You may not need online methods at all. Sorting the rows of a 200 x 300000 matrix doesn't take very long on my laptop:
julia> X = randn(200,300000); julia> @time X = sortrows(X); elapsed time: 0.297998739 seconds (480053384 bytes allocated) On Tue, Jan 6, 2015 at 2:33 PM, Tomas Mikoviny <[email protected]> wrote: > Hi Kevin, > > generally I'm trying to do baseline correction on mass spectra with > ~300000 bins. I've tried several algorithms to evaluate baseline but the > ones working the best implement running median and mean. I've just got mean > sorted out via cumsum trick in coincidence with Tim's suggestion (found > some MATLAB discussion on that). Although I'll check Tamas' suggestion too. > > I've got stacked with running median that would have reasonable > performance since computer has to crunch runmed of array of 200 x 300000 > within couple of seconds (max) to manage online analysis. > > On Tuesday, January 6, 2015 6:18:02 PM UTC+1, Kevin Squire wrote: >> >> Hi Tomas, >> I'm bit aware of any (though they might exist). It might help if you gave >> a little more context--what kind of data are you working with? >> >> Cheers, >> Kevin >> >> On Tuesday, January 6, 2015, Tomas Mikoviny <[email protected]> wrote: >> >>> Hi, >>> I was just wondering if anyone knows if there is a package that >>> implements *fast* running median/mean algorithms? >>> >>> Thanks a lot... >>> >>> >>
