def test_PSOLB_random(self):
"""
Check if solution computed by PSOL + edge removal is included in the full solution computed by
Zielonka's algorithm.
"""
print("test psolb random")
not_solved_size = []
for i in range(5, self.number_of_random + 5):
g = gen.random(i, i / 2, 1, i / 3)
winning_region_0, winning_region_1 = zielonka.strong_parity_solver_no_strategies(
g)
resulting_arena, fatal_region_0, fatal_region_1 = fatal.psolB(
g, [], [])
self.assertTrue(elem in winning_region_0
for elem in fatal_region_0)
self.assertTrue(elem in winning_region_1
for elem in fatal_region_1)
# if the game is completely solved by PSOL
if set(winning_region_0) == set(fatal_region_0) and set(
winning_region_1) == set(fatal_region_1):
self.fully_solved_random += 1
else:
not_solved_size.append(i)
print("Number of random games fully solved by PSOLB = " +
str(self.fully_solved_random))
print("Size of games not solved = " + str(not_solved_size) + "\n")
def test_recursive_single_priority_random(self):
"""
Check if solution computed by the recursive algorithm is correct.
We create random parity games and transform them into generalized parity games by using a copy of the first
priority function as a second priority function.
"""
print("test recursive single priority random")
for i in range(5, self.number_of_random + 5):
g = gen.random(i, i / 2, 1, i / 3)
winning_region_0, winning_region_1 = zielonka.strong_parity_solver_no_strategies(
g)
computed_winning_0, computed_winning_1 = recursive.generalized_parity_solver(
g)
self.assertTrue(set(winning_region_0) == set(computed_winning_0))
self.assertTrue(set(winning_region_1) == set(computed_winning_1))
def random_games(i):
# for some reason this does not work for indices < 5
j = i + 5
return generators.random(j, j, 1, j / 3)