Introduction

In this blog post, we will explore how to solve the LeetCode problem "3229" 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 two positive integer arrays nums and target, of the same length. In a single operation, you can select any subarray of nums and increment each element within that subarray by 1 or decrement each element within that subarray by 1. Return the minimum number of operations required to make nums equal to the array target. Example 1: Input: nums = [3,5,1,2], target = [4,6,2,4] Output: 2 Explanation: We will perform the following operations to make nums equal to target: - Increment nums[0..3] by 1, nums = [4,6,2,3]. - Increment nums[3..3] by 1, nums = [4,6,2,4]. Example 2: Input: nums = [1,3,2], target = [2,1,4] Output: 5 Explanation: We will perform the following operations to make nums equal to target: - Increment nums[0..0] by 1, nums = [2,3,2]. - Decrement nums[1..1] by 1, nums = [2,2,2]. - Decrement nums[1..1] by 1, nums = [2,1,2]. - Increment nums[2..2] by 1, nums = [2,1,3]. - Increment nums[2..2] by 1, nums = [2,1,4]. Constraints: 1 <= nums.length == target.length <= 105 1 <= nums[i], target[i] <= 108

Explanation

Here's a solution to the problem of finding the minimum operations to transform nums into target:

• Calculate Differences: The core idea is to realize that operations on subarrays can be simplified by considering the differences between consecutive elements of the transformed array. The required number of operations is the sum of the absolute differences between corresponding elements in the difference array.

• Compute Absolute Difference Sum: Calculate the absolute difference between each corresponding element in nums and target. Sum these absolute differences to get the result. This avoids tracking subarrays and focuses on the net change required at each position relative to the previous one.

• Runtime Complexity: O(n), where n is the length of the arrays. Storage Complexity: O(1).

Code

    def minOperations(nums, target):
    """
    Calculates the minimum number of operations to transform nums into target.

    Args:
        nums: The source array.
        target: The target array.

    Returns:
        The minimum number of operations.
    """

    n = len(nums)
    operations = abs(nums[0] - target[0])

    for i in range(1, n):
        operations += abs(nums[i] - target[i] - (nums[i-1] - target[i-1]))

    return operations