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]
> <javascript:>> 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...
>>>>
>>>>
>>>
>
