def mono_pruning(q_id, q, k, index, cache):
IO = 0
partitions = list(common.partitions(q, index.space, 6))
points = index.points
vd = index.voronoi_diagram
candidate_idx = set()
candidates = list()
for partition in partitions:
h = MinHeap()
h.push((0, q_id, q))
visited = {q_id}
knn = list()
while len(h) > 0 and len(knn) < k:
dist, o, p = h.pop()
if o != q_id and partition.intersects(p):
knn.append((o, p, dist))
if o not in candidate_idx:
candidate_idx.add(o)
candidates.append((o, p, dist))
for neighbor in vd.neighbors(o):
if neighbor not in visited:
visited.add(neighbor)
if neighbor in cache:
neighbor_p = cache[neighbor]
else:
neighbor_p = points[neighbor]
cache[neighbor] = neighbor_p
IO += 1
if partition.intersects(vd.cell(neighbor)):
h.push((neighbor_p.distance(q), neighbor, neighbor_p))
return candidates, IO
def bi_pruning(q_id, q, k, index, cache):
IO = 0
partitions = list(common.partitions(q, index.space, 6))
region_list = list()
points = index.points
vd = index.voronoi_diagram
for partition in partitions:
h = MinHeap()
h.push((0, q_id, q))
visited = {q_id}
knn = list()
while len(h) > 0 and len(knn) < k:
dist, o, p = h.pop()
if o != q_id and partition.intersects(p):
knn.append((o, p, dist))
for neighbor in vd.neighbors(o):
if neighbor not in visited:
visited.add(neighbor)
if neighbor in cache:
neighbor_p = cache[neighbor]
else:
neighbor_p = points[neighbor]
cache[neighbor] = neighbor_p
IO += 1
if partition.intersects(vd.cell(neighbor)):
h.push((neighbor_p.distance(q), neighbor, neighbor_p))
if len(knn) > 0:
r = knn[-1][2]
if r > 0:
region_list.append(
common.sector(q, r, partition.angles).buffer(0.01))
region = reduce(lambda x, y: x.union(y), region_list)
return region, IO
def pruning(q_id, q, k, index, partition_num):
partitions = common.partitions(q, index.space, partition_num)
sigLists = [[] for i in range(partition_num)]
upper_arc_radius_heaps = [common.MaxHeap() for i in range(partition_num)]
shaded_areas = [calculate_shaded_area(partition, partition.r) for partition in partitions]
h = common.MinHeap()
IO = 0
h.push((0, index.root))
while len(h) > 0:
e_dist, e = h.pop()
if may_contains_significant_facility(e, shaded_areas):
if e.is_data_node:
pruneSpace(q_id, e, k, partitions, sigLists, upper_arc_radius_heaps, shaded_areas)
else:
for child in e.children:
h.push((child.geom.distance(q), child))
IO += 1
unpruned_area_list = list()
for i in range(partition_num):
r_b = min(upper_arc_radius_heaps[i].first(), partitions[i].r)
angles = [2 * pi / partition_num * i, 2 * pi / partition_num * (i + 1)]
if r_b > 0:
unpruned_area_list.append(common.sector(q, r_b, angles).buffer(0.01))
unpruned_area = reduce(lambda x, y: x.union(y), unpruned_area_list)
return sigLists, unpruned_area, IO
def bi_pruning(q_id, q, k, index, cache):
IO = 0
partitions = list(common.partitions(q, index.space, 6))
region_list = list()
points = index.points
vd = index.voronoi_diagram
visited = {q_id}
H = common.MinHeap()
S = [common.MaxHeap() for i in range(6)]
for neighbor_id in vd.neighbors(q_id):
if neighbor_id in cache:
neighbor_p = cache[neighbor_id]
else:
neighbor_p = points[neighbor_id]
cache[neighbor_id] = neighbor_p
IO += 1
H.push((1, neighbor_id, neighbor_p))
visited.add(neighbor_id)
while len(H) > 0:
gd_p, p_id, p = H.pop()
for i in range(6):
if partitions[i].intersects(p):
if len(S[i]) < k:
dist_bound = float('inf')
else:
dist_bound = S[i].first()[0]
dist_p = p.distance(q)
if gd_p <= k and dist_p < dist_bound:
S[i].push((dist_p, p_id, p))
for neighbor_id in vd.neighbors(p_id):
if neighbor_id not in visited:
if neighbor_id in cache:
neighbor_p = cache[neighbor_id]
else:
neighbor_p = points[neighbor_id]
cache[neighbor_id] = neighbor_p
IO += 1
gd_neighbor = gd_p + 1
visited.add(neighbor_id)
H.push((gd_neighbor, neighbor_id, neighbor_p))
for i in range(6):
s = sorted(S[i])
if len(s) >= k:
r = s[k - 1][0]
elif len(s) > 0:
r = s[-1][0]
else:
r = 0
if r > 0:
region_list.append(
common.sector(q, r, partitions[i].angles).buffer(0.01))
region = reduce(lambda x, y: x.union(y), region_list)
return region, IO
def mono_pruning(q_id, q, k, index, cache):
IO = 0
partitions = list(common.partitions(q, index.space, 6))
region_list = list()
points = index.points
vd = index.voronoi_diagram
visited = {q_id}
H = common.MinHeap()
S = [common.MaxHeap() for i in range(6)]
for neighbor_id in vd.neighbors(q_id):
if neighbor_id in cache:
neighbor_p = cache[neighbor_id]
else:
neighbor_p = points[neighbor_id]
cache[neighbor_id] = neighbor_p
IO += 1
H.push((1, neighbor_id, neighbor_p))
visited.add(neighbor_id)
while len(H) > 0:
gd_p, p_id, p = H.pop()
for i in range(6):
if partitions[i].intersects(p):
if len(S[i]) < k:
dist_bound = float('inf')
else:
dist_bound = S[i].first()[0]
dist_p = p.distance(q)
if gd_p <= k and dist_p < dist_bound:
S[i].push((dist_p, p_id, p))
for neighbor_id in vd.neighbors(p_id):
if neighbor_id not in visited:
if neighbor_id in cache:
neighbor_p = cache[neighbor_id]
else:
neighbor_p = points[neighbor_id]
cache[neighbor_id] = neighbor_p
IO += 1
gd_neighbor = gd_p + 1
visited.add(neighbor_id)
H.push((gd_neighbor, neighbor_id, neighbor_p))
candidate_idx = set()
candidates = list()
for i in range(6):
s = sorted(S[i])
if len(s) >= k:
s = s[:k]
for dist, p_id, p in s:
if p_id not in candidate_idx:
candidate_idx.add(p_id)
candidates.append((p_id, p, dist))
return candidates, IO