結果
| 問題 | No.1302 Random Tree Score |
| ユーザー |
 zkou
|
| 提出日時 | 2021-03-17 19:16:02 |
| 言語 | PyPy3 (7.3.15) |
| 結果 |
AC
|
| 実行時間 | 642 ms / 3,000 ms |
| コード長 | 8,357 bytes |
| コンパイル時間 | 762 ms |
| コンパイル使用メモリ | 82,304 KB |
| 実行使用メモリ | 127,772 KB |
| 最終ジャッジ日時 | 2024-11-15 13:14:07 |
| 合計ジャッジ時間 | 7,636 ms |
|
ジャッジサーバーID （参考情報） |
judge2 / judge3 |
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テストケース
テストケース表示| 入力 | 結果 | 実行時間 実行使用メモリ |
|---|---|---|
| testcase_00 | AC | 58 ms
68,352 KB |
| testcase_01 | AC | 57 ms
68,224 KB |
| testcase_02 | AC | 240 ms
87,988 KB |
| testcase_03 | AC | 368 ms
100,944 KB |
| testcase_04 | AC | 235 ms
87,548 KB |
| testcase_05 | AC | 639 ms
127,196 KB |
| testcase_06 | AC | 639 ms
127,252 KB |
| testcase_07 | AC | 237 ms
87,904 KB |
| testcase_08 | AC | 368 ms
101,840 KB |
| testcase_09 | AC | 639 ms
127,748 KB |
| testcase_10 | AC | 634 ms
124,724 KB |
| testcase_11 | AC | 234 ms
87,080 KB |
| testcase_12 | AC | 636 ms
126,332 KB |
| testcase_13 | AC | 58 ms
68,352 KB |
| testcase_14 | AC | 640 ms
127,772 KB |
| testcase_15 | AC | 642 ms
127,772 KB |
| testcase_16 | AC | 58 ms
68,352 KB |
ソースコード
# For the sake of speed,
# this convolution is specialized to mod 998244353.
_fft_mod = 998244353
_fft_sum_e = (911660635, 509520358, 369330050, 332049552, 983190778, 123842337, 238493703, 975955924, 603855026, 856644456, 131300601,
842657263, 730768835, 942482514, 806263778, 151565301, 510815449, 503497456, 743006876, 741047443, 56250497, 867605899, 0, 0, 0, 0, 0, 0, 0, 0)
_fft_sum_ie = (86583718, 372528824, 373294451, 645684063, 112220581, 692852209, 155456985, 797128860, 90816748, 860285882, 927414960, 354738543,
109331171, 293255632, 535113200, 308540755, 121186627, 608385704, 438932459, 359477183, 824071951, 103369235, 0, 0, 0, 0, 0, 0, 0, 0)
def _butterfly(a):
n = len(a)
h = (n - 1).bit_length()
for ph in range(1, h + 1):
w = 1 << (ph - 1)
p = 1 << (h - ph)
now = 1
for s in range(w):
offset = s << (h - ph + 1)
for i in range(p):
l = a[i + offset]
r = a[i + offset + p] * now % _fft_mod
a[i + offset] = (l + r) % _fft_mod
a[i + offset + p] = (l - r) % _fft_mod
now *= _fft_sum_e[(~s & -~s).bit_length() - 1]
now %= _fft_mod
def _butterfly_inv(a):
n = len(a)
h = (n - 1).bit_length()
for ph in range(h, 0, -1):
w = 1 << (ph - 1)
p = 1 << (h - ph)
inow = 1
for s in range(w):
offset = s << (h - ph + 1)
for i in range(p):
l = a[i + offset]
r = a[i + offset + p]
a[i + offset] = (l + r) % _fft_mod
a[i + offset + p] = (l - r) * inow % _fft_mod
inow *= _fft_sum_ie[(~s & -~s).bit_length() - 1]
inow %= _fft_mod
def _convolution_naive(a, b):
n = len(a)
m = len(b)
ans = [0] * (n + m - 1)
if n < m:
for j in range(m):
for i in range(n):
ans[i + j] = (ans[i + j] + a[i] * b[j]) % _fft_mod
else:
for i in range(n):
for j in range(m):
ans[i + j] = (ans[i + j] + a[i] * b[j]) % _fft_mod
return ans
def _convolution_fft(a, b):
a = a.copy()
b = b.copy()
n = len(a)
m = len(b)
z = 1 << (n + m - 2).bit_length()
a += [0] * (z - n)
_butterfly(a)
b += [0] * (z - m)
_butterfly(b)
for i in range(z):
a[i] = a[i] * b[i] % _fft_mod
_butterfly_inv(a)
a = a[:n + m - 1]
iz = pow(z, _fft_mod - 2, _fft_mod)
for i in range(n + m - 1):
a[i] = a[i] * iz % _fft_mod
return a
def _convolution_square(a):
a = a.copy()
n = len(a)
z = 1 << (2 * n - 2).bit_length()
a += [0] * (z - n)
_butterfly(a)
for i in range(z):
a[i] = a[i] * a[i] % _fft_mod
_butterfly_inv(a)
a = a[:2 * n - 1]
iz = pow(z, _fft_mod - 2, _fft_mod)
for i in range(2 * n - 1):
a[i] = a[i] * iz % _fft_mod
return a
def convolution(a, b):
"""It calculates (+, x) convolution in mod 998244353.
Given two arrays a[0], a[1], ..., a[n - 1] and b[0], b[1], ..., b[m - 1],
it calculates the array c of length n + m - 1, defined by
> c[i] = sum(a[j] * b[i - j] for j in range(i + 1)) % 998244353.
It returns an empty list if at least one of a and b are empty.
Complexity
----------
> O(n log n), where n = len(a) + len(b).
"""
n = len(a)
m = len(b)
if n == 0 or m == 0:
return []
if min(n, m) <= 100:
return _convolution_naive(a, b)
if a is b:
return _convolution_square(a)
return _convolution_fft(a, b)
# Reference: https://opt-cp.com/fps-fast-algorithms/
def inv(a):
"""It calculates the inverse of formal power series in O(n log n) time, where n = len(a).
"""
n = len(a)
assert n > 0 and a[0] != 0
res = [pow(a[0], _fft_mod - 2, _fft_mod)]
m = 1
while m < n:
f = a[:min(n, 2 * m)]
g = res.copy()
f += [0] * (2 * m - len(f))
_butterfly(f)
g += [0] * (2 * m - len(g))
_butterfly(g)
for i in range(2 * m):
f[i] = f[i] * g[i] % _fft_mod
_butterfly_inv(f)
f = f[m:] + [0] * m
_butterfly(f)
for i in range(2 * m):
f[i] = f[i] * g[i] % _fft_mod
_butterfly_inv(f)
f = f[:m]
iz = pow(2 * m, _fft_mod - 2, _fft_mod)
iz *= -iz
iz %= _fft_mod
for i in range(m):
f[i] = f[i] * iz % _fft_mod
res.extend(f)
m *= 2
res = res[:n]
return res
def integ_inplace(a):
n = len(a)
assert n > 0
if n == 1:
return []
a.pop()
a.insert(0, 0)
inv = [1, 1]
for i in range(2, n):
inv.append(-inv[_fft_mod%i] * (_fft_mod//i) % _fft_mod)
a[i] = a[i] * inv[i] % _fft_mod
def deriv_inplace(a):
n = len(a)
assert n > 0
for i in range(2, n):
a[i] = a[i] * i % _fft_mod
a.pop(0)
a.append(0)
def log(a):
a = a.copy()
n = len(a)
assert n > 0 and a[0] == 1
a_inv = inv(a)
deriv_inplace(a)
a = convolution(a, a_inv)[:n]
integ_inplace(a)
return a
def exp(a):
a = a.copy()
n = len(a)
assert n > 0 and a[0] == 0
g = [1]
a[0] = 1
h_drv = a.copy()
deriv_inplace(h_drv)
m = 1
while m < n:
f_fft = a[:m] + [0] * m
_butterfly(f_fft)
if m > 1:
_f = [f_fft[i] * g_fft[i] % _fft_mod for i in range(m)]
_butterfly_inv(_f)
_f = _f[m // 2:] + [0] * (m // 2)
_butterfly(_f)
for i in range(m):
_f[i] = _f[i] * g_fft[i] % _fft_mod
_butterfly_inv(_f)
_f = _f[:m//2]
iz = pow(m, _fft_mod - 2, _fft_mod)
iz *= -iz
iz %= _fft_mod
for i in range(m//2):
_f[i] = _f[i] * iz % _fft_mod
g.extend(_f)
t = a[:m]
deriv_inplace(t)
r = h_drv[:m - 1]
r.append(0)
_butterfly(r)
for i in range(m):
r[i] = r[i] * f_fft[i] % _fft_mod
_butterfly_inv(r)
im = pow(-m, _fft_mod - 2, _fft_mod)
for i in range(m):
r[i] = r[i] * im % _fft_mod
for i in range(m):
t[i] = (t[i] + r[i]) % _fft_mod
t = [t[-1]] + t[:-1]
t += [0] * m
_butterfly(t)
g_fft = g + [0] * (2 * m - len(g))
_butterfly(g_fft)
for i in range(2 * m):
t[i] = t[i] * g_fft[i] % _fft_mod
_butterfly_inv(t)
t = t[:m]
i2m = pow(2 * m, _fft_mod - 2, _fft_mod)
for i in range(m):
t[i] = t[i] * i2m % _fft_mod
v = a[m:min(n, 2 * m)]
v += [0] * (m - len(v))
t = [0] * (m - 1) + t + [0]
integ_inplace(t)
for i in range(m):
v[i] = (v[i] - t[m + i]) % _fft_mod
v += [0] * m
_butterfly(v)
for i in range(2 * m):
v[i] = v[i] * f_fft[i] % _fft_mod
_butterfly_inv(v)
v = v[:m]
i2m = pow(2 * m, _fft_mod - 2, _fft_mod)
for i in range(m):
v[i] = v[i] * i2m % _fft_mod
for i in range(min(n - m, m)):
a[m + i] = v[i]
m *= 2
return a
def pow_fps(a, k):
a = a.copy()
n = len(a)
l = 0
while l < len(a) and not a[l]:
l += 1
if l * k >= n:
return [0] * n
ic = pow(a[l], _fft_mod - 2, _fft_mod)
pc = pow(a[l], k, _fft_mod)
a = log([a[i] * ic % _fft_mod for i in range(l, len(a))])
for i in range(len(a)):
a[i] = a[i] * k % _fft_mod
a = exp(a)
for i in range(len(a)):
a[i] = a[i] * pc % _fft_mod
a = [0] * (l * k) + a[:n - l * k]
return a
MOD = 998244353
table_len = 10 ** 5 + 10
def main():
import sys
input = sys.stdin.buffer.readline
fac = [1, 1]
for i in range(2, table_len):
fac.append(fac[-1] * i % MOD)
finv = [0] * table_len
finv[-1] = pow(fac[-1], MOD - 2, MOD)
for i in range(table_len-1, 0, -1):
finv[i - 1] = finv[i] * i % MOD
N = int(input())
f = [(i + 1) * finv[i] % MOD for i in range(N - 1)]
ans = pow_fps(f, N)
print(ans[N - 2] * fac[N - 2] % MOD * pow(N, MOD - N + 1, MOD) % MOD)
main()