def cora():
G = nx.barabasi_albert_graph(1000, 3)
# G = nx.watts_strogatz_graph(1000, 5, 0.3)
# G = nx.random_regular_graph(4, 1000)
p = Population(G)
e = Evolution()
g = game.PDG(2)
e.set_population(p).set_game(g)
# p.strategy = np.ones(len(p), np.int)
f, axs = plt.subplots(3, 4)
axs = axs.reshape(12)
for r in range(11):
if r > 5:
r_ = 10 - r
p.strategy = np.zeros(len(p), dtype=np.int)
s = 1
else:
r_ = r
p.strategy = np.ones(len(p), dtype=np.int)
s = 0
n = int(round(len(p) / 10.0 * r_))
selected_list = np.random.choice(range(len(p)), n)
p.strategy[selected_list] = s
# print p.strategy
g.strategy = p.strategy
g.play()
p.show_degree(axs[r])
plt.show()
def repeat_b():
# 博弈收益参数不同，合作率曲线
e = Evolution(has_mut=False)
G = nx.random_regular_graph(4, 1000)
p = Population(G)
b = 5
for i in range(b):
g = game.PDG(i * 2 + 2)
e.set_population(p).set_game(g).set_rule(u)
print('Control Variable b: %d' % (i * 2 + 2))
e.evolve(100000, restart=True, quiet=True, autostop=False)
e.show(fmt[i], label="b=%d" % (i * 2 + 2))
plt.legend(loc='lower right')
plt.show()
def lattice():
l = 100
def observe(s, f):
plt.imshow(s.reshape((l, l)), interpolation='sinc', cmap='bwr')
plt.show()
G = nx.grid_2d_graph(l, l)
# nx.draw(G, node_size=200, with_labels=True)
# plt.show()
p = Population(G)
e = Evolution()
e.set_population(p).set_game(g).set_rule(u)
# e.evolve(1)
observe(p.strategy, p.fitness)
def repeat2d():
e = Evolution()
bs = np.linspace(1, 10, 3)
# fig, axes = plt.subplots()
colors = 'brgcmykwa'
symbs = '.ox+*sdph-'
for i in range(1, 10):
i = 4
G = nx.random_regular_graph(i + 1, 1000)
p = Population(G)
a = [0] * len(bs)
for j, b in enumerate(bs):
g = game.PDG(b)
e.set_population(p).set_game(g).set_rule(u)
e.evolve(10000)
a[j] = e.cooperate[-1]
plt.plot(bs, a, colors[j] + symbs[j], label='b=%f' % b)
break
plt.show()
def repeat_start_pc():
# 初始Pc不同的合作变化曲线
# G = nx.watts_strogatz_graph(1000, 4, 0.2)
G = nx.barabasi_albert_graph(1000, 3)
p = Population(G)
g = game.PDG(b=10)
u = rule.DeathBirth()
e = Evolution(has_mut=False)
e.set_population(p).set_game(g).set_rule(u)
for i in range(5):
pc = (2 * i + 1) / 10.0
p.init_strategies(g, [pc, 1 - pc])
print('Initial P(C) is %.2f' % pc)
e.evolve(100000, restart=True, quiet=True, autostop=False)
e.show(fmt[i], label=r'start $P_C$=%.2f' % pc)
plt.legend(loc='lower right')
plt.title(r'Evolution under Different Start $P_C$')
plt.xlabel('Number of generations')
plt.ylabel(r'Fraction of cooperations, $\rho_c$')
plt.show()
def repeat_k():
# 网络平均度不同，合作率曲线
e = Evolution(has_mut=False)
k = 5
a = [0] * k
for i in range(k):
G = nx.random_regular_graph(i * 2 + 2, 1000)
p = Population(G)
e.set_population(p).set_game(g).set_rule(u)
print('Control Variable k: %d' % (i * 2 + 2))
e.evolve(100000, restart=True, quiet=True)
# TODO: if e is CoEvolution, population need re-copy
# a[i] = e.cooperate[-1]
e.show(fmt[i], label="k=%d" % (i * 2 + 2))
# plt.plot(range(2, k+1), a[1:], 'r-')
# plt.plot([400+i*i for i in range(20)], 'ro--', label='k=4')
# plt.plot([400 + i for i in range(20)], 'g^-.', label='k=6')
# plt.plot([400 - i for i in range(20)], 'cx:', label='k=8')
plt.legend(loc='lower right')
plt.show()
def once():
e = Evolution(has_mut=True)
e.set_population(p).set_game(g).set_rule(u)
e.evolve(1000)
e.show()
