-
Notifications
You must be signed in to change notification settings - Fork 32
/
Copy pathTopKSum-两个堆.py
136 lines (116 loc) · 3.85 KB
/
TopKSum-两个堆.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
# !维护topK之和 (这里topK是最小值)
# TopKSum
from collections import defaultdict
from heapq import heappop, heappush
from random import randint
from typing import List
from sortedcontainers import SortedList
class TopKSum:
"""
默认是`最小`的k个数之和.
"""
# in d_in 是大根堆,out d_out 是小根堆
__slots__ = ("_sum", "_k", "_in", "_out", "_d_in", "_d_out", "_c", "_min")
def __init__(self, k: int, min=True) -> None:
self._k = k
self._sum = 0
self._in = []
self._out = []
self._d_in = []
self._d_out = []
self._min = min
self._c = defaultdict(int)
def query(self) -> int:
return self._sum if self._min else -self._sum
def add(self, x: int) -> None:
if not self._min:
x = -x
self._c[x] += 1
heappush(self._in, -x)
self._sum += x
self._modify()
def discard(self, x: int) -> None:
if not self._min:
x = -x
if self._c[x] == 0:
return
self._c[x] -= 1
if self._in and -self._in[0] == x:
self._sum -= x
heappop(self._in)
elif self._in and -self._in[0] > x:
self._sum -= x
heappush(self._d_in, -x)
else:
heappush(self._d_out, x)
self._modify()
def set_k(self, k: int) -> None:
self._k = k
self._modify()
def get_k(self) -> int:
return self._k
def _modify(self) -> None:
while self._out and (len(self._in) - len(self._d_in) < self._k):
p = heappop(self._out)
if self._d_out and p == self._d_out[0]:
heappop(self._d_out)
else:
self._sum += p
heappush(self._in, -p)
while len(self._in) - len(self._d_in) > self._k:
p = -heappop(self._in)
if self._d_in and p == -self._d_in[0]:
heappop(self._d_in)
else:
self._sum -= p
heappush(self._out, p)
while self._d_in and self._in[0] == self._d_in[0]:
heappop(self._in)
heappop(self._d_in)
def __len__(self) -> int:
return len(self._in) + len(self._out) - len(self._d_in) - len(self._d_out)
def __contains__(self, x: int) -> bool:
if not self._min:
x = -x
return self._c[x] > 0
if __name__ == "__main__":
# brute force
k = 5
ts = TopKSum(k, min=False)
sl = SortedList(key=lambda x: -x)
for _ in range(1000):
# add
x = randint(0, 100)
ts.add(x)
sl.add(x)
ts.add(x)
sl.add(x)
assert ts.query() == sum(sl[:k])
# setK
k = randint(1, 10)
ts.set_k(k)
assert ts.query() == sum(sl[:k])
# discard
x = randint(0, 100)
ts.discard(x)
sl.discard(x)
assert ts.query() == sum(sl[:k])
assert len(ts) == len(sl)
assert (x in ts) == (x in sl)
# 2163. 删除元素后和的最小差值
# https://leetcode.cn/problems/minimum-difference-in-sums-after-removal-of-elements/
class Solution:
def minimumDifference(self, nums: List[int]) -> int:
# 前面最小n个和后面大n个
n = len(nums) // 3
minK, maxK = TopKSum(n, min=True), TopKSum(n, min=False)
for i in range(n):
minK.add(nums[i])
for i in range(n, 3 * n):
maxK.add(nums[i])
res = minK.query() - maxK.query()
for i in range(n, 2 * n):
minK.add(nums[i])
maxK.discard(nums[i])
res = min(res, minK.query() - maxK.query())
return res