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https://issues.apache.org/jira/browse/MATH-749?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13892622#comment-13892622
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Thomas Neidhart commented on MATH-749:
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Added so far the following algorithms:
* GrahamScan (most known)
* MonotoneChain (good for pre-sorted points)
* GiftWrap (used within Chan's algorithm)
I plan to complete this issue with the implementation of Chan's algorithm which
is a optimal output-sensitive algorithm with complexity of O(n log h).
All algorithms are implemented with special care for identical and collinear
points and there exist several test cases to ensure this.
> Convex Hull algorithm
> ---------------------
>
> Key: MATH-749
> URL: https://issues.apache.org/jira/browse/MATH-749
> Project: Commons Math
> Issue Type: Sub-task
> Reporter: Thomas Neidhart
> Assignee: Thomas Neidhart
> Priority: Minor
> Labels: 2d, geometric
> Attachments: MATH-749.tar.gz
>
>
> It would be nice to have convex hull implementations for 2D/3D space. There
> are several known algorithms
> [http://en.wikipedia.org/wiki/Convex_hull_algorithms]:
> * Graham scan: O(n log n)
> * Incremental: O(n log n)
> * Divide and Conquer: O(n log n)
> * Kirkpatrick-Seidel: O(n log h)
> * Chan: O(n log h)
> The preference would be on an algorithm that is easily extensible for higher
> dimensions, so *Incremental* and *Divide and Conquer* would be prefered.
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