{ "data": { "question": { "questionId": "3344", "questionFrontendId": "3102", "categoryTitle": "Algorithms", "boundTopicId": 2673010, "title": "Minimize Manhattan Distances", "titleSlug": "minimize-manhattan-distances", "content": "
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 <= 105
points[i].length == 2
1 <= points[i][0], points[i][1] <= 108
给你一个下标从 0 开始的数组 points
,它表示二维平面上一些点的整数坐标,其中 points[i] = [xi, yi]
。
两点之间的距离定义为它们的曼哈顿距离。
\n\n请你恰好移除一个点,返回移除后任意两点之间的 最大 距离可能的 最小 值。
\n\n\n\n
示例 1:
\n\n\n输入:points = [[3,10],[5,15],[10,2],[4,4]]\n输出:12\n解释:移除每个点后的最大距离如下所示:\n- 移除第 0 个点后,最大距离在点 (5, 15) 和 (10, 2) 之间,为 |5 - 10| + |15 - 2| = 18 。\n- 移除第 1 个点后,最大距离在点 (3, 10) 和 (10, 2) 之间,为 |3 - 10| + |10 - 2| = 15 。\n- 移除第 2 个点后,最大距离在点 (5, 15) 和 (4, 4) 之间,为 |5 - 4| + |15 - 4| = 12 。\n- 移除第 3 个点后,最大距离在点 (5, 15) 和 (10, 2) 之间的,为 |5 - 10| + |15 - 2| = 18 。\n在恰好移除一个点后,任意两点之间的最大距离可能的最小值是 12 。\n\n\n
示例 2:
\n\n\n输入:points = [[1,1],[1,1],[1,1]]\n输出:0\n解释:移除任一点后,任意两点之间的最大距离都是 0 。\n\n\n
\n\n
提示:
\n\n3 <= points.length <= 105
points[i].length == 2
1 <= 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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"status": null,
"sampleTestCase": "[[3,10],[5,15],[10,2],[4,4]]",
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