Leetcode1218 最长定差子序列 哈希表优化DP
一道中规中矩的 DP 题目,但因为问题空间较大,需要做一些优化。
分治法:
int an = 0; public final int longestSubsequence(int[] arr, int difference) { if (arr.length == 0) { return 0; } longestSubsequence(arr, difference, 0, new int[arr.length]); return an + 1; } /** * @Author Niuxy * @Date 2020/7/15 9:47 上午 * @Description G(point) 表示以 arr[point] 为头元素的最长定差子序列的长度 */ public final int longestSubsequence(int[] arr, int difference, int point, int[] cache) { if (point == arr.length - 1) { return 0; } if (cache[point] != 0) { return cache[point]; } int an = 0; for (int i = point + 1; i < arr.length; i++) { int currentDiff = arr[i] - arr[point]; int next = longestSubsequence(arr, difference, i, cache); if (currentDiff != difference) { continue; } an = Math.max(an, 1 + next); } cache[point] = an; this.an = Math.max(an, this.an); return an; }
转为 DP :
public final int longestSubsequenceDP0(int[] arr, int difference) { if (arr.length == 0) { return 0; } int[] dp = new int[arr.length]; int an = 0; for (int i = arr.length - 2; i >= 0; i--) { int temp = 0; for (int j = i + 1; j < arr.length; j++) { int currentDiff = arr[j] - arr[i]; if (currentDiff != difference) { continue; } temp = Math.max(temp, dp[j] + 1); } dp[i] = temp; an = Math.max(an, temp); } return an+1; }
分治转为 DP 后依然超时,要么需要重新定义状态转移方程,要么需要剪枝。
内部的 for 循环是为了寻找定差的下一个元素,其实有了基准值和差值,完全可以通过哈希表替代循环。使用哈希表优化:
public final int longestSubsequenceDP1(int[] arr, int difference) { Map<Integer, Integer> dp = new HashMap<Integer, Integer>(); dp.put(arr[arr.length-1],1); int an = 0; for (int i = arr.length - 2; i >= 0; i--) { int pre = 1; int key=arr[i]+difference; if(dp.containsKey(key)){pre=dp.get(key)+1;} dp.put(arr[i], pre); an = Math.max(an, pre); } return an; }
当你看清人们的真相,于是你知道了,你可以忍受孤独