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I don't think it's the loop implementation. The stuff in the loop should take multiple orders of magnitude more time than the loop itself:

    for poly in polygon_subset:
        if np.linalg.norm(poly.center - point) < max_dist:
            close_polygons.append(poly)


I don’t know if numpy fixed this, but it used to be that mixing Python numbers with numpy in a tight loop is horribly slow. Try hoisting max_dist out of the loop and replacing it with max_dist_np that converts it to a numpy float once.


Speaking of this, I once find that

    for x in numpy.array:
is 9X slower than

    for x in numpy.array.tolist():
in 2021.




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