def test_no_downsampling():
mockenv = MockEnv(act_space=BoxSpace(-1, 1, shape=(2,)), obs_space=BoxSpace(-1, 1, shape=(2,)))
wenv = DownsamplingWrapper(mockenv, factor=1)
# Perform some actions
wenv.step(np.array([4, 1]))
assert mockenv.last_act == [4, 1]
wenv.step(np.array([7, 5]))
assert mockenv.last_act == [7, 5]
def test_act_downsampling():
mockenv = MockEnv(act_space=BoxSpace(-1, 1, shape=(2,)), obs_space=BoxSpace(-1, 1, shape=(2,)))
wenv = DownsamplingWrapper(mockenv, factor=2)
# Perform some actions
wenv.step(np.array([0, 1]))
assert mockenv.last_act == [0, 1]
wenv.step(np.array([2, 4])) # should be ignored
assert mockenv.last_act == [0, 1]
wenv.step(np.array([1, 2]))
assert mockenv.last_act == [1, 2]
wenv.step(np.array([2, 3])) # should be ignored
assert mockenv.last_act == [1, 2]
def test_reset():
mockenv = MockEnv(act_space=BoxSpace(-1, 1, shape=(2,)), obs_space=BoxSpace(-1, 1, shape=(2,)))
wenv = DownsamplingWrapper(mockenv, factor=2)
# Perform some actions
wenv.step(np.array([0, 4]))
assert mockenv.last_act == [0, 4]
wenv.step(np.array([4, 4]))
assert mockenv.last_act == [0, 4]
wenv.step(np.array([4, 4]))
assert mockenv.last_act == [4, 4]
# The next action would be [4, 4] again, but now we reset
wenv.reset()
assert wenv._act_last is None
assert wenv._cnt == 0
wenv.step(np.array([1, 2]))
assert mockenv.last_act == [1, 2]
wenv.step(np.array([2, 3]))
assert mockenv.last_act == [1, 2]
def test_combination_downsampling_delay():
mockenv = MockEnv(act_space=BoxSpace(-1, 1, shape=(2, )),
obs_space=BoxSpace(-1, 1, shape=(2, )))
wenv_ds_dl = DownsamplingWrapper(mockenv, factor=2)
wenv_ds_dl = ActDelayWrapper(wenv_ds_dl, delay=3)
# Reset to initialize buffer
wenv_ds_dl.reset()
# The first ones are 0 because the ActDelayWrapper's queue is initialized with 0
wenv_ds_dl.step(np.array([0, 1]))
assert mockenv.last_act == [0, 0]
wenv_ds_dl.step(np.array([0, 2]))
assert mockenv.last_act == [0, 0]
wenv_ds_dl.step(np.array([0, 3]))
assert mockenv.last_act == [0, 0]
wenv_ds_dl.step(np.array([0, 4]))
# Intuitively one would think last_act would be [0, 1] here, but this is the effect of the wrappers' combination
assert mockenv.last_act == [0, 0]
wenv_ds_dl.step(np.array([0, 5]))
assert mockenv.last_act == [0, 2]
wenv_ds_dl.step(np.array([0, 6]))
assert mockenv.last_act == [0, 2]
wenv_ds_dl.step(np.array([0, 7]))
assert mockenv.last_act == [0, 4]
wenv_ds_dl.step(np.array([0, 8]))
assert mockenv.last_act == [0, 4]
wenv_ds_dl.step(np.array([0, 9]))
assert mockenv.last_act == [0, 6]
wenv_ds_dl.step(np.array([1, 0]))
assert mockenv.last_act == [0, 6]
def test_domain_param():
mockenv = MockEnv(act_space=BoxSpace(-1, 1, shape=(2, )),
obs_space=BoxSpace(-1, 1, shape=(2, )))
wenv = DownsamplingWrapper(mockenv, factor=2)
# Reset to initialize buffer
wenv.reset()
# Perform some actions
wenv.step(np.array([0, 1]))
assert mockenv.last_act == [0, 1]
wenv.step(np.array([2, 4]))
assert mockenv.last_act == [0, 1]
wenv.step(np.array([4, 4]))
assert mockenv.last_act == [4, 4]
# change the downsampling and reset
wenv.domain_param = {'downsampling': 1}
wenv.reset()
wenv.step(np.array([1, 2]))
assert mockenv.last_act == [1, 2]
wenv.step(np.array([2, 3]))
assert mockenv.last_act == [2, 3]
wenv.step(np.array([8, 9]))
assert mockenv.last_act == [8, 9]