[_glass]

Isn't this the version of refenced on the github repo [0] which speeds up 6x instead of 101x?

  There's also a "v1.5" version which is 6x faster, and uses "vectorizing" (doing more of the work directly in numpy). This version is much harder to optimize further.

[0] https://github.com/ohadravid/poly-match

[brahbrah]

No, their v1.5 is still calling norm on every polygon. They’re still using it wrong

On Google colab

    import numpy as np
    import time


    vals = np.random.randn(1000000, 2)
    point = np.array([.2, .3])
    s = time.time()
    for x in vals:
        np.linalg.norm(x - point) < 3
    a = time.time() - s

    s = time.time()
    np.linalg.norm(vals - point, axis=1) < 3
    b = time.time() - s

    print(a / b)

~296x faster, significantly faster than the solution in the article.