Certainly do file an issue with an easy to produce test case. I am pretty sure we have not paid much attention to sortrows, and there is room for improvement.
-viral On Sunday, January 18, 2015 at 5:30:38 PM UTC+5:30, Tim Holy wrote: > > If you can reduce this to a standalone, runnable test case that uses only > code > from Base, it would be helpful to file an issue. > > --Tim > > On Saturday, January 17, 2015 05:36:36 PM Arch Call wrote: > > Give alg=MergeSort a whirl. The doc says this is slower than > alg=QuickSort > > for numeric arrays, but who knows until you try. > > > > On Saturday, January 17, 2015 at 4:57:20 PM UTC-5, Petr Krysl wrote: > > > Hi guys, > > > > > > This one has me scratching my head. > > > > > > Matlab code: > > > > > > function Out =myunique(A) > > > > > > sA=sort(A,2); > > > [sA,rix] = sortrows(sA);; > > > d=sA(1:end-1,:)~=sA(2:end,:); > > > ad=[true; any(d,2)]; > > > iu =find((ad&[ad(2:end);true])==true); > > > Out =A(rix(iu),:); > > > > > > end > > > > > > was rewritten in Julia. Since some of the functionality is different > (or > > > slower) as written, I had to rewrite a bit. The surprise was that > even > > > after the rewrite the Julia code runs in around 24 seconds whereas the > > > Matlab code gets it done in two seconds. As I went poking around to > find > > > what is slow, I found that 95% of the time were spent in the sort() > and > > > sortrrows() functions. > > > > > > Any idea of what could cause this slowness? By the way, @code_warntype > > > gives the code a clean bill... So are those two functions somehow slow > by > > > themselves? > > > > > > The Julia version of this is posted at > > > https://gist.github.com/PetrKryslUCSD/cde67dfa0f1b0a1f98ac > > > > > > Thanks, > > > > > > Petr > >
