結果

問題 No.2337 Equidistant
ユーザー Shirotsume
提出日時 2023-06-02 22:01:57
言語 PyPy3
(7.3.15)
結果
AC  
実行時間 2,330 ms / 4,000 ms
コード長 3,588 bytes
コンパイル時間 218 ms
コンパイル使用メモリ 82,300 KB
実行使用メモリ 193,168 KB
最終ジャッジ日時 2024-12-28 17:57:58
合計ジャッジ時間 27,944 ms
ジャッジサーバーID
(参考情報)
judge5 / judge4
このコードへのチャレンジ
(要ログイン)
ファイルパターン 結果
sample AC * 1
other AC * 28
権限があれば一括ダウンロードができます

ソースコード

diff #
プレゼンテーションモードにする

import sys, time, random
from collections import deque, Counter, defaultdict
input = lambda: sys.stdin.readline().rstrip()
ii = lambda: int(input())
mi = lambda: map(int, input().split())
li = lambda: list(mi())
inf = 2 ** 63 - 1
mod = 998244353
import sys
class LcaDoubling:
"""
links[v] = { u1, u2, ... } (u:, )
LCA
2LCA
"""
def __init__(self, n, links, root=0):
self.depths = [-1] * n
prev_ancestors = self._init_dfs(n, links, root)
self.ancestors = [prev_ancestors]
max_depth = max(self.depths)
d = 1
while d < max_depth:
next_ancestors = [prev_ancestors[p] for p in prev_ancestors]
self.ancestors.append(next_ancestors)
d <<= 1
prev_ancestors = next_ancestors
def _init_dfs(self, n, links, root):
q = [root]
direct_ancestors = [-1] * (n + 1) # 1-1(-1)-1
self.depths[root] = 0
while q:
u = q.pop()
for v in links[u]:
if self.depths[v] != -1:
continue
direct_ancestors[v] = u
self.depths[v] = self.depths[u] + 1
links[v].discard(u)
q.append(v)
return direct_ancestors
def get_lca(self, u, v):
du, dv = self.depths[u], self.depths[v]
if du > dv:
u, v = v, u
du, dv = dv, du
tu = u
tv = self.upstream(v, dv - du)
if u == tv:
return u
for k in range(du.bit_length() - 1, -1, -1):
mu = self.ancestors[k][tu]
mv = self.ancestors[k][tv]
if mu != mv:
tu = mu
tv = mv
lca = self.ancestors[0][tu]
assert lca == self.ancestors[0][tv]
return lca
def upstream(self, v, k):
i = 0
while k:
if k & 1:
v = self.ancestors[i][v]
k >>= 1
i += 1
return v
def jump(self, u: int, v: int, i: int) -> int:
""" uvi0-indexed-1 """
c = self.get_lca(u, v)
du = self.depths[u]
dv = self.depths[v]
dc = self.depths[c]
path_len = du - dc + dv - dc
if path_len < i:
return -1
if du - dc >= i:
return self.upstream(u, i)
return self.upstream(v, path_len - i)
n, q = mi()
graph = [set() for _ in range(n)]
for _ in range(n - 1):
u, v = mi()
u -= 1; v -= 1
graph[u].add(v)
graph[v].add(u)
L = LcaDoubling(n, graph)
def size_of_subtree(s, t):
if L.depths[s] < L.depths[t]:
return subt[t]
else:
return n - subt[s]
p = list(range(n))
p.sort(key = lambda x: L.depths[x], reverse=True)
subt = [0] * n
for v in p:
for to in graph[v]:
if L.depths[to] > L.depths[v]:
subt[v] += subt[to]
subt[v] += 1
for _ in range(q):
s, t = mi()
s -= 1; t -= 1
x = L.get_lca(s, t)
l = L.depths[s] + L.depths[t] - 2 * L.depths[x]
if l % 2 == 1:
print(0)
else:
u = L.jump(s, t, l // 2)
s1 = L.jump(u, s, 1)
t1 = L.jump(u, t, 1)
ans = n - size_of_subtree(u, s1) - size_of_subtree(u, t1)
print(ans)
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0