def it_draws_from_the_expected_range(self):
matrix = Factory.create_observation_matrix(sample_count=5)
game = matrix.toGame()
indexes = np.random.random_integers(0, game.max_samples - 1, size=1000)
assert min(indexes) == 0
assert max(indexes) == 4
assert len(indexes) == 1000
def it_gives_the_requested_observations_with_duplicates(self):
matrix = Factory.create_observation_matrix(sample_count=5)
game = matrix.toGame()
sbg = SimulationBasedGame(game)
target_profile = game.knownProfiles()[0]
observations = sbg.get_observations(target_profile, [0, 2, 2])
assert observations == {
r: [
PayoffData(
s,
count,
[
game.getPayoffData(target_profile, r, s)[0],
game.getPayoffData(target_profile, r, s)[2],
game.getPayoffData(target_profile, r, s)[2],
],
)
for s, count in s_hash.items()
]
for r, s_hash in target_profile.items()
}
def it_provides_a_two_sided_confidence_interval(self):
bootstrap_method = lambda *args: [i+1 for i in range(100)]
ci = BootstrapConfidenceInterval(bootstrap_method)
print ci.two_sided_interval(Factory.create_observation_matrix(), "fake profile", 0.90)
assert ci.two_sided_interval(Factory.create_observation_matrix(), "fake profile", 0.95) == [3, 97]
