code: def get_suggestion(self, random_search=False):
          
  
          rval = self.rval
          trials = rval.trials
          algorithm = rval.algo
          new_ids = rval.trials.new_trial_ids(1)
          rval.trials.refresh()
          random_state = rval.rstate.randint(2**31-1)
          if random_search:
              new_trials = hp.rand.suggest(new_ids, rval.domain, trials, random_state)
          else:
              new_trials = algorithm(new_ids, rval.domain, trials, random_state)
          rval.trials.refresh()
          vals = new_trials[0]['misc']['vals']
          parameter = dict()
          for key in vals:
              try:
                  parameter[key] = vals[key][0].item()
              except (KeyError, IndexError):
                  parameter[key] = None
  
          # remove '_index' from json2parameter and save params-id
          total_params = json2parameter(self.json, parameter)
          return total_params
docs: get suggestion from hyperopt
  
          Parameters
          ----------
          random_search : bool
              flag to indicate random search or not (default: {False})
  
          Returns
          ----------
          total_params : dict
              parameter suggestion