[Numpy-discussion] New numpy functions: filled, filled_like
Thu Jan 17 16:10:14 CST 2013
On Thu, Jan 17, 2013 at 5:04 PM, Eric Firing <email@example.com> wrote:
> On 2013/01/17 4:13 AM, Pierre Haessig wrote:
> > Hi,
> > Le 14/01/2013 20:05, Benjamin Root a écrit :
> >> I do like the way you are thinking in terms of the broadcasting
> >> semantics, but I wonder if that is a bit awkward. What I mean is, if
> >> one were to use broadcasting semantics for creating an array, wouldn't
> >> one have just simply used broadcasting anyway? The point of
> >> broadcasting is to _avoid_ the creation of unneeded arrays. But maybe
> >> I can be convinced with some examples.
> > I feel that one of the point of the discussion is : although a new (or
> > not so new...) function to create a filled array would be more elegant
> > than the existing pair of functions "np.zeros" and "np.ones", there are
> > maybe not so many usecases for filled arrays *other than zeros values*.
> > I can remember having initialized a non-zero array *some months ago*.
> > For the anecdote it was a vector of discretized vehicule speed values
> > which I wanted to be initialized with a predefined mean speed value
> > prior to some optimization. In that usecase, I really didn't care about
> > the performance of this initialization step.
> > So my overall feeling after this thread is
> > - *yes* a single dedicated fill/init/someverb function would give a
> > slightly better API,
> > - but *no* it's not important because np.empty and np.zeros covers 95
> > % usecases !
> I agree with your summary and conclusion.
Can we at least have a np.nans() and np.infs() functions? This should
cover an additional 4% of use-cases.
P.S. - I know they aren't verbs...
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