Which Python Library Offers the Fastest Point-in-Polygon Check?

Matplotlib's Efficient Point-in-Polygon Checking

In Python, there are various methods for determining whether a point resides within a polygon. Two popular options are ray tracing and Matplotlib's contains_points function.

Evaluating the Options

After comparing the two methods, the performance analysis revealed that Matplotlib's contains_points function significantly outperforms ray tracing. The experiment demonstrates that contains_points takes a fraction of the time to process a large number of points.

Considering Shapely

For specific geometric operations, you may consider using the Shapely library. It provides comprehensive functionality for handling polygons and other geometric shapes. However, it's worth noting that Shapely may be slower than Matplotlib's contains_points for simple point-in-polygon checks.

Creating a Precomputed Boolean Grid

In certain scenarios, where precision is less critical, precomputing a boolean grid can be a time-efficient solution. By creating a grid that indicates which points lie within the polygon, you can quickly check a large number of points without the need for repetitive calculations.

Conclusion

For efficient point-in-polygon checking in Python, Matplotlib's contains_points function is highly recommended. Its superior performance makes it well-suited for applications involving a large number of points and polygons. However, if precision is a paramount concern, alternative methods such as Shapely or the ray tracing algorithm should be considered.

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