def test_probend_matches():
for strategy in all_strategies:
for opponent in (Alternator, Cooperator, Defector):
players = (Player(strategy), opponent())
match = Match(players, prob_end=0.5, noise=0.5)
assert all(action in (C, D) for interaction in match.play()
for action in interaction)
def test_matches():
for strategy in all_strategies:
for opponent in (Alternator, Cooperator, Defector):
players = (Player(strategy), opponent())
match = Match(players, turns=200)
assert all(action in (C, D) for interaction in match.play()
for action in interaction)
def test_reset(self):
player = self.player()
opponent = axl.Cooperator()
match = Match((player, opponent), turns=100)
match.play()
self.assertFalse(player.countCC == 0)
player.reset()
self.assertTrue(player.countCC == 0)
def test_matches_with_different_game():
for strategy in all_strategies:
for opponent in (Alternator, Cooperator, Defector):
game = Game(r=4, s=0, p=2, t=6)
players = (Player(strategy), opponent())
match = Match(players, turns=200, game=game)
assert all(action in (C, D) for interaction in match.play()
for action in interaction)
def test_warning_for_self_interaction(recwarn):
"""
Test that a warning is given for a self interaction.
"""
player = Player("k42r")
opponent = player
match = Match((player, opponent))
interactions = match.play()
assert len(recwarn) == 1
def test_no_warning_for_normal_interaction(recwarn):
"""
Test that a warning is not given for a normal interaction
"""
for players in [(Player("k42r"), Alternator()),
(Player("k42r"), Player("k41r"))]:
match = Match(players)
interactions = match.play()
assert len(recwarn) == 0
def test_deterministic_strategies():
"""
Test that the strategies classified as deterministic indeed act
deterministically.
"""
for strategy in all_strategies:
player = Player(strategy)
if player.classifier["stochastic"] is False:
for opponent in basic_strategies:
match = Match((player, opponent()))
interactions = match.play()
for _ in range(2): # Repeat 3 matches
assert interactions == match.play(), player
def matches(
draw,
strategies=short_run_time_strategies,
min_turns=1,
max_turns=200,
min_noise=0,
max_noise=1,
):
"""
A hypothesis decorator to return a random match.
Parameters
----------
strategies : list
The strategies from which to sample the two the players
min_turns : integer
The minimum number of turns
max_turns : integer
The maximum number of turns
min_noise : float
The minimum noise
max_noise : float
The maximum noise
Returns
-------
match : a random match
"""
strategies = draw(strategy_lists(min_size=2, max_size=2))
players = [s() for s in strategies]
turns = draw(integers(min_value=min_turns, max_value=max_turns))
noise = draw(floats(min_value=min_noise, max_value=max_noise))
match = Match(players, turns=turns, noise=noise)
return match
def test_champion_v_alternator():
"""
Specific regression test for a bug. See:
https://github.com/Axelrod-Python/axelrod-fortran/issues/62
"""
player = Player("k61r")
opponent = Alternator()
seed = 3
match = Match((player, opponent), seed=seed)
interactions = match.play()
assert interactions[25:30] == [(C, D), (C, C), (C, D), (D, C), (C, D)]
match = Match((player, opponent), seed=seed)
assert interactions == match.play()
def test_match_reproducibility():
for _ in range(100):
rng = RandomGenerator()
seed = rng.random_seed_int()
strategies = rng.choice(all_strategies, size=2)
players1 = [Player(strategy) for strategy in strategies]
match1 = Match(players1, turns=200, noise=0.1, seed=seed)
results1 = match1.play()
players2 = [Player(strategy) for strategy in strategies]
match2 = Match(players2, turns=200, noise=0.1, seed=seed)
results2 = match2.play()
assert (results1 == results2)
def test_strategy(self):
player = self.player()
# Test against cyclers
for opponent in [
axl.CyclerCCD(),
axl.CyclerCCCD(),
axl.CyclerCCCCCD(),
axl.Alternator(),
]:
player.reset()
match = Match((player, opponent), turns=50)
match.play()
self.assertEqual(player.history[-1], D)
# Test against non-cyclers and cooperators
for opponent in [
axl.Random(),
axl.AntiCycler(),
axl.DoubleCrosser(),
axl.Cooperator(),
]:
player.reset()
match = Match((player, opponent), turns=50, seed=43)
match.play()
self.assertEqual(player.history[-1], C)
def test_implemented_strategies():
"""
Test that the deterministic strategies that are implemented in Axelrod
give the same outcomes.
"""
for strategy, dictionary in characteristics.items():
axelrod_class = dictionary["axelrod-python_class"]
stochastic = Player(strategy).classifier["stochastic"]
if axelrod_class is not None and not stochastic:
for opponent_strategy in basic_strategies:
player = Player(strategy)
opponent = opponent_strategy()
match = Match((player, opponent))
interactions = match.play()
axl_player = axelrod_class()
opponent = opponent_strategy()
axl_match = Match((axl_player, opponent))
axl_interactions = axl_match.play()
assert interactions == axl_interactions
