Hans Georg Krauthaeuser hgk at et.uni-magdeburg.de
Wed Dec 21 10:50:02 CET 2005

```Hi All,

I was playing with scipy.stats.itemfreq when I observed the following
overflow:

In [119]:for i in [254,255,256,257,258]:
.....:    l=[0]*i
.....:    print i, stats.itemfreq(l), l.count(0)
.....:
254 [ [  0 254]] 254
255 [ [  0 255]] 255
256 [ [0 0]] 256
257 [ [0 1]] 257
258 [ [0 2]] 258

itemfreq is pretty small (in stats.py):

----------------------------------------------------------------------
def itemfreq(a):
"""
Returns a 2D array of item frequencies.  Column 1 contains item values,
column 2 contains their respective counts.  Assumes a 1D array is passed.

Returns: a 2D frequency table (col [0:n-1]=scores, col n=frequencies)
"""
scores = _support.unique(a)
scores = sort(scores)
freq = zeros(len(scores))
for i in range(len(scores)):
return array(_support.abut(scores, freq))
----------------------------------------------------------------------

It seems that add.reduce is the source for the overflow:

In [116]:from scipy import *

In [117]:for i in [254,255,256,257,258]:
.....:    l=[0]*i
.....:
254 254
255 255
256 0
257 1
258 2

Is there any possibility to avoid the overflow?

BTW:
Python 2.3.5 (#2, Aug 30 2005, 15:50:26)
[GCC 4.0.2 20050821 (prerelease) (Debian 4.0.1-6)] on linux2

scipy_version.scipy_version  --> '0.3.2'

Thanks and best regards
Hans Georg Krauthäuser

```