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Solving Leetcode Interviews in Seconds with AI: Diagonal Traverse II

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2 min read

Introduction

In this blog post, we will explore how to solve the LeetCode problem "1424" 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

Given a 2D integer array nums, return all elements of nums in diagonal order as shown in the below images. Example 1: Input: nums = [[1,2,3],[4,5,6],[7,8,9]] Output: [1,4,2,7,5,3,8,6,9] Example 2: Input: nums = [[1,2,3,4,5],[6,7],[8],[9,10,11],[12,13,14,15,16]] Output: [1,6,2,8,7,3,9,4,12,10,5,13,11,14,15,16] Constraints: 1 <= nums.length <= 105 1 <= nums[i].length <= 105 1 <= sum(nums[i].length) <= 105 1 <= nums[i][j] <= 105

Explanation

Here's a breakdown of the approach, complexity analysis, and the Python code:

  • High-Level Approach:

    • Group elements based on their diagonal index (row + col). Elements with the same sum belong to the same diagonal.
    • Iterate through the diagonals. For each diagonal, traverse the elements in reverse order (from bottom to top) as per the diagonal traversal requirement.
    • Combine the elements from all diagonals to form the final output.
  • Complexity:

    • Runtime Complexity: O(N), where N is the total number of elements in the input array.
    • Storage Complexity: O(N), to store the diagonal groups and the final output array.

Code

    def diagonalOrder(nums):
    """
    Traverses a 2D array in diagonal order.

    Args:
        nums: A 2D list of integers.

    Returns:
        A list of integers representing the diagonal order traversal of nums.
    """

    diagonals = {}
    for row in range(len(nums)):
        for col in range(len(nums[row])):
            diagonal_index = row + col
            if diagonal_index not in diagonals:
                diagonals[diagonal_index] = []
            diagonals[diagonal_index].append(nums[row][col])

    result = []
    diagonal_keys = sorted(diagonals.keys())  # Ensure diagonals are processed in the correct order

    for key in diagonal_keys:
        result.extend(reversed(diagonals[key]))  # Reverse to get correct diagonal order

    return result

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