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scipy.special.

# h2vp

scipy.special.h2vp(v, z, n=1)

  Compute derivatives of Hankel function H2v(z) with respect to z.

  Parameters:
    v array_like

      Order of Hankel function

    z array_like

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

    n int, default 1

      Order of derivative. For 0 returns the Hankel function h2v itself.

  Returns:
    scalar or ndarray

      Values of the derivative of the Hankel function.

  See also

  `hankel2`

  Notes

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

  References

  [1]

  Zhang, Shanjie and Jin, Jianming. “Computation of Special Functions”, John Wiley and Sons, 1996, chapter 5. https://people.sc.fsu.edu/~jburkardt/f77_src/special_functions/special_functions.html

  [2]

  NIST Digital Library of Mathematical Functions. https://dlmf.nist.gov/10.6.E7

  Examples

  Compute the Hankel function of the second kind of order 0 and its first two derivatives at 1.

      >>> from scipy.special import h2vp
      >>> h2vp(0, 1, 0), h2vp(0, 1, 1), h2vp(0, 1, 2)
      ((0.7651976865579664-0.088256964215677j),
       (-0.44005058574493355-0.7812128213002889j),
       (-0.3251471008130329+0.8694697855159659j))

  Compute the first derivative of the Hankel function of the second kind for several orders at 1 by providing an array for v.

      >>> h2vp([0, 1, 2], 1, 1)
      array([-0.44005059-0.78121282j,  0.3251471 -0.86946979j,
             0.21024362-2.52015239j])

  Compute the first derivative of the Hankel function of the second kind of order 0 at several points by providing an array for z.

      >>> import numpy as np
      >>> points = np.array([0.5, 1.5, 3.])
      >>> h2vp(0, points, 1)
      array([-0.24226846-1.47147239j, -0.55793651-0.41230863j,
             -0.33905896+0.32467442j])