| Re: setting histogram bin sizes? [message #61660 is a reply to message #61604] |
Thu, 24 July 2008 06:23  |
humanumbrella
Messages: 52
Registered: June 2008
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Member |
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On Jul 22, 1:18 pm, Bennett <juggernau...@gmail.com> wrote:
> On Jul 22, 12:59 pm, Bennett <juggernau...@gmail.com> wrote:
>
>
>
>> On Jul 22, 11:52 am, "Jeff N." <jeffnettles4...@gmail.com> wrote:
>
>>> Hi folks,
>
>>> I'm looking for suggestions for a way to set bin sizes for a histogram
>>> when I don't know much about the data before calculating the
>>> histogram. Here's my situation: I'm putting together some code that
>>> takes a hyperspectral image cube and extracts a series of one-band
>>> parameters from the cube (band depth at a certain wavelength, etc.).
>>> In trying to assess which of these parameters is most useful for our
>>> particular application i thought about calculating a histogram for
>>> each parameter. The problem is that these parameter images (one band,
>>> floating point images per parameter) will not necessarily fall into
>>> the same range. Many have possible values of 0 - 1, but they won't
>>> necessarily take up that entire range. Some however, will not have
>>> possible values of 0 - 1, but could instead have numbers in the 10s or
>>> even hundreds. Some parameters have values that are actually in log
>>> space.
>
>>> I know that I could simply set the NBINS keyword to HISTOGRAM(), but
>>> then the question would become how many bins to use? I did some quick
>>> searching, and there are a few attempts at calculating bin sizes or
>>> the number of bins on Wikipedia (http://en.wikipedia.org/wiki/
>>> Histogram). Short of any other information, i am going to use an
>>> equation from that page that is at least based on the standard
>>> deviation of the data. But, since I don't have a lot to go on, I
>>> would very much like to have input from anyone on this newsgroup who
>>> might have any suggestions for me.
>
>>> Thanks,
>>> Jeff
>
>> I'd have to say if I was going to approach this and this is definitely
>> not a very fun problem is to do the following.
>> nels = n_elements(data)
>> range = max(data) - min(data)
>> IF range/median(data) GT 10 THEN nbins = 10 ELSE nbins = round(range/
>> median(data))
>> nbins = nbins < nels/10 ;- Make sure you don't have way too many bins
>> This is just off the top of my head and working with some random
>> data...
>> I'm sure there are special cases that require some serious thought.
>
>> Hope it helps a bit....somehow....someway
>
> The GT should be a LT by the way...sorry for the confusion
David Fanning's article here: http://www.dfanning.com/tips/histogram_tutorial.html
might help.
Cheers,
--Justin
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