• Leetcode 978 最长湍流子数组


    题目定义:

    当 A 的子数组 A[i], A[i+1], ..., A[j] 满足下列条件时,我们称其为湍流子数组:
    
    若 i <= k < j,当 k 为奇数时, A[k] > A[k+1],且当 k 为偶数时,A[k] < A[k+1];
    或 若 i <= k < j,当 k 为偶数时,A[k] > A[k+1] ,且当 k 为奇数时, A[k] < A[k+1]。
    也就是说,如果比较符号在子数组中的每个相邻元素对之间翻转,则该子数组是湍流子数组。
    返回 A 的最大湍流子数组的长度。
        
    示例 1:
    输入:[9,4,2,10,7,8,8,1,9]
    输出:5
    解释:(A[1] > A[2] < A[3] > A[4] < A[5])
        
    示例 2:
    输入:[4,8,12,16]
    输出:2
        
    示例 3:
    输入:[100]
    输出:1
     
    

    方式一(滑动窗口):

    class Solution {
        public int maxTurbulenceSize(int[] arr) {
            int n = arr.length;
            int ret = 1;
            int left = 0,right = 0;
            while(right < n - 1){
                if(left == right){
                    if(arr[left] == arr[left + 1])
                        left++;
                    right++;
                }else{
                    if((arr[right - 1] < arr[right] && arr[right] > arr[right + 1] ) ||
                     (arr[right -1] > arr[right] && arr[right] < arr[right + 1]))
                        right ++;
                    else 
                        left  = right;
                }
                ret = Math.max(ret,right - left + 1);
            }
            return ret;
        }
    }
    

    方式二(动态规划):

    /*
    * 状态定义:
    * increased[i]:以 arr[i] 结尾,并且 arr[i - 1] < arr[i] 的湍流子数组的长度;
    * decreased[i]:以 arr[i] 结尾,并且 arr[i - 1] > arr[i] 的湍流子数组的长度。
    *
    * 状态转移方程:
    * increased[i] = decreased[i - 1] + 1 if arr[i - 1] < arr[i] for i > 0;
    * decreased[i] = increased[i - 1] + 1 if arr[i - 1] > arr[i] for i > 0。
    *
    * 初始化:只有一个元素的时候,湍流子数组的长度是 11;
    * 输出:两个状态数组所有元素的最大值是最长湍流子数组的长度;
    * 空间优化:空间优化:当前阶段状态只和上一个阶段状态有关,可以对状态数组进行重复利用。
    * */
    class Solution {
        public int maxTurbulenceSize(int[] arr) {
            int len = arr.length;
            if(len < 2)
                return len;
            int[] increased = new int[len];
            int[] decreased = new int[len];
            increased[0] = 1;
            decreased[0] = 1;
            int res = 1;
            for(int i = 1; i < len; i++){
                if(arr[i - 1] < arr[i]){
                    increased[i] = decreased[i - 1] + 1;
                    decreased[i] = 1;
                }else if(arr[i - 1] > arr[i]){
                    decreased[i] = increased[i - 1] + 1;
                    increased[i] = 1;
                }else{
                    increased[i] = 1;
                    decreased[i] = 1;
                }
                res = Math.max(res,Math.max(increased[i],decreased[i]));
            }
            return res;
        }
    }
    

    方式三(另一种动态规划):

    class Solution {
        public int maxTurbulenceSize(int[] arr) {
            int res = 1;
            int[][] dp =new int[arr.length][2];
            dp[0][0] = dp[0][1] = 1;
            for(int i = 1; i < arr.length; i++){
                if(arr[i] < arr[i - 1]){
                    dp[i][0] = dp[i - 1][1] + 1; 
                    dp[i][1] = 1;
                }else if(arr[i] > arr[i - 1]){
                    dp[i][1] = dp[i - 1][0] + 1;
                    dp[i][0] = 1;
                }else{
                    dp[i][0] = dp[i][1] = 1;
                }
                res = Math.max(res,Math.max(dp[i][0],dp[i][1]));
            }
            return res;
        }
    }
    

    方式四(优化版动态规划):

    class Solution {
        public int maxTurbulenceSize(int[] arr) {
            int res = 1;
            int increased = 1,decreased = 1;
            for(int i = 1; i < arr.length; i++){
                if(arr[i] > arr[i - 1]){
                    increased = decreased + 1;
                    decreased = 1;
                }else if(arr[i] < arr[i -1]){
                    decreased = increased + 1;
                    increased = 1;
                }else{
                    increased = 1;
                    decreased = 1;
                }
                res = Math.max(res,Math.max(increased,decreased)); 
            }
            return res;
        }
    }
    

    参考:

    https://leetcode-cn.com/problems/longest-turbulent-subarray/solution/zui-chang-tuan-liu-zi-shu-zu-by-leetcode-t4d8/

    https://leetcode-cn.com/problems/longest-turbulent-subarray/solution/zui-chang-tuan-liu-zi-shu-zu-by-leetcode-zqoq/

  • 相关阅读:
    3.10 Go Map哈希表
    3.9 Go Slice切片
    3.8 Go Array数组
    3.7 Go指针
    3.6 Go String型
    3.5 Go布尔型
    3.4 Go字符型
    3.3 Go浮点型
    3.2 Go整数类型
    3.1Go变量
  • 原文地址:https://www.cnblogs.com/CodingXu-jie/p/14393007.html
Copyright © 2020-2023  润新知