Re: [Numpy-discussion] NumPy-Discussion Digest, Vol 180, Issue 9

Thank you for offering your help, Holam! We have quite a few options for you. If you’d like to help us improve numpy.org, this is the latest discussion on this topic: https://github.com/numpy/numpy.org/issues/342 . We could also apply your graphic design skills to enhance our documentation and educ

Re: [Numpy-discussion] NumPy-Discussion Digest, Vol 171, Issue 39

On Tue, Dec 29, 2020 at 5:35 PM Brian Soto wrote: > I'm still learning proper mailing list etiquette so I'm not sure if this > is where I should respond. > FWIW, if you want to reply to conversations regularly, it's more ergonomic all around to subscribe regularly and not use the digests. But if

Re: [Numpy-discussion] NumPy-Discussion Digest, Vol 171, Issue 39

I'm still learning proper mailing list etiquette so I'm not sure if this is where I should respond. But users just getting into debugging might also benefit from knowing this: You can turn off optimizations when compiling numpy by passing CFLAGS to setup.py like so: *CFLAGS="-O0 -g3" python setup

Re: [Numpy-discussion] NumPy-Discussion Digest, Vol 163, Issue 23

g ArrayLike to the top > level NumPy namespace as np.ArrayLike. > > Type annotations are becoming an increasingly core part of modern Python > code. We should make it easy to appropriately type check functions that act > on NumPy arrays, and a top level np.ArrayLike is definitely more conven

Re: [Numpy-discussion] NumPy-Discussion Digest, Vol 162, Issue 27

n/NumPy. > > > > I am not quite sure, but maybe memory fragmentation plays its part, or > > simply are actually out of memory for that process, 1.44TB is a > > significant portion of the total memory after all. > > > > Not sure what to say, but I think you should probab

Re: [Numpy-discussion] NumPy-Discussion Digest, Vol 161, Issue 14

Documentation is imperative for project sustainability, yet often overlooked. Millions of NumPy stakeholders will benefit from this initiative. Melissa, Mars and Ralf, thank you for taking a lead on this! On Thu, Feb 13, 2020 at 3:05 AM wrote: > Send NumPy-Discussion mailing list submissions to

Re: [Numpy-discussion] NumPy-Discussion Digest, Vol 148, Issue 27

I start to learn python from 《Numpy Beginner's Guide》second edition written by Ivan Idris now I know what the problem is ,the reason is that Numpy converts 2000 to an `int32`.When I use code `a=np.arange(2000, dtype='int64')**3 that you taught me, the calculation is correct thank you all ! Yu

Re: [Numpy-discussion] Numpy-discussion

. -CHB > > > Matti > > ___ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion _______ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion

Re: [Numpy-discussion] Numpy-discussion

On Tue, 29 Jan 2019 10:15:00 +0200, Matti Picus wrote: > 2000*2000*2000 overflows a 32 bit signed integer, so it wraps around to a > negative value. I was curious about what happens, bit-wise, in this case. We are dealing with a signed integer, so I presume of the 33 bits in 2000**3, only 32 are

Re: [Numpy-discussion] Numpy-discussion

On 29/1/19 9:22 am, Yuping Wang wrote: Dear Nmupy developers and users:         I am a new user of Numpy ,I have encountered a question about Numpy recently, which need your help. The question is below:      I don  know why there are negative numbers      can somebody explain to me why these

Re: [Numpy-discussion] Numpy-discussion

ussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion

[Numpy-discussion] Numpy-discussion

Dear Nmupy developers and users: I am a new user of Numpy ,I have encountered a question about Numpy recently, which need your help. The question is below: I don know why there are negative numbers can somebody explain to me why these happens Thanks in advan

Re: [Numpy-discussion] NumPy-Discussion Digest, Vol 140, Issue 25

If someone implements a separate library for masked arrays without changing anything in numpy and its better and people use it then maybe the deprecation of it in numpy would be wise. But for me it seems like a large disruption to force such a transition. Much in the way that the numeric standa

Re: [Numpy-discussion] NumPy-Discussion Digest, Vol 134, Issue 10

On 04/11/17 18:00, numpy-discussion-requ...@python.org wrote: Date: Fri, 3 Nov 2017 20:56:38 -0600 From: Charles R Harris To: numpy-discussion Subject: [Numpy-discussion] NumPy 1.14 branch. Message-ID: Content-Type: text/plain; charset="utf-8" Hi All,

Re: [Numpy-discussion] NumPy-Discussion Digest, Vol 132, Issue 1

mail.gmail.com> > Content-Type: text/plain; charset="UTF-8" > > str(numpy.version.citation) and numpy.version.citation.to_bibtex()? > > On Tue, Sep 5, 2017 at 2:15 PM, Paul Hobson wrote: > > Just a thought that popped into my head: > > It'd be cool with the sci/py/data stack had a convent

Re: [Numpy-discussion] [NumPy-discussion] Wish List of Possible ufunc Enhancements

On Fri, Apr 28, 2017 at 9:53 AM, Matthew Harrigan wrote: > Here is a link to a wish list of possible ufunc enhancements. I would like > to know what the community thinks. It looks like a pretty good list of ideas worth thinking about as and when someone has time :-). I'm not sure what feedback y

[Numpy-discussion] [NumPy-discussion] Wish List of Possible ufunc Enhancements

Here is a link to a wish list of possible ufunc enhancements. I would like to know what the community thinks. Thank you, Matt Harrigan ___ NumPy-Discussion mailing list NumPy-Discus