def _reset_agents()

in gym-compete/gym_compete/new_envs/sumo.py [0:0]

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

    def _reset_agents(self):
        # set agent 0
        min_gap = 0.3 + self.MIN_RADIUS / 2
        for i in range(self.n_agents):
            if i % 2 == 0:
                x = np.random.uniform(-self.RADIUS + min_gap, -0.3)
                y_lim = np.sqrt(self.RADIUS**2 - x**2)
                y = np.random.uniform(-y_lim + min_gap, y_lim - min_gap)
            else:
                x = np.random.uniform(0.3, self.RADIUS - min_gap)
                y_lim = np.sqrt(self.RADIUS**2 - x**2)
                y = np.random.uniform(-y_lim + min_gap, y_lim - min_gap)
            self.agents[i].set_xyz((x,y,None))