def test_do_calculate_reward_if_goal_reached():
env = NavigationGoal()
env._ranges = np.array([2, 1, 10, 4, 5])
env._distance_from_goal = 0.01
reward = env._do_calculate_reward(env._FORWARD)
assert reward == 200
def test_do_calculate_reward_if_collision():
env = NavigationGoal()
env._ranges = np.array([0.5, 1, 0.01, 4, 5])
env._distance_from_goal = 10
reward = env._do_calculate_reward(env._FORWARD)
assert reward == -200
def test_do_check_if_done_false():
env = NavigationGoal()
env._ranges = np.array([2, 1, 10, 4, 5])
env._distance_from_goal = 10
done = env._do_check_if_done()
assert not done
def test_do_check_if_done_true_goal_reached():
env = NavigationGoal()
env._ranges = np.array([2, 1, 10, 4, 5])
env._distance_from_goal = 0.01
done = env._do_check_if_done()
assert done
def test_do_check_if_done_true_collision():
env = NavigationGoal()
env._ranges = np.array([0.5, 1, 0.01, 4, 5])
env._distance_from_goal = 10
done = env._do_check_if_done()
assert done
def test_do_calculate_reward_if_action():
env = NavigationGoal()
env._ranges = np.array([2, 1, 10, 4, 5])
env._distance_from_goal = 1
env._observation = np.array([2, 1, 10, 4, 5, 3, 0.5])
reward = env._do_calculate_reward(env._FORWARD)
assert reward == 20
def test_do_update_observation():
env = NavigationGoal()
env._pose = Pose(Point(0, 8.5), 0.78539816339)
env._goal = Point(1.5, 8.5)
env._do_update_observation()
expected_observation = [
2.12132034356, 1.5, 2.12132034356, 10, 14.1421356237, 1.5,
0.78539816339
]
assert np.allclose(env._observation, expected_observation, atol=0.06)
def test_invalid_track_id():
with pytest.raises(ValueError):
_ = NavigationGoal(-1)