docs: def online_trial(self, bandit=None, payout=None, strategy='eps_greedy',
                       parameters=None):
          '''
          Update the bandits with the results of the previous live, online trial.
              Next run a the selection algorithm. If the stopping criteria is
              met, return the best arm estimate. Otherwise return the next arm to
              try.
  
          Parameters
          ----------
          bandit : int
              Bandit index
          payout : float
              Payout value
          strategy : string
              Name of update strategy
          parameters : dict
              Parameters for update strategy function
  
          Returns
          -------
          dict
              Format: {'new_trial': boolean, 'choice': int, 'best': int}
          '''
  
          if bandit is not None and payout is not None:
              self.update(bandit=bandit, payout=payout)
          else:
              raise Exception('slots.online_trial: bandit and/or payout value'
                              ' missing.')
  
          if self.crit_met():
              return {'new_trial': False, 'choice': self.best(),
                      'best': self.best()}
          else:
              return {'new_trial': True,
                      'choice': self.run_strategy(strategy, parameters),
                      'best': self.best()}