cat numtst.py import Numeric
We have a speed problem with Numeric.sort on large arrays with only a few different values. Here is my example -- snip -- print Numeric.__version__ class timer: def __init__(self): import time self.start = time.time() def stop(self): import time print "%.3f" % (time.time() - self.start) from RandomArray import random from Numeric import sort, Int r=random((71400,)) t = timer() ; p=sort(r) ; t.stop() r=(random((71400,))*70000).astype(Int) t = timer() ; p=sort(r) ; t.stop() r=(random((71400,))*70).astype(Int) t = timer() ; p=sort(r) ; t.stop() r=(random((71400,))*7).astype(Int) t = timer() ; p=sort(r) ; t.stop() 16:27 hoel@seeve:hoel 2>python numtst.py 17.3.0 0.185 0.148 2.053 21.668 -- snip -- So the less different values are contained in the array the longer takes the sorting. Is this also the case with newer versions of Numeric (But this is Python 1.5.2)? Why is sorting of these arrays so slow? Thanks Berthold -- email: hoel@GermanLloyd.org ) tel. : +49 (40) 3 61 49 - 73 74 ( C[_] These opinions might be mine, but never those of my employer.