yes, that was my negligence, change type is first thing I usually check... however it has no significant impact on performance...
I've got caught with some different things last days but continuing to play with online methods tm On Wednesday, January 7, 2015 at 7:49:43 PM UTC+1, Stefan Karpinski wrote: > > Try deleting the line where you initially assign to subset – it isn't > necessary and causes that variable to change type over the course of your > loop. > > On Tue, Jan 6, 2015 at 6:50 PM, Tomas Mikoviny <[email protected] > <javascript:>> wrote: > >> Hi Stefan, >> >> you are right. But the moment I try to do this for any subset along the >> array it gets inefficient. >> Here is the simplest code for running median of one dimensional array. >> Time consuming... >> >> function runmed(input::Array, w::Int) >> L = length(input) >> output = zeros(input) >> subset = zeros(w+1) >> for i in 1:L-w >> subset = sub(input, i:i+w) >> output[i] = median!(subset) >> end >> return output >> end >> >> a = zeros(300000); >> >> runmed(a, 200); >> >> @time runmed(a, 200); >> elapsed time: 1.460171594 seconds (43174976 bytes allocated) >> >> >> On Tuesday, January 6, 2015 10:10:39 PM UTC+1, Stefan Karpinski wrote: >>> >>> 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... >>>>>> >>>>>> >>>>> >>> >
