def test_pathological_tracking(self):
level_count = 5
p_count = 16
levels = []
shift = 1
for j in range(level_count):
level = []
for k in np.arange(p_count) * 2:
level.append(PointND(k // 2, (j, k + j * shift)))
levels.append(level)
hash_generator = lambda: Hash_table(
(level_count + 1, p_count * 2 + level_count * shift + 1), .5)
tracks = self.link(levels, 8, hash_generator)
assert len(tracks) == p_count, len(tracks)
def test_easy_tracking(self):
level_count = 5
p_count = 16
levels = []
for j in range(level_count):
level = []
for k in np.arange(p_count) * 2:
level.append(PointND(j, (j, k)))
levels.append(level)
hash_generator = lambda: Hash_table(
(level_count + 1, p_count * 2 + 1), .5)
tracks = self.link(levels, 1.5, hash_generator)
assert len(tracks) == p_count
for t in tracks:
x, y = zip(*[p.pos for p in t])
dx = np.diff(x)
dy = np.diff(y)
assert np.sum(dx) == level_count - 1
assert np.sum(dy) == 0
def hash_generator(dims, box_size):
return lambda: Hash_table(dims, box_size)