def test_timestep_contextual_bernoulli_bandit(fix_random):
always_bandit = single_interaction_step.Bandit(conversion_rate=1)
never_bandit = single_interaction_step.Bandit(conversion_rate=0)
periodicity = single_interaction_step.Periodicity(
single_interaction_step.weekly_periodicity([0, 0.1, 2, 0, 0.1, 2, 0]))
env = single_interaction_step.TimestepContextualBernoulliBandits(
bandits=[always_bandit, never_bandit], step_contexts=[periodicity])
observation, reward, done, info = env.step(selected_bandit=0)
assert not observation
assert reward == 0.0
observation, reward, done, info = env.step(selected_bandit=0)
assert not observation
assert reward == 0.0
observation, reward, done, info = env.step(selected_bandit=0)
assert observation
assert reward == 1.0
for _ in range(3):
observation, reward, done, info = env.step(selected_bandit=1)
assert not observation
assert reward == 0.0
def test_heirarchical_static_bernoulli_bandits(action, expected_observation,
expected_reward):
always_bandit = single_interaction_step.Bandit(conversion_rate=1)
never_bandit = single_interaction_step.Bandit(conversion_rate=0)
context = {"country": {"always": 1.0, "never": 0.0}}
env = single_interaction_step.HeirarchicalStaticBernoulliBandits(
bandits=[always_bandit, never_bandit], context=context)
for _ in range(5):
observation, reward, done, info = env.step(action=action)
assert observation == expected_observation
assert reward == expected_reward
def test_basic_discrete_bernoulli_bandit():
always_bandit = single_interaction_step.Bandit(conversion_rate=1)
never_bandit = single_interaction_step.Bandit(conversion_rate=0)
env = single_interaction_step.BasicDiscreteBernoulliBandits(
bandits=[always_bandit, never_bandit])
for _ in range(5):
observation, reward, done, info = env.step(selected_bandit=0)
assert observation
assert reward == 1.0
for _ in range(5):
observation, reward, done, info = env.step(selected_bandit=1)
assert not observation
assert reward == 0.0
def test_heirarchical_static_bernoulli_bandits_context_keys():
bandit = single_interaction_step.Bandit(conversion_rate=0)
env = single_interaction_step.HeirarchicalStaticBernoulliBandits(
bandits=[bandit], context={"country": {
"always": 1,
"never": 0
}})
assert env.context_keys == {"country": ["always", "never"]}
def test_heirarchical_static_bernoulli_bandits_raises_too_few_bandits(action):
bandit = single_interaction_step.Bandit(conversion_rate=0)
env = single_interaction_step.HeirarchicalStaticBernoulliBandits(
bandits=[bandit], context={"country": {
"always": 1,
"never": 0
}})
with pytest.raises(AssertionError):
env.step(action)
def test_bandit_multiplier(fix_random):
low_bandit = single_interaction_step.Bandit(conversion_rate=0.1)
assert low_bandit.action(multiplier=6)
def test_bandit(fix_random):
low_bandit = single_interaction_step.Bandit(conversion_rate=0.1)
high_bandit = single_interaction_step.Bandit(conversion_rate=0.9)
assert not low_bandit.action()
assert high_bandit.action()