point_list = [Point(N, 0)]
for i in range(1, N): # points are denser near Point(N, 0)
point_list.append(
Point(N * math.cos(math.pi / i), N * math.sin(math.pi / i)))
random.shuffle(point_list)
print("Testing GrahamScan1 ...")
t1 = timeit.Timer(lambda: GrahamScan1(point_list).run())
print("{} {}".format(N, t1.timeit(1))) # single run
random.shuffle(point_list)
print("Testing GrahamScan2 ...")
t1 = timeit.Timer(lambda: GrahamScan2(point_list).run())
print("{} {}".format(N, t1.timeit(1))) # single run
random.shuffle(point_list)
print("Testing JarvisMarch ...")
t1 = timeit.Timer(lambda: JarvisMarch(point_list).run())
print("{} {}".format(N, t1.timeit(1))) # single run
random.shuffle(point_list)
print("Testing QuickHull ...")
t1 = timeit.Timer(lambda: QuickHull(point_list).run())
print("{} {}".format(N, t1.timeit(1))) # single run
# EOF
def test_jarvis(self):
algorithm = JarvisMarch(self.point_list)
algorithm.run()
self.assertEqual(algorithm.convex_hull, self.convex_hull)