def reset_world()

in multiagent/scenarios/simple_adversary.py [0:0]

• 17 lines of code
• 8 McCabe index (conditional complexity)

    def reset_world(self, world):
        # random properties for agents
        world.agents[0].color = np.array([0.85, 0.35, 0.35])
        for i in range(1, world.num_agents):
            world.agents[i].color = np.array([0.35, 0.35, 0.85])
        # random properties for landmarks
        for i, landmark in enumerate(world.landmarks):
            landmark.color = np.array([0.15, 0.15, 0.15])
        # set goal landmark
        goal = np.random.choice(world.landmarks)
        goal.color = np.array([0.15, 0.65, 0.15])
        for agent in world.agents:
            agent.goal_a = goal
        # set random initial states
        for agent in world.agents:
            agent.state.p_pos = np.random.uniform(-1, +1, world.dim_p)
            agent.state.p_vel = np.zeros(world.dim_p)
            agent.state.c = np.zeros(world.dim_c)
        for i, landmark in enumerate(world.landmarks):
            landmark.state.p_pos = np.random.uniform(-1, +1, world.dim_p)
            landmark.state.p_vel = np.zeros(world.dim_p)