| Re: array manipulation (TOTAL-ing or MEDIAN-ing) in uneven bins [message #82491 is a reply to message #82403] |
Wed, 12 December 2012 14:18   |
Jeremy Bailin
Messages: 618
Registered: April 2008
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Senior Member |
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On 12/12/12 4:03 PM, Jeremy Bailin wrote:
> On 12/12/12 10:16 AM, havok2063@gmail.com wrote:
>>
>> I have several unrelated problems that I'm solving in the same
>> efficient way (with loops). I'm trying to perform some array
>> operation on an array, according to a list of (let's call them) uneven
>> bins.
>>
>> I have an array, say d, of 146 elements. I have a separate array that
>> represents uneven bins that I want to perform the operation on, like
>> MEDIAN, or TOTAL. For example,
>>
>> ntot = [15,45,56,90,116,146]
>>
>> I want as output an array, of 6 elements, that contains the MEDIAN (or
>> TOTAL) of array d according to the indices listed in ntot.
>>
>> So the 1st element would contain median(d[0:14],/even), the 2nd
>> median(d[15:44],/even), etc....
>>
>> Or the same thing with total....total(d[0:14]), total(d[15:44]) , etc...
>>
>> Right now I'm looping over the number of elements in ntot to do this
>> and I don't much care for loops.
>>
>> I don't think this is quite the same thing as the example given in the
>> "Horror and Disgust of Histogram" article nor does this sound like
>> something I can do with value_locate, although I'm not too familiar
>> with value_locate.
>>
>> Any ideas on this? Thanks a lot.
>>
>
> As David says, this screams VALUE_LOCATE. And HISTOGRAM. They play very
> nicely together for this sort of problem!
>
> First we need to label the bin for each element:
>
> nelements = 146
> binlabel = value_locate(ntot, lindgen(nelements))
>
> Then use histogram to group the elements by bin label. Notice that the
> way you've defined ntot, elements 0 through 14 will be labelled "-1" by
> value_locate, so we start the histogram there:
>
> nbin = n_elements(ntot)
> hist = histogram(binlabel, min=-1, max=nbin-1, reverse_indices=ri)
>
> And finally we do the usual loop through the reverse indices to
> calculate the statistics:
>
> medianbin = fltarr(nbin)
> totbin = fltarr(nbin)
> for i=0L,nbin-1 do if hist[i] gt 0 then begin
> these = ri[ri[i]:ri[i+1]-1]
> medianbin[i] = median(d[these], /even)
> totbin[i] = total(d[these])
> endif
>
> -Jeremy.
Actually, for the total you can do a lot better by using cumulative:
runningtotal = total(d, /cumulative)
totbin = runningtotal[ntot] - [0,runningtotal[ntot]]
-Jeremy.
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