Thanks, that is very helpful!
On 01/30/2016 01:40 PM, Jeff Reback wrote:
just my 2c
it's fairly straightforward to add a test to the Travis matrix to grab
numpy wheels built numpy wheels (works for conda or pip installs).
so in pandas we r testing 2.7/3.5 against numpy master continuously
On 02/01/2016 04:25 PM, Ralf Gommers wrote:
It would be nice but its not realistic, I doubt most upstreams
that are
not themselves major downstreams are even subscribed to this list.
I'm pretty sure that some core devs from all major scipy stack
packages are subscribed to this
2016-02-09 18:02 GMT+01:00 Gregor Thalhammer :
>> It is not suitable as a standard for numpy.
>
> Why should numpy not provide fast transcendental math functions? For
linear algebra it supports fast implementations, even non-free (MKL).
Wouldn’t it be nice if numpy
On Tue, Feb 9, 2016 at 1:02 AM, Chris Barker wrote:
> As you can see in the timeline:
>
> https://developers.google.com/open-source/gsoc/timeline
>
> We are now in the stage where mentoring organizations are getting their
> act together. So the question now is -- are there
On Wed, Feb 10, 2016 at 11:48 PM, Chris Barker
wrote:
> Thanks Ralf,
>
> Note that we have always done a combined numpy/scipy ideas page and
>> submission. For really good students numpy may be the right challenge, but
>> in general scipy is easier to get started on.
>>
>
On Wed, Feb 10, 2016 at 2:58 PM, Pauli Virtanen wrote:
> 10.02.2016, 04:09, Charles R Harris kirjoitti:
> > I'm pleased to announce the release of NumPy 1.11.0b3. This beta contains
> [clip]
> > Please test, hopefully this will be that last beta needed.
>
> FWIW,
10.02.2016, 04:09, Charles R Harris kirjoitti:
> I'm pleased to announce the release of NumPy 1.11.0b3. This beta contains
[clip]
> Please test, hopefully this will be that last beta needed.
FWIW, https://travis-ci.org/pv/testrig/builds/108384173
___
Thanks Ralf,
Note that we have always done a combined numpy/scipy ideas page and
> submission. For really good students numpy may be the right challenge, but
> in general scipy is easier to get started on.
>
yup -- good idea. Is there a page ready to go, or do we need to get one up?
(I don't
>
> We might consider adding "improve duck typing for numpy arrays"
>
care to elaborate on that one?
I know it come up on here that it would be good to have some code in numpy
itself that made it easier to make array-like objects (I.e. do indexing the
same way) Is that what you mean?
-CHB
I have created a PR to deprecate `np.iterable`
(https://github.com/numpy/numpy/pull/7202). It is a very old function,
introduced as a utility in 2005
(https://github.com/numpy/numpy/commit/052a7b2e3276a303be1083022fc24d43084d2e14),
and there is no good reason for it to be part of the public API.
On Wed, Feb 10, 2016 at 5:36 PM, Charles R Harris wrote:
>
>
> On Wed, Feb 10, 2016 at 2:58 PM, Pauli Virtanen wrote:
>
>> 10.02.2016, 04:09, Charles R Harris kirjoitti:
>> > I'm pleased to announce the release of NumPy 1.11.0b3. This beta
>> contains
>>
On Wed, Feb 10, 2016 at 11:55 PM, Ralf Gommers
wrote:
>
>
> On Wed, Feb 10, 2016 at 11:48 PM, Chris Barker
> wrote:
>
>> Thanks Ralf,
>>
>> Note that we have always done a combined numpy/scipy ideas page and
>>> submission. For really good students
On Wed, Feb 10, 2016 at 3:02 PM, Ralf Gommers
wrote:
> OK first version:
> https://github.com/scipy/scipy/wiki/GSoC-2016-project-ideas
> I kept some of the ideas from last year, but removed all potential mentors
> as the same people may not be available this year - please
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