def test_secfxp(self):
secfxp = mpc.SecFxp()
a = getrandbits(secfxp, 10)
self.assertTrue(a.integral)
a = mpc.run(mpc.output(a))
self.assertGreaterEqual(int(a), 0)
self.assertLessEqual(int(a), 2**10 - 1)
x = mpc.run(mpc.output(random_unit_vector(secfxp, 6)))
self.assertEqual(int(sum(x)), 1)
x = mpc.run(mpc.output(random_permutation(secfxp, range(1, 9))))
self.assertSetEqual(set(range(1, 9)), set(map(int, x)))
x = mpc.run(mpc.output(random_derangement(secfxp, [0.0, 1.0])))
self.assertListEqual([1, 0], list(map(int, x)))
a = mpc.run(mpc.output(choice(secfxp, [0.8, 0.9, 1.0, 1.1, 1.2])))
self.assertAlmostEqual(float(a), 1.0, 0)
a = mpc.run(mpc.output(choice(secfxp, [0.08, 0.09, 0.1, 0.11, 0.12])))
self.assertAlmostEqual(float(a), 0.1, 1)
a = mpc.run(mpc.output(random(secfxp)))
self.assertGreaterEqual(float(a), 0)
self.assertLessEqual(float(a), 1)
a = mpc.run(mpc.output(uniform(secfxp, 13.13, 13.17)))
self.assertGreaterEqual(float(a), 13.13)
self.assertLessEqual(float(a), 13.17)
a = mpc.run(mpc.output(uniform(secfxp, -13.13, -13.17)))
self.assertGreaterEqual(float(a), -13.17)
self.assertLessEqual(float(a), -13.13)
def test_secint(self):
secint = mpc.SecInt()
a = mpc.run(mpc.output(getrandbits(secint, 10)))
self.assertGreaterEqual(a, 0)
self.assertLessEqual(a, 2**10 - 1)
x = mpc.run(mpc.output(random_unit_vector(secint, 4)))
self.assertEqual(sum(x), 1)
a = mpc.run(mpc.output(randrange(secint, 37))) # French roulette
self.assertGreaterEqual(a, 0)
self.assertLessEqual(a, 36)
a = mpc.run(mpc.output(randrange(secint, 1, 7))) # one die
self.assertGreaterEqual(a, 1)
self.assertLessEqual(a, 6)
a = mpc.run(mpc.output(randrange(secint, 1, 7) + randrange(secint, 1, 7))) # two dice
self.assertGreaterEqual(a, 2)
self.assertLessEqual(a, 12)
a = mpc.run(mpc.output(randrange(secint, 1, 32, 2)))
self.assertGreaterEqual(a, 1)
self.assertLessEqual(a, 31)
self.assertEqual(a % 2, 1)
a = mpc.run(mpc.output(randint(secint, -1, 1)))
self.assertIn(a, [-1, 0, 1])
x = list(range(8))
shuffle(secint, x)
shuffle(secint, x)
x = mpc.run(mpc.output(x))
self.assertSetEqual(set(x), set(range(8)))
x = mpc.run(mpc.output(random_permutation(secint, 8)))
self.assertSetEqual(set(x), set(range(8)))
x = mpc.run(mpc.output(random_derangement(secint, 2)))
self.assertListEqual(x, [1, 0])
x = mpc.run(mpc.output(random_derangement(secint, range(1, 9))))
self.assertSetEqual(set(x), set(range(1, 9)))
x = mpc.run(mpc.output(choice(secint, [1, 2, 3, 4, 5])))
self.assertIn(x, [1, 2, 3, 4, 5])
x = mpc.run(mpc.output(choice(secint, [secint(-100), secint(200), secint(-300)])))
self.assertIn(x, [-100, 200, -300])
x = mpc.run(mpc.output(mpc.sum(choices(secint, [0, 1], k=5)))) # uniform
self.assertGreaterEqual(x, 0)
self.assertLessEqual(x, 5)
x = mpc.run(mpc.output(mpc.sum(choices(secint, [0, 1], [25, 75])))) # Bernoulli
self.assertGreaterEqual(x, 0)
self.assertLessEqual(x, 1)
x = mpc.run(mpc.output(mpc.sum(choices(secint, [0, 1], [25, 75], k=10)))) # binomial
self.assertGreaterEqual(x, 0)
self.assertLessEqual(x, 10)
x = mpc.run(mpc.output(sample(secint, [2**i for i in range(16)], 8)))
self.assertGreaterEqual(sum(x), 2**8 - 1)
self.assertLessEqual(sum(x), 2**8 * (2**8 - 1))
x = mpc.run(mpc.output(sample(secint, range(10**8), 10)))
self.assertGreaterEqual(min(x), 0)
self.assertLessEqual(max(x), 10**8 - 1)
x = mpc.run(mpc.output(sample(secint, range(1000000, 3000000, 1000), 10)))
self.assertGreaterEqual(min(x) // 1000, 1000)
self.assertLessEqual(max(x) // 1000, 3000)
self.assertEqual(sum(x) % 1000, 0)
