[Numpy-discussion] sorting -inf, nan, inf
Tim Hochberg
tim.hochberg at ieee.org
Tue Sep 19 16:04:49 CDT 2006
Charles R Harris wrote:
>
>
> On 9/19/06, *Tim Hochberg* <tim.hochberg at ieee.org
> <mailto:tim.hochberg at ieee.org>> wrote:
>
> A. M. Archibald wrote:
> > On 19/09/06, Tim Hochberg <tim.hochberg at ieee.org
> <mailto:tim.hochberg at ieee.org>> wrote:
> >
> >> Keith Goodman wrote:
> >>
> >>> In what order would you like argsort to sort the values -inf,
> nan, inf?
> >>>
> >>>
> >> Ideally, -inf should sort first, inf should sort last and nan
> should
> >> raise an exception if present.
> >>
> >> -tim
> >>
> >
> > Mmm. Somebody who's working with NaNs has more or less already
> decided
> > they don't want to be pestered with exceptions for invalid data.
> Do you really think so? In my experience NaNs are nearly always
> just an
> indication of a mistake somewhere that didn't get trapped for one
> reason
> or another.
>
> > I'd
> > be happy if they wound up at either end, but I'm not sure it's worth
> > hacking up the sort algorithm when a simple isnan() can pull
> them out.
> >
> Moving them to the end seems to be the worst choice to me. Leaving
> them
> alone is fine with me. Or raising an exception would be fine. Or doing
> one or the other depending on the error mode settings would be even
> better if it is practical.
>
> > What's happening now is that NaN<a, NaN==a, and NaN>a are all
> false,
> > which rather confuses the sorting algorithm. But as long as it
> doesn't
> > actually *break* (that is, leave some of the non-NaNs incorrectly
> > sorted) I don't care.
> >
> Is that true? Are all of numpy's sorting algorithms robust against
> nontransitive objects laying around? The answer to that appears to be
> no. Try running this a couple of times to see what I mean:
>
> n = 10
> for i in range(10):
> for kind in 'quicksort', 'heapsort', 'mergesort':
> a = rand(n)
> b = a.copy()
> a[n//2] = nan
> a.sort(kind=kind)
> b.sort(kind=kind)
> assert alltrue(a[:n//2] == b[:n//2]), (kind, a, b)
>
>
> The values don't correctly cross the inserted NaN and the sort is
> incorrect.
>
>
> Except for heapsort those are doing insertion sorts because n is so
> small. Heapsort is trickier to understand because of the way the heap
> is formed and values pulled off.
I'm not sure where the breakpoint is, but I was seeing failures for all
three sort types with N as high as 10000. I suspect that they're all
broken in the presence of NaNs. I further suspect you'd need some
punishingly slow n**2 algorithm to be robust in the presence of NaNs.
> I'll look into that. I bet searchsorted gets messed up by nan's. Do
> you think it worthwhile to worry about it?
No. But that's because it's my contention is that any sequence with NaNs
in it is *not sorted* and thus isn't suitable input for searchsorted.
-tim
More information about the Numpy-discussion
mailing list