On 1/16/2023 1:18 PM, Edmondo Giovannozzi wrote:
As a comparison with numpy. Given the following lines: import numpy as np a = np.random.randn(400,100_000) ia = np.argsort(a[0,:]) a_elem = a[56, ia[0]] I have just taken an element randomly in a numeric table of 400x100000 elements To find it with numpy: %timeit isel = a == a_elem 35.5 ms ± 2.79 ms per loop (mean ± std. dev. of 7 runs, 10 loops each) And %timeit a[isel] 9.18 ms ± 371 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) As data are not ordered it is searching it one by one but at C level. Of course it depends on a lot of thing...
thank you for this. It's probably my lack of experience with Numpy, but... can you explain what is going on here in more detail?
Thank you Dino -- https://mail.python.org/mailman/listinfo/python-list
