3 ms·

You made this assertion multiple times, but so far it’s been entirely unsupported in fact, despite TFA having made the entire code set available for you to test

• deleted 4y ago
  [deleted]
• brahbrah 4y ago
  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. And my assertion was supported by nearly 20 years of numpy being a leading tool in various quantitative fields. It’s not hard to imagine that a ubiquitous tool that’s been used and optimized for almost 20 years is actually pretty good if used properly.
  • akasakahakada 4y ago
    Finally some dude knows how to use numpy properly. I wish I can upvote 5 times. I basically raise the same question somewhere below and got downvoted LOL.
• akasakahakada 4y ago
  [flagged]