leetcode1074. Number of Submatrices That Sum to Target
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题目如下:
Given a
matrix
, and atarget
, return the number of non-empty submatrices that sum to target.A submatrix
x1, y1, x2, y2
is the set of all cellsmatrix[x][y]
withx1 <= x <= x2
andy1 <= y <= y2
.Two submatrices
(x1, y1, x2, y2)
and(x1‘, y1‘, x2‘, y2‘)
are different if they have some coordinate that is different: for example, ifx1 != x1‘
.
Example 1:
Input: matrix = [[0,1,0],[1,1,1],[0,1,0]], target = 0 Output: 4 Explanation: The four 1x1 submatrices that only contain 0.
Example 2:
Input: matrix = [[1,-1],[-1,1]], target = 0 Output: 5 Explanation: The two 1x2 submatrices, plus the two 2x1 submatrices, plus the 2x2 submatrix.
Note:
1 <= matrix.length <= 300
1 <= matrix[0].length <= 300
-1000 <= matrix[i] <= 1000
-10^8 <= target <= 10^8
解题思路:暴力计算的方法时间复杂度是O(n^4),而matrix.length最大值是300,应该无法被AC。那O(n^3)可以吗?试试吧。首先引入一个二维数组val_grid , 记var_grid[m][n] 为从0开始到第m行这个区间内第n列的值的和,例如用例1中的输入[[0,1,0],[1,1,1],[0,1,0]],其对应的val_grid为[[0, 1, 0], [1, 2, 1], [1, 3, 1]] 。如果要计算matrix中第j行~第i行区间内有多少满足和等于target的子矩阵,很轻松就可以求出这个子矩阵每一列的和,例如第k的列的和为 val_grid[i][k] - val_grid[j-1][k] (j>0),接下来令k in range(0,len(matrix[0]),依次判断[j~i]每一列的和是否等于target,同时累加并记录从0开始的列和,假设[0~k]累计的列和是sum,只要判断历史的列和中有多少个满足 sum - target,即可求出[j~i]子矩阵里面以k列为右边列的满足条件的子矩阵个数。这样即可将复杂度优化成O(n^3)。
代码如下:
class Solution(object): def numSubmatrixSumTarget(self, matrix, target): """ :type matrix: List[List[int]] :type target: int :rtype: int """ val_grid = [[0 for i in range(len(matrix[0]))] for j in range(len(matrix))] for j in range(len(matrix[0])): amount = 0 for i in range(len(matrix)): amount += matrix[i][j] val_grid[i][j] = amount #print val_grid res = 0 for i in range(len(matrix)): for j in range(i+1): dic = amount = 0 for k in range(len(matrix[i])): v = val_grid[i][k] if j > 0: v -= val_grid[j-1][k] amount += v if amount == target:res += 1 if amount - target in dic: res += dic[amount - target] dic[amount] = dic.setdefault(amount,0) + 1 return res
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