def reset_world()

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

• 12 lines of code
• 7 McCabe index (conditional complexity)

    def reset_world(self, world):
        # random properties for agents
        for i, agent in enumerate(world.agents):
            agent.color = np.array([0.35, 0.35, 0.85])
        # random properties for landmarks
        for i, landmark in enumerate(world.landmarks):
            landmark.color = np.array([0.25, 0.25, 0.25])
        # 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)