結果

問題 No.434 占い
ユーザー Navier_BoltzmannNavier_Boltzmann
提出日時 2024-11-01 19:53:42
言語 PyPy3
(7.3.15)
結果
WA  
実行時間 -
コード長 16,269 bytes
コンパイル時間 359 ms
コンパイル使用メモリ 82,464 KB
実行使用メモリ 80,288 KB
最終ジャッジ日時 2024-11-01 19:53:50
合計ジャッジ時間 7,813 ms
ジャッジサーバーID
(参考情報)
judge3 / judge1
このコードへのチャレンジ
(要ログイン)

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 55 ms
66,320 KB
testcase_01 WA -
testcase_02 AC 55 ms
66,384 KB
testcase_03 AC 59 ms
66,280 KB
testcase_04 AC 59 ms
66,564 KB
testcase_05 AC 56 ms
67,244 KB
testcase_06 WA -
testcase_07 AC 66 ms
71,132 KB
testcase_08 AC 91 ms
78,092 KB
testcase_09 AC 90 ms
78,116 KB
testcase_10 AC 106 ms
78,096 KB
testcase_11 AC 162 ms
79,644 KB
testcase_12 WA -
testcase_13 AC 117 ms
78,312 KB
testcase_14 AC 112 ms
78,012 KB
testcase_15 AC 166 ms
79,824 KB
testcase_16 AC 179 ms
79,344 KB
testcase_17 AC 154 ms
78,192 KB
testcase_18 AC 223 ms
78,348 KB
testcase_19 AC 256 ms
80,288 KB
testcase_20 WA -
testcase_21 AC 179 ms
79,580 KB
testcase_22 AC 225 ms
79,796 KB
testcase_23 WA -
testcase_24 WA -
testcase_25 WA -
testcase_26 AC 181 ms
79,504 KB
testcase_27 WA -
testcase_28 WA -
testcase_29 WA -
testcase_30 WA -
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 pypyjit
# pypyjit.set_param('max_unroll_recursion=-1')
from collections import *
from functools import *
from heapq import *
from itertools import *
import sys, math,random
# input = sys.stdin.buffer.readline
# sys.setrecursionlimit(10**6)
def cle(a, D):
"""
Counts the number of elements in D that are less than or equal to a.
Parameters:
a (int): The value to compare against.
D (list): A sorted list of integers.
Returns:
int: The count of elements in D that are less than or equal to a.
"""
y = len(D) - 1
x = 0
if D[x] > a:
return 0
if D[y] <= a:
return y + 1
while y - x > 1:
mid = (y + x) // 2
if D[mid] <= a:
x = mid
else:
y = mid
return y
class cs_2d:
"""
2D cumulative sum class.
"""
def __init__(self, x):
"""
Initializes the 2D cumulative sum array.
Parameters:
x (list of list of int): A 2D list of integers.
"""
n = len(x)
m = len(x[0])
self.n = n
self.m = m
tmp = [0] * ((n + 1) * (m + 1))
for i in range(n):
for j in range(m):
tmp[m * (i + 1) + j + 1] = (
tmp[m * (i + 1) + j] + tmp[m * i + j + 1] - tmp[m * i + j] + x[i][j]
)
self.S = tmp
def query(self, ix, jx, iy, jy):
"""
Queries the sum of the submatrix from (ix, iy) to (jx, jy).
Parameters:
ix (int): Starting row index.
jx (int): Ending row index.
iy (int): Starting column index.
jy (int): Ending column index.
Returns:
int: The sum of the submatrix.
"""
return (
self.S[self.m * jx + jy]
- self.S[self.m * jx + iy]
- self.S[self.m * ix + jy]
+ self.S[self.m * ix + iy]
)
class prime_factorize:
"""
Class for prime factorization and related operations.
"""
def __init__(self, M=10**6):
"""
Initializes the sieve for prime factorization.
Parameters:
M (int): The maximum number to factorize.
"""
self.sieve = [-1] * (M + 1)
self.sieve[1] = 1
self.p = [False] * (M + 1)
self.mu = [1] * (M + 1)
for i in range(2, M + 1):
if self.sieve[i] == -1:
self.p[i] = True
i2 = i**2
for j in range(i2, M + 1, i2):
self.mu[j] = 0
for j in range(i, M + 1, i):
self.sieve[j] = i
self.mu[j] *= -1
def factors(self, x):
"""
Returns the prime factors of x.
Parameters:
x (int): The number to factorize.
Returns:
list: A list of prime factors of x.
"""
tmp = []
while self.sieve[x] != x:
tmp.append(self.sieve[x])
x //= self.sieve[x]
tmp.append(self.sieve[x])
return tmp
def divisors(self, x):
"""
Returns all divisors of x.
Parameters:
x (int): The number to find divisors for.
Returns:
list: A sorted list of all divisors of x.
"""
C = Counter(self.factors(x))
tmp = []
for p in product(*[[pow(k, i) for i in range(v + 1)] for k, v in C.items()]):
res = 1
for pp in p:
res *= pp
tmp.append(res)
tmp.sort()
return tmp
def is_prime(self, x):
"""
Checks if x is a prime number.
Parameters:
x (int): The number to check.
Returns:
bool: True if x is prime, False otherwise.
"""
return self.p[x]
def mobius(self, x):
"""
Returns the Möbius function value of x.
Parameters:
x (int): The number to find the Möbius function value for.
Returns:
int: The Möbius function value of x.
"""
return self.mu[x]
class combination:
"""
Class for computing combinations (nCr) modulo p.
"""
def __init__(self, N, p):
"""
Initializes the combination class.
Parameters:
N (int): The maximum value of n.
p (int): The modulus.
"""
self.fact = [1, 1] # fact[n] = (n! mod p)
self.factinv = [1, 1] # factinv[n] = ((n!)^(-1) mod p)
self.inv = [0, 1] # factinv calculation
self.p = p
for i in range(2, N + 1):
self.fact.append((self.fact[-1] * i) % p)
self.inv.append((-self.inv[p % i] * (p // i)) % p)
self.factinv.append((self.factinv[-1] * self.inv[-1]) % p)
def cmb(self, n, r):
"""
Computes the combination (nCr) modulo p.
Parameters:
n (int): The total number of items.
r (int): The number of items to choose.
Returns:
int: The value of nCr modulo p.
"""
if (r < 0) or (n < r):
return 0
r = min(r, n - r)
return self.fact[n] * self.factinv[r] * self.factinv[n - r] % self.p
def md(n):
"""
Returns all divisors of n.
Parameters:
n (int): The number to find divisors for.
Returns:
list: A sorted list of all divisors of n.
"""
lower_divisors, upper_divisors = [], []
i = 1
while i * i <= n:
if n % i == 0:
lower_divisors.append(i)
if i != n // i:
upper_divisors.append(n // i)
i += 1
return lower_divisors + upper_divisors[::-1]
class DSU:
"""
Disjoint Set Union (Union-Find) class.
"""
def __init__(self, n):
"""
Initializes the DSU.
Parameters:
n (int): The number of elements.
"""
self._n = n
self.parent_or_size = [-1] * n
self.member = [[i] for i in range(n)]
self._max = [i for i in range(n)]
self._min = [i for i in range(n)]
def merge(self, a, b):
"""
Merges the sets containing a and b.
Parameters:
a (int): An element in the first set.
b (int): An element in the second set.
Returns:
int: The leader of the merged set.
"""
assert 0 <= a < self._n
assert 0 <= b < self._n
x, y = self.leader(a), self.leader(b)
if x == y:
return x
if -self.parent_or_size[x] < -self.parent_or_size[y]:
x, y = y, x
self.parent_or_size[x] += self.parent_or_size[y]
self._max[x] = max(self._max[x],self._max[y])
self._min[x] = min(self._min[x],self._min[y])
for tmp in self.member[y]:
self.member[x].append(tmp)
self.parent_or_size[y] = x
return x
def get_max(self,x):
return self._max[self.leader(x)]
def get_min(self,x):
return self._min[self.leader(x)]
def members(self, a):
"""
Returns the members of the set containing a.
Parameters:
a (int): An element in the set.
Returns:
list: A list of members in the set containing a.
"""
return self.member[self.leader(a)]
def same(self, a, b):
"""
Checks if a and b are in the same set.
Parameters:
a (int): An element in the first set.
b (int): An element in the second set.
Returns:
bool: True if a and b are in the same set, False otherwise.
"""
assert 0 <= a < self._n
assert 0 <= b < self._n
return self.leader(a) == self.leader(b)
def leader(self, a):
"""
Finds the leader of the set containing a.
Parameters:
a (int): An element in the set.
Returns:
int: The leader of the set containing a.
"""
assert 0 <= a < self._n
if self.parent_or_size[a] < 0:
return a
self.parent_or_size[a] = self.leader(self.parent_or_size[a])
return self.parent_or_size[a]
def size(self, a):
"""
Returns the size of the set containing a.
Parameters:
a (int): An element in the set.
Returns:
int: The size of the set containing a.
"""
assert 0 <= a < self._n
return -self.parent_or_size[self.leader(a)]
def groups(self):
"""
Returns all sets as a list of lists.
Returns:
list: A list of lists, where each list contains the members of a set.
"""
leader_buf = [self.leader(i) for i in range(self._n)]
result = [[] for _ in range(self._n)]
for i in range(self._n):
result[leader_buf[i]].append(i)
return [r for r in result if r != []]
class SegTree:
"""
Segment Tree class.
"""
def __init__(self, init_val, segfunc, ide_ele):
"""
Initializes the Segment Tree.
Parameters:
init_val (list): The initial values for the leaves of the tree.
segfunc (function): The function to use for segment operations.
ide_ele (any): The identity element for the segment function.
"""
n = len(init_val)
self.segfunc = segfunc
self.ide_ele = ide_ele
self.num = 1 << (n - 1).bit_length()
self.tree = [ide_ele] * 2 * self.num
# Set the initial values to the leaves
for i in range(n):
self.tree[self.num + i] = init_val[i]
# Build the tree
for i in range(self.num - 1, 0, -1):
self.tree[i] = segfunc(self.tree[2 * i], self.tree[2 * i + 1])
def update(self, k, x):
"""
Updates the k-th value to x.
Parameters:
k (int): The index to update (0-indexed).
x (any): The new value.
"""
k += self.num
self.tree[k] = x
while k > 1:
tk = k >> 1
self.tree[tk] = self.segfunc(self.tree[tk << 1], self.tree[(tk << 1) + 1])
k >>= 1
def get(self, x):
return self.tree[x + self.num]
def query(self, l, r):
"""
Queries the segment function result for the range [l, r).
Parameters:
l (int): The start index (0-indexed).
r (int): The end index (0-indexed).
Returns:
any: The result of the segment function for the range [l, r).
"""
res_l = self.ide_ele
res_r = self.ide_ele
l += self.num
r += self.num
while l < r:
if l & 1:
res_l = self.segfunc(res_l, self.tree[l])
l += 1
if r & 1:
res_r = self.segfunc(self.tree[r - 1], res_r)
l >>= 1
r >>= 1
res = self.segfunc(res_l, res_r)
return res
class RSQandRAQ():
"""O(logN)
add: [l, r)val
query: [l, r)
l, r0-indexed
"""
def __init__(self, n, mod=None):
self.n = n
self.bit0 = [0] * (n + 1)
self.bit1 = [0] * (n + 1)
self.mod = mod
def _add(self, bit, i, val):
i = i + 1
while i <= self.n:
if self.mod is None:
bit[i] += val
else:
bit[i] = (bit[i]+val)%self.mod
i += i & -i
def _get(self, bit, i):
s = 0
while i > 0:
if self.mod is None:
s += bit[i]
else:
s = (s + bit[i])%self.mod
i-= i & -i
return s
def add(self, l, r, val):
"""[l, r)val"""
self._add(self.bit0, l, -val * l)
self._add(self.bit0, r, val * r)
self._add(self.bit1, l, val)
self._add(self.bit1, r, -val)
def query(self, l, r):
"""[l, r)"""
_res = (self._get(self.bit0, r) + r * self._get(self.bit1, r)
- self._get(self.bit0, l) - l * self._get(self.bit1, l) )
if self.mod is None:
return _res
else:
return _res%self.mod
class Dinic:
def __init__(self, n):
self.n = n
self.links = [[] for _ in range(n)]
self.depth = None
self.progress = None
def add_link(self, _from, to, cap):
self.links[_from].append([cap, to, len(self.links[to])])
self.links[to].append([0, _from, len(self.links[_from]) - 1])
def bfs(self, s):
depth = [-1] * self.n
depth[s] = 0
q = deque([s])
while q:
v = q.popleft()
for cap, to, rev in self.links[v]:
if cap > 0 and depth[to] < 0:
depth[to] = depth[v] + 1
q.append(to)
self.depth = depth
def dfs(self, v, t, flow):
if v == t:
return flow
links_v = self.links[v]
for i in range(self.progress[v], len(links_v)):
self.progress[v] = i
cap, to, rev = link = links_v[i]
if cap == 0 or self.depth[v] >= self.depth[to]:
continue
d = self.dfs(to, t, min(flow, cap))
if d == 0:
continue
link[0] -= d
self.links[to][rev][0] += d
return d
return 0
def max_flow(self, s, t):
flow = 0
while True:
self.bfs(s)
if self.depth[t] < 0:
return flow
self.progress = [0] * self.n
current_flow = self.dfs(s, t, float('inf'))
while current_flow > 0:
flow += current_flow
current_flow = self.dfs(s, t, float('inf'))
def modinv(a,MOD):
r0,r1,s0,s1 = a,MOD,1,0
while r1:
r0,r1, s0,s1 = r1,r0%r1, s1,s0-r0//r1*s1
return s0%MOD
def factorize(N):
factorization = []
for i in range(2,N+1):
if i*i > N: break
if N%i: continue
c = 0
while N%i == 0:
N //= i
c += 1
factorization.append((i,i**c))
if N != 1: factorization.append((N,N))
return factorization
class BinomialCoefficient:
def __init__(self,m):
self.MOD = m
self.factorization = factorize(m)
self.facs = []
self.invs = []
self.coeffs = []
self.pows = []
for p,pe in self.factorization:
fac = [1]*pe
for i in range(1,pe):
fac[i] = fac[i-1]*(i if i%p else 1)%pe
inv = [1]*pe
inv[-1] = fac[-1]
for i in range(1,pe)[::-1]:
inv[i-1] = inv[i]*(i if i%p else 1)%pe
self.facs.append(fac)
self.invs.append(inv)
# coeffs
c = modinv(m//pe,pe)
self.coeffs.append(m//pe*c%m)
# pows
powp = [1]
while powp[-1]*p != pe:
powp.append(powp[-1]*p)
self.pows.append(powp)
def choose(self,n,k):
if k < 0 or k > n: return 0
if k == 0 or k == n: return 1%self.MOD
res = 0
for i,(p,pe) in enumerate(self.factorization):
res += self._choose_pe(n,k,p,pe,self.facs[i],self.invs[i],self.pows[i]) * self.coeffs[i]
res %= self.MOD
return res
def _E(self,n,k,r,p):
res = 0
while n:
n //= p
k //= p
r //= p
res += n - k - r
return res
def _choose_pe(self,n,k,p,pe,fac,inv,powp):
r = n-k
e0 = self._E(n,k,r,p)
if e0 >= len(powp): return 0
res = powp[e0]
if (p != 2 or pe == 4) and self._E(n//(pe//p),k//(pe//p),r//(pe//p),p)%2:
res = pe-res
while n:
res = res * fac[n%pe]%pe * inv[k%pe]%pe * inv[r%pe]%pe
n //= p
k //= p
r //= p
return res
def answer():
S = list(input())
C = BinomialCoefficient(9)
S = [int(s) for s in S]
ans = 0
N = len(S)
for i,s in enumerate(S):
ans = (ans + s*C.choose(N-1,i))%9
if ans==0:
ans = 9
print(ans)
for _ in range(int(input())):
answer()
הההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההה
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
0