【leetcode】221. Maximal Square

题目:
Given a 2D binary matrix filled with 0’s and 1’s, find the largest square containing only 1’s and return its area.


思路:
动态规划。公式为:dp[i][j] = min(dp[i-1][j], dp[i][j-1], dp[i-1][j-1]) + 1。dp数组的首行或首列与matrix相同。dp[i][j]意思是以(i,j)为右下角的最大正方形的边长。

举个例子说明dp[i][j]的求解过程(即动态规划公式)。例如,dp[i][j]从1升3的所有情况如下:
在这里插入图片描述
Example中的dp数组值如下:
在这里插入图片描述


代码实现:

class Solution {
public:
    int min(int a, int b, int c){
        int t = INT_MAX;
        if (a < t){
            t = a;
        }
        if (b < t){
            t = b;
        }
        if (c < t){
            t = c;
        }
        
        return t;
    }
    int maximalSquare(vector<vector<char>>& matrix) {
        if (matrix.size() <= 0 || matrix[0].size() <= 0){
            return 0;
        }
        
        int rows = matrix.size();
        int cols = matrix[0].size();
        vector<vector<int>> dp(rows, vector<int>(cols, 0));
        int ret = INT_MIN;
        
        for (int i = 0; i < rows; ++i){
            for (int j = 0; j < cols; ++j){
                if (i == 0 || j == 0 || matrix[i][j] == '0'){
                    dp[i][j] = matrix[i][j] - '0';
                }else{
                    dp[i][j] = min(dp[i-1][j], dp[i][j-1], dp[i-1][j-1]) + 1;
                }
                
                ret = max(ret, dp[i][j]);
            }
        }
        
        return ret*ret;
    }
};

参考:
https://www.cnblogs.com/grandyang/p/4550604.html

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转载自blog.csdn.net/zxc120389574/article/details/106087305