code: def spherical_yn(n, z, derivative=False):
      r"""Spherical Bessel function of the second kind or its derivative.
  
      Defined as [1]_,
  
      .. math:: y_n(z) = \sqrt{\frac{\pi}{2z}} Y_{n + 1/2}(z),
  
      where :math:`Y_n` is the Bessel function of the second kind.
  
      Parameters
      ----------
      n : int, array_like
          Order of the Bessel function (n >= 0).
      z : complex or float, array_like
          Argument of the Bessel function.
      derivative : bool, optional
          If True, the value of the derivative (rather than the function
          itself) is returned.
  
      Returns
      -------
      yn : ndarray
  
      Notes
      -----
      For real arguments, the function is computed using the ascending
      recurrence [2]_.  For complex arguments, the definitional relation to
      the cylindrical Bessel function of the second kind is used.
  
      The derivative is computed using the relations [3]_,
  
      .. math::
          y_n' = y_{n-1} - \frac{n + 1}{z} y_n.
  
          y_0' = -y_1
  
  
      .. versionadded:: 0.18.0
  
      References
      ----------
      .. [1] https://dlmf.nist.gov/10.47.E4
      .. [2] https://dlmf.nist.gov/10.51.E1
      .. [3] https://dlmf.nist.gov/10.51.E2
      .. [AS] Milton Abramowitz and Irene A. Stegun, eds.
          Handbook of Mathematical Functions with Formulas,
          Graphs, and Mathematical Tables. New York: Dover, 1972.
  
      Examples
      --------
      The spherical Bessel functions of the second kind :math:`y_n` accept
      both real and complex second argument. They can return a complex type:
  
      >>> from scipy.special import spherical_yn
      >>> spherical_yn(0, 3+5j)
      (8.022343088587197-9.880052589376795j)
      >>> type(spherical_yn(0, 3+5j))
      <class 'numpy.complex128'>
  
      We can verify the relation for the derivative from the Notes
      for :math:`n=3` in the interval :math:`[1, 2]`:
  
      >>> import numpy as np
      >>> x = np.arange(1.0, 2.0, 0.01)
      >>> np.allclose(spherical_yn(3, x, True),
      ...             spherical_yn(2, x) - 4/x * spherical_yn(3, x))
      True
  
      The first few :math:`y_n` with real argument:
  
      >>> import matplotlib.pyplot as plt
      >>> x = np.arange(0.0, 10.0, 0.01)
      >>> fig, ax = plt.subplots()
      >>> ax.set_ylim(-2.0, 1.0)
      >>> ax.set_title(r'Spherical Bessel functions $y_n$')
      >>> for n in np.arange(0, 4):
      ...     ax.plot(x, spherical_yn(n, x), label=rf'$y_{n}$')
      >>> plt.legend(loc='best')
      >>> plt.show()
  
      """
      n = np.asarray(n, dtype=np.dtype("long"))
      if derivative:
          return _spherical_yn_d(n, z)
      else:
          return _spherical_yn(n, z)
  
imports: import numpy
  from ._ufuncs import _spherical_jn, _spherical_yn, _spherical_in, _spherical_kn, _spherical_jn_d, _spherical_yn_d, _spherical_in_d, _spherical_kn_d
label_desc: Use image node_id 2 for calling a global function with example usage: spherical_yn(n, z, derivative) and returns: _spherical_yn_d, _spherical_yn