def test_multi_population_three_populations(self):
payoff_matrix = np.arange(3 * 2 * 3 * 4).reshape(3, 2, 3, 4)
rd = dynamics.replicator
dyn = dynamics.MultiPopulationDynamics(payoff_matrix, [rd] * 3)
x = np.concatenate(
[np.ones(k) / float(k) for k in payoff_matrix.shape[1:]])
self.assertEqual(dyn(x).shape, (9, ))
def pd_phaseplot_boltzmann(fig):
#Load game and payoff matrices
size = 111
game = pyspiel.load_game("matrix_mp")
#A = game_payoffs_array(game)[0]
#print(A)
payoff_tensor = np.array([[[3, 0], [0, 2]], [[2, 0], [0, 3]]])
#Make phase plot using LFAQ
dyn = dynamics.MultiPopulationDynamics(payoff_tensor, lenient_boltzmannq)
sub = fig.add_subplot(1, 2, 1, projection="2x2")
sub.quiver(dyn)
startx = [0.75, 0.45, 0.85, 0.3]
starty = [0.75, 0.84, 0.45, 0.7]
#Follow trajectory for 5 points
for i in range(4):
p_x = startx[i]
p_y = starty[i]
x = np.array([p_x, 1 - p_x, p_y, 1 - p_y])
xlist = list()
ylist = list()
alpha = 0.01
iterations = 1000
for _ in range(iterations):
x += alpha * dyn(x)
xlist.append(x[0])
ylist.append(x[2])
sub.plot(xlist, ylist)
sub.set_title("τ = 50, κ = 1")
return fig
def test_meshgrid(self):
n = 10
payoff_tensor = np.ones(shape=(2, 2, 2))
identity = lambda x, f: x
allzero = lambda x, f: np.zeros(x.shape)
dyn = dynamics.MultiPopulationDynamics(payoff_tensor,
(identity, allzero))
x, y, u, v = visualization._eval_dynamics_2x2_grid(dyn, n)
np.testing.assert_allclose(x, u)
np.testing.assert_allclose(v, np.zeros(shape=(n, n)))
dyn = dynamics.MultiPopulationDynamics(payoff_tensor,
(allzero, identity))
x, y, u, v = visualization._eval_dynamics_2x2_grid(dyn, n)
np.testing.assert_allclose(u, np.zeros(shape=(n, n)))
np.testing.assert_allclose(y, v)
def test_multi_population_rps(self):
game = pyspiel.load_matrix_game('matrix_rps')
payoff_matrix = game_payoffs_array(game)
rd = dynamics.replicator
dyn = dynamics.MultiPopulationDynamics(payoff_matrix, [rd] * 2)
x = np.concatenate(
[np.ones(k) / float(k) for k in payoff_matrix.shape[1:]])
np.testing.assert_allclose(dyn(x), np.zeros((6, )), atol=1e-15)
def test_multi_population_four_populations(self):
payoff_matrix = np.zeros((4, 2, 2, 2, 2))
payoff_matrix[:, 0, 0, 0, 0] = np.ones((4, ))
rd = dynamics.replicator
dyn = dynamics.MultiPopulationDynamics(payoff_matrix, [rd] * 4)
x = np.concatenate(
[np.ones(k) / float(k) for k in payoff_matrix.shape[1:]])
avg_fitness = 1. / float(2**4) # if all players play uniform random
dx = dyn(x)
np.testing.assert_allclose(dx[::2], np.ones((4, )) * avg_fitness / 2.)
np.testing.assert_allclose(dx[1::2],
np.ones((4, )) * (-avg_fitness) / 2.)
def matrix_bots_phaseplot(size=None, fig=None):
fig = plt.figure(figsize=(10, 10)) if fig is None else fig
size = 111 if size is None else size
assert isinstance(fig, plt.Figure)
payoff_tensor = np.array([[[3, 0], [0, 2]], [[2, 0], [0, 3]]])
dyn = dynamics.MultiPopulationDynamics(payoff_tensor, dynamics.replicator)
sub = fig.add_subplot(size, projection="2x2")
sub.quiver(dyn)
sub.set_title("Phaseplot Battle of the sexes")
sub.set_xlabel("Man")
sub.set_ylabel("Woman")
return sub
def matrix_mp_phaseplot(size=None, fig=None):
fig = plt.figure(figsize=(10, 10)) if fig is None else fig
size = 111 if size is None else size
assert isinstance(fig, plt.Figure)
game = pyspiel.load_game("matrix_mp")
payoff_tensor = game_payoffs_array(game)
dyn = dynamics.MultiPopulationDynamics(payoff_tensor, dynamics.replicator)
sub = fig.add_subplot(size, projection="2x2")
sub.quiver(dyn)
sub.set_title("Phaseplot Matching pennies")
sub.set_xlabel("Player 1")
sub.set_ylabel("Player 2")
return sub
def _build_dynamics2x2():
"""Build multi-population dynamics."""
game = pyspiel.load_game("matrix_pd")
payoff_tensor = utils.nfg_to_ndarray(game)
return dynamics.MultiPopulationDynamics(payoff_tensor, dynamics.replicator)
def _build_dynamics2x2_beta():
"""Build multi-population dynamics."""
game = pyspiel.load_game("matrix_pd")
payoff_tensor = utils.game_payoffs_array(game)
return dynamics.MultiPopulationDynamics(payoff_tensor,
dynamics_beta.replicator_beta)
