Follow up for "Unique Paths":
Now consider if some obstacles are added to the grids. How many unique paths would there be?
An obstacle and empty space is marked as
1
and 0
respectively in the grid.
For example,
There is one obstacle in the middle of a 3x3 grid as illustrated below.
[ [0,0,0], [0,1,0], [0,0,0] ]
The total number of unique paths is
2
.
Note: m and n will be at most 100.
Solution:
想法跟Unique Path是一样的, 只是要单独考虑下障碍物对整个棋盘的影响。
先看看初始条件会不会受到障碍物的影响。
假设整个棋盘只有一行,那么在第i个位置上设置一个障碍物后,说明位置i到最后一个格子这些路都没法走了。
如果整个棋盘只有一列,那么第i位置上的障碍物,也会影响从第i位置往后的路。
所以说明,在初始条件时,如果一旦遇到障碍物,障碍物后面所有格子的走法都是0。
再看求解过程,当然按照上一题的分析dp[i][j] = dp[i-1][j] + dp[i][j-1] 的递推式依然成立(机器人只能向下或者向右走嘛)。但是,一旦碰到了障碍物,那么这时的到这里的走法应该设为0,因为机器人只能向下走或者向右走,所以到这个点就无法通过。
一维数组解法:
每次判断一下是不是障碍,如果是障碍,则res[i][j]=0,否则还是res[i][j]=res[i-1][j]+res[i][j-1]。
实现中还是只需要一个一维数组,因为更新的时候所需要的信息足够了。这样时间复杂度是O(m*n), 空间复杂度是是O(n)。
public class Solution { public int uniquePathsWithObstacles(int[][] obstacleGrid) { int m = obstacleGrid.length; int n = obstacleGrid[0].length; if(obstacleGrid == null || m <= 0 || n <= 0) return 0; int[] res = new int[n]; res[0] = 1; for(int i = 0; i < m; i++) { for(int j = 0; j < n; j++) { if(obstacleGrid[i][j] == 1) { res[j] = 0; }else { if(j > 0) res[j] += res[j - 1]; } } } return res[n - 1]; } }二维数组解法:
public class Solution { public int uniquePathsWithObstacles(int[][] obstacleGrid) { int m = obstacleGrid.length; int n = obstacleGrid[0].length; if(m == 0 || n == 0) return 0; if(obstacleGrid[0][0] == 1 || obstacleGrid[m - 1][n - 1] == 1) return 0; int[][] dp = new int[m][n]; dp[0][0] = 1; for(int i = 1; i < n; i++) { if(obstacleGrid[0][i] == 1) dp[0][i] = 0; else dp[0][i] = dp[0][i - 1]; } for(int i = 1; i < m; i++) { if(obstacleGrid[i][0] == 1) dp[i][0] = 0; else dp[i][0] = dp[i - 1][0]; } for(int i = 1; i < m; i++) { for(int j = 1; j < n; j++) { if(obstacleGrid[i][j] == 1) dp[i][j] = 0; else dp[i][j] = dp[i - 1][j] + dp[i][j - 1]; } } return dp[m - 1][n - 1]; } }
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