Bessel functions of the first kind.

Extended Summary

Compute the nth derivative of the Bessel function Jv with respect to z.

Parameters

v : array_like or float

Order of Bessel function

z : complex

Argument at which to evaluate the derivative; can be real or complex.

n : int, default 1

Order of derivative. For 0 returns the Bessel function jv itself.

Returns

: scalar or ndarray

Values of the derivative of the Bessel function.

Notes

The derivative is computed using the relation DLFM 10.6.7 [2].

Examples

Compute the Bessel function of the first kind of order 0 and its first two derivatives at 1.
from scipy.special import jvp
jvp(0, 1, 0), jvp(0, 1, 1), jvp(0, 1, 2)
Compute the first derivative of the Bessel function of the first kind for several orders at 1 by providing an array for `v`.
jvp([0, 1, 2], 1, 1)
Compute the first derivative of the Bessel function of the first kind of order 0 at several points by providing an array for `z`.
import numpy as np
points = np.array([0., 1.5, 3.])
jvp(0, points, 1)
Plot the Bessel function of the first kind of order 1 and its first three derivatives.
import matplotlib.pyplot as plt
x = np.linspace(-10, 10, 1000)
fig, ax = plt.subplots()
ax.plot(x, jvp(1, x, 0), label=r"$J_1$")
ax.plot(x, jvp(1, x, 1), label=r"$J_1'$")
ax.plot(x, jvp(1, x, 2), label=r"$J_1''$")
ax.plot(x, jvp(1, x, 3), label=r"$J_1'''$")
plt.legend()
plt.show()
fig-2097db44fe5c9b83.png

Aliases

  • scipy.special.jvp