結果
| 問題 |
No.3207 Digital Font
|
| コンテスト | |
| ユーザー |
|
| 提出日時 | 2025-07-22 18:01:47 |
| 言語 | PyPy3 (7.3.15) |
| 結果 |
WA
|
| 実行時間 | - |
| コード長 | 5,335 bytes |
| コンパイル時間 | 494 ms |
| コンパイル使用メモリ | 82,220 KB |
| 実行使用メモリ | 192,412 KB |
| 最終ジャッジ日時 | 2025-07-22 18:02:46 |
| 合計ジャッジ時間 | 56,658 ms |
|
ジャッジサーバーID (参考情報) |
judge3 / judge5 |
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| ファイルパターン | 結果 |
|---|---|
| sample | AC * 2 |
| other | AC * 25 WA * 13 |
ソースコード
# Generated By Gemini 2.5 Pro
import sys
from bisect import bisect_left, bisect_right
import random
def solve():
"""
Solves the point-symmetric matrix problem using an offline sweep-line
algorithm with double hashing to check for symmetry.
"""
try:
# Fast I/O
readline = sys.stdin.readline
H, W = map(int, readline().split())
N = int(readline())
points = [tuple(map(int, readline().split())) for _ in range(N)]
Q = int(readline())
queries = [tuple(map(int, readline().split())) for _ in range(Q)]
except (IOError, ValueError):
return
# --- 1. Hashing and Coordinate Compression Setup ---
# Use two independent sets of constants for double hashing
MOD1, P1_1, P2_1 = 10**9 + 7, 37, 41
MOD2, P1_2, P2_2 = 998244353, 43, 47
# Pre-compute powers of P and their modular inverses
max_pow_dim1 = 2 * H + 1
max_pow_dim2 = 2 * W + 1
def precompute_powers(p, mod, size):
p_inv = pow(p, mod - 2, mod)
pows = [1] * size
inv_pows = [1] * size
for i in range(1, size):
pows[i] = (pows[i - 1] * p) % mod
inv_pows[i] = (inv_pows[i - 1] * p_inv) % mod
return pows, inv_pows
pow1_1, inv_pow1_1 = precompute_powers(P1_1, MOD1, max_pow_dim1)
pow2_1, inv_pow2_1 = precompute_powers(P2_1, MOD1, max_pow_dim2)
pow1_2, inv_pow1_2 = precompute_powers(P1_2, MOD2, max_pow_dim1)
pow2_2, inv_pow2_2 = precompute_powers(P2_2, MOD2, max_pow_dim2)
# Assign random hash values to digits
rng = random.Random(42)
f = {0: 0, 1: 1, 2: 2, 5: 5, 6: 9, 8: 8, 9: 6}
R = {x: rng.randint(1, MOD1 - 1) for x in range(10)}
R_f = {k: R[v] for k, v in f.items()}
# Coordinate compression for columns
all_cols = sorted(list(set(p[1] for p in points) | set(q[1] for q in queries) | set(q[3] for q in queries)))
col_map = {val: i for i, val in enumerate(all_cols)}
# --- 2. Event Creation for Sweep-line ---
events = []
# Point events: (row, type=0, col_idx, hashes...)
for r, c, x in points:
comp_c = col_map[c]
h1_fwd = (pow1_1[r] * pow2_1[c] * R[x]) % MOD1
h1_bwd = (inv_pow1_1[r] * inv_pow2_1[c] * R_f[x]) % MOD1
h2_fwd = (pow1_2[r] * pow2_2[c] * R[x]) % MOD2
h2_bwd = (inv_pow1_2[r] * inv_pow2_2[c] * R_f[x]) % MOD2
events.append((r, 0, comp_c, h1_fwd, h1_bwd, h2_fwd, h2_bwd))
# Query events: (row, type=1, query_idx, start_col_idx, end_col_idx, sign)
ans = [[0, 0, 0, 0] for _ in range(Q)] # fwd1, bwd1, fwd2, bwd2
for i in range(Q):
l, d, r, u = queries[i]
cd = bisect_left(all_cols, d)
cu = bisect_right(all_cols, u) - 1
if cd <= cu:
events.append((r, 1, i, cd, cu, 1))
if l > 1:
events.append((l - 1, 1, i, cd, cu, -1))
events.sort()
# --- 3. Sweep-line Processing ---
bit1_fwd = FenwickTree(len(all_cols), MOD1)
bit1_bwd = FenwickTree(len(all_cols), MOD1)
bit2_fwd = FenwickTree(len(all_cols), MOD2)
bit2_bwd = FenwickTree(len(all_cols), MOD2)
for event in events:
type = event[1]
if type == 0: # Point Event
_, _, c_idx, h1f, h1b, h2f, h2b = event
bit1_fwd.add(c_idx, h1f)
bit1_bwd.add(c_idx, h1b)
bit2_fwd.add(c_idx, h2f)
bit2_bwd.add(c_idx, h2b)
else: # Query Event
_, _, q_idx, cd, cu, sign = event
s1f, s1b = bit1_fwd.query_range(cd, cu), bit1_bwd.query_range(cd, cu)
s2f, s2b = bit2_fwd.query_range(cd, cu), bit2_bwd.query_range(cd, cu)
term1f = (sign * s1f + MOD1) % MOD1
term1b = (sign * s1b + MOD1) % MOD1
term2f = (sign * s2f + MOD2) % MOD2
term2b = (sign * s2b + MOD2) % MOD2
ans[q_idx][0] = (ans[q_idx][0] + term1f) % MOD1
ans[q_idx][1] = (ans[q_idx][1] + term1b) % MOD1
ans[q_idx][2] = (ans[q_idx][2] + term2f) % MOD2
ans[q_idx][3] = (ans[q_idx][3] + term2b) % MOD2
# --- 4. Final Judgment ---
for i in range(Q):
l, d, r, u = queries[i]
# Check first hash
factor1 = (pow1_1[r + l] * pow2_1[u + d]) % MOD1
target1_bwd = (ans[i][1] * factor1) % MOD1
check1 = (ans[i][0] == target1_bwd)
# Check second hash
factor2 = (pow1_2[r + l] * pow2_2[u + d]) % MOD2
target2_bwd = (ans[i][3] * factor2) % MOD2
check2 = (ans[i][2] == target2_bwd)
if check1 and check2:
print("Yes")
else:
print("No")
class FenwickTree:
"""1D Fenwick Tree (BIT) - defined inside solve for encapsulation"""
def __init__(self, n, mod):
self.n = n
self.mod = mod
self.data = [0] * (n + 1)
def add(self, i, x):
i += 1
while i <= self.n:
self.data[i] = (self.data[i] + x) % self.mod
i += i & -i
def _query(self, i):
s = 0
while i > 0:
s = (s + self.data[i]) % self.mod
i -= i & -i
return s
def query_range(self, l, r):
if l > r: return 0
return (self._query(r + 1) - self._query(l) + self.mod) % self.mod
if __name__ == "__main__":
solve()