On Sun, Feb 16, 2014 at 6:12 PM, Daπid <davidmen...@gmail.com> wrote: > On 16 February 2014 23:43, <josef.p...@gmail.com> wrote: >> >> What's the fastest argsort for a 1d array with around 28 Million >> elements, roughly uniformly distributed, random order? > > > On numpy latest version: > > for kind in ['quicksort', 'mergesort', 'heapsort']: > print kind > %timeit np.sort(data, kind=kind) > %timeit np.argsort(data, kind=kind) > > > quicksort > 1 loops, best of 3: 3.55 s per loop > 1 loops, best of 3: 10.3 s per loop > mergesort > 1 loops, best of 3: 4.84 s per loop > 1 loops, best of 3: 9.49 s per loop > heapsort > 1 loops, best of 3: 12.1 s per loop > 1 loops, best of 3: 39.3 s per loop > > > It looks quicksort is quicker sorting, but mergesort is marginally faster > sorting args. The diference is slim, but upon repetition, it remains > significant. > > Why is that? Probably part of the reason is what Eelco said, and part is > that in sort comparison are done accessing the array elements directly, but > in argsort you have to index the array, introducing some overhead.
Thanks, both. I also gain a second with mergesort. matlab would be nicer in my case, it returns both. I still need to use the argsort to index into the array to also get the sorted array. Josef > > I seem unable to find the code for ndarray.sort, so I can't check. I have > tried to grep it tring all possible combinations of "def ndarray", > "self.sort", etc. Where is it? > > > /David. > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
