LeetCode 347. 前 K 个高频元素
题目描述
思路分析
小顶堆
参考代码
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
type Item struct {
num int
freq int
}
type MinHeap []Item
func (h MinHeap) Len() int { return len(h) }
func (h MinHeap) Less(i, j int) bool { return h[i].freq < h[j].freq }
func (h MinHeap) Swap(i, j int) { h[i], h[j] = h[j], h[i] }
func (h *MinHeap) Push(x interface{}) {
*h = append(*h, x.(Item))
}
func (h *MinHeap) Pop() interface{} {
old := *h
n := len(old)
x := old[n-1]
*h = old[0 : n-1]
return x
}
func topKFrequent(nums []int, k int) []int {
// 统计频率
freqMap := make(map[int]int)
for _, num := range nums {
freqMap[num]++
}
// 使用最小堆
h := &MinHeap{}
heap.Init(h)
for num, freq := range freqMap {
heap.Push(h, Item{num, freq})
if h.Len() > k {
heap.Pop(h)
}
}
res := make([]int, 0, k)
for h.Len() > 0 {
res = append(res, heap.Pop(h).(Item).num)
}
return res
}
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
type Element struct {
num int
frequency int
}
// 定义一个最小堆
type MinHeap []Element
func (h MinHeap) Len() int { return len(h) }
func (h MinHeap) Less(i, j int) bool { return h[i].frequency < h[j].frequency }
func (h MinHeap) Swap(i, j int) { h[i], h[j] = h[j], h[i] }
func (h *MinHeap) Push(x interface{}) {
*h = append(*h, x.(Element))
}
func (h *MinHeap) Pop() interface{} {
old := *h
n := len(old)
x := old[n-1]
*h = old[:n-1]
return x
}
func topKFrequent(nums []int, k int) []int {
// 使用哈希表统计每个元素的频率
frequencyMap := make(map[int]int)
for _, num := range nums {
frequencyMap[num]++
}
// 使用最小堆来维护频率最高的前 k 个元素
h := &MinHeap{}
heap.Init(h)
for num, frequency := range frequencyMap {
heap.Push(h, Element{num, frequency})
if h.Len() > k {
heap.Pop(h)
}
}
// 提取最小堆中的元素,即前 k 高频元素
res := make([]int, k)
for i := k - 1; i >= 0; i-- {
res[i] = heap.Pop(h).(Element).num
}
return res
}
- 时间复杂度:O (n log k),其中 n 是数组的长度。
- 空间复杂度:O (n),用于存储频率哈希表和堆。
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
func topKFrequent(nums []int, k int) []int {
if len(nums) <= 0 {
return nil
}
// 统计频率
freqMap := make(map[int]int)
for _, num := range nums {
freqMap[num]++
}
// 小顶堆
type pair struct {
num int
freq int
}
// 手动实现一个小顶堆,使用 sort.Slice 维护堆结构
heap := []pair{}
for num, freq := range freqMap {
heap = append(heap, pair{num, freq})
// 排序使堆顶最小
sort.Slice(heap, func(i, j int) bool {
return heap[i].freq < heap[j].freq
})
// 超出 k 就弹出最小的
if len(heap) > k {
heap = heap[1:]
}
}
var res []int
for _, p := range heap {
res = append(res, p.num)
}
return res
}
1
write your code here
CC BY-NC-SA 4.0
许可协议,转载请注明出处!
本博客所有文章除特别声明外,均采用