John Doty:
> Yes. The efficient exact algorithms for this problem use *partial*
> sorts. The Forth one from the FSL is of this class (although I know of
> two better ones for big arrays). But it's tough to beat the efficiency
> of the approximate histogram-based method the Python stats module
> implements.
The usual way to compute a true median with Python may be:
def median(inlist):
newlist = sorted(inlist)
index = len(newlist) // 2
if len(newlist) % 2:
return newlist[index]
else:
return (newlist[index] + newlist[index-1]) / 2.0
If you can use Psyco and your FITS lines are really long (well, maybe
too much, the treshold if about >~3000 in my PC) you can use something
like this instead the builtin timsort:
http://aspn.activestate.com/ASPN/Cookbook/Python/Recipe/466330
(To compute the median on a image line the median that uses sort is
probably better in most cases, expecially if you use the built in sort
of numerical libraries.)
Bye,
bearophile
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