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简单 |
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设计一个找到数据流中第 k 大元素的类（class）。注意是排序后的第 k 大元素，不是第 k 个不同的元素。
请实现 KthLargest 类：
KthLargest(int k, int[] nums)使用整数k和整数流nums初始化对象。int add(int val)将val插入数据流nums后，返回当前数据流中第k大的元素。
示例：
输入： ["KthLargest", "add", "add", "add", "add", "add"] [[3, [4, 5, 8, 2]], [3], [5], [10], [9], [4]] 输出： [null, 4, 5, 5, 8, 8] 解释： KthLargest kthLargest = new KthLargest(3, [4, 5, 8, 2]); kthLargest.add(3); // return 4 kthLargest.add(5); // return 5 kthLargest.add(10); // return 5 kthLargest.add(9); // return 8 kthLargest.add(4); // return 8
提示：
1 <= k <= 1040 <= nums.length <= 104-104 <= nums[i] <= 104-104 <= val <= 104- 最多调用
add方法104次 - 题目数据保证，在查找第
k大元素时，数组中至少有k个元素
class KthLargest:
def __init__(self, k: int, nums: List[int]):
self.q = []
self.size = k
for num in nums:
self.add(num)
def add(self, val: int) -> int:
heappush(self.q, val)
if len(self.q) > self.size:
heappop(self.q)
return self.q[0]
# Your KthLargest object will be instantiated and called as such:
# obj = KthLargest(k, nums)
# param_1 = obj.add(val)class KthLargest {
private PriorityQueue<Integer> q;
private int size;
public KthLargest(int k, int[] nums) {
q = new PriorityQueue<>(k);
size = k;
for (int num : nums) {
add(num);
}
}
public int add(int val) {
q.offer(val);
if (q.size() > size) {
q.poll();
}
return q.peek();
}
}
/**
* Your KthLargest object will be instantiated and called as such:
* KthLargest obj = new KthLargest(k, nums);
* int param_1 = obj.add(val);
*/class KthLargest {
public:
priority_queue<int, vector<int>, greater<int>> q;
int size;
KthLargest(int k, vector<int>& nums) {
size = k;
for (int num : nums) add(num);
}
int add(int val) {
q.push(val);
if (q.size() > size) q.pop();
return q.top();
}
};
/**
* Your KthLargest object will be instantiated and called as such:
* KthLargest* obj = new KthLargest(k, nums);
* int param_1 = obj->add(val);
*/type KthLargest struct {
h *IntHeap
k int
}
func Constructor(k int, nums []int) KthLargest {
h := &IntHeap{}
heap.Init(h)
for _, v := range nums {
heap.Push(h, v)
}
for h.Len() > k {
heap.Pop(h)
}
return KthLargest{
h: h,
k: k,
}
}
func (this *KthLargest) Add(val int) int {
heap.Push(this.h, val)
for this.h.Len() > this.k {
heap.Pop(this.h)
}
return this.h.Top()
}
func connectSticks(sticks []int) int {
h := IntHeap(sticks)
heap.Init(&h)
res := 0
for h.Len() > 1 {
val := heap.Pop(&h).(int)
val += heap.Pop(&h).(int)
res += val
heap.Push(&h, val)
}
return res
}
type IntHeap []int
func (h IntHeap) Len() int { return len(h) }
func (h IntHeap) Less(i, j int) bool { return h[i] < h[j] }
func (h IntHeap) Swap(i, j int) { h[i], h[j] = h[j], h[i] }
func (h *IntHeap) Push(x any) {
*h = append(*h, x.(int))
}
func (h *IntHeap) Pop() any {
old := *h
n := len(old)
x := old[n-1]
*h = old[0 : n-1]
return x
}
func (h *IntHeap) Top() int {
if (*h).Len() == 0 {
return 0
}
return (*h)[0]
}
/**
* Your KthLargest object will be instantiated and called as such:
* obj := Constructor(k, nums);
* param_1 := obj.Add(val);
*//**
* @param {number} k
* @param {number[]} nums
*/
var KthLargest = function (k, nums) {
this.k = k;
this.heap = new MinHeap();
for (let num of nums) {
this.add(num);
}
};
/**
* @param {number} val
* @return {number}
*/
KthLargest.prototype.add = function (val) {
this.heap.offer(val);
if (this.heap.size() > this.k) {
this.heap.poll();
}
return this.heap.peek();
};
class MinHeap {
constructor(data = []) {
this.data = data;
this.comparator = (a, b) => a - b;
this.heapify();
}
heapify() {
if (this.size() < 2) return;
for (let i = 1; i < this.size(); i++) {
this.bubbleUp(i);
}
}
peek() {
if (this.size() === 0) return null;
return this.data[0];
}
offer(value) {
this.data.push(value);
this.bubbleUp(this.size() - 1);
}
poll() {
if (this.size() === 0) {
return null;
}
const result = this.data[0];
const last = this.data.pop();
if (this.size() !== 0) {
this.data[0] = last;
this.bubbleDown(0);
}
return result;
}
bubbleUp(index) {
while (index > 0) {
const parentIndex = (index - 1) >> 1;
if (this.comparator(this.data[index], this.data[parentIndex]) < 0) {
this.swap(index, parentIndex);
index = parentIndex;
} else {
break;
}
}
}
bubbleDown(index) {
const lastIndex = this.size() - 1;
while (true) {
const leftIndex = index * 2 + 1;
const rightIndex = index * 2 + 2;
let findIndex = index;
if (
leftIndex <= lastIndex &&
this.comparator(this.data[leftIndex], this.data[findIndex]) < 0
) {
findIndex = leftIndex;
}
if (
rightIndex <= lastIndex &&
this.comparator(this.data[rightIndex], this.data[findIndex]) < 0
) {
findIndex = rightIndex;
}
if (index !== findIndex) {
this.swap(index, findIndex);
index = findIndex;
} else {
break;
}
}
}
swap(index1, index2) {
[this.data[index1], this.data[index2]] = [this.data[index2], this.data[index1]];
}
size() {
return this.data.length;
}
}
/**
* Your KthLargest object will be instantiated and called as such:
* var obj = new KthLargest(k, nums)
* var param_1 = obj.add(val)
*/class KthLargest {
#pq = new MinPriorityQueue();
#k = 0;
constructor(k: number, nums: number[]) {
this.#k = k;
for (const x of nums) {
this.#pq.enqueue(x);
if (this.#pq.size() > k) {
this.#pq.dequeue();
}
}
}
add(val: number): number {
this.#pq.enqueue(val);
if (this.#pq.size() > this.#k) {
this.#pq.dequeue();
}
return this.#pq.front().element;
}
}
/**
* Your KthLargest object will be instantiated and called as such:
* var obj = new KthLargest(k, nums)
* var param_1 = obj.add(val)
*/