jfpuget

8 ms·

31.
Python Performance Matches Julia's(ibm.com)
2 points by jfpuget 11y ago|0 comments
32.
by jfpuget 11y ago
And you lose python interactivity. If I have to compile code then I use C or C++ directly.
33.
by jfpuget 11y ago
Agreed.
34.
by jfpuget 11y ago
I didn't use C. Read again ;) Pypy was not an option either, details in the post now.
35.
by jfpuget 11y ago
I did it. It runs way faster than the loop, but it runs about 4x slower than my approximation. Details in the post. Thanks for suggesting that.
36.
by jfpuget 11y ago
Raw longitude is by far the largest approximation. It becomes really flawed near poles. But all my points are in mainland USA, and there we're pretty safe. Anyway, I did say that I was using an approximation.
37.
by jfpuget 11y ago
I agree it is well known. I am just providing yet another example. I contemplated quad trees but the performance of these 2 lines of code was good enough. Why would I bother writing something more complex? you'd be surprised by my ma
38.
by jfpuget 11y ago
You should reread the post to find the acknowledgement that was there since the begining: ' ignoring the fact that 1 degree difference in latitude yields a larger distance than 1 degree difference in longitude'
39.
by jfpuget 11y ago
You missed the point: I did not had to change data structure to get the speedup.
40.
by jfpuget 11y ago
I tried numba. It isn't helping here. Yes, I used @jit(nopython=True). It does not compile pandas code.
41.
by jfpuget 11y ago
It is simple indeed. The performance I got was good enough to spare me the effort of using quad trees. Yes, I know what quad trees are. I even coded octrees for 3D reasoning in a previous life ;)
42.
by jfpuget 12y ago
Revenue tax (impot sur le revenu) is also much higher in the US unless your salary is really high in France.
43.
NP Or Not NP? That Is The Question (ibm.com)
1 points by jfpuget 14y ago|0 comments