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| 1 | +package pp.arithmetic.leetcode; |
| 2 | + |
| 3 | +/** |
| 4 | + * Created by wangpeng on 2019-03-29. |
| 5 | + * 978. 最长湍流子数组 |
| 6 | + * <p> |
| 7 | + * 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: |
| 8 | + * <p> |
| 9 | + * 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]; |
| 10 | + * 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]。 |
| 11 | + * 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。 |
| 12 | + * <p> |
| 13 | + * 返回 A 的最大湍流子数组的长度。 |
| 14 | + * <p> |
| 15 | + * <p> |
| 16 | + * <p> |
| 17 | + * 示例 1: |
| 18 | + * <p> |
| 19 | + * 输入:[9,4,2,10,7,8,8,1,9] |
| 20 | + * 输出:5 |
| 21 | + * 解释:(A[1] > A[2] < A[3] > A[4] < A[5]) |
| 22 | + * 示例 2: |
| 23 | + * <p> |
| 24 | + * 输入:[4,8,12,16] |
| 25 | + * 输出:2 |
| 26 | + * 示例 3: |
| 27 | + * <p> |
| 28 | + * 输入:[100] |
| 29 | + * 输出:1 |
| 30 | + * <p> |
| 31 | + * <p> |
| 32 | + * 提示: |
| 33 | + * <p> |
| 34 | + * 1 <= A.length <= 40000 |
| 35 | + * 0 <= A[i] <= 10^9 |
| 36 | + * |
| 37 | + * @see <a href="https://leetcode-cn.com/problems/longest-turbulent-subarray/">longest-turbulent-subarray</a> |
| 38 | + */ |
| 39 | +public class _978_maxTurbulenceSize { |
| 40 | + |
| 41 | + public static void main(String[] args) { |
| 42 | + _978_maxTurbulenceSize size = new _978_maxTurbulenceSize(); |
| 43 | + System.out.println(size.maxTurbulenceSize(new int[]{9, 4, 2, 10, 7, 8, 8, 1, 9})); |
| 44 | + System.out.println(size.maxTurbulenceSize(new int[]{4, 8, 12, 16})); |
| 45 | + System.out.println(size.maxTurbulenceSize(new int[]{4, 4})); |
| 46 | + System.out.println(size.maxTurbulenceSize(new int[]{4, 4, 4})); |
| 47 | + } |
| 48 | + |
| 49 | + /** |
| 50 | + * 解法二:代码简化了解法一的行数,窗口的思想 |
| 51 | + * 先确定一个起始锚点anchor,再确定一个终止的点,两点相减得到区间长度 |
| 52 | + * |
| 53 | + * @param A |
| 54 | + * @return |
| 55 | + */ |
| 56 | + public int maxTurbulenceSize2(int[] A) { |
| 57 | + int N = A.length; |
| 58 | + int ans = 1; |
| 59 | + int anchor = 0; |
| 60 | + |
| 61 | + for (int i = 1; i < N; ++i) { |
| 62 | + int c = Integer.compare(A[i - 1], A[i]); |
| 63 | + if (i == N - 1 || c * Integer.compare(A[i], A[i + 1]) != -1) { |
| 64 | + if (c != 0) ans = Math.max(ans, i - anchor + 1); |
| 65 | + anchor = i; |
| 66 | + } |
| 67 | + } |
| 68 | + |
| 69 | + return ans; |
| 70 | + } |
| 71 | + |
| 72 | + /** |
| 73 | + * 简单解法:一次遍历,通过多个变量控制循环累加 |
| 74 | + * |
| 75 | + * @param A |
| 76 | + * @return |
| 77 | + */ |
| 78 | + public int maxTurbulenceSize(int[] A) { |
| 79 | + if (A.length <= 1) { |
| 80 | + return A.length; |
| 81 | + } |
| 82 | + int max = 1; |
| 83 | + int subMax = 0; |
| 84 | + boolean isAccumlation = false; |
| 85 | + int preMinus = 0; |
| 86 | + for (int i = 1; i < A.length; i++) { |
| 87 | + int minus = A[i] - A[i - 1]; |
| 88 | + if (minus == 0) { |
| 89 | + max = Math.max(max, subMax); |
| 90 | + isAccumlation = false; |
| 91 | + continue; |
| 92 | + } |
| 93 | + if (!isAccumlation) { |
| 94 | + preMinus = minus; |
| 95 | + subMax = 2; |
| 96 | + isAccumlation = true; |
| 97 | + continue; |
| 98 | + } |
| 99 | + if (preMinus > 0 ^ minus > 0) { |
| 100 | + //替换 |
| 101 | + subMax++; |
| 102 | + preMinus = minus; |
| 103 | + } else { |
| 104 | + //结束,重新计数 |
| 105 | + max = Math.max(max, subMax); |
| 106 | + preMinus = minus; |
| 107 | + subMax = 2; |
| 108 | + } |
| 109 | + } |
| 110 | + max = Math.max(max, subMax); |
| 111 | + |
| 112 | + return max; |
| 113 | + } |
| 114 | +} |
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