[Numpy-discussion] What should be the result in some statistics corner cases?
Sebastian Berg
sebastian at sipsolutions.net
Mon Jul 15 11:55:44 EDT 2013
On Mon, 2013-07-15 at 08:47 -0600, Charles R Harris wrote:
>
>
> On Mon, Jul 15, 2013 at 8:34 AM, Sebastian Berg
> <sebastian at sipsolutions.net> wrote:
> On Mon, 2013-07-15 at 07:52 -0600, Charles R Harris wrote:
> >
> >
> > On Sun, Jul 14, 2013 at 3:35 PM, Charles R Harris
> > <charlesr.harris at gmail.com> wrote:
> >
>
>
> <snip>
>
> >
> > For nansum, I would expect 0 even in the
> case of all
> > nans. The point
> > of these functions is to simply ignore nans,
> correct?
> > So I would aim
> > for this behaviour: nanfunc(x) behaves the
> same as
> > func(x[~isnan(x)])
> >
> >
> > Agreed, although that changes current behavior. What
> about the
> > other cases?
> >
> >
> >
> > Looks like there isn't much interest in the topic, so I'll
> just go
> > ahead with the following choices:
> >
> > Non-NaN case
> >
> > 1) Empty array -> ValueError
> >
> > The current behavior with stats is an accident, i.e., the
> nan arises
> > from 0/0. I like to think that in this case the result is
> any number,
> > rather than not a number, so *the* value is simply not
> defined. So in
> > this case raise a ValueError for empty array.
> >
>
> To be honest, I don't mind the current behaviour much sum([])
> = 0,
> len([]) = 0, so it is in a way well defined. At least I am not
> sure if I
> would prefer always an error. I am a bit worried that just
> changing it
> might break code out there, such as plotting code where it
> makes
> perfectly sense to plot a NaN (i.e. nothing), but if that is
> the case it
> would probably be visible fast.
>
> I'm talking about mean, var, and std as statistics, sum isn't part of
> that. If there is agreement that nansum of empty arrays/columns should
> be zero I will do that. Note the sums of empty arrays may or may not
> be empty.
>
> In [1]: ones((0, 3)).sum(axis=0)
> Out[1]: array([ 0., 0., 0.])
>
> In [2]: ones((3, 0)).sum(axis=0)
> Out[2]: array([], dtype=float64)
>
> Which, sort of, makes sense.
>
>
I think we can agree that the behaviour for reductions with an identity
should default to returning the identity, including for the nanfuncs,
i.e. sum([]) is 0, product([]) is 1...
Since mean = sum/length is a sensible definition, having 0/0 as a result
doesn't seem to bad to me to be honest, it might be accidental but it is
not a special case in the code ;). Though I don't mind an error as long
as it doesn't break matplotlib or so.
I agree about the nanfuncs raising an error would probably be more of a
problem then for a usual ufunc, but still a bit hesitant about saying
that it is ok too. I could imagine adding a very general "identity"
argument (though I would not call it identity, because it is not the
same as `np.add.identity`, just used in a place where that would be used
otherwise):
np.add.reduce([], identity=123) -> [123]
np.add.reduce([1], identity=123) -> [1]
np.nanmean([np.nan], identity=None) -> Error
np.nanmean([np.nan], identity=np.nan) -> np.nan
It doesn't really make sense, but:
np.subtract.reduce([]) -> Error, since np.substract.identity is None
np.subtract.reduce([], identity=0) -> 0, suppressing the error.
I am not sure if I am convinced myself, but especially for the nanfuncs
it could maybe provide a way to circumvent the problem somewhat.
Including functions such as np.nanargmin, whose result type does not
even support NaN. Plus it gives an argument allowing for warnings about
changing behaviour.
- Sebastian
>
> > 2) ddof >= n -> ValueError
> >
> > If the number of elements, n, is not zero and ddof >= n,
> raise a
> > ValueError for the ddof value.
> >
>
> Makes sense to me, especially for ddof > n. Just returning nan
> in all
> cases for backward compatibility would be fine with me too.
>
> > Nan case
> >
> > 1) Empty array -> Value Error
> > 2) Empty slice -> NaN
> > 3) For slice ddof >= n -> Nan
> >
>
> Personally I would somewhat prefer if 1) and 2) would at least
> default
> to the same thing. But I don't use the nanfuncs anyway. I was
> wondering
> about adding the option for the user to pick what the fill is
> (and i.e.
> if it is None (maybe default) -> ValueError). We could also
> allow this
> for normal reductions without an identity, but I am not sure
> if it is
> useful there.
>
>
> Chuck
>
>
>
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