human
1.5 get_state
The get_state method extracts features from within the environments and provides then as inputs to the policy provided by the RL agent. Several helper methods exist within flow to help facilitate this process. Some useful helper method can be accessed from the following objects:
* self.k.vehicle: provides current state information for all vehicles within the network
* self.k.traffic_light: provides state information on the traffic lights
* self.k.scenario: information on the scenario, which unlike the vehicles and traffic lights is static
* More accessor objects and methods can be found within the Flow documentation at: http://berkeleyflow.readthedocs.io/en/latest/
In order to model global observability within the network, our state space consists of the speeds and positions of all vehicles (as mentioned in section 1.3). This is implemented as follows:"
Please write code following the instructions in jupyter notebook style.

Can you provide a code to 1?
assistant
#Here is code to 1.

import numpy as np

class myEnv(myEnv):  # update my environment class

    def get_state(self, **kwargs):
        # the get_ids() method is used to get the names of all vehicles in the network
        ids = self.k.vehicle.get_ids()

        # we use the get_absolute_position method to get the positions of all vehicles
        pos = [self.k.vehicle.get_x_by_id(veh_id) for veh_id in ids]

        # we use the get_speed method to get the velocities of all vehicles
        vel = [self.k.vehicle.get_speed(veh_id) for veh_id in ids]

        # the speeds and positions are concatenated to produce the state
        return np.concatenate((pos, vel))