def test_actions(self):
N_bandits = 20
posse = Posse(self.env, GreedyBandit, n_bandits=N_bandits)
N_actions = 2
posse.take_actions(N_actions)
assert posse.n_actions_taken == 2
assert len(posse.bandits[0].choice_history) == 2
def test_var_best_choice(self):
N_bandits = 20
posse = Posse(self.env, GreedyBandit, n_bandits=N_bandits)
N_actions = 100
posse.take_actions(N_actions)
bc = np.zeros(100)
assert posse.var_best_choice(bc).shape == (100, )
assert posse.var_best_choice(0).shape == (100, )
assert posse.var_best_choice(bc.tolist()).shape == (100, )
with pytest.raises(TypeError):
posse.var_best_choice(3.1415)
def test_numbers(self):
N_bandits = 20
posse = Posse(self.env, GreedyBandit, n_bandits=N_bandits)
assert len(posse.bandits) == N_bandits
assert posse.n_actions_taken == 0
assert posse.len_env == len(self.env)
assert posse.n_rewards == self.n_rewards
def test_mean_var_reward(self):
N_bandits = 20
posse = Posse(self.env, GreedyBandit, n_bandits=N_bandits)
N_actions = 100
posse.take_actions(N_actions)
assert posse.mean_reward().shape == (100, )
assert posse.var_reward().shape == (100, )
def test_mean_best_choice_with_int(self):
N_bandits = 20
posse = Posse(self.env, GreedyBandit, n_bandits=N_bandits)
N_actions = 100
posse.take_actions(N_actions)
bc = self.env.expected_rewards().argmax()
assert posse.mean_best_choice(bc).shape == (100, )
assert posse.var_best_choice(bc).shape == (100, )
def test_bandit_kwargs(self):
N_bandits = 20
eps = 0.1
posse = Posse(self.env, EpsGreedyBandit, n_bandits=N_bandits, eps=eps)
assert posse.bandits[0].eps == eps
def test_smoke(self):
posse = Posse(self.env, GreedyBandit, n_bandits=20)
assert isinstance(posse, Posse)