Integrate a simple agent that sends alarms in Grid2op/Agent

[marota]

From L2RPN_ICAP2021 starting kit - notebook 2_L2RPN_ICAPS_Alarm_feature_Notebook

class DoNothing_Attention_Agent(BaseAgent):
    """
    This is the most basic BaseAgent. It is purely passive, and does absolutely nothing.
    As opposed to most reinforcement learning environments, in grid2op, doing nothing is often
    the best solution.
    """

    def __init__(self, action_space, alarms_lines_area):
        BaseAgent.__init__(self, action_space)
        self.alarms_lines_area = alarms_lines_area
        self.alarms_area_names = env.alarms_area_names

    def act(self, observation, reward, done=False):
        """
        As better explained in the document of :func:`grid2op.BaseAction.update` or
        :func:`grid2op.BaseAction.ActionSpace.__call__`.
        The preferred way to make an object of type action is to call :func:`grid2op.BaseAction.ActionSpace.__call__`
        with the dictionary representing the action. In this case, the action is "do nothing" and it is represented by
        the empty dictionary.
        Parameters
        ----------
        observation: :class:`grid2op.Observation.Observation`
            The current observation of the :class:`grid2op.Environment.Environment`
        reward: ``float``
            The current reward. This is the reward obtained by the previous action
        done: ``bool``
            Whether the episode has ended or not. Used to maintain gym compatibility
        Returns
        -------
        res: :class:`grid2op.Action.Action`
            The action chosen by the bot / controller / agent.
        """
        res = self.action_space({})
        if (np.max(observation.rho) >= 1):
            zones_alert = self.get_region_alert(observation)
            print(zones_alert)
            res = self.action_space({"raise_alarm": zones_alert})
            print(res)
        # print(res)
        return res

    def get_region_alert(self, observation):
        # extract the zones they belong too
        zones_these_lines = set()
        zone_for_each_lines = self.alarms_lines_area

        lines_overloaded = np.where(observation.rho >= 1)[0].tolist()  # obs.rho>0.6
        #print(lines_overloaded)
        for line_id in lines_overloaded:
            line_name = observation.name_line[line_id]
            for zone_name in zone_for_each_lines[line_name]:
                zones_these_lines.add(zone_name)

        zones_these_lines = list(zones_these_lines)
        zones_ids_these_lines = [self.alarms_area_names.index(zone) for zone in zones_these_lines]
        return zones_ids_these_lines