You are given a array points representing integer coordinates of some points on a 2D plane, where points[i] = [xi, yi].
The distance between two points is defined as their Manhattan distance.
\n\nReturn the minimum possible value for maximum distance between any two points by removing exactly one point.
\n\n\n
Example 1:
\n\nInput: points = [[3,10],[5,15],[10,2],[4,4]]
\n\nOutput: 12
\n\nExplanation:
\n\nThe maximum distance after removing each point is the following:
\n\n|5 - 10| + |15 - 2| = 18.|3 - 10| + |10 - 2| = 15.|5 - 4| + |15 - 4| = 12.|5 - 10| + |15 - 2| = 18.12 is the minimum possible maximum distance between any two points after removing exactly one point.
\nExample 2:
\n\nInput: points = [[1,1],[1,1],[1,1]]
\n\nOutput: 0
\n\nExplanation:
\n\nRemoving any of the points results in the maximum distance between any two points of 0.
\n\n
Constraints:
\n\n3 <= points.length <= 105points[i].length == 21 <= points[i][0], points[i][1] <= 108[xi, yi] and [xj, yj] is max({xi - xj + yi - yj, xi - xj - yi + yj, - xi + xj + yi - yj, - xi + xj - yi + yj}).",
"If you replace points as [xi - yi, xi + yi] then the Manhattan distance is max(max(xi) - min(xi), max(yi) - min(yi)) over all i.",
"After those observations, the problem just becomes a simulation. Create multiset of points [xi - yi, xi + yi], you can iterate on a point you might remove and get the maximum Manhattan distance over all other points."
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