Iain Dunning wrote: > > Updated gist for the doubly-even order case > https://gist.github.com/IainNZ/9b5f1eb1bcf923ed02d9 > Nice, thanks for your answers, hints and especially to Iain, thanks for your example code. For doubly even numbers it indeed beats Matlab:
*N=3..999, odd numbers only:* Iain's version: elapsed time: 3.570507583 seconds (1333360560 bytes allocated, 7.64% gc time) Matlab: Elapsed time is 3.026155 seconds. Python: 1 loops, best of 3: 875 ms per loop *N=4..1000, doubly even numbers only:* Iain's version: elapsed time: 0.35992636 seconds (670684544 bytes allocated, 38.27% gc time) Matlab: Elapsed time is 0.961886 seconds. Python: 1 loops, best of 3: 263 ms per loop Still, Python (Numpy and cPython, not pypy) clearly performs better for odd numbers. I'll look further into that and appreciate any further suggestions to improve speed ;) I tried to implement a fast version for the non-doubly even numbers at https://gist.github.com/phillipberndt/7dc0aed7eb855f900f0d/8611596eebac1291a6e5869242c880fa790d4e1c with these results: *N=6..998, non-doubly even numbers only* My new version: elapsed time: 0.988820401 seconds (833368960 bytes allocated, 16.78% gc time) Matlab: Elapsed time is 0.933938 seconds. Python: 1 loops, best of 3: 503 ms per loop Did I miss any obvious optimizations in the latter version? Since you've tested your code with N=10,000, I thought that a comparison with large N might also be interesting. For N=9,980..10,000, the latest version gives Iain's & my non-doubly even version: elapsed time: 24.108401104 seconds (17764425968 bytes allocated, 1.12% gc time) Matlab: Elapsed time is 32.327293 seconds. Python: 1 loops, best of 3: 9.52 s per loop Clearly beats Matlab, but Python's still far ahead. - Phillip