164 lines
3.8 KiB
JavaScript
164 lines
3.8 KiB
JavaScript
/*
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215. 数组中的第K个最大元素
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中等
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相关标签
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相关企业
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给定整数数组 nums 和整数 k，请返回数组中第 k 个最大的元素。
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请注意，你需要找的是数组排序后的第 k 个最大的元素，而不是第 k 个不同的元素。
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你必须设计并实现时间复杂度为 O(n) 的算法解决此问题。
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示例 1:
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输入: [3,2,1,5,6,4], k = 2
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输出: 5
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示例 2:
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输入: [3,2,3,1,2,4,5,5,6], k = 4
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输出: 4
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提示：
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1 <= k <= nums.length <= 105
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-104 <= nums[i] <= 104
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*/
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// 思路1:排序之后直接取，但是不符合题目要求
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/**
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* @param {number[]} nums
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* @param {number} k
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* @return {number}
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*/
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const findKthLargest = function (nums, k) {
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nums.sort((a, b) => a - b);
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return nums[nums.length - k];
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};
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// 使用快速选择算法
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/**
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* @param {number[]} nums
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* @param {number} k
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* @return {number}
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*/
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const partition = (nums, left, right) => {
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const pivot = nums[right];
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let i = left;
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for (let j = left; j < right; j++) {
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if (nums[j] < pivot) {
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[nums[i], nums[j]] = [nums[j], nums[i]];
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i++;
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}
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}
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[nums[i], nums[right]] = [nums[right], nums[i]];
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return i;
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};
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const quickSelect = (nums, left, right, k) => {
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if (left === right) return nums[left];
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const pivotIndex = partition(nums, left, right);
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if (pivotIndex === k) {
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return nums[k];
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} if (pivotIndex < k) {
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return quickSelect(nums, pivotIndex + 1, right, k);
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}
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return quickSelect(nums, left, pivotIndex - 1, k);
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};
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const findKthLargest2 = function (nums, k) {
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return quickSelect(nums, 0, nums.length - 1, nums.length - k);
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};
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// 使用最小堆
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class MinHeap {
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constructor() {
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this.heap = [];
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}
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size() {
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return this.heap.length;
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}
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peek() {
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return this.heap[0];
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}
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insert(value) {
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this.heap.push(value);
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this.heapifyUp();
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}
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remove() {
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if (this.size() === 1) {
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return this.heap.pop();
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}
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const root = this.heap[0];
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this.heap[0] = this.heap.pop();
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this.heapifyDown();
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return root;
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}
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heapifyUp() {
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let index = this.size() - 1;
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while (index > 0) {
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const parentIndex = Math.floor((index - 1) / 2);
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if (this.heap[parentIndex] <= this.heap[index]) break;
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[this.heap[parentIndex], this.heap[index]] = [this.heap[index], this.heap[parentIndex]];
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index = parentIndex;
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}
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}
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heapifyDown() {
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let index = 0;
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const length = this.size();
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const element = this.heap[0];
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while (true) {
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const leftChildIndex = 2 * index + 1;
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const rightChildIndex = 2 * index + 2;
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let leftChild; let
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rightChild;
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let swap = null;
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if (leftChildIndex < length) {
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leftChild = this.heap[leftChildIndex];
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if (leftChild < element) {
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swap = leftChildIndex;
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}
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}
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if (rightChildIndex < length) {
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rightChild = this.heap[rightChildIndex];
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if ((swap === null && rightChild < element) || (swap !== null && rightChild < leftChild)) {
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swap = rightChildIndex;
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}
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}
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if (swap === null) break;
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[this.heap[index], this.heap[swap]] = [this.heap[swap], this.heap[index]];
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index = swap;
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}
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}
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}
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const findKthLargest3 = function (nums, k) {
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const minHeap = new MinHeap();
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for (const num of nums) {
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minHeap.insert(num);
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if (minHeap.size() > k) {
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minHeap.remove();
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}
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}
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return minHeap.peek();
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};
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// 示例测试
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console.log(findKthLargest([3, 2, 1, 5, 6, 4], 2)); // 输出: 5
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console.log(findKthLargest([3, 2, 3, 1, 2, 4, 5, 5, 6], 4)); // 输出: 4
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console.log(findKthLargest2([3, 2, 1, 5, 6, 4], 2)); // 输出: 5
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console.log(findKthLargest2([3, 2, 3, 1, 2, 4, 5, 5, 6], 4)); // 输出: 4
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console.log(findKthLargest3([3, 2, 1, 5, 6, 4], 2)); // 输出: 5
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console.log(findKthLargest3([3, 2, 3, 1, 2, 4, 5, 5, 6], 4)); // 输出: 4
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