Solving Leetcode Interviews in Seconds with AI: Largest Local Values in a Matrix
Introduction
In this blog post, we will explore how to solve the LeetCode problem "2373" using AI. LeetCode is a popular platform for preparing for coding interviews, and with the help of AI tools like Chatmagic, we can generate solutions quickly and efficiently - helping you pass the interviews and get the job offer without having to study for months.
Problem Statement
You are given an n x n integer matrix grid. Generate an integer matrix maxLocal of size (n - 2) x (n - 2) such that: maxLocal[i][j] is equal to the largest value of the 3 x 3 matrix in grid centered around row i + 1 and column j + 1. In other words, we want to find the largest value in every contiguous 3 x 3 matrix in grid. Return the generated matrix. Example 1: Input: grid = [[9,9,8,1],[5,6,2,6],[8,2,6,4],[6,2,2,2]] Output: [[9,9],[8,6]] Explanation: The diagram above shows the original matrix and the generated matrix. Notice that each value in the generated matrix corresponds to the largest value of a contiguous 3 x 3 matrix in grid. Example 2: Input: grid = [[1,1,1,1,1],[1,1,1,1,1],[1,1,2,1,1],[1,1,1,1,1],[1,1,1,1,1]] Output: [[2,2,2],[2,2,2],[2,2,2]] Explanation: Notice that the 2 is contained within every contiguous 3 x 3 matrix in grid. Constraints: n == grid.length == grid[i].length 3 <= n <= 100 1 <= grid[i][j] <= 100
Explanation
Here's a solution to the problem, along with explanations:
High-Level Approach:
- Iterate through the
gridmatrix, focusing on the cells that can be the center of a 3x3 submatrix. This means the row and column indices will range from 1 ton - 2. - For each such center cell
(i, j), find the maximum value within the 3x3 submatrix centered at(i, j). - Store this maximum value in the corresponding position
(i - 1, j - 1)of themaxLocalmatrix.
- Iterate through the
Complexity Analysis:
- Runtime: O(n2), where n is the dimension of the grid. We iterate through a (n-2)x(n-2) subgrid and then iterate through a 3x3 grid, both being constant factor of n2.
- Storage: O(n2) because the
maxLocalmatrix has a size of (n-2) x (n-2), which is proportional to n2.
Code
def largestLocal(grid: list[list[int]]) -> list[list[int]]:
n = len(grid)
max_local = [[0] * (n - 2) for _ in range(n - 2)]
for i in range(1, n - 1):
for j in range(1, n - 1):
max_val = 0
for x in range(i - 1, i + 2):
for y in range(j - 1, j + 2):
max_val = max(max_val, grid[x][y])
max_local[i - 1][j - 1] = max_val
return max_local