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Given an m x n integers matrix, return the length of the longest increasing path inmatrix.
From each cell, you can either move in four directions: left, right, up, or down. You may not move diagonally or move outside the boundary (i.e., wrap-around is not allowed).
Example 1:
Input: matrix = [[9,9,4],[6,6,8],[2,1,1]]
Output: 4
Explanation: The longest increasing path is [1, 2, 6, 9].
Example 2:
Input: matrix = [[3,4,5],[3,2,6],[2,2,1]]
Output: 4
Explanation: The longest increasing path is [3, 4, 5, 6]. Moving diagonally is not allowed.
class Solution {
public:
vector<vector<int>> dirs = {{0, -1}, {-1, 0}, {0, 1}, {1, 0}};
int longestIncreasingPath(vector<vector<int>>& matrix) {
if (matrix.empty() || matrix[0].empty()) return 0;
int res = 1, m = matrix.size(), n = matrix[0].size();
vector<vector<int>> dp(m, vector<int>(n, 0));
for (int i = 0; i < m; ++i) {
for (int j = 0; j < n; ++j) {
res = max(res, dfs(matrix, dp, i, j));
}
}
return res;
}
int dfs(vector<vector<int>> &matrix, vector<vector<int>> &dp, int i, int j) {
if (dp[i][j]) return dp[i][j];
int mx = 1, m = matrix.size(), n = matrix[0].size();
for (auto a : dirs) {
int x = i + a[0], y = j + a[1];
if (x < 0 || x >= m || y < 0 || y >= n || matrix[x][y] <= matrix[i][j]) continue;
int len = 1 + dfs(matrix, dp, x, y);
mx = max(mx, len);
}
dp[i][j] = mx;
return mx;
}
};
class Solution {
public:
int longestIncreasingPath(vector<vector<int>>& matrix) {
if (matrix.empty() || matrix[0].empty()) return 0;
int m = matrix.size(), n = matrix[0].size(), res = 1;
vector<vector<int>> dirs{{0,-1},{-1,0},{0,1},{1,0}};
vector<vector<int>> dp(m, vector<int>(n, 0));
for (int i = 0; i < m; ++i) {
for (int j = 0; j < n; ++j ) {
if (dp[i][j] > 0) continue;
queue<pair<int, int>> q{{{i, j}}};
int cnt = 1;
while (!q.empty()) {
++cnt;
int len = q.size();
for (int k = 0; k < len; ++k) {
auto t = q.front(); q.pop();
for (auto dir : dirs) {
int x = t.first + dir[0], y = t.second + dir[1];
if (x < 0 || x >= m || y < 0 || y >= n || matrix[x][y] <= matrix[t.first][t.second] || cnt <= dp[x][y]) continue;
dp[x][y] = cnt;
res = max(res, cnt);
q.push({x, y});
}
}
}
}
}
return res;
}
};
Given an
m x n
integersmatrix
, return the length of the longest increasing path inmatrix
.From each cell, you can either move in four directions: left, right, up, or down. You may not move diagonally or move outside the boundary (i.e., wrap-around is not allowed).
Example 1:
Example 2:
Example 3:
Constraints:
m == matrix.length
n == matrix[i].length
1 <= m, n <= 200
0 <= matrix[i][j] <= 231 - 1
这道题给了一个二维数组,让求矩阵中最长的递增路径,规定只能上下左右行走,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。这里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,当用递归调用时,遇到某个位置 (x, y), 如果 dp[x][y] 不为0的话,直接返回 dp[x][y] 即可,不需要重复计算。这里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:
解法一:
下面再来看一种 BFS 的解法,需要用 queue 来辅助遍历,还是需要dp数组来减少重复运算。遍历数组中的每个数字,跟上面的解法一样,把每个遍历到的点都当作 BFS 遍历的起始点,需要优化的是,如果当前点的 dp 值大于0了,说明当前点已经计算过了,直接跳过。否则就新建一个 queue,然后把当前点的坐标加进去,再用一个变量 cnt,初始化为1,表示当前点为起点的递增长度,然后进入 while 循环,然后 cnt 自增1,这里先自增1没有关系,因为只有当周围有合法的点时候才会用 cnt 来更新。由于当前结点周围四个相邻点距当前点距离都一样,所以采用类似二叉树层序遍历的方式,先出当前 queue 的长度,然后遍历跟长度相同的次数,取出 queue 中的首元素,对周围四个点进行遍历,计算出相邻点的坐标后,要进行合法性检查,横纵坐标不能越界,且相邻点的值要大于当前点的值,并且相邻点的 dp 值要小于 cnt,才有更新的必要。用 cnt 来更新 dp[x][y],并用 cnt 来更新结果 res,然后把相邻点排入 queue 中继续循环即可,参见代码如下:
解法二:
Github 同步地址:
#329
参考资料:
https://leetcode.com/problems/longest-increasing-path-in-a-matrix/
https://leetcode.com/problems/longest-increasing-path-in-a-matrix/discuss/78308/15ms-Concise-Java-Solution
https://leetcode.com/problems/longest-increasing-path-in-a-matrix/discuss/78317/C%2B%2B-DP-DFS-solution-sharing
LeetCode All in One 题目讲解汇总(持续更新中...)
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