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Re: I would like to average the first n columns based on duplicate values of the n+1th column [message #93710 is a reply to message #93709] Tue, 04 October 2016 04:23 Go to previous messageGo to previous message
belkaraza is currently offline  belkaraza
Messages: 6
Registered: June 2016
Junior Member
Am Dienstag, 4. Oktober 2016 13:17:24 UTC+2 schrieb belk...@web.de:
> Am Dienstag, 4. Oktober 2016 12:32:48 UTC+2 schrieb Markus Schmassmann:
>> On 10/03/2016 11:05 PM, belkaraza@web.de wrote:
>>> Can Someone help me solve this problem in IDL:
>>> "I have a matrix with duplicate numbers in one of the columns. I
>>> would
>>> like to average the rows with duplicate numbers. For example, I have
>>> duplicate values in a matrix A in column 3:
>>> A =
>>> 1 2 1
>>> 4 4 2
>>> 5 4 2
>>> 4 5 2
>>> 5 5 3
>>> 10 3 3
>>>
>>>
>>> B =
>>> 1 2 1
>>> 4.3333 4.3333 2.0000
>>> 7.5000 4.0000 3.0000
>>>
>>> where each row is the average values of the duplicate rows of column 3.
>>>
>>> Can anyone help?"
>>>
>>> found here:
>>> http://stackoverflow.com/questions/15270019/i-would-like-to- average-the-first-n-columns-based-on-duplicate-values-of-the -n1
>>
>> if isa(A,/integer) then begin
>> h=histogram(A[2,*],reverse_indices=ri)
>> idx=where(h ne 0,n)
>> B=fltarr(3,n)
>> for i=0,n-1 do begin
>> if ri[idx[i]] eq ri[idx[i]+1]-1 then $
>> B[0,i]=A[*,ri[ri[idx[i]]:ri[idx[i]+1]-1]] else $
>> B[0,i]=mean(A[*,ri[ri[idx[i]]:ri[idx[i]+1]-1]],dim=2)
>> endfor
>> endif else
>> values=A[2,uniq(A[2,*],sort(A[2,*]))]
>> ; if A[2,*] is already sorted, A[2,uniq(A[2,*])] is sufficient there
>> n=n_elements(values)
>> B=fltarr(3,n)
>> for i=0,n-1 do begin
>> w=where(A[2,*] eq values[i],cnt)
>> if w cnt 1 then B[0,i]=A[*,where(A[2,*] eq values[i])] else $
>> B[0,i]=mean(A[*,where(A[2,*] eq values[i])],dim=2,/nan)
>> endfor
>> endelse
>>
>>
>> hope that does it, Markus
>
>
> Hey, thanks for the answer. The last if loop is bugged. if w cnt 1 then B[0,i]
> Can't see how to fix that
Ok fixed it with "if w[cnt] eq 1 then B[0,i]"
Again thanks alot for your help ;)
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