Given an integer matrix, find the length of the longest increasing path. From each cell, you can either move to four directions: left, right, up or down. You may NOT move diagonally or move outside of the boundary (i.e. wrap-around is not allowed). Example 1: nums = [ [9,9,4], [6,6,8], [2,1,1] ] Return 4 The longest increasing path is [1, 2, 6, 9]. Example 2: nums = [ [3,4,5], [3,2,6], [2,2,1] ] Return 4 The longest increasing path is [3, 4, 5, 6]. Moving diagonally is not allowed. Credits: Special thanks to @dietpepsi for adding this problem and creating all test cases.
这道题给我们一个二维数组,让我们求矩阵中最长的递增路径,规定我们只能上下左右行走,不能走斜线或者是超过了边界。那么这道题的解法要用递归和DP来解,用DP的原因是为了提高效率,避免重复运算。我们需要维护一个二维动态数组dp,其中dp[i][j]表示数组中以(i,j)为起点的最长递增路径的长度,初始将dp数组都赋为0,当我们用递归调用时,遇到某个位置(x, y), 如果dp[x][y]不为0的话,我们直接返回dp[x][y]即可,不需要重复计算。我们需要以数组中每个位置都为起点调用递归来做,比较找出最大值。在以一个位置为起点用DFS搜索时,对其四个相邻位置进行判断,如果相邻位置的值大于上一个位置,则对相邻位置继续调用递归,并更新一个最大值,搜素完成后返回即可,参见代码如下:
public class Solution { int[][] dp; int[][] directions = new int[][]{{-1,0},{1,0},{0,-1},{0,1}}; int m; int n; public int longestIncreasingPath(int[][] matrix) { if (matrix==null || matrix.length==0 || matrix[0].length==0) return 0; m = matrix.length; n = matrix[0].length; dp = new int[m][n]; int result = 0; for (int i=0; i<m; i++) { for (int j=0; j<n; j++) { if (dp[i][j] == 0) dp[i][j] = DFS(i, j, matrix); result = Math.max(result, dp[i][j]); } } return result; } public int DFS(int i, int j, int[][] matrix) { if (dp[i][j] != 0) return dp[i][j]; dp[i][j] = 1; for (int[] dir : directions) { int x = i + dir[0]; int y = j + dir[1]; if (x<0 || y<0 || x>=m || y>=n || matrix[x][y]<=matrix[i][j]) continue; dp[i][j] = Math.max(dp[i][j], DFS(x, y, matrix)+1); } return dp[i][j]; } }
矩阵常用的记忆化搜索, 返回值为基本数据类型
不要怀疑dfs的能力, 人家会一直递归再回溯给上一层正确的返回值