More precise logics for n_actions in Dataset and Simulator

[yoongi0428]

Possible Issue

In bandit feedback, n_actions are set as int(self.action.max() + 1), which doesn't raise any error in above code,
assuming that logs generated by policy covered all possible actions.

However, to be more precise, I think n_actions should be explicitly given, rather than extracted from log data.
And if changed, the above code might raise error.
If 1000 possible actions and only 0~998 actions exist in bandit _feedback and somehow policy selected action 999,
this might raise out-of-index error.

Idea

1. BanditFeedback data is given n_actions explicitly.
   Rather than:
   

   zr-obp/obp/dataset/real.py

   Lines 78 to 81 in 55ab57e

   	@property
   	def n_actions(self) -> int:
   	"""Number of actions."""
   	return int(self.action.max() + 1)

2. Use n_actions directly in convert_to_action_dist
   Rather than:
   

   zr-obp/obp/simulator/simulator.py

   Lines 75 to 78 in 55ab57e

   	action_dist = convert_to_action_dist(
   	n_actions=bandit_feedback["action"].max() + 1,
   	selected_actions=np.array(selected_actions_list),
   	)