On Wed, 2021-02-10 at 17:31 -0500, Joseph Fox-Rabinovitz wrote:
> I've created PR#18386 to add a function called atleast_nd to numpy
> and
> numpy.ma. This would generalize the existing atleast_1d, atleast_2d,
> and
> atleast_3d functions.
>
> I proposed a similar idea about four and a half years
t soon), sounds like
a good way forward. "1, 2, nd" is pretty good. `atleast_3d` seems not
used all that much and is an odd one out. Having the `nd` version
should make a future deprecation painless, so long term we will be
better off.
- Sebastian
> Not having `atleast_3d(x) == atleast_
e same thing. atleast_3d() adapts those correctly for the (H,
> W,
> nchannels) case.
Right, my initial feeling it that without such context `atleast_3d` is
pretty surprising. So I wonder if we can design `atleast_nd` in a way
that it is explicit about this context.
The `pos` argument is the
d it yourself. (There may be other ways.)
Just remember to run valgrind with `PYTHONMALLOC=malloc valgrind` and
ignore some errors e.g. when importing NumPy.
Cheers,
Sebastian
>
> There are some points which were not clarified yet; I am citing them
> below.
>
> So far,
> F
ple.
Uninitialized + "suboffsets" seemed fairly clear, but I may have
underestimated it alot because I recognize "suboffsets" for buffers
immediately.
Cheers,
Sebastian
>
> > But feel free to find it yourself :)
>
> Yes :-D
>
> Best wishes,
&g
Hi all,
In https://github.com/numpy/numpy/issues/18407 it was reported that
there is a regression for `np.array()` and friends in NumPy 1.20 for
code such as:
np.array(["1234"], dtype=("U1", 4))
# NumPy 1.20: array(['1', '1', '1', '1'], dtype='>> np.array(["1234"], dtype="(4)U1,i")
ar
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On Wed, 2021-02-17 at 11:15 +0100, Ralf Gommers wrote:
> On Wed, Feb 17, 2021 at 2:14 AM Stephan Hoyer
> wrote:
>
> > On Tue, Feb 16, 2021 at 3:13 PM Sebastian Berg <
> > sebast...@sipsolutions.net>
> > wrote:
> >
> > > Hi all,
> > >
&g
`shape_base` in `numpy.core`.
Others, like `arraysetops` are fully exported to the main namespace,
but represent complete topical groupings, so I am less sure what we
should aim for there.
Cheers,
Sebastian
> - it should be explicitly documented that this is a "lower bar
> namespace&qu
ld be very tricky, unless we are patient enough to
wait for NumPy proper to evolve.
Hopefully I am just too pessimistic and e.g. a mild form of code
duplication can solve all of that. Probably time and trial-and-error
will be the judge on that...
Cheers,
Sebastian
>
> See
> https://m
> way to avoid a dispatch, it may make sense to just check array inputs
> for
> the presence of __array_function__ and raise an exception if it's
> present.
>
I do not think our functions where ever rewritten to only use e.g.
`._implementation()` internally. I am not even quite ce
PRs that you feel should
be prioritized, discussed, or reviewed.
Best regards
Sebastian
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lly this integer behaviour in the docs, that may be a
good idea. (The way the promotion is done also breaks the "minimal"
claim, but that is much more subtle.)
Cheers,
Sebastian
[1] However, before that happens, we may also consider an API where you
have to explicitly allow the `np.arra
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PS: Sorry for the
ghts!
An interesting aside is that `arr.imag` and `arr.real` fall into the
same category. But they are narrow enough that we can just have a
specific solution for them.
Cheers,
Sebastian
[1] Datetimes/timedelta might have some use of basic timezone handling
(not sure if relevant to NumPy&
re from the NumFOCUS spreadshirt shop [1] here:
https://shop.spreadshirt.com/numfocus/numpy?idea=604683f7998267255de40bcc
If there is popular demand to add something else that should be no
problem :).
Unfortunately, I doubt we can add those amazing mittens there!
Cheers,
Sebastian
[1] https://
or PRs that you feel should
be prioritized, discussed, or reviewed.
Best regards
Sebastian
PS: We will probably schedule the community meeting in UTC next week
probably, shifting to avoid shifting it by one hour.
Which means that the times will shift for whoever has daylight saving
time changes
still open, at least for me
personally.
Cheers,
Sebastian
On Sun, 2021-02-21 at 17:30 +0100, Ralf Gommers wrote:
> Hi all,
>
> Here is a NEP, written together with Stephan Hoyer and Aaron Meurer,
> for
> discussion on adoption of the array API standard (
> https://data-apis.g
On Wed, 2021-03-10 at 13:44 -0700, Aaron Meurer wrote:
> On Wed, Mar 10, 2021 at 10:42 AM Sebastian Berg
> wrote:
> >
> > Top Posting, to discuss post specific questions about NEP 47 and
> > partially the start on implementing it in:
> >
> > https
On Thu, 2021-03-11 at 12:37 +0100, Ralf Gommers wrote:
> On Wed, Mar 10, 2021 at 6:41 PM Sebastian Berg <
> sebast...@sipsolutions.net>
> wrote:
>
> > Top Posting, to discuss post specific questions about NEP 47 and
> > partially the start on implementing it in:
&
eason for the huge fluctuations
we see in the NumPy benchmarks due to absolutely unrelated code
changes.
But I did not have the energy to try it (and a probably fixed bug in
gcc makes it a bit harder right now).
Cheers,
Sebastian
> Cheers,
> Pierre
>
differences in the same `memcpy` or similar
calls, due to whatever reasons (maybe due to compiler changes, or due
to address space changes... or maybe the former causing the latter, I
don't know.).
Cheers,
Sebastian
>
> Cheers,
>
> Pierre
>
> - Mail original -
y understand whats going on, you would have to drill into what the
CPU caches are doing here?
The only thing I do know for sure currently, is that it is a rabbit
hole that I would love to understand, but don't really want to spend
days just to get nowhere.
Cheers,
Sebastian
[1] That run
nchmarking.
Right now, I am willing to get that if you repeat that whole thing with
a different commit range, you will find another random bad commit.
Cheers,
Sebastian
>
> Best,
> Peter
>
>
>
> On Mon, Mar 15, 2021 at 12:29 PM PIERRE AUGIER
> wrote:
> >
>
course, all the small issues/limitations that are not fixed
because nobody tried yet...
I hope this doesn't scare you away, or at least not for long :/. It
could be very useful to start experimentation soon to push things
forward a bit quicker. And I really want to have at least an
experim
and/or print out a warning.
Am I missing some obvious solution? Aside from "be patient and get it
right the first time"?
Cheers,
Sebastian
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PS: As the subject says, we will stay
something I firmly kept on the back-burner... It should not be very
hard (if rudimentary), but unless it would help experiments a lot, I
would tend to leave it on the back-burner for now.
Cheers,
Sebastian
[1] Maybe a `uint8` storage that maps to evenly spaced values on a
parametric ra
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On Wed, 2021-03-17 at 17:12 -0500, Sebastian Berg wrote:
> On Wed, 2021-03-17 at 07:56 -0500, Lee Johnston wrote:
> 3. In parallel, I will create a small "toy" DType based on that
> experimental API. Probably in a separate repo (in the NumPy
> organization?).
>
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PS: As the subject says, we will stay
...` always be honored as the
correct output dtype, I don't disagree. But it seems to me we probably
would have wade through a FutureWarning first, so a warning is the
"right direction". (Or just add an `output_dtypes` keyword argument.)
Cheers,
Sebastian
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De
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On Fri, 2021-04-02 at 15:46 -0500, Sebastian Berg wrote:
> Hi all,
>
> I have to do some changes to the type resolution, and I started these
> here: https://github.com/numpy/numpy/pull/18718
>
Just to keep everyone updated. We discussed this yesterdays meeting,
and settled
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the `a == 1` greedily after all.
Cheers,
Sebastian
> Haven't investigated further since your times are much longer than
> mine and
> secondly the equality check for 1 implies that perhaps a short
> circuit
> actually exists somewhere
>
>
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alue is
opaque, we even have the ability to turn it into a proper Python object
if we want to.
Cheers,
Sebastian
> Adding support for stateful allocators at a later date would almost
> certainly create an ABI breakage or lots of pain around avoiding one.
>
> I haven't thought ve
need reference counting
or similar!
But right now the proposal says this is static, and I honestly don't
see much reason for it to be freeable? The current use-cases `cupy` or
`pnumpy` don't not seem to need it.
If we return a new struct (I do not care if opaque or not), all of
e struct/PyObject is probably good enough to
to ensure we have a path for modifying/extending the ABI.
I hope that the actual end-users can chip in and clear it up a bit...
Cheers,
Sebastian
>
> > If someone wants a different strategy (i.e. different alignment)
> > they
> c
On Thu, 2021-03-25 at 17:27 -0500, Sebastian Berg wrote:
> On Wed, 2021-03-17 at 17:12 -0500, Sebastian Berg wrote:
> > On Wed, 2021-03-17 at 07:56 -0500, Lee Johnston wrote:
>
>
>
> > 3. In parallel, I will create a small "toy" DType based on that
>
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e, clean-up the old code) that this is still a
decent sized project. The old 80-20 problem, I guess...
So, it just never quite reached the motivation/priority threshold for
me since the original push.
Cheers,
Sebastian
>
> ___
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is released.
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ation, most
of those points seem unproblematic.
Cheers,
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uss better
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and record if
> they don't mind.
We have made a recording, but I did not plan on making it available
publicly. Please contact me directly if you are interested.
Cheers,
Sebastian
> Stéfan
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on. But if *nobody* voices
any concern about just changing the meaning of the string inputs, I
think the current default may be to just do it.
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Sebastian
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Wednesday and announce with the new time tomorrow.
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`
* `PyArray_ArgMaxWithKeepdims`
in the C-API. We have barely extended the C-API in a very long time,
so if anyone has concerns, we could pull that out again [1].
Otherwise, this should go in soon, and we will have `keepdims` for both
of those functions in the next release :).
Cheers,
Sebastian
[1] I do not see
On Thu, 2021-07-01 at 00:39 -0700, Stefan van der Walt wrote:
> Hi Sebastian,
>
> On Wed, Jun 30, 2021, at 18:23, Sebastian Berg wrote:
> > The PR https://github.com/numpy/numpy/pull/19211 proposes to extend
> > argmin and argmax with a `keepdims=False` keyword-only argu
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viour at the time – not based on use-cases.
Even functions like `isnan` give a warning for signalling NaNs!
The "fix" for anyone having sNaN's is to convert them to qNaNs as early
as possible. Which e.g. `np.positive(arr, out=arr)` should probably
do. If this becomes an issue, ma
up a possible NEP if there is no clarity of
where things are going. IMO, a NEP should be a concrete proposal, and
that means that whoever writes it must have confidence in a proposal.
If we transitioned from the brain-storming stage to a "formal decision
making" one, then maybe a NE
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o that has full precision.
* smallest_subnormal:
- Equivalent to `np.nextafter(0., 1.)`
- The smallest subnormal/denormal number. I.e. the smallest
representable number larger than zero.
Please don't hesitate to comment if you have any thoughts on the API
addition.
Cheers,
Sebastian
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econd means that we have to be careful when consider changing the
default even after implementing the NEP. But it may be possible, at
least if we do it slowly/gently.
Cheers,
Sebastian
>
> In multiarray/alloc.c the allocator (beneath the cache) using the
> POSIX malloc/calloc/reallo
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Hi all,
there is a proposal to add some Intel specific fast math routine to
NumPy:
https://github.com/numpy/numpy/pull/19478
part of numerical algorithms is that there is always a speed vs.
precision trade-off, giving a more precise result is slower.
So there is a question what the general
On Fri, 2021-07-30 at 11:04 -0700, Jerry Morrison wrote:
> On Tue, Jul 27, 2021 at 4:55 PM Sebastian Berg <
> sebast...@sipsolutions.net>
> wrote:
>
> > Hi all,
> >
> > there is a proposal to add some Intel specific fast math routine to
> > NumPy:
&
deserved. This would be especially worrying if it is a
regression for anyone?
Cheers,
Sebastian
PS: One additional note, is that this does not work for object arrays
(it cannot reasonable):
>>> np.unique(a.astype(object))
array([1.0, nan, nan, nan], dtype=object)
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int64) – unless otherwise specified.
As an aside, I am not sure what is returned for booleans right now
int8, uint8, or boolean? (Returning boolean for a count seems an
oversight though).
Cheers,
Sebastian
>
> Implementation
> -
On Mon, 2021-08-02 at 13:10 -0700, Stefan van der Walt wrote:
> On Mon, Aug 2, 2021, at 10:50, Sebastian Berg wrote:
> > * Should `np.ndarray.bit_count()` exist? I tend against this;
> > but we should have it on (integer) scalars to mirror the
> > Python `int`.
>
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me right now, unless I am
missing something awesome?
I will note that a lot of the functions that we want to template like
this, are – and should be – accessible as public API (i.e. you can ask
NumPy to give you the function pointer).
Cheers,
Sebastian
> - coding style?
> - (I'm-not-a-
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alling `trunc`.
So, I agree, I lean towards moving forward here. (Unless anyone has
e.g. an example of code that would break?)
There is a tiny possibility of catastrophic failure (silent wrong
results). But my best guess is that the vast majority of code probably
will not notice.
E.g. one pattern
On Fri, 2021-09-10 at 14:51 -0600, Aaron Meurer wrote:
> On Thu, Sep 9, 2021 at 7:11 PM Sebastian Berg
> wrote:
> >
> > On Sun, 2021-09-05 at 21:08 +0200, Ralf Gommers wrote:
> > > On Sat, Sep 4, 2021 at 10:02 AM Kshitij Kalambarkar <
> > > kshitijkalambar
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depending on whether the array is 1-D or N-D and even link to a website
for more pointers.
Cheers,
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>
> George
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> htt
And I think getting rid of it might help with removing other quirks
around item assignment.
Personally, I would be happy to change both, but they are probably
distinct. And I think the worry is mainly/only about the cost (user
pain) to benefit ratio.
Nico has taken some time to try and make
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accessible to anyone
interested.
Without any comments, I will announce and change the calendar starting
with next weeks meeting.
Cheers,
Sebastian
[1] I have to see whether we will stick with UTC or do any daylight
savings.
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On Wed, 2021-09-22 at 21:11 +0200, Ralf Gommers wrote:
> On Wed, Sep 22, 2021 at 8:31 PM Sebastian Berg <
> sebast...@sipsolutions.net>
> wrote:
>
> > Hi all,
> >
> > Melissa brought up that we should reschedule the bi-weekly
> > community
> > mee
57f20
Any comments to the approach (especially from anyone more familiar with
C++) would be much appreciated!
Cheers,
Sebastian
>
> Basically, templated code is an easy and robust way to replace
> generated code
> (the C++ compiler becomes the code generator when instantiating
> co
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NOTE: The time is different
r arrays.
The approach below moves the work of the element to pick from which
choice into a (fairly involved) pre-processing step to make the final
assignment more streamlined.
Cheers,
Sebastian
```
from itertools import chain
def choose(a, choices):
# Make sure we work with the correc
e have a plan e.g. to also move SciPy-dev to the same place, there
could be a very concrete benefit of allowing easier reach across
projects.
(Even NumPy is pretty diverse in topics. Discussions in random
numbers, fft, or linalg may find a lot of interest in SciPy.)
Cheers,
Sebastian
> e
a problem somewhere) please let us
know so we can revert/reconsider the change!
Cheers,
Sebastian
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On Wed, 2021-08-25 at 17:50 -0500, Sebastian Berg wrote:
> On Wed, 2021-08-25 at 17:48 +0200, Serge Guelton wrote:
> > Hi folks,
> >
> > https://github.com/numpy/numpy/pull/19713 showcases what *could* be
> > a
> > first step
> > toward getting rid of gen
is that we have two ways to template C now... I
hope that will pay off soon (as in C++ is proofs useful in some way),
since it feels like replacing all `c.src` code is a pretty large
(although probably doable) endeavor.
Cheers,
Sebastian
> On Thu, Oct 7, 2021 at 3:02 PM Sebastian Berg
>
>
gh, there should be a shorter (easier to type) password as well.
Cheers,
Sebastian
>
> On Mon, Oct 11, 2021 at 1:10 PM Rumanu Bhardwaj
>
> wrote:
>
> > I'm not able to join without the meeting password ;-;
> >
> > On Mon, 11 Oct, 2021, 4:46 am Meli
Hi all,
There will be a NumPy Community meeting Wednesday September 29th at
16:30 UTC. Everyone is invited and encouraged to join in and edit the
work-in-progress meeting topics and notes at:
https://hackmd.io/76o-IxCjQX2mOXO_wwkcpg?both
Best wishes
Sebastian
PS: Sorry for the late reminder
rror value, computing linear
extrapolation, or assuming a constant value.
The current choice is clipping (assuming a constant value), but this
could be modified.
Any feedback is appreciated! Otherwise, this will probably move
forward in the current state for the next release.
Cheers,
Sebastian
Hi all,
for simplicity, I suggest to move the triage meeting also by 30 minutes
later to 16:30 UTC, sorry for not thinking of that when moving the
community meeting.
If no one protests I will announce it and change the calendar
accordingly tomorrow.
Cheers,
Sebastian
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issues or PRs that you feel should
be prioritized, discussed, or reviewed.
Best regards
Sebastian
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Hi all,
There will be a NumPy Community meeting Wednesday October 27th at
16:30 UTC. Everyone is invited and encouraged to join in and edit the
work-in-progress meeting topics and notes at:
https://hackmd.io/76o-IxCjQX2mOXO_wwkcpg?both
Best wishes
Sebastian
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