def test_play_the_game_less_badly():
bad_seeds_01_env = BadSeeds01(seed_count=5,
bad_seed_count=3,
max_episode_length=2)
a_bad_seed_ndx = bad_seeds_01_env.bad_seed_indices[0]
next_state, terminal, reward = bad_seeds_01_env.execute(
actions=a_bad_seed_ndx)
assert next_state[0, a_bad_seed_ndx] != 0.0
assert terminal is False
assert reward == 0.0
measurement_counts, measured_seed_counts = count_measurements(
bad_seeds_01_env.state)
print(measurement_counts)
expected_measurement_counts = np.zeros_like(measurement_counts)
expected_measurement_counts[0, a_bad_seed_ndx] += 1.0
assert np.all(measurement_counts == expected_measurement_counts)
assert measured_seed_counts == 1
next_state, terminal, reward = bad_seeds_01_env.execute(
actions=a_bad_seed_ndx)
assert next_state[1, a_bad_seed_ndx] != 0.0
assert terminal is True
assert reward == 2.0
measurement_counts, measured_seed_counts = count_measurements(
bad_seeds_01_env.state)
print(measurement_counts)
expected_measurement_counts[0, a_bad_seed_ndx] += 1.0
assert np.all(measurement_counts == expected_measurement_counts)
assert measured_seed_counts == 1
def test_play_the_game_badly():
bad_seeds_01_env = BadSeeds01(seed_count=5,
bad_seed_count=3,
max_episode_length=5)
# measure all seeds but the last seed
for time_i, seed_i in enumerate(range(len(bad_seeds_01_env.all_seeds) -
1)):
next_state, terminal, reward = bad_seeds_01_env.execute(actions=seed_i)
assert next_state[time_i, seed_i] != 0.0
assert terminal is False
assert reward == 0.0
# measurement_counts looks like this
# time_i = 0: [1 0 0 0 0 ]
# time_i = 1: [1 1 0 0 0 ]
# ...
# time_i = 3: [1 1 1 1 0 ]
measurement_counts, measured_seed_counts = count_measurements(
bad_seeds_01_env.state)
for seed_j in range(seed_i):
assert measurement_counts[0, seed_j] == 1
assert measured_seed_counts == (seed_i + 1)
# measure the first seed again
# no reward because the last seed is never measured
next_state, terminal, reward = bad_seeds_01_env.execute(actions=0)
assert next_state[len(bad_seeds_01_env.all_seeds) - 1, 0] != 0.0
assert terminal is True
assert reward == 0.0
measurement_counts, measured_seed_counts = count_measurements(
bad_seeds_01_env.state)
assert np.all(measurement_counts == np.array([[2, 1, 1, 1, 0]]))
assert measured_seed_counts == 4
def test_count_measurements():
state = np.array([
[0.0, 0.5, 0.0, 0.0],
[0.0, 0.0, -0.5, 0.0],
[0.5, 0.0, 0.0, 0.0],
[0.0, -0.5, 0.0, 0.0],
[0.0, 0.0, 0.5, 0.0],
[0.0, 0.5, 0.0, 0.0],
])
measurement_counts, measured_seed_counts = count_measurements(
time_steps_by_seeds_state=state)
assert np.all(measurement_counts == np.array([1, 3, 2, 0]))
assert measured_seed_counts == 3