class_docstr: generic multivariate Archimedean copula with additional power transforms
  
  Nelson p.144, equ. 4.5.2
  
  experimental, not yet tested and used
class_docstr_tok: ["generic","multivariate","Archimedean","copula","with","additional","power","transforms","Nelson","p.144",",","equ",".","4.5.2","experimental",",","not","yet","tested","and","used"]
code: def evaluate(self, t, alpha, beta, *tr_args):
      t = np.asarray(t)
  
      phi = np.power(
          self.transform.evaluate(np.power(t, alpha), *tr_args), beta
      )
      return phi
  
imports: import warnings
  import numpy
  from scipy.special import expm1, gamma
label_desc: Use image node_id 2 for calling the _TransfPower obj's underlying member method code with example usage: obj.evaluate(t, alpha, beta) and returns: phi