code: def _print_convergence(self):
          
  
          if self.verbosity:
              if (self.num_acquisitions == self.max_iter) and (not self.initial_iter):
                  print('   ** Maximum number of iterations reached **')
                  return 1
              elif (self._distance_last_evaluations() < self.eps) and (not self.initial_iter):
                  print('   ** Two equal location selected **')
                  return 1
              elif (self.max_time < self.cum_time) and not (self.initial_iter):
                  print('   ** Evaluation time reached **')
                  return 0
  
              if self.initial_iter:
                  print('** GPyOpt Bayesian Optimization class initialized successfully **')
                  self.initial_iter = False
docs: Prints the reason why the optimization stopped.