scipy.special.y0#

scipy.special.y0(x, out=None) = <ufunc 'y0'>#

Bessel function of the second kind of order 0.

Parameters:

xarray_like: Argument (float).
outndarray, optional: Optional output array for the function results

Returns:

Yscalar or ndarray: Value of the Bessel function of the second kind of order 0 at x.

See also

j0: Bessel function of the first kind of order 0
yv: Bessel function of the first kind

Notes

The domain is divided into the intervals [0, 5] and (5, infinity). In the first interval a rational approximation \(R(x)\) is employed to compute,

\[Y_0(x) = R(x) + \frac{2 \log(x) J_0(x)}{\pi},\]

where \(J_0\) is the Bessel function of the first kind of order 0.

In the second interval, the Hankel asymptotic expansion is employed with two rational functions of degree 6/6 and 7/7.

This function is a wrapper for the Cephes [1] routine y0.

y0 has experimental support for Python Array API Standard compatible backends in addition to NumPy. Please consider testing these features by setting an environment variable SCIPY_ARRAY_API=1 and providing CuPy, PyTorch, JAX, or Dask arrays as array arguments. The following combinations of backend and device (or other capability) are supported.

Library	CPU	GPU
NumPy	✅	n/a
CuPy	n/a	✅
PyTorch	✅	✅
JAX	⚠️ no JIT	⛔
Dask	✅	n/a

See Support for the array API standard for more information.

References

[1]

Cephes Mathematical Functions Library, http://www.netlib.org/cephes/

Examples

Calculate the function at one point:

>>> from scipy.special import y0
>>> y0(1.)
0.08825696421567697

Calculate at several points:

>>> import numpy as np
>>> y0(np.array([0.5, 2., 3.]))
array([-0.44451873,  0.51037567,  0.37685001])

Plot the function from 0 to 10.

>>> import matplotlib.pyplot as plt
>>> fig, ax = plt.subplots()
>>> x = np.linspace(0., 10., 1000)
>>> y = y0(x)
>>> ax.plot(x, y)
>>> plt.show()