Dear Michael, Thank you for your feedback!
I've fixed the x86_64 typo. I'll think how to reformulate the int32 part. I work on debian x86_64 and windows 10 64bit. Constructing an array with np.array([1,2,3]) as well as np.array([1,2,3], dtype=np.int_) gives me int64 dtype on linux, and int32 on windows. As suggested by Matti, I've put the rst source (and images) into a separate github repository https://github.com/axil/numpy-data-types PRs are welcome. My primary concern is to exclude serious typos/mistakes that might mislead/harm the readers if used. My personal preference is towards explicit width types like np.int32, but from reading the docs I have a feeling there's a trend of migrating towards the c-style notation. Best regards, Lev On Sun, Dec 26, 2021 at 7:05 PM Michael Siebert <michael.sieber...@gmail.com> wrote: > Dear Lev, > > thank you a lot! Something like this should be part of the Numpy > documentation. I like the diagram, looks very nice! Also, I’ve opened an > issue regarding data types > > https://github.com/numpy/numpy/issues/20662 > > Some feedback from my side: > > 1. When calling numpy.array([1,2,3,4]) it gives me an int64 data type most > of the time (two x86_64 systems, one arm64 system). The only time I’ve got > int32 was on a Raspberry Pi, which is a software limitation, since the CPU > is 64 bit and they have even replaced their so-far 32bit only Raspberry Pi > Zero with a 64bit version (yes, one day Raspberry OS with 64 bit might > actually become the default!). I don’t know what machine you are working > on, but int64 should be the default. > 2. x64 refers to the obsolete Intel Itanium architecture (mentioned once). > Should be x86_64. > 3. np.errstate looks nice, I could use that for my pull request as well. > > Many thanks & best regards, Michael > > > On 25. Dec 2021, at 10:02, Lev Maximov <lev.maxi...@gmail.com> wrote: > > Hi everyone, > > I'm almost done with the article about numpy types – something I haven't > covered in Numpy Illustrated. > > Would someone please have a look to confirm I haven't written anything > anti-climatic there? > > https://axil.github.io/numpy-data-types.html > > -- > Best regards, > Lev > > PS Earlier today I've mistakenly sent an email with the wrong link. > _______________________________________________ > NumPy-Discussion 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: michael.sieber...@gmail.com > > > _______________________________________________ > NumPy-Discussion 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: lev.maxi...@gmail.com >
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