[Numpy-discussion] PR to add an initializer kwarg to ufunc.reduce (and similar functions)

Mon Mar 26 11:45:56 EDT 2018

On Mon, 2018-03-26 at 11:39 -0400, Hameer Abbasi wrote:
> That is the idea, but NaN functions are in a separate branch for
> another PR to be discussed later. You can see it on my fork, if
> you're
> interested.

Except that as far as I understand I am not sure it will help much with
it, since it is not a default, but an initializer. Initializing to NaN
would just make all results NaN.

- Sebastian

> On 26/03/2018 at 17:35, Benjamin wrote: Hmm, this is neat.
> I imagine it would finally give some people a choice on what
> np.nansum([np.nan]) should return? It caused a huge hullabeloo a few
> years ago when we changed it from returning NaN to returning zero.
> Ben
> Root On Mon, Mar 26, 2018 at 11:16 AM, Sebastian Berg
> <sebastian at sipsolutions.net> wrote: OK, the new documentation is
> actually clear: initializer : scalar, optional The value with which
> to
> start the reduction. Defaults to the `~numpy.ufunc.identity` of the
> ufunc. If ``None`` is given, the first element of the reduction is
> used, and an error is thrown if the reduction is empty. If
> ``a.dtype``
> is ``object``, then the initializer is _only_ used if reduction is
> empty. I would actually like to say that I do not like the object
> special case much (and it is probably the reason why I was confused),
> nor am I quite sure this is what helps a lot? Logically, I would
> argue
> there are two things: 1. initializer/start (always used) 2. default
> (oly used for empty reductions) For example, I might like to give
> `np.nan` as the default for some empty reductions, this will not
> work.
> I understand that this is a minimal invasive PR and I am not sure I
> find the solution bad enough to really dislike it, but what do other
> think? My first expectation was the default behaviour (in all cases,
> not just object case) for some reason. To be honest, for now I just
> wonder a bit: How hard would it be to do both, or is that too
> annoying? It would at least get rid of that annoying thing with
> object
> ufuncs (which currently have a default, but not really an
> identity/initializer). Best, Sebastian On Mon, 2018-03-26 at 08:20
> -0400, Hameer Abbasi wrote: > Actually, the behavior right now isn’t
> that of `default` but that of > `initializer` or `start`. > > This
> was
> discussed further down in the PR but to reiterate: > `np.sum([10],
> initializer=5)` becomes `15`. > > Also, `np.min([5], initializer=0)`
> becomes `0`, so it isn’t really > the default value, it’s the initial
> value among which the reduction > is performed. > > This was the
> reason to call it initializer in the first place. I like > `initial`
> and `initial_value` as well, and `start` also makes sense > but isn’t
> descriptive enough. > > Hameer > Sent from Astro for Mac > > > On Mar
> 26, 2018 at 12:06, Sebastian Berg <sebastian at sipsolutions.ne > > t>
> wrote: > > > > Initializer or this sounds fine to me. As an other
> data
> point which > > I > > think has been mentioned before, `sum` uses
> start and min/max use > > default. `start` does not work, unless we
> also change the code to > > always use the identity if given
> (currently that is not the case), > > in > > which case it might be
> nice. However, "start" seems a bit like > > solving > > a different
> issue in any case. > > > > Anyway, mostly noise. I really like adding
> this, the only thing > > worth > > discussing a bit is the name :). >
> > > > - Sebastian > > > > > > On Mon, 2018-03-26 at 05:57 -0400,
> 
> Hameer Abbasi wrote: > > > It calls it `initializer` - See
> https://docs.python.org/3.5/libra > > > ry/f > > >
> unctools.html#functools.reduce > > > > > > Sent from Astro for Mac >
> >
> > > > > > On Mar 26, 2018 at 09:54, Eric Wieser
> 
> <wieser.eric+numpy at gmail. > > > > com> > > > > wrote: > > > > > > > >
> It turns out I mispoke - functools.reduce calls the argument > > > >
> `initial` > > > > > > > > On Mon, 26 Mar 2018 at 00:17 Stephan Hoyer
> <shoyer at gmail.com> > > > > wrote: > > > > > This looks like a very
> logical addition to the reduce > > > > > interface. > > > > > It has
> my support! > > > > > > > > > > I would have preferred the more
> descriptive name > > > > > "initial_value", > > > > > but consistency
> with functools.reduce makes a compelling case > > > > > for > > > > >
> "initializer". > > > > > > > > > > On Sun, Mar 25, 2018 at 1:15 PM
> Eric Wieser <wieser.eric+nump > > > > > y at gm > > > > > ail.com>
> wrote:
> > > > > > > To reiterate my comments in the issue - I'm in favor of >
> > > > > > 
> > > > > > this. > > > > > > > > > > > > It seems seem especially
> 
> valuable for identity-less > > > > > > functions > > > > > > (`min`,
> `max`, `lcm`), and the argument name is consistent > > > > > > with >
> > > > > > `functools.reduce`. too. > > > > > > > > > > > > The only
> 
> argument I can see against merging this would be > > > > > >
> `kwarg`-creep of `reduce`, and I think this has enough use > > > > >
> >
> cases to justify that. > > > > > > > > > > > > I'd like to merge in a
> few days, if no one else has any > > > > > > opinions. > > > > > > >
> >
> > > > > Eric > > > > > > > > > > > > On Fri, 16 Mar 2018 at 10:13
> 
> Hameer Abbasi <einstein.edison > > > > > > @gma > > > > > > il.com>
> wrote: > > > > > > > Hello, everyone. I’ve submitted a PR to add a
> initializer > > > > > > > kwarg to ufunc.reduce. This is useful in a
> few cases, > > > > > > > e.g., > > > > > > > it allows one to supply
> a
> “default” value for identity- > > > > > > > less > > > > > > > ufunc
> reductions, and specify an initial value for > > > > > > > reductions
> > > > > > > > such as sum (other than zero.) > > > > > > > > > > > >
> > > > > > > > >
> > 
> > Please feel free to review or leave feedback, (although I > > > > >
> > > think Eric and Marten have picked it apart pretty well). > > > >
> > > >
> > > > > > > > > > https://github.com/numpy/numpy/pull/10635 > > > > >
> > > > > > > > > > Thanks, > > > > > > > > > > > > > > Hameer > > > >
> > > > > > > > > > >
> > > 
> > > Sent from Astro for Mac > > > > > > > > > > > > > >
> 
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