Solution: Minimize Manhattan Distances
Explore how to minimize the maximum Manhattan distance between any two points in a 2D plane by removing exactly one point. Understand the use of sums and differences of coordinates to identify extreme values and learn to efficiently evaluate candidate points for removal to achieve optimal results.
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Statement
You are given an array, points, where each element in points[i]
Your task is to determine and return the smallest possible value for the maximum distance between any two points after removing exactly one point from the array.
Constraints:
points.lengthpoints[i].lengthpoints[i][0], points[i][1]
Solution
This solution calculates the minimum possible maximum Manhattan distance between any two points by analyzing the properties of the Manhattan metric in a 2D coordinate plane. The essence of the solution lies in observing that the sums and differences of the coordinates determine the Manhattan distance. By focusing on the extreme values of these sums and differences, we can identify the optimal point to remove to minimize the maximum distance.
Intuition:
The Manhattan distance between two points