from microgridRLsimulator.gym_wrapper import MicrogridEnv
env = MicrogridEnv(from_date,to_date, case)

  File "./abstract/manager/manager.py", line 100, in _train_simulate
    o_r_d_i = env.step(action)
  File "/home/da/Documents/emploi/postdoc/2018_2019/dev/rl/venv/lib/python3.6/site-packages/gym/core.py", line 304, in step
    observation, reward, done, info = self.env.step(action)
  File "/home/da/Documents/emploi/postdoc/2018_2019/dev/rl/venv/src/microgridrlsimulator/microgridRLsimulator/gym_wrapper/microgrid_env.py", line 62, in step
    state_formatted = self.state_formatting(state)
  File "/home/da/Documents/emploi/postdoc/2018_2019/dev/rl/venv/src/microgridrlsimulator/microgridRLsimulator/gym_wrapper/microgrid_env.py", line 91, in state_formatting
    delta_t = state_array[n + 2]
IndexError: list index out of range

    def state_refactoring(self, state):
        """
        Convenience function that flattens the received state into an array

        :param state: State of the agent as a list
        :return: Flattened representation of the state as an array
        """
        consumption = state[0]
        storages_soc = state[1]
        production = state[2]
        delta_t = state[3]
        state_array = np.concatenate((np.array([consumption]), np.array(storages_soc).reshape(-1), np.array([production]), np.array([delta_t])),
                                     axis=0)
        return state_array

    def state_formatting(self, state_array):
        """
        Inverse of state_refactoring
        """
        n= len(self.simulator.grid.storages)
        consumption = state_array[0]
        storages_soc = list(state_array[1:1+n])
        production = state_array[n + 1]
        delta_t = state_array[n + 2]
        state = [consumption, storages_soc, production, delta_t]
        return state

[3.52440585725, [6.0, 6.0], 0.0, 0.0]

    def step(self, action, state=None):
        """
        Step function, as in gym.
        May also accept a state as input (useful for MCTS, for instance).
        """
        assert self.action_space.contains(action), "%r (%s) invalid" % (action, type(action))

        if state is None:
            state = self.state
        state_formatted = self.state_formatting(state)
        next_state, reward, done = self.simulator.step(high_level_action = action, state = state_formatted)
        self.state = self.state_refactoring(next_state)

        return np.array(self.state), reward, done, {}

    def state_formatting(self, state_array):
        """
        Inverse of state_refactoring
        """
        consumption = state_array[0]
        storages_soc = list(state_array[1])
        production = state_array[2]
        delta_t = state_array[3]
        state = [consumption, storages_soc, production, delta_t]
        return state