def replicator_equation(x, t, number_of_players):
x /= np.sum(x)
G = network.create_braess_network()
R = ReplicatorDynamics(G, number_of_players)
fitness_vector = R.compute_payoff(x)
average_fitness = np.dot(x, fitness_vector)
return x * (fitness_vector - average_fitness)
def test_invariable_population_size(self):
braess_graph = network.create_braess_network()
population_array=[2, 3, 5, 0]
pop_size = sum(population_array)
mp = MoranProcess(graph=braess_graph, number_of_players=2, w=5, mutation_probability=0.001, population_array=[2, 3, 5, 0], seed=123)
for i in range(10000):
mp.step()
self.assertTrue(pop_size == np.sum(mp.population))
self.assertTrue(np.all(mp.population >=0))
def replicator_mutator_equation(x, t, number_of_players, mutation_matrix):
x /= np.sum(x)
G = network.create_braess_network()
R = ReplicatorDynamics(G, number_of_players)
fitness_vector = R.compute_payoff(x)
average_fitness = np.dot(x, fitness_vector)
temp = np.zeros_like(R.network_game.strategy_set)
for i in range(len(R.network_game.strategy_set)):
for j in range(len(R.network_game.strategy_set)):
temp[i] += x[j] * fitness_vector[j] * mutation_matrix[j, i] # - (x[i] * average_fitness)
b = x * average_fitness
c = np.array(temp) - b
return np.array(c, dtype=float)
def test_braess_network(self):
my_graph = network.create_braess_network()
my_network_game = network.Network(my_graph, 2)
# print(my_network_game.payoff)
# print(my_network_game.strategy_set)
profile = (0, 0, 0, 2)
payoff_expected = np.array([0, 0, 0, 4])
computed_payoff = my_network_game.payoff[profile]
np.testing.assert_almost_equal(
payoff_expected,
computed_payoff,
decimal=3,
err_msg="Payoff for profile {} should be {}, but it is {}".format(
profile, payoff_expected, computed_payoff
),
)
profile = (0, 0, 1, 1)
payoff_expected = np.array([0, 0, 3, 3])
computed_payoff = my_network_game.payoff[profile]
np.testing.assert_almost_equal(
payoff_expected,
computed_payoff,
decimal=3,
err_msg="Payoff for profile {} should be {}, but it is {}".format(
profile, payoff_expected, computed_payoff
),
)
profile = (0, 0, 2, 0)
payoff_expected = np.array([0, 0, 4, 0])
computed_payoff = my_network_game.payoff[profile]
np.testing.assert_almost_equal(
payoff_expected,
computed_payoff,
decimal=3,
err_msg="Payoff for profile {} should be {}, but it is {}".format(
profile, payoff_expected, computed_payoff
),
)
profile = (0, 1, 0, 1)
payoff_expected = np.array([0, 2, 0, 2])
computed_payoff = my_network_game.payoff[profile]
np.testing.assert_almost_equal(
payoff_expected,
computed_payoff,
decimal=3,
err_msg="Payoff for profile {} should be {}, but it is {}".format(
profile, payoff_expected, computed_payoff
),
)
profile = (0, 1, 1, 0)
payoff_expected = np.array([0, 3, 3, 0])
computed_payoff = my_network_game.payoff[profile]
np.testing.assert_almost_equal(
payoff_expected,
computed_payoff,
decimal=3,
err_msg="Payoff for profile {} should be {}, but it is {}".format(
profile, payoff_expected, computed_payoff
),
)
profile = (0, 2, 0, 0)
payoff_expected = np.array([0, 4, 0, 0])
computed_payoff = my_network_game.payoff[profile]
np.testing.assert_almost_equal(
payoff_expected,
computed_payoff,
decimal=3,
err_msg="Payoff for profile {} should be {}, but it is {}".format(
profile, payoff_expected, computed_payoff
),
)
profile = (1, 0, 0, 1)
payoff_expected = np.array([3, 0, 0, 3])
computed_payoff = my_network_game.payoff[profile]
np.testing.assert_almost_equal(
payoff_expected,
computed_payoff,
decimal=3,
err_msg="Payoff for profile {} should be {}, but it is {}".format(
profile, payoff_expected, computed_payoff
),
)
profile = (1, 0, 1, 0)
payoff_expected = np.array([2, 0, 2, 0])
computed_payoff = my_network_game.payoff[profile]
np.testing.assert_almost_equal(
payoff_expected,
computed_payoff,
decimal=3,
err_msg="Payoff for profile {} should be {}, but it is {}".format(
profile, payoff_expected, computed_payoff
),
)
profile = (1, 1, 0, 0)
payoff_expected = np.array([3, 3, 0, 0])
computed_payoff = my_network_game.payoff[profile]
np.testing.assert_almost_equal(
payoff_expected,
computed_payoff,
decimal=3,
err_msg="Payoff for profile {} should be {}, but it is {}".format(
profile, payoff_expected, computed_payoff
),
)
profile = (2, 0, 0, 0)
payoff_expected = np.array([4, 0, 0, 0])
computed_payoff = my_network_game.payoff[profile]
np.testing.assert_almost_equal(
payoff_expected,
computed_payoff,
decimal=3,
err_msg="Payoff for profile {} should be {}, but it is {}".format(
profile, payoff_expected, computed_payoff
),
)