Disclaimer : this is a user's point of view. I never commited a line in
numpy.
In my usage, missing values happen or the need for some kind of mask, such
as sea/land.
I've been told, here, that using MA is superior to using NaNs, and indeed,
I found a couple case where other libraries (matplotlib
Hi All,
I agree with comments above that deprecating/removing MaskedArray is
premature; we certainly depend on it in astropy (which is indeed what
got me started to contribute to numpy -- it was quite buggy!).
I also think that, unlike Matrix, it is far from a neglected part of
numpy. Eric Wiese
On 05/24/2018 11:31 AM, Sebastian Berg wrote:
> I also somewhat like the idea of taking it out (once we have a first
> replacement) in the case that we have a plan to do a better/lower level
> replacement at a later point within numpy.
> Removal generally has its merits, but if a (mid term) replac
I also somewhat like the idea of taking it out (once we have a first
replacement) in the case that we have a plan to do a better/lower level
replacement at a later point within numpy.
Removal generally has its merits, but if a (mid term) replacement will
come in any case, it would be nice to get th
On Wed, 2018-05-23 at 23:48 +0200, Sebastian Berg wrote:
> On Wed, 2018-05-23 at 17:33 -0400, Allan Haldane wrote:
>
> If we do not plan to replace it within numpy, we need to discuss a
> bit
> how it might affect infrastructure (multiple implementations).
>
> There is the other discussion
As further evidence of a widely used package that is often considered
"critical" to an ecosystem that gets negligible support, look no further
than Basemap. It went almost two years without any commits before I took it
up (and then only because my employer needed a couple of fixes).
I worry that a
users of a package does not equate to maintainers of a package. Scikits are
successful because scientists that have specialty in a field can contribute
code and support the packages using their domain knowledge. How many people
here are specialists in masked/missing value computation?
Would I like
Hi Eric,
On Wed, 23 May 2018 10:02:22 -1000, Eric Firing wrote:
> Masked arrays are critical to my numpy usage, and I suspect they are
> critical for many other use cases as well.
That's good to know; and the goal of this NEP should be to improve your
siatuion, not make it worse.
> In fact, I wo
Hi All,
*Disclaimer: I don't spend any hours actually maintaining Numpy, so please
don't take my comments here with much weight.*
My gut reaction here is that if removing masked array allows Numpy to
evolve more quickly then this excites me.
It could be that a plan goes something like the follow
On Wed, 23 May 2018 13:30:49 -0700, Ralf Gommers wrote:
> > Good point, which certainly needs to be discussed. My thought was to
> > move it out into a separate package that could be maintained more in the
> > spirit of a scikit by people who care deeply about its functionality.
> >
> That would b
Hi,
On Wed, May 23, 2018 at 10:42 PM, Stefan van der Walt
wrote:
> On May 23, 2018 14:28:05 Matthew Brett wrote:
>>
>>
>> Can I ask what the plans are for supporting missing values, inside or
>> outside numpy? Is there are successor to MaskedArray - and is this
>> part of the succession plan?
>
On Wed, 2018-05-23 at 17:33 -0400, Allan Haldane wrote:
> On 05/23/2018 04:02 PM, Eric Firing wrote:
> > Bad or missing values (and situations where one wants to use a mask
> > to
> > operate on a subset of an array) are found in many domains of real
> > life;
> > do you really want python users in
On May 23, 2018 14:28:05 Matthew Brett wrote:
Can I ask what the plans are for supporting missing values, inside or
outside numpy? Is there are successor to MaskedArray - and is this
part of the succession plan?
I am not aware of any concrete plans, maybe others can chime in?
It's a bit str
On 05/23/2018 04:02 PM, Eric Firing wrote:
> Bad or missing values (and situations where one wants to use a mask to
> operate on a subset of an array) are found in many domains of real life;
> do you really want python users in those domains to have to fall back on
> Matlab-style reliance on nans a
Hi,
On Wed, May 23, 2018 at 9:51 PM, Stefan van der Walt
wrote:
> Hi Eric,
>
> On May 23, 2018 13:25:44 Eric Firing wrote:
>
>> On 2018/05/23 9:06 AM, Matti Picus wrote:
>> I understand at least some of the motivation and potential advantages,
>> but as it stands, I find this NEP highly alarmin
As far as I understand from the discussion above, I think the opposite
would be a better strategy for the sanity of our scarce but brave
maintainers. I would argue that if there is a maintenance burden, then the
ballasts seem to be the linalg and random indeed. Similar pain points exist
in SciPy t
Hi Eric,
On May 23, 2018 13:25:44 Eric Firing wrote:
On 2018/05/23 9:06 AM, Matti Picus wrote:
I understand at least some of the motivation and potential advantages,
but as it stands, I find this NEP highly alarming.
I am not at my computer right now, so I will respond in more detail later.
On Wed, May 23, 2018 at 1:03 PM, Stefan van der Walt
wrote:
> On Wed, 23 May 2018 12:29:32 -0700, Ralf Gommers wrote:
> > >> * Compatibility: MaskedArray objects, being subclasses of `ndarrays`,
> > >>often cause complications when being used with other packages.
> > >>Fixing these issue
On 2018/05/23 9:06 AM, Matti Picus wrote:
MaskedArray is a strange but useful creature. This NEP proposes to
distribute it as a separate package under the NumPy brand.
As I understand the process, a proposed NEP should be first discussed
here to gauge general acceptance, then after that the de
On Wed, 23 May 2018 12:29:32 -0700, Ralf Gommers wrote:
> >> * Compatibility: MaskedArray objects, being subclasses of `ndarrays`,
> >>often cause complications when being used with other packages.
> >>Fixing these issues is outside the scope of NumPy development.
> >
> Hmm, I wouldn't say
On Wed, May 23, 2018 at 12:06 PM, Matti Picus wrote:
> MaskedArray is a strange but useful creature. This NEP proposes to
> distribute it as a separate package under the NumPy brand.
>
> As I understand the process, a proposed NEP should be first discussed here
> to gauge general acceptance, then
MaskedArray is a strange but useful creature. This NEP proposes to
distribute it as a separate package under the NumPy brand.
As I understand the process, a proposed NEP should be first discussed
here to gauge general acceptance, then after that the details should be
discussed on the pull requ
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