[Numpy-discussion] Histograms via indirect index arrays

Travis Oliphant oliphant.travis at ieee.org
Fri Mar 17 01:16:03 CST 2006

```Norbert Nemec wrote:
> 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.
>
This may be something we are lacking.

It depends on what you mean by efficient, I suppose.  The sorting
algorithms are very fast, and the histogram routines that are scattered
all over the place (including the histogram function in numpy) has been
in use for a long time, and you are the first person to complain of its
efficiency.  That isn't to say your complaint may not be valid, it's
just that for most people the speed has been sufficient.
> What would instead be needed is a function that simply gives the count
> of occurances of given values in a given array:
>
I presume you are talking of "integer" arrays,  since
equality-comparison of floating-point values is usually not very helpful
so most histograms on floating-point values are given in terms of bins.
Thus, the searchsorted function uses bins for it's "counting" operation.
>
>>>> [4,5,2,3,2,1,4].count([0,1,2,3,4,5])
>>>>
> [0,1,2,1,1,2]
>
>

A count function for integer arrays could certainly be written using a
C-loop.  But, I would first just use histogram([4,5,2,3,2,1,4],
[0,1,2,3,4,5]) and make sure that's really too slow, before worrying

Also, I according to the above function, the right answer is:

[0, 1, 2, 1, 2, 1]

Best,

-Travis

```