Re: [Numpy-discussion] Moving forward with value based casting

On Tue, 2019-06-18 at 04:28 +0200, Hameer Abbasi wrote: > On Wed, 2019-06-12 at 12:55 -0500, Sebastian Berg wrote: > > On Wed, 2019-06-05 at 15:41 -0500, Sebastian Berg wrote: > > > Hi all, > > > > > > TL;DR: > > > > > > Value

Re: [Numpy-discussion] Syntax Improvement for Array Transpose

+1 for this. I have often seen (and sometimes written) code that does this automatically, and it is a common mistake. However, we will need some way to filter for intent, as the people who write this code are the ones who didn’t read docs on it at the time, and so there might be a fair amount o

Re: [Numpy-discussion] Syntax Improvement for Array Transpose

Given that np.dot and np.matmul do the right thing for 1-D arrays, I would be opposed to introducing an error as well. From: NumPy-Discussion on behalf of Ilhan Polat Reply-To: Discussion of Numerical Python Date: Monday, 24. June 2019 at 11:58 To: Discussion of Numerical Python Subject:

Re: [Numpy-discussion] Syntax Improvement for Array Transpose

Hello Marten, I was suggesting not changing the shape at all, since dot/matmul/solve do the right thing already in such a case. In my proposal, only for ndim >=2 do we switch the last two dimensions. Ilhan is right that adding a special case for ndim=1 (error) adds programmer overhead, which i

Re: [Numpy-discussion] Problem with absolute value

: It's an error with how the integer is stored in memory and how you're running out of space. Regards, Hameer Abbasi On 03.07.19, 17:03, "NumPy-Discussion on behalf of Nicolas Rougier" wrote: Hi, I’m a bit surprised with the following code: >>&

[Numpy-discussion] uarray update: API changes, overhead and comparison to __array_function__

Hello all, I just wrote a blog post on uarray and how it compares against NumPy’s __array_function__ protocol. Give it a read here: https://labs.quansight.org/blog/2019/07/uarray-update-api-changes-overhead-and-comparison-to-__array_function__/ Best Regards, Hameer Abbasi

Re: [Numpy-discussion] Creating a sine wave with exponential decay

Hi Ram, No, NumPy doesn’t have a way. And it newer versions, it probably won’t create two arrays if all the dtypes match, it’ll do some magic to re use the existing ones, although it will use multiple loops instead of just one. You might want to look into NumExpr or Numba if you want an efficie

Re: [Numpy-discussion] Adding generic dtypes

Hi Sebastian; all: I plan to attend the dtype meeting. Monday 11 AM California time is fine for me. Best regards, Hameer Abbasi Get Outlook for iOS<https://aka.ms/o0ukef> From: NumPy-Discussion on behalf of Sebastian Berg Sent: Thursday, July 25, 2019

Re: [Numpy-discussion] NEP 31: Context-local and global overrides of the NumPy API

The full-text of the NEP is quoted below, apologies for not including it earlier: NEP 31 — Context-local and global overrides of the NumPy API :Author: Hameer Abbasi

[Numpy-discussion] NEP 31 — Context-local and global overrides of the NumPy API

: NEP 31 — Context-local and global overrides of the NumPy API :Author: Hameer Abbasi <mailto:habb...@quansight.com> :Author: Ralf Gommers <mailto:rgomm...@quansight.com> :Author

Re: [Numpy-discussion] NEP 31 — Context-local and global overrides of the NumPy API

Hi Nathaniel, On 02.09.19 23:09, Nathaniel Smith wrote: On Mon, Sep 2, 2019 at 2:15 AM Hameer Abbasi wrote: Me, Ralf Gommers and Peter Bell (both cc’d) have come up with a proposal on how to solve the array creation and duck array problems. The solution is outlined in NEP-31, currently in

Re: [Numpy-discussion] NEP 31 — Context-local and global overrides of the NumPy API

. NEP 31 — Context-local and global overrides of the NumPy API :Author: Hameer Abbasi :Author: Ralf Gommers :Author: Peter Bell :Status: Draft :Type: Standards Track :Created: 2019-08-22 Abstract This NEP proposes to

Re: [Numpy-discussion] NEP 31 — Context-local and global overrides of the NumPy API

Hameer or Quansight move onto other things. That seems like a lot to take on for such vague benefits? I can assure you Travis has had the goal of "replatforming SciPy" from as far back as I met him, he's spawned quite a few efforts in that direction along with others from Quansigh

Re: [Numpy-discussion] NEP 31 — Context-local and global overrides of the NumPy API

On 08.09.19 09:53, Nathaniel Smith wrote: On Fri, Sep 6, 2019 at 11:53 AM Ralf Gommers wrote: On Fri, Sep 6, 2019 at 12:53 AM Nathaniel Smith wrote: On Tue, Sep 3, 2019 at 2:04 AM Hameer Abbasi wrote: The fact that we're having to design more and more protocols for a lot of very si

Re: [Numpy-discussion] NEP 31 — Context-local and global overrides of the NumPy API

On 08.09.19 10:56, Nathaniel Smith wrote: On Sun, Sep 8, 2019 at 1:04 AM Hameer Abbasi wrote: On 08.09.19 09:53, Nathaniel Smith wrote: OTOH, __array_function__ doesn't allow this kind of simplification: if we were using __array_function__ for ufuncs, every library would have to special

Re: [Numpy-discussion] NEP 31 — Context-local and global overrides of the NumPy API

On 08.09.19 10:56, Nathaniel Smith wrote: On Sun, Sep 8, 2019 at 1:04 AM Hameer Abbasi wrote: On 08.09.19 09:53, Nathaniel Smith wrote: OTOH, __array_function__ doesn't allow this kind of simplification: if we were using __array_function__ for ufuncs, every library would have to special

Re: [Numpy-discussion] NEP 31 — Context-local and global overrides of the NumPy API

On 09.09.19 03:26, Nathaniel Smith wrote: [snip] Generic in the sense that you can write __array_ufunc__ once and have it work for all ufuncs. You can do that too with __ua_function__, you get np.ufunc.__call__, with self=. The same holds for say, RandomState objects, once implemented. Most

Re: [Numpy-discussion] NEP 31 — Context-local and global overrides of the NumPy API

On 10.09.19 05:32, Stephan Hoyer wrote: On Mon, Sep 9, 2019 at 6:27 PM Ralf Gommers > wrote: I think we've chosen to try the former - dispatch on functions so we can reuse the NumPy API. It could work out well, it could give some long-term maintenance i

Re: [Numpy-discussion] NEP 31 — Context-local and global overrides of the NumPy API

On 07.09.19 22:06, Sebastian Berg wrote: On Fri, 2019-09-06 at 14:45 -0700, Ralf Gommers wrote: Let me try to move the discussion from the github issue here (this may not be the best place). (https://github.com/numpy/numpy/issues/14441 which asked for easier creation functions together with `_

Re: [Numpy-discussion] "Spring cleaning" sprint

Is the meeting ongoing? I tried to join but there were no participants. On 10.10.19, 02:56, "NumPy-Discussion on behalf of Sebastian Berg" wrote: Hi all, we are planning to remote spring to try to reduce the number of open PRs and issues, and do triage work. This is p

Re: [Numpy-discussion] "Spring cleaning" sprint

My bad... It's not until later. On 15.10.19, 16:16, "NumPy-Discussion on behalf of Hameer Abbasi" wrote: Is the meeting ongoing? I tried to join but there were no participants. On 10.10.19, 02:56, "NumPy-Discussion on behalf of Sebastian Berg" w

Re: [Numpy-discussion] Recommended way to utilize GPUs via OpenCL, ROCm

Hello Pankaj, There's ClPy for OpenCL: https://github.com/fixstars/clpy Also this pull request for CuPy (merged, but as yet unreleased): https://github.com/cupy/cupy/pull/1094 Best regards, Hameer Abbasi On 18.10.19, 12:53, "NumPy-Discussion on behalf of Pankaj Jangid" wrote

[Numpy-discussion] New draft of NEP 31 — Context-local and global overrides of the NumPy API

793>. NEP 31 — Context-local and global overrides of the NumPy API :Author: Hameer Abbasi :Author: Ralf Gommers :Author: Peter Bell :Status: Draft :Type: Standards Track :Created: 2019-08-22 Ab

Re: [Numpy-discussion] Adding an nd generalization of np.ma.mask_rowscols

IMHO, masked arrays and extending masks like that is a weird API. I would prefer a more functional approach: Where we take in an input 1-D or N-D boolean array in addition to a masked array with multiple axes over which to extend the mask. From: NumPy-Discussion on behalf of Eric Wieser Rep

Re: [Numpy-discussion] NEP 38 - Universal SIMD intrinsics

—snip— > 1) Once NumPy adds the framework and initial set of Universal Intrinsic, if > contributors want to leverage a new architecture specific SIMD instruction, > will they be expected to add software implementation of this instruction for > all other architectures too? In my opinion, if the

Re: [Numpy-discussion] New DTypes: Are scalars a central concept in NumPy or not?

Hi, Sebastian, On 22.02.20, 02:37, "NumPy-Discussion on behalf of Sebastian Berg" wrote: Hi all, When we create new datatypes, we have the option to make new choices for the new datatypes [0] (not the existing ones). The question is: Should every NumPy datatype have a

[Numpy-discussion] Output type of round is inconsistent with python built-in

nd the following plan of action was proposed: * change scalar floats to return integers for __round__ (which integer type was not discussed, I propose np.int64) * not change anything else: not 0d arrays and not other numpy functionality Does an

Re: [Numpy-discussion] Output type of round is inconsistent with python built-in

Maybe not a big problem but can have significant impact. Best regards, Hameer Abbasi ___ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion

Re: [Numpy-discussion] Proposal: add `force=` or `copy=` kwarg to `__array__` interface

Hi! Yes, I would advocate for a `force=` kwarg but personally I don't think it's explicit enough, but probably as explicit as can be given NumPy's API. Personally, I'd also raise a warning within PyData/Sparse and I hope it's in big bold letters in the docs in NumPy to be careful with this. Get

[Numpy-discussion] Announcing PyData/Sparse 0.10.0

users who can upgrade to Numba 0.49 or later to upgrade to this release. For users who cannot update to this version, we recommend staying with 0.9.x until you can. Best regards, Hameer Abbasi ___ NumPy-Discussion mailing list NumPy-Discussion@python.org

Re: [Numpy-discussion] Using nditer + external_loop to Always Iterate by Column

help. In [1]: import numpy as np In [2]: a = np.arange(3).reshape((1, 3)) In [3]: for x in a.T: ...: print(x) ...: [0] [1] [2] Best regards, Hameer Abbasi From: NumPy-Discussion on behalf of William Ayd Reply to: Discussion of Numerical Python Date: Tuesday, 19. May 2020 a

Re: [Numpy-discussion] Experimental `like=` attribute for array creation functions

Hi, We should have a higher-bandwidth meeting/communication for all stakeholders, and particularly some library authors, to see what would be good for them. We should definitely have language in the NEP that says it won’t be in a release unless the NEP is accepted. Best regards, Hameer Abbasi

[Numpy-discussion] [Release] PyData/Sparse 0.11.0

sources and bug tracker: https://github.com/pydata/sparse The changelog for this release can be viewed at: https://sparse.pydata.org/en/0.11.0/changelog.html Best Regards, Hameer Abbasi -- Sent from Canary (https://canarymail.io) ___ NumPy-Discussion

[Numpy-discussion] [ANN] PyData/Sparse 0.11.1

. The official website and documentation is available at: https://sparse.pydata.org (https://sparse.pydata.org/) The sources and bug tracker: https://github.com/pydata/sparse The changelog for this release can be viewed at: https://sparse.pydata.org/en/0.11.1/changelog.html Best Regards, Hameer

Re: [Numpy-discussion] Request for comments on PEP 637 - Support for indexing with keyword arguments

, kw) arr[*a] # arr.__setitem__(a) arr[**kw] # arr.__setitem__((), kw) This is driven by my love for generality and hatred of special cases. So I’m +1 for empty tuple or the third form. Best regards, Hameer Abbasi -- Sent from Canary (https://canarymail.io) > On Friday, Sep 25, 2020 at 4:22

Re: [Numpy-discussion] Comment published in Nature Astronomy about The ecological impact of computing with Python

Hello, We’re trying to do a part of this in the TACO team, and with a Python wrapper in the form of PyData/Sparse. It will allow an abstract array/scheduling to take place, but there are a bunch of constraints, the most important one being that a C compiler cannot be required at runtime. Howev

Re: [Numpy-discussion] Comment published in Nature Astronomy about The ecological impact of computing with Python

that requirement. It can’t do arbitrary non-pointwise functions, e.g. SVD, inverse. This is a long way from being completely solved. As for why not Numba/llvmlite: Re-writing TACO is a large task that would be hard to do, wrapping/extending it is much easier. Best regards, Hameer Abbasi -- Sent

Re: [Numpy-discussion] Value based promotion and user DTypes

hoosing types. Which is nice. It eliminates whole classes of bugs. > > Or maybe better just limit it completely to always use the default for > user DTypes? > > > But I would be interested if the "limit to Python operators" is > something we should aim for here. This d

[Numpy-discussion] Announcing PyData/Sparse 0.13.0

ta.org/en/0.13.0/ <https://sparse.pydata.org/en/0.13.0/> Changelog: https://sparse.pydata.org/en/0.13.0/changelog.html <https://sparse.pydata.org/en/0.13.0/changelog.html> Best regards, Hameer Abbasi signature.asc Description: Message s

Re: [Numpy-discussion] deprecating float(x) for ndim > 0

Hello Nico, Any step in the direction of consistency and type safety is a good one to me. I’m +1 on this change. Best regards, Hameer Abbasi > Am 15.09.2021 um 14:18 schrieb Nico Schlömer : > > Hi everyone, > > This is seeking input on PR [1] which I've worked on wit

[Numpy-discussion] Re: spam on the mailing lists

, hoping it’ll get better, but it hasn’t so far. I’d very much prefer Discourse or GitHub discussions, of the two I prefer Discussions, but Discourse isn’t too bad either. With best regards, Hameer Abbasi > Am 06.10.2021 um 22:57 schrieb Aaron Meurer : > > Coming back to earth on the

[Numpy-discussion] Re: Make the pickle default protocol 4.

mailing list -- numpy-discussion@python.org > To unsubscribe send an email to numpy-discussion-le...@python.org > https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ > Member address: einstein.edi...@gmail.com Best regards, Hameer Abbasi __

[Numpy-discussion] Re: representation of valid float type range

points. I believe this would fix the issue here among many others. However, it was always rejected due to backward-incompatibility concerns. Perhaps it’s time to revisit this issue. Best regards, Hameer Abbasi > Am 10.01.2022 um 12:59 schrieb alejandro.giacome...@gmail.com: > > I se

[Numpy-discussion] Re: Out paramter for argsort?

, Hameer Abbasi Von meinem iPhone gesendet > Am 22.10.2022 um 17:51 schrieb Paul Rudin : > > Argsort returns its result in a new array. It would be useful if allocation > of the new array could be avoided when a suitable array is already available. > > Is there a reason wh

[Numpy-discussion] ANN: A new version (0.14.0) of sparse has been released.

I’d like to announce the release of PyData/Sparse 0.14.0. PyData/Sparse is available on conda-forge and PyPI. PyData/Sparse is a package that provides sparse arrays conforming to the NumPy API, along with a subset of NumPy operations on sparse arrays. The highlights of this release include fast

[Numpy-discussion] Re: welcome Raghuveer, Chris, Mateusz and Matt to the NumPy maintainers team

Welcome, Raghuveer, Chris, Mateusz and Matt! > Am 26.01.2024 um 21:04 schrieb Ralf Gommers : > > Hi all, > > We've got four new NumPy maintainers! Welcome to the team, and > congratulations to: > > - Raghuveer Devulapalli (https://github.com/r-devulap) > - Chris Sidebottom (https://github.com/

[Numpy-discussion] Re: ENH: Uniform interface for accessing minimum or maximum value of a dtype

I’d advocate for something like a `DTypeInfo` object in the Array API itself, with `max_value` and `min_value` being members. Of course, one would have to imagine how this would work with complex-valued dtypes, but I’d like API that returns an object rather than a million different calls, simila

[Numpy-discussion] Re: Invalid value encoutered : how to prevent numpy.where to do this?

Hi! You can use a context manager: with np.errstate(all=”ignore”): … Best regards, Hameer Abbasi Von meinem iPhone gesendet > Am 18.02.2023 um 16:00 schrieb David Pine : > > I agree. The problem can be avoided in a very inelegant way by turning > warnings off before calling

[Numpy-discussion] Re: removing NUMPY_EXPERIMENTAL_ARRAY_FUNCTION env var

+1 from my side as well.Von meinem iPhone gesendetAm 10.03.2023 um 19:10 schrieb Stephan Hoyer :+1 for removing this environment variable. It was never intended to stick around this long.On Fri, Mar 10, 2023 at 6:48 AM Ralf Gommers wrote:Hi all,In https://github.com/numpy/

[Numpy-discussion] ANN: PyData/Sparse 0.17.0 released

Hello all, PyData/Sparse > 0.17.0 is now available on GitHub , pypi and conda-forge. PyData/Sparse provides sparse multi-dimensional arrays for t

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