結果
| 問題 |
No.1471 Sort Queries
|
| コンテスト | |
| ユーザー |
 None
|
| 提出日時 | 2021-10-07 11:45:01 |
| 言語 | PyPy3 (7.3.15) |
| 結果 |
AC
|
| 実行時間 | 159 ms / 2,000 ms |
| コード長 | 6,212 bytes |
| コンパイル時間 | 466 ms |
| コンパイル使用メモリ | 82,784 KB |
| 実行使用メモリ | 78,356 KB |
| 最終ジャッジ日時 | 2024-07-23 03:06:03 |
| 合計ジャッジ時間 | 6,381 ms |
|
ジャッジサーバーID （参考情報） |
judge3 / judge1 |
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| ファイルパターン | 結果 |
|---|---|
| sample | AC * 3 |
| other | AC * 37 |
ソースコード
class FullyIndexableDictionary():
def __init__(self, size, bit = None):
self.size = size
self.block = (size + 31) >> 5
self.b = [0] * self.block
self.s = [0] * self.block
if bit is not None:
for i in range(self.size-1, -1, -1):
if bit & 1:
self.set(i)
bit >>= 1
self.build()
def set(self, p):
self.b[p >> 5] |= 1 << (p & 31)
def build(self):
for i in range(1, self.block):
self.s[i] = self.s[i - 1] + self.popcount(self.b[i - 1])
def popcount(self, x):
x = x - ((x >> 1) & 0x55555555)
x = (x & 0x33333333) + ((x >> 2) & 0x33333333)
x = (x + (x >> 4)) & 0x0f0f0f0f
x = x + (x >> 8)
x = x + (x >> 16)
return x & 0x0000007f
def access(self, p):
return (self.b[p >> 5] >> (p & 31)) & 1
def _rank(self, p): # [0, p)
mask = (1 << (p & 31)) - 1
return self.s[p >> 5] + self.popcount(self.b[p >> 5] & mask)
def rank(self, p, b):
if b:
return self._rank(p)
else:
return p - self._rank(p)
def select(self, x): # not verified
lb, ub = 0, self.block
while ub - lb > 1:
mid = (ub + lb) // 2
if self.s[mid] <= x:
lb = mid
else:
ub = mid
b_id = lb
lb = b_id * 32
ub = (b_id + 1) * 32
while ub - lb > 1:
mid = (ub + lb) // 2
if self.rank(mid) <= x:
lb = mid
else:
ub = mid
return lb
class WaveletMatrix:
def __init__(self, lis, MAXLOG=32):
self.N = len(lis)
self.mat = list()
self.zs = list()
self.MAXLOG = MAXLOG
self.build(lis)
def build(self, _lis):
lis = _lis[:]
for dep in range(self.MAXLOG-1, -1, -1):
ls = list()
rs = list()
fid = FullyIndexableDictionary(self.N + 1)
for i in range(self.N):
if lis[i] & (1 << dep):
rs.append(lis[i])
fid.set(i)
else:
ls.append(lis[i])
fid.build()
self.mat.append(fid)
self.zs.append(len(ls))
lis = ls + rs
return
def rank(self, r, x):
""" count number of occurrences of x in [0,r) """
return self._rank(0, r, x)
def rangemax_k(self, l, r, k):
""" k-th largest value in [l, r) (k in 1-indexed)"""
ret = 0
for dep in range(self.MAXLOG):
ret <<= 1
cntl = self.mat[dep].rank(l, 1)
cntr = self.mat[dep].rank(r, 1)
if cntr - cntl >= k:
l = cntl + self.zs[dep]
r = cntr + self.zs[dep]
ret |= 1
else:
l = l - cntl
r = r - cntr
k = k - (cntr - cntl)
return ret
def rangemin_k(self, l, r, k):
""" k-th smallest value in [l, r) (k in 1-indexed)"""
return self.rangemax_k(l,r,r-l-k+1)
def rangefreq(self, l, r, x, y):
""" count number of occurrences of [x,y) in [l,r) """
return self._freq_dfs(0, l, r, 0, x, y)
def rangelist(self, l, r, x, y):
""" count number of occurrences of each x in [x,y) in [l,r) """
return self._list_dfs(0, l, r, 0, x, y)
def rangemax(self, l, r):
ret = 0
for dep in range(self.MAXLOG):
ret <<= 1
cntl = self.mat[dep].rank(l, 1)
cntr = self.mat[dep].rank(r, 1)
if cntl == cntr:
l = l - cntl
r = r - cntr
else:
l = cntl + self.zs[dep]
r = cntr + self.zs[dep]
ret |= 1
return ret
def rangemin(self, l, r):
ret = 0
for dep in range(self.MAXLOG):
ret <<= 1
cntl = self.mat[dep].rank(l, 0)
cntr = self.mat[dep].rank(r, 0)
if cntl == cntr:
l = l - cntl + self.zs[dep]
r = r - cntr + self.zs[dep]
ret |= 1
else:
l = cntl
r = cntr
return ret
def _rank(self, l, r, x):
for dep in range(self.MAXLOG):
bit = (x >> (self.MAXLOG - (dep + 1))) & 1
l = self.mat[dep].rank(l, bit) + self.zs[dep] * bit
r = self.mat[dep].rank(r, bit) + self.zs[dep] * bit
return r - l
def _freq_dfs(self, dep, l, r, val, a, b):
if l == r:
return 0
if dep == self.MAXLOG:
return r - l if a <= val < b else 0
mid = 1 << (self.MAXLOG - dep - 1) | val
right = (1 << (self.MAXLOG - dep - 1)) - 1 | mid
if right < a or b <= val:
return 0
if a <= val and mid < b:
return r - l
cntl = self.mat[dep].rank(l, 1)
cntr = self.mat[dep].rank(r, 1)
return self._freq_dfs(dep + 1, l - cntl, r - cntr, val, a, b) + \
self._freq_dfs(dep + 1, cntl + self.zs[dep], cntr + self.zs[dep], mid, a, b)
def _list_dfs(self, dep, l, r, val, a, b):
vs = list()
if l == r or b <= val:
return vs
if dep == self.MAXLOG:
if a <= val < b:
vs.append((val, r - l))
return vs
mid = 1 << (self.MAXLOG - dep - 1) | val
right = (1 << (self.MAXLOG - dep - 1)) - 1 | mid
if right < a:
return vs
cntl = self.mat[dep].rank(l, 1)
cntr = self.mat[dep].rank(r, 1)
vs.extend(self._list_dfs(dep + 1, l - cntl, r - cntr, val, a, b))
vs.extend(self._list_dfs(dep + 1, cntl + self.zs[dep], cntr + self.zs[dep], mid, a, b))
return vs
###############################################################################
N,Q=map(int, input().split())
P=[]
for s in input().rstrip():
P.append(ord(s)-ord("a"))
WM=WaveletMatrix(P)
for _ in range(Q):
l,r,x=map(int, input().split())
p=WM.rangemin_k(l-1,r,x)
print(chr(p+ord("a")))