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Slides by: Arjun Dasgupta BINARY PLANAR PARTITION Lecture 2 Advanced Algorithms II Slides by: Arjun Dasgupta
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Example 1 l1 l212l334 1 2 3 4 l1 l2 l3 Each oval node stores information about the infinite line l i The leaves denote the line segments being partitioned
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Example 2 1 2 3 4 L1L2 1 L3 34 L4 4 L5 32 l1 l2 l3 l4 l5 Smallest Tree that can be created from the partitions is O(n)
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Auto-Partition Algorithm Index(u, v) = # of cuts that u makes when extended to v Algorithm: Input: S = {S 1,S 2, …. S n } 1.Generate a random permutation of S U = {u 1,u 2,…..u n } 2.Start constructing the tree by using the segments in this order as partitioning lines Upper Bound of the size of tree created by Auto-Partition -> O(n)
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Analysis Our objective is to calculate ∑ n i=1 ∑ n j≠i,j=1 Prob(i cuts j) Now, ∑ n j≠i Prob(i cuts j) ≤ (1/2 + 1/3 + …..) ≤ 2 ln n And, ∑ n i=1 ∑ n j≠i,j=1 Prob(i cuts j) ≤ 2 n ln n Thus, E[# of cuts] ≤ 2 n ln n and, E[Tree Size] = O(nlogn)
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