def check_cluster(spawnpoint, cluster, radius, time_threshold):
# discard infinite cost or too far away
if cost(spawnpoint, cluster, time_threshold) > 2 * radius:
return False
new_centroid = cluster.simulate_centroid(spawnpoint)
# we'd be removing ourselves
if clsmath.distance(spawnpoint.position, new_centroid) > radius:
return False
# we'd be removing x
if any(clsmath.distance(x.position, new_centroid) > radius for x in cluster):
return False
return True
def cost(spawnpoint, cluster, time_threshold):
distance = clsmath.distance(spawnpoint.position, cluster.centroid)
min_time = min(cluster.min_time, spawnpoint.time)
max_time = max(cluster.max_time, spawnpoint.time)
if max_time - min_time > time_threshold:
return float('inf')
return distance
def test(cluster, radius, time_threshold):
assert cluster.max_time - cluster.min_time <= time_threshold
for p in cluster:
assert clsmath.distance(p.position, cluster.centroid) <= radius
assert cluster.min_time <= p.time <= cluster.max_time