def test_01_01_permute_one(self):
np.random.seed(11)
a = [np.random.uniform()]
b = [p for p in F.permutations(a)]
self.assertEqual(len(b), 1)
self.assertEqual(len(b[0]), 1)
self.assertEqual(b[0][0], a[0])
def test_01_02_permute_two(self):
np.random.seed(12)
a = np.random.uniform(size=2)
b = [p for p in F.permutations(a)]
self.assertEqual(len(b), 2)
self.assertEqual(len(b[0]), 2)
self.assertTrue(np.all(np.array(b) == a[np.array([[0, 1], [1, 0]])]))
def test_01_03_permute_three(self):
np.random.seed(13)
a = np.random.uniform(size=3)
b = [p for p in F.permutations(a)]
self.assertEqual(len(b), 6)
self.assertEqual(len(b[0]), 3)
expected = np.array([[0, 1, 2], [0, 2, 1], [1, 0, 2], [1, 2, 0],
[2, 0, 1], [2, 1, 0]])
self.assertTrue(np.all(np.array(b) == a[expected]))
def test_01_02(self):
r = np.random.RandomState()
r.seed(11)
for reductions in [0,2]:
for _ in range(100):
c = r.randint(1,10,(5,5))
i,j = np.mgrid[0:5,0:5]
i = i.flatten()
j = j.flatten()
x,y,u,v = LAPJV.lapjv(i, j, c.flatten(), True, reductions)
min_cost = np.sum(c)
best = None
for permutation in permutations([0,1,2,3,4]):
cost = sum([c[i,permutation[i]] for i in range(5)])
if cost < min_cost:
best = list(permutation)
min_cost = cost
result_cost = sum([c[i,x[i]] for i in range(5)])
self.assertAlmostEqual(min_cost, result_cost)
