code: def cumulative_distribution(self, X):
          
          self.check_fit()
  
          U, V = self.split_matrix(X)
  
          if self.theta == 1:
              return np.multiply(U, V)
  
          else:
              h = np.power(-np.log(U), self.theta) + np.power(-np.log(V), self.theta)
              h = -np.power(h, 1.0 / self.theta)
              cdfs = np.exp(h)
              return cdfs
docs: Computes the cumulative distribution function for the copula, :math:`C(u, v)`
  
          Args:
              X: `np.ndarray`
  
          Returns:
              np.array: cumulative probability