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This library provides a robust method for computing the orientation of a tuple of points in n-dimensional space, ensuring exact results even in edge cases where floating-point precision might otherwise fail. It is based on Jonathan Shewchuk's adaptive precision arithmetic predicates and is implemented in JavaScript for use in computational geometry applications. The project is ideal for developers working on geometry algorithms who require reliable orientation tests, such as those involved in mesh processing, collision detection, or geometric modeling.

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mikolalysenko/robust-scale
Multiplies a nonoverlapping increasing sequence of floats by a single float
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mikolalysenko/robust-sum
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mikolalysenko/two-product
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mikolalysenko/robust-subtract
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tape-testing/tape
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mikolalysenko/robust-orientation

Robustly computes the orientation of a tuple of points

JavaScript
29
6
MIT License