algorithm-base/animation-simulation/数组篇/leetcode1438绝对值不超过限制的最长子数组.md
2023-05-07 11:18:42 +08:00

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> 如果阅读时,发现错误,或者动画不可以显示的问题可以添加我微信好友 **[tan45du_one](https://raw.githubusercontent.com/tan45du/tan45du.github.io/master/个人微信.15egrcgqd94w.jpg)** ,备注 github + 题目 + 问题 向我反馈
>
> 感谢支持,该仓库会一直维护,希望对各位有一丢丢帮助。
>
> 另外希望手机阅读的同学可以来我的 <u>[**公众号:程序厨**](https://raw.githubusercontent.com/tan45du/test/master/微信图片_20210320152235.2pthdebvh1c0.png)</u> 两个平台同步,想要和题友一起刷题,互相监督的同学,可以在我的小屋点击<u>[**刷题小队**](https://raw.githubusercontent.com/tan45du/test/master/微信图片_20210320152235.2pthdebvh1c0.png)</u>进入。
#### [1438. 绝对差不超过限制的最长连续子数组](https://leetcode-cn.com/problems/longest-continuous-subarray-with-absolute-diff-less-than-or-equal-to-limit/)
给你一个整数数组 nums ,和一个表示限制的整数 limit请你返回最长连续子数组的长度该子数组中的任意两个元素之间的绝对差必须小于或者等于 limit 。
如果不存在满足条件的子数组,则返回 0 。
示例
> 输入nums = [10,1,2,4,7,2], limit = 5
> 输出4
> 解释:满足题意的最长子数组是 [2,4,7,2],其最大绝对差 |2-7| = 5 <= 5 。
**提示:**
- 1 <= nums.length <= 10^5
- 1 <= nums[i] <= 10^9
- 0 <= limit <= 10^9
**题目解析**
我们结合题目,示例,提示来看,这个题目也可以使用滑动窗口的思想来解决。我们需要判断某个子数组是否满足最大绝对差不超过限制值。
那么我们应该怎么解决呢?
我们想一下,窗口内的最大绝对差,如果我们知道窗口的最大值和最小值,最大值减去最小值就能得到最大绝对差。
所以我们这个问题就变成了获取滑动窗口内的最大值和最小值问题,哦?滑动窗口的最大值,是不是很熟悉,大家可以先看一下[滑动窗口的最大值](https://leetcode-cn.com/problems/hua-dong-chuang-kou-de-zui-da-zhi-lcof/solution/yi-shi-pin-sheng-qian-yan-shuang-duan-du-mbga/)这个题目,那我们完全可以借助刚才题目的思想来解决这个题目。啪的一下我就搞懂了。
滑动窗口的最大值,我们当时借助了双端队列,来维护一个单调递减的双端队列,进而得到滑动窗口的最大值
那么我们同样可以借助双端队列,来维护一个单调递增的双端队列,来获取滑动窗口的最小值。既然知道了最大值和最小值,我们就可以判断当前窗口是否符合要求,如果符合要求则扩大窗口,不符合要求则缩小窗口,循环结束返回最大的窗口值即可。
下面我们来看一下我们的动画模拟,一下就能看懂!
<img src="https://img-blog.csdnimg.cn/20210320092423565.gif" style="zoom:150%;" />
其实,我们只要把握两个重点即可,我们的 maxdeque 维护的是一个单调递减的双端队列,头部为当前窗口的最大值, mindeque 维护的是一个单调递增的双端队列,头部为窗口的最小值,即可。好啦我们一起看代码吧。
Java Code:
```java
class Solution {
public int longestSubarray(int[] nums, int limit) {
Deque<Integer> maxdeque = new LinkedList<>();
Deque<Integer> mindeque = new LinkedList<>();
int len = nums.length;
int right = 0, left = 0, maxwin = 0;
while (right < len) {
while (!maxdeque.isEmpty() && maxdeque.peekLast() < nums[right]) {
maxdeque.removeLast();
}
while (!mindeque.isEmpty() && mindeque.peekLast() > nums[right]) {
mindeque.removeLast();
}
//需要更多视频解算法,可以来我的公众号:程序厨
maxdeque.addLast(nums[right]);
mindeque.addLast(nums[right]);
while (maxdeque.peekFirst() - mindeque.peekFirst() > limit) {
if (maxdeque.peekFirst() == nums[left]) maxdeque.removeFirst();
if (mindeque.peekFirst() == nums[left]) mindeque.removeFirst();
left++;
}
//保留最大窗口
maxwin = Math.max(maxwin,right-left+1);
right++;
}
return maxwin;
}
}
```
Python Code:
```python
from typing import List
import collections
class Solution:
def longestSubarray(self, nums: List[int], limit: int)->int:
maxdeque = collections.deque()
mindeque = collections.deque()
leng = len(nums)
right = 0
left = 0
maxwin = 0
while right < leng:
while len(maxdeque) != 0 and maxdeque[-1] < nums[right]:
maxdeque.pop()
while len(mindeque) != 0 and mindeque[-1] > nums[right]:
mindeque.pop()
maxdeque.append(nums[right])
mindeque.append(nums[right])
while (maxdeque[0] - mindeque[0]) > limit:
if maxdeque[0] == nums[left]:
maxdeque.popleft()
if mindeque[0] == nums[left]:
mindeque.popleft()
left += 1
# 保留最大窗口
maxwin = max(maxwin, right - left + 1)
right += 1
return maxwin
```
Swift Code
Swift数组模拟超时58 / 61 个通过测试用例)
```swift
class Solution {
func longestSubarray(_ nums: [Int], _ limit: Int) -> Int {
var maxQueue:[Int] = []
var minQueue:[Int] = []
let len = nums.count
var right = 0, left = 0, maxWin = 0
while right < len {
while !maxQueue.isEmpty && (maxQueue.last! < nums[right]) {
maxQueue.removeLast()
}
while !minQueue.isEmpty && (minQueue.last! > nums[right]) {
minQueue.removeLast()
}
maxQueue.append(nums[right])
minQueue.append(nums[right])
while (maxQueue.first! - minQueue.first!) > limit {
if maxQueue.first! == nums[left] {
maxQueue.removeFirst()
}
if minQueue.first! == nums[left] {
minQueue.removeFirst()
}
left += 1
}
maxWin = max(maxWin, right - left + 1)
right += 1
}
return maxWin
}
}
```
Swift使用双端队列击败了 100.00%
```swift
class Solution {
func longestSubarray(_ nums: [Int], _ limit: Int) -> Int {
var maxQueue = Deque<Int>.init()
var minQueue = Deque<Int>.init()
let len = nums.count
var right = 0, left = 0, maxWin = 0
while right < len {
while !maxQueue.isEmpty && (maxQueue.peekBack()! < nums[right]) {
maxQueue.dequeueBack()
}
while !minQueue.isEmpty && (minQueue.peekBack()! > nums[right]) {
minQueue.dequeueBack()
}
maxQueue.enqueue(nums[right])
minQueue.enqueue(nums[right])
while (maxQueue.peekFront()! - minQueue.peekFront()!) > limit {
if maxQueue.peekFront()! == nums[left] {
maxQueue.dequeue()
}
if minQueue.peekFront()! == nums[left] {
minQueue.dequeue()
}
left += 1
}
maxWin = max(maxWin, right - left + 1)
right += 1
}
return maxWin
}
// 双端队列数据结构
public struct Deque<T> {
private var array: [T?]
private var head: Int
private var capacity: Int
private let originalCapacity: Int
public init(_ capacity: Int = 10) {
self.capacity = max(capacity, 1)
originalCapacity = self.capacity
array = [T?](repeating: nil, count: capacity)
head = capacity
}
public var isEmpty: Bool {
return count == 0
}
public var count: Int {
return array.count - head
}
public mutating func enqueue(_ element: T) {
array.append(element)
}
public mutating func enqueueFront(_ element: T) {
if head == 0 {
capacity *= 2
let emptySpace = [T?](repeating: nil, count: capacity)
array.insert(contentsOf: emptySpace, at: 0)
head = capacity
}
head -= 1
array[head] = element
}
public mutating func dequeue() -> T? {
guard head < array.count, let element = array[head] else { return nil }
array[head] = nil
head += 1
if capacity >= originalCapacity && head >= capacity*2 {
let amountToRemove = capacity + capacity/2
array.removeFirst(amountToRemove)
head -= amountToRemove
capacity /= 2
}
return element
}
public mutating func dequeueBack() -> T? {
if isEmpty {
return nil
} else {
return array.removeLast()
}
}
public func peekFront() -> T? {
if isEmpty {
return nil
} else {
return array[head]
}
}
public func peekBack() -> T? {
if isEmpty {
return nil
} else {
return array.last!
}
}
}
}
```
Go Code:
```go
func longestSubarray(nums []int, limit int) int {
maxdeq := []int{} // 递减队列
mindeq := []int{} // 递增队列
length := len(nums)
left, right, maxwin := 0, 0, 0
for right < length {
for len(maxdeq) != 0 && maxdeq[len(maxdeq) - 1] < nums[right] {
maxdeq = maxdeq[: len(maxdeq) - 1]
}
maxdeq = append(maxdeq, nums[right])
for len(mindeq) != 0 && mindeq[len(mindeq) - 1] > nums[right] {
mindeq = mindeq[: len(mindeq) - 1]
}
mindeq = append(mindeq, nums[right])
for maxdeq[0] - mindeq[0] > limit {
if maxdeq[0] == nums[left] {
maxdeq = maxdeq[1:]
}
if mindeq[0] == nums[left] {
mindeq = mindeq[1:]
}
left++
}
maxwin = max(maxwin, right - left + 1)
right++
}
return maxwin
}
func max(a, b int) int {
if a > b {
return a
}
return b
}
```