code: def tau_frank(theta):
      """Kendall's tau for Frank Copula
  
      This uses Taylor series expansion for theta <= 1.
  
      Parameters
      ----------
      theta : float
          Parameter of the Frank copula. (not vectorized)
  
      Returns
      -------
      tau : float, tau for given theta
      """
  
      if theta <= 1:
          tau = _tau_frank_expansion(theta)
      else:
          debye_value = _debye(theta)
          tau = 1 + 4 * (debye_value - 1) / theta
  
      return tau
  
imports: import sys
  import numpy
  from scipy import stats, integrate, optimize
  from .None import transforms
  from .copulas import Copula
  from statsmodels.tools.rng_qrng import check_random_state
label_desc: Use image node_id 3 for calling a global function with example usage: tau_frank(theta) and returns: tau