Solving Leetcode Interviews in Seconds with AI: Minimize the Maximum Difference of Pairs
Introduction
In this blog post, we will explore how to solve the LeetCode problem "2616" 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 a 0-indexed integer array nums and an integer p. Find p pairs of indices of nums such that the maximum difference amongst all the pairs is minimized. Also, ensure no index appears more than once amongst the p pairs. Note that for a pair of elements at the index i and j, the difference of this pair is |nums[i] - nums[j]|, where |x| represents the absolute value of x. Return the minimum maximum difference among all p pairs. We define the maximum of an empty set to be zero. Example 1: Input: nums = [10,1,2,7,1,3], p = 2 Output: 1 Explanation: The first pair is formed from the indices 1 and 4, and the second pair is formed from the indices 2 and 5. The maximum difference is max(|nums[1] - nums[4]|, |nums[2] - nums[5]|) = max(0, 1) = 1. Therefore, we return 1. Example 2: Input: nums = [4,2,1,2], p = 1 Output: 0 Explanation: Let the indices 1 and 3 form a pair. The difference of that pair is |2 - 2| = 0, which is the minimum we can attain. Constraints: 1 <= nums.length <= 105 0 <= nums[i] <= 109 0 <= p <= (nums.length)/2
Explanation
Here's the breakdown of the approach, followed by the code:
- Sort the array: Sorting allows us to consider adjacent elements for forming pairs, which is crucial for minimizing the maximum difference.
- Binary Search: We use binary search to find the minimum possible maximum difference. The search space is from 0 to the maximum possible difference between any two numbers in the array.
Greedy Pair Formation: In each binary search iteration, we greedily try to form
ppairs with a maximum difference no greater than the current mid-value.Runtime Complexity: O(n log n) due to sorting and binary search. Storage Complexity: O(1) excluding the space used to store the input and sorted array.
Code
def minimizeMax(nums, p):
"""
Finds the minimum maximum difference among p pairs in the given array.
Args:
nums: A list of integers.
p: The number of pairs to form.
Returns:
The minimum maximum difference among all p pairs.
"""
nums.sort()
n = len(nums)
def count_pairs(max_diff):
"""
Counts how many pairs can be formed with a maximum difference no greater than max_diff.
"""
count = 0
i = 0
while i < n - 1 and count < p:
if nums[i+1] - nums[i] <= max_diff:
count += 1
i += 2
else:
i += 1
return count
left = 0
right = nums[-1] - nums[0]
ans = right
while left <= right:
mid = (left + right) // 2
if count_pairs(mid) >= p:
ans = mid
right = mid - 1
else:
left = mid + 1
return ans