def step(self, action): 
        """ Take one time step through the world """
        self.action = action.copy().ravel()
        self.timestep += 1 
        step_size = self.action[0] - self.action[1]
        # An approximation of metabolic energy
        energy = self.action[0] + self.action[1]
        self.world_state = self.world_state + step_size
        # At random intervals, jump to a random position in the world
        if self.JUMP_FRACTION < np.random.random_sample():
            self.world_state = (self.num_real_sensors * 
                                np.random.random_sample())
        # Ensure that the world state falls between 0 and num_real_sensors 
        self.world_state -= (self.num_real_sensors * 
                             np.floor_divide(self.world_state, 
                                             self.num_real_sensors))
        self.simple_state = int(np.floor(self.world_state))
        # Assign sensors as zeros or ones. 
        # Represent the presence or absence of the current position in the bin.
        real_sensors = np.zeros(self.num_real_sensors)
        real_sensors[self.simple_state] = 1
        # Generate a set of noise sensors
        noise_sensors = np.round(np.random.random_sample(
                self.num_noise_sensors))
        sensors = np.hstack((real_sensors, noise_sensors))
        reward = -self.REWARD_MAGNITUDE
        if self.simple_state == 1:
            reward = self.REWARD_MAGNITUDE
        reward -= energy * self.ENERGY_COST        
        return sensors, reward
dataset/ETHPy150Open matt2000/becca/worlds/grid_1D_noise.py/World.step/swapped operands of `<`