Solving Leetcode Interviews in Seconds with AI: Path with Maximum Gold
Introduction
In this blog post, we will explore how to solve the LeetCode problem "1219" 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
In a gold mine grid of size m x n, each cell in this mine has an integer representing the amount of gold in that cell, 0 if it is empty. Return the maximum amount of gold you can collect under the conditions: Every time you are located in a cell you will collect all the gold in that cell. From your position, you can walk one step to the left, right, up, or down. You can't visit the same cell more than once. Never visit a cell with 0 gold. You can start and stop collecting gold from any position in the grid that has some gold. Example 1: Input: grid = [[0,6,0],[5,8,7],[0,9,0]] Output: 24 Explanation: [[0,6,0], [5,8,7], [0,9,0]] Path to get the maximum gold, 9 -> 8 -> 7. Example 2: Input: grid = [[1,0,7],[2,0,6],[3,4,5],[0,3,0],[9,0,20]] Output: 28 Explanation: [[1,0,7], [2,0,6], [3,4,5], [0,3,0], [9,0,20]] Path to get the maximum gold, 1 -> 2 -> 3 -> 4 -> 5 -> 6 -> 7. Constraints: m == grid.length n == grid[i].length 1 <= m, n <= 15 0 <= grid[i][j] <= 100 There are at most 25 cells containing gold.
Explanation
Here's an efficient solution to the gold mine problem, along with an explanation:
- Depth-First Search (DFS): Explore all possible paths from each cell containing gold using DFS.
- Backtracking: Mark cells as visited during a path and unmark them when backtracking to explore alternative paths. This ensures no cell is visited more than once.
Maximization: Keep track of the maximum gold collected so far and update it whenever a new path yields a higher amount.
Runtime Complexity: O(4m*n), where m and n are the dimensions of the grid, as in the worst case, we might explore all possible paths.
- Storage Complexity: O(m*n) due to the recursion depth of DFS, which can be at most the number of cells in the grid.
Code
def getMaximumGold(grid):
"""
Calculates the maximum gold that can be collected from the gold mine grid.
Args:
grid: A 2D list of integers representing the gold mine grid.
Returns:
The maximum amount of gold that can be collected.
"""
rows = len(grid)
cols = len(grid[0])
max_gold = 0
def dfs(row, col, current_gold):
"""
Performs a depth-first search to explore possible paths and collect gold.
Args:
row: The current row index.
col: The current column index.
current_gold: The amount of gold collected so far in the current path.
Returns:
The maximum gold that can be collected starting from the current cell.
"""
nonlocal max_gold # Access the max_gold variable in the outer scope
# Base cases: out of bounds or cell with no gold or already visited
if row < 0 or row >= rows or col < 0 or col >= cols or grid[row][col] == 0:
return current_gold
# Collect the gold and mark the cell as visited
gold = grid[row][col]
grid[row][col] = 0 # Mark as visited
# Explore adjacent cells
max_path_gold = 0
max_path_gold = max(max_path_gold, dfs(row + 1, col, current_gold + gold)) # Down
max_path_gold = max(max_path_gold, dfs(row - 1, col, current_gold + gold)) # Up
max_path_gold = max(max_path_gold, dfs(row, col + 1, current_gold + gold)) # Right
max_path_gold = max(max_path_gold, dfs(row, col - 1, current_gold + gold)) # Left
# Backtrack: restore the original value of the cell
grid[row][col] = gold
return max_path_gold
# Iterate over all cells in the grid and start DFS from cells with gold
for row in range(rows):
for col in range(cols):
if grid[row][col] != 0:
max_gold = max(max_gold, dfs(row, col, 0))
return max_gold