So this petered off...any objections to np.full?

On 29 Jun 2013 05:03, <> wrote:
On Wed, Jun 12, 2013 at 8:10 AM, Nathaniel Smith <> wrote:
> Hi all,
> It looks like we've gotten a bit confused and need to untangle
> something. There's a PR to add new functions 'np.filled' and
> 'np.filled_like':
> And there was a discussion about this on the list back in January:
> I think a reasonable summary of the opinions in the thread are:
> - This functionality is great, ...
> - ...but we can't call it 'np.filled' because there's also
> '' which does something else...
> - ...but there really aren't any better names...
> - we should overload np.empty, like: 'np.empty(shape, fill=value)'
> In the mean time the original submitter has continued puttering along
> polishing the original patch, and it's ready to merge... except it's
> still the original interface, somehow the thread discussion and the PR
> discussion never met up.
> So, we have to decide what to do.
> Personally I think that overloading np.empty is horribly ugly, will
> continue confusing newbies and everyone else indefinitely, and I'm
> 100% convinced that we'll regret implementing such a warty interface
> for something that should be so idiomatic. (Unfortunately I got busy
> and didn't actually say this in the previous thread though.) So I
> think we should just merge the PR as is. The only downside is the
> inconsistency, but, is already inconsistent (cf.
> masked_array.fill versus masked_array.filled!), somewhat deprecated,
> and AFAICT there are far more people who will benefit from a clean
> np.filled idiom than who actually use (and in particular its
> fill-value functionality). So there would be two
> bad-but-IMHO-acceptable options: either live with an inconsistency
> between np.filled and, or deprecate in favor
> of masked_array.filled (which does exactly the same thing) and
> eventually switch to be consistent with the new
> np.filled.
> But, that's just my opinion.
> -n
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> NumPy-Discussion mailing list

Why we need this animal whatever it is called

 Scientific Python @SciPyTip
Create a 2x3 array filled with integer 7's: 7*np.ones((2,3), int)

and I just did this yesterday,  np.nan * np.ones(3)
maybe I should have used np.zeros(3) / 0.

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