A while back, I developed an early freely available implementation of the additively weighted Voronoi Diagram, but I haven’t shared it widely until now. So, better late than never—I’d like to present it here. It’s an algorithm for computing the additively weighted Voronoi Diagram, which extends the classic Voronoi diagram by assigning different influence weights to sites.<p>My approach is quite fast since it leverages triangulation. This makes it efficient for computational geometry, geospatial analysis, and clustering, where sites have varying importance. While my implementation isn’t the most robust, I believe it could still be useful or serve as a starting point for improvements. Would love to hear any feedback or see how others might build on it!<p>Website+git: <a href="https://tetramatrix.github.io/awvd/" rel="nofollow">https://tetramatrix.github.io/awvd/</a>