[Numpy-discussion] Histograms via indirect index arrays
Norbert Nemec
Norbert.Nemec.list at gmx.de
Thu Mar 16 08:01:02 CST 2006
I have a very much related problem: Not only that the idea described by
Mads Ipsen does not work, but I could generally find no efficient way to
do a "counting" of elements in an array, as it is needed for a histogram.
The function "histogram" contained in numpy uses a rather inefficient
method, involving the sorting of the data array.
What would instead be needed is a function that simply gives the count
of occurances of given values in a given array:
>>> [4,5,2,3,2,1,4].count([0,1,2,3,4,5])
[0,1,2,1,1,2]
All the solutions that I found so far involve either sorting of the data
or writing a loop in Python, both of which are unacceptable for performance.
Am I missing something obvious?
Mads Ipsen wrote:
>Hey,
>
>First of all, thanks for the new release.
>
>Here's another question regarding something I cannot quite understand:
>
>Suppose you want to update bins for a histogram, you might think you
>could do something like:
>
> g = zeros(4,Int)
> x = array([0.2, 0.2])
> idx = floor(x/0.1).astype(int)
> g[idx] += 1
>
>Here idx becomes
>
> array([2, 2])
>
>In this case, I would naively expect g to end up like
>
> array([0, 0, 2, 0]) (1)
>
>but instead you get
>
> array([0, 0, 1, 0]) (2)
>
>Is this intended? Just being plain novice-like naive, I would expect
>the slice operation g[idx] += 1 to do something like
>
> for i in range(len(I)):
> g[ idx[i] ] += 1
>
>resulting in (1) and not (2).
>
>// Mads
>
>
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