def test_3(self):
matrix = np.array([[4, 0, 6, 2, 2, 1], [3, 8, 4, 10, 4, 4],
[1, 2, 6, 5, 0, 0], [6, 6, 4, 4, 10, 3],
[10, 4, 6, 4, 0, 9], [10, 7, 0, 7, 9, 8]])
func_p, func_q, func_cost = nash_equilibrium1(matrix)
p, q, cost = nash.nash_equilibrium(matrix)
assert_equals(abs(func_cost - cost) < 0.00001, True)
assert_equals(sum(abs(x - y) < 0.00001 for x, y in zip(func_p, p)),
len(func_p))
assert_equals(sum(abs(x - y) < 0.00001 for x, y in zip(func_q, q)),
len(func_q))
def test_6(self):
matrix = np.array([
[8, 4, 7],
[6, 5, 9],
[7, 6, 8],
])
func_p, func_q, func_cost = nash_equilibrium1(matrix)
p, q, cost = nash.nash_equilibrium(matrix)
assert_equals(abs(func_cost - cost) < 0.00001, True)
assert_equals(sum(abs(x - y) < 0.00001 for x, y in zip(func_p, p)),
len(func_p))
assert_equals(sum(abs(x - y) < 0.00001 for x, y in zip(func_q, q)),
len(func_q))
def test_2(self):
matrix = np.array([
[0, 0, 0],
[1, 3, 5],
[2, 4, 6],
])
func_p, func_q, func_cost = nash_equilibrium1(matrix)
p, q, cost = nash.nash_equilibrium(matrix)
assert_equals(abs(func_cost - cost) < 0.00001, True)
assert_equals(sum(abs(x - y) < 0.00001 for x, y in zip(func_p, p)),
len(func_p))
assert_equals(sum(abs(x - y) < 0.00001 for x, y in zip(func_q, q)),
len(func_q))