def test(self):
g1 = [True, False, True]
g2 = [False, False, False]
uc = UniformCrossover()
crossed = uc(Individual(g1, g1, 0.0), Individual(g2, g2, 0.0))
for i in range(len(g1)):
self.assertIn(crossed[i], [g1[i], g2[i]])
def test(self):
g1 = [True, False, True]
g2 = [False, False, False]
mpx = MultiPointCrossover(1)
crossed = mpx(Individual(g1, g1, 0.0), Individual(g2, g2, 0.0))
for i in range(len(g1)):
self.assertIn(crossed[i], [g1[i], g2[i]])
def test_make_move(self):
sem12 = SwapElementsMove(1, 2)
perm_gen = RandomPermutation(10)
perm = perm_gen()
ind = Individual(perm, perm, 0.0)
perm_act = sem12.make_move(ind)
ind2 = Individual(perm_act, perm_act, 0.0)
perm_act_rev = sem12.reverse().make_move(ind2)
self.assertListEqual(perm, perm_act_rev)
def test(self):
rpm = ReversePartMove(1, 2)
rpm_r = rpm.reverse()
self.assertEqual(rpm.i, rpm_r.i)
self.assertEqual(rpm.j, rpm_r.j)
self.assertTrue(rpm.conflicts(rpm))
ind = Individual([0, 1, 2], [0, 1, 2], 0.0)
ind_moved = rpm.make_move(ind)
self.assertEqual(ind.g[0], ind_moved[0])
self.assertEqual(ind.g[1], ind_moved[2])
self.assertEqual(ind.g[2], ind_moved[1])
def test(self):
g1 = [True, False, True, False, True, True, False]
for num_flips in range(4):
for can_repeat in [True, False]:
uso = BitFlips(num_flips, can_repeat=can_repeat)
mutated = uso(Individual(g1, g1, 0.0))
flipped = 0
for i in range(len(g1)):
if mutated[i] != g1[i]:
flipped += 1
if can_repeat:
self.assertTrue(flipped <= num_flips)
else:
self.assertEqual(num_flips, flipped)
def test(self):
population = [
Individual([0], [0], 0.0, fitness=0.0),
Individual([1], [1], 0.0, fitness=0.0),
Individual([2], [2], 0.0, fitness=0.0),
Individual([3], [3], 0.0, fitness=0.0),
Individual([4], [4], 0.0, fitness=0.0)
]
universal_parent = Individual([-1], [-1], 0.0, fitness=0.0)
for ind in population:
ind.reproduction_auxiliary = universal_parent
selectors = [
RouletteWheel(2),
TournamentSelection(2, 3),
TruncationSelection(3),
ParentReplacementSelection(),
PopulationTracker(RouletteWheel(2))
]
for s in selectors:
selected = s(population)
for ind in selected:
self.assertIsInstance(ind, Individual)
def test(self):
ind = Individual([0, 1, 2], [0, 1, 2], 0.0)
neighbourhood = tsp_swap_neighbourhood(ind)
for neighbour in neighbourhood:
self.assertNotEqual(neighbour.i, neighbour.j)
def test(self):
pss = PermutationSingleSwap(2)
g = [1, 2]
permuted = pss(Individual(g, g, 0.0))
self.assertEqual(permuted, [2, 1])