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lmas / opensimplex

This repo has been migrated to https://code.larus.se/lmas/opensimplex
MIT License
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Faster code execution with Numba and Numpy #13

Closed diegocaro closed 4 years ago

diegocaro commented 4 years ago

Hi all, I have been playing with drawing from noise using opensimplex. Sadly, is too slow if you want to compute a large picture, or a long animation. Here I propose a patch to use the Numba jit and numpy. There are few lines changed and the improvement is very promising with a 75% speed improvement (from ~270msec to ~68msec in the benchmark below).

Old code benchmark:

PYTHONPATH=opensimplex/ python3 -m timeit 'from opensimplex import OpenSimplex; s=OpenSimplex(seed=0); [s.noise2d(0.1, 0.1) for n in range(100000)]' 1 loop, best of 5: 278 msec per loop

Patched code benchmark:

PYTHONPATH=opensimplex/ python3 -m timeit 'from opensimplex import OpenSimplex; s=OpenSimplex(seed=0); [s.noise2d(0.1, 0.1) for n in range(100000)]' 1 loop, best of 5: 68.7 msec per loop

Cheers from Chile!

lmas commented 4 years ago

Hello and thanks for your request!

Appreciate your work but unfortunately I'll have to say no, just as I've said before to others. Please see the open issue #4