Mailman 3 March 2021 - NumPy-Discussion

ANN: SfePy 2021.1
by Robert Cimrman March 29, 2021

March 29, 2021

I am pleased to announce the release of SfePy 2021.1. Description ----------- SfePy (simple finite elements in Python) is a software for solving systems of coupled partial differential equations by finite element methods. It is distributed under the new BSD license. Home page: https://sfepy.org Mailing list: https://mail.python.org/mm3/mailman3/lists/sfepy.python.org/ Git (source) repository, issue tracker: https://github.com/sfepy/sfepy Highlights of this release -------------------------- - non-square homogenized coefficient matrices - new implementation of multi-linear terms - improved handling of Dirichlet and periodic boundary conditions in common nodes - terms in the term table document linked to examples For full release notes see [1]. Cheers, Robert Cimrman [1] http://docs.sfepy.org/doc/release_notes.html#id1 --- Contributors to this release in alphabetical order: Robert Cimrman Antony Kamp Vladimir Lukes

1 0

Unreliable crash when converting using numpy.asarray via C buffer interface
by Friedrich Romstedt March 29, 2021

March 29, 2021

Hi, This is with Python 3.8.2 64-bit and numpy 1.19.2 on Windows 10. I'd like to be able to convert some C++ extension type to a numpy array by using ``numpy.asarray``. The extension type implements the Python buffer interface to support this. The extension type, called "Image" here, holds some chunk of ``double``, C order, contiguous, 2 dimensions. It "owns" the buffer; the buffer is not shared with other objects. The following Python code crashes:: image = <... Image production ...> ar = numpy.asarray(image) However, when I say:: image = <... Image production ...> print("---") ar = numpy.asarray(image) the entire program is executing properly with correct data in the numpy ndarray produced using the buffer interface. The extension type permits reading the pixel values by a method; copying them over by a Python loop works fine. I am ``Py_INCREF``-ing the producer in the C++ buffer view creation function properly. The shapes and strides of the buffer view are ``delete[]``-ed upon releasing the buffer; avoiding this does not prevent the crash. I am catching ``std::exception`` in the view creation function; no such exception occurs. The shapes and strides are allocated by ``new Py_ssize_t[2]``, so they will survive the view creation function. I spent some hours trying to figure out what I am doing wrong. Maybe someone has an idea about this? I double-checked each line of code related to this problem and couldn't find any mistake. Probabaly I am not looking at the right aspect. Best, Friedrich

7 16

Japanese translation of numpy.org complete - proofreader help wanted
by Ralf Gommers March 28, 2021

March 28, 2021

Hi all, We have our first complete translation of the numpy.org content, Japanese, thanks to Atsushi Sakai. It would be really helpful if someone else who speaks Japanese can proofread the translations. Then it's ready to deploy I think - we just need to enable the language switcher widget, the code for that was tested already. Proofreading is done in Crowdin, which is a friendly interface for translators see - https://github.com/numpy/numpy/wiki/Translations-of-the-NumPy-website. This should not take more than an hour or two I think, and would be a very valuable contribution. If you'd like to do this and want help, or report that it all looks good, you can reply here, comment on the PR that the crowdin bot opened (https://github.com/numpy/numpy.org/pull/385), or use the Discussions tab in Crowdin. The Brazilian Portuguese translation is also close to complete (72%). If anyone feels motivated to complete that, that'd be great too - it could be taken along in the initial launch then. There were also some discussions about correct Portuguese terminology I believe, Melissa could you point to those in case that is relevant for completion? Cheers, Ralf

1 0

NumPy 1.20.2 released.
by Charles R Harris March 27, 2021

March 27, 2021

Charles R Harris <charlesr.harris(a)gmail.com> Sun, Feb 7, 2:23 PM to numpy-discussion, SciPy, SciPy-User, bcc: python-announce-list Hi All, On behalf of the NumPy team I am pleased to announce the release of NumPy 1.20.2. NumPy 1,20.2 is a bugfix release containing several fixes merged to the main branch after the NumPy 1.20.1 release. The Python versions supported for this release are 3.7-3.9. Wheels can be downloaded from PyPI <https://pypi.org/project/numpy/1.20.2/>; source archives, release notes, and wheel hashes are available on Github <https://github.com/numpy/numpy/releases/tag/v1.20.2>. Linux users will need pip >= 0.19.3 in order to install manylinux2010 and manylinux2014 wheels. *Contributors* A total of 7 people contributed to this release. People with a "+" by their names contributed a patch for the first time. - Allan Haldane - Bas van Beek - Charles Harris - Christoph Gohlke - Mateusz Sokół + - Michael Lamparski - Sebastian Berg *Pull requests merged* A total of 20 pull requests were merged for this release. - #18382: MAINT: Update f2py from master. - #18459: BUG: ``diagflat`` could overflow on windows or 32-bit platforms - #18460: BUG: Fix refcount leak in f2py ``complex_double_from_pyobj``. - #18461: BUG: Fix tiny memory leaks when ``like=`` overrides are used - #18462: BUG: Remove temporary change of descr/flags in VOID functions - #18469: BUG: Segfault in nditer buffer dealloc for Object arrays - #18485: BUG: Remove suspicious type casting - #18486: BUG: remove nonsensical comparison of pointer < 0 - #18487: BUG: verify pointer against NULL before using it - #18488: BUG: check if PyArray_malloc succeeded - #18546: BUG: incorrect error fallthrough in nditer - #18559: CI: Backport CI fixes from main. - #18599: MAINT: Add annotations for `dtype.__getitem__`, `__mul__` and... - #18611: BUG: NameError in numpy.distutils.fcompiler.compaq - #18612: BUG: Fixed ``where`` keyword for ``np.mean`` & ``np.var`` methods - #18617: CI: Update apt package list before Python install - #18636: MAINT: Ensure that re-exported sub-modules are properly annotated - #18638: BUG: Fix ma coercion list-of-ma-arrays if they do not cast to... - #18661: BUG: Fix small valgrind-found issues - #18671: BUG: Fix small issues found with pytest-leaks Cheers, Charles Harris

1 0

ANN: SciPy 1.6.2
by Tyler Reddy March 25, 2021

March 25, 2021

Hi all, On behalf of the SciPy development team I'm pleased to announce the release of SciPy 1.6.2, which is a bug fix release. Sources and binary wheels can be found at: https://pypi.org/project/scipy/ and at: https://github.com/scipy/scipy/releases/tag/v1.6.2 <https://github.com/scipy/scipy/releases/tag/v1.6.1> One of a few ways to install this release with pip: pip install scipy==1.6.2 ===================== SciPy 1.6.2 Release Notes ===================== SciPy 1.6.2 is a bug-fix release with no new features compared to 1.6.1. This is also the first SciPy release to place upper bounds on some dependencies to improve the long-term repeatability of source builds. Authors ====== * Pradipta Ghosh + * Tyler Reddy * Ralf Gommers * Martin K. Scherer + * Robert Uhl * Warren Weckesser A total of 6 people contributed to this release. People with a "+" by their names contributed a patch for the first time. This list of names is automatically generated, and may not be fully complete. Issues closed for 1.6.2 ------------------------------ * `#13512 <https://github.com/scipy/scipy/issues/13512>`__: \`stats.gaussian_kde.evaluate\` broken on S390X * `#13584 <https://github.com/scipy/scipy/issues/13584>`__: rotation._compute_euler_from_matrix() creates an array with negative... * `#13585 <https://github.com/scipy/scipy/issues/13585>`__: Behavior change in coo_matrix when dtype=None * `#13686 <https://github.com/scipy/scipy/issues/13686>`__: delta0 argument of scipy.odr.ODR() ignored Pull requests for 1.6.2 ------------------------------ * `#12862 <https://github.com/scipy/scipy/pull/12862>`__: REL: put upper bounds on versions of dependencies * `#13575 <https://github.com/scipy/scipy/pull/13575>`__: BUG: fix \`gaussian_kernel_estimate\` on S390X * `#13586 <https://github.com/scipy/scipy/pull/13586>`__: BUG: sparse: Create a utility function \`getdata\` * `#13598 <https://github.com/scipy/scipy/pull/13598>`__: MAINT, BUG: enforce contiguous layout for output array in Rotation.as_euler * `#13687 <https://github.com/scipy/scipy/pull/13687>`__: BUG: fix scipy.odr to consider given delta0 argument Checksums ========= MD5 ~~~ fc81d43879a28270d593aaea37c74ff8 scipy-1.6.2-cp37-cp37m-macosx_10_9_x86_64.whl 9213533bfd3c2f1563d169009c39825c scipy-1.6.2-cp37-cp37m-manylinux1_i686.whl 2ddd03b89efdb1619fa995da7b83aa6f scipy-1.6.2-cp37-cp37m-manylinux1_x86_64.whl d378f725958bd6a83db7ef23e8659762 scipy-1.6.2-cp37-cp37m-manylinux2014_aarch64.whl 87bc2771b8a8ab1f10168b1563300415 scipy-1.6.2-cp37-cp37m-win32.whl 861dab18fe41e82c08c8f585f2710545 scipy-1.6.2-cp37-cp37m-win_amd64.whl d2e2002b526adeebf94489aa95031f54 scipy-1.6.2-cp38-cp38-macosx_10_9_x86_64.whl 2dc36bfbe3938c492533604aba002c17 scipy-1.6.2-cp38-cp38-manylinux1_i686.whl 0114de2118d41f9440cf86fdd67434fc scipy-1.6.2-cp38-cp38-manylinux1_x86_64.whl ede6db56b1bf0a7fed0c75acac7dcb85 scipy-1.6.2-cp38-cp38-manylinux2014_aarch64.whl 191636ac3276da0ee9fd263b47927b73 scipy-1.6.2-cp38-cp38-win32.whl 8bdf7ab041b9115b379f043bb02d905f scipy-1.6.2-cp38-cp38-win_amd64.whl 608c82b227b6077d9a7871ac6278e64d scipy-1.6.2-cp39-cp39-macosx_10_9_x86_64.whl 4c0313b2cccc85666b858ffd692a3c87 scipy-1.6.2-cp39-cp39-manylinux1_i686.whl 92da8ffe165034dbbe5f098d0ed58aec scipy-1.6.2-cp39-cp39-manylinux1_x86_64.whl b4b225fb1deeaaf0eda909fdd3bd6ca6 scipy-1.6.2-cp39-cp39-manylinux2014_aarch64.whl 662969220eadbb6efec99030e4d00268 scipy-1.6.2-cp39-cp39-win32.whl f19186d6d91c7e37000e9f6ccd9b9b60 scipy-1.6.2-cp39-cp39-win_amd64.whl cbcb9b39bd9d877ad3deeccc7c37bb7f scipy-1.6.2.tar.gz b56e705c653ad808a9725dfe840d1258 scipy-1.6.2.tar.xz 6f615549670cd3d312dc9e4359d2436a scipy-1.6.2.zip SHA256 ~~~~~~ 77f7a057724545b7e097bfdca5c6006bed8580768cd6621bb1330aedf49afba5 scipy-1.6.2-cp37-cp37m-macosx_10_9_x86_64.whl e547f84cd52343ac2d56df0ab08d3e9cc202338e7d09fafe286d6c069ddacb31 scipy-1.6.2-cp37-cp37m-manylinux1_i686.whl bc52d4d70863141bb7e2f8fd4d98e41d77375606cde50af65f1243ce2d7853e8 scipy-1.6.2-cp37-cp37m-manylinux1_x86_64.whl adf7cee8e5c92b05f2252af498f77c7214a2296d009fc5478fc432c2f8fb953b scipy-1.6.2-cp37-cp37m-manylinux2014_aarch64.whl e3e9742bad925c421d39e699daa8d396c57535582cba90017d17f926b61c1552 scipy-1.6.2-cp37-cp37m-win32.whl ffdfb09315896c6e9ac739bb6e13a19255b698c24e6b28314426fd40a1180822 scipy-1.6.2-cp37-cp37m-win_amd64.whl 6ca1058cb5bd45388041a7c3c11c4b2bd58867ac9db71db912501df77be2c4a4 scipy-1.6.2-cp38-cp38-macosx_10_9_x86_64.whl 993c86513272bc84c451349b10ee4376652ab21f312b0554fdee831d593b6c02 scipy-1.6.2-cp38-cp38-manylinux1_i686.whl 37f4c2fb904c0ba54163e03993ce3544c9c5cde104bcf90614f17d85bdfbb431 scipy-1.6.2-cp38-cp38-manylinux1_x86_64.whl 96620240b393d155097618bcd6935d7578e85959e55e3105490bbbf2f594c7ad scipy-1.6.2-cp38-cp38-manylinux2014_aarch64.whl 03f1fd3574d544456325dae502facdf5c9f81cbfe12808a5e67a737613b7ba8c scipy-1.6.2-cp38-cp38-win32.whl 0c81ea1a95b4c9e0a8424cf9484b7b8fa7ef57169d7bcc0dfcfc23e3d7c81a12 scipy-1.6.2-cp38-cp38-win_amd64.whl c1d3f771c19af00e1a36f749bd0a0690cc64632783383bc68f77587358feb5a4 scipy-1.6.2-cp39-cp39-macosx_10_9_x86_64.whl 50e5bcd9d45262725e652611bb104ac0919fd25ecb78c22f5282afabd0b2e189 scipy-1.6.2-cp39-cp39-manylinux1_i686.whl 816951e73d253a41fa2fd5f956f8e8d9ac94148a9a2039e7db56994520582bf2 scipy-1.6.2-cp39-cp39-manylinux1_x86_64.whl 1fba8a214c89b995e3721670e66f7053da82e7e5d0fe6b31d8e4b19922a9315e scipy-1.6.2-cp39-cp39-manylinux2014_aarch64.whl e89091e6a8e211269e23f049473b2fde0c0e5ae0dd5bd276c3fc91b97da83480 scipy-1.6.2-cp39-cp39-win32.whl d744657c27c128e357de2f0fd532c09c84cd6e4933e8232895a872e67059ac37 scipy-1.6.2-cp39-cp39-win_amd64.whl e9da33e21c9bc1b92c20b5328adb13e5f193b924c9b969cd700c8908f315aa59 scipy-1.6.2.tar.gz 8fadc443044396283c48191d48e4e07a3c3b6e2ae320b1a56e76bb42929e84d2 scipy-1.6.2.tar.xz 2af283054d91865336b4579aa91f9e59d648d436cf561f96d4692008f795c750 scipy-1.6.2.zip

1 0

Programmatically contracting multiple tensors
by Michael Lamparski March 25, 2021

March 25, 2021

Greetings, I have something in my code where I can receive an array M of unknown dimensionality and a list of "labels" for each axis. E.g. perhaps I might get an array of shape (2, 47, 3, 47, 3) with labels ['spin', 'atom', 'coord', 'atom', 'coord']. For every axis that is labeled "coord", I want to multiply in some rotation matrix R. So, for the above example, this could be done with the following handwritten line: return np.einsum('Cc,Ee,abcde->abCdE', R, R, M) But since I want to do this programmatically, I find myself in the awkward situation of having to construct this string (and e.g. having to arbitrarily limit the number of axes to 26 or something like that). Is there a more idiomatic way to do this that would let me supply integer labels for summation indices? Or should I just bite the bullet and start generating strings? --- Michael

3 3

NumPy Development Meeting Wednesday - Triage Focus
by Sebastian Berg March 24, 2021

March 24, 2021

Hi all, Our bi-weekly triage-focused NumPy development meeting is Wednesday, March 10th at 11 am Pacific Time (18:00 UTC). Everyone is invited to join in and edit the work-in-progress meeting topics and notes: https://hackmd.io/68i_JvOYQfy9ERiHgXMPvg I encourage everyone to notify us of issues or PRs that you feel should be prioritized, discussed, or reviewed. Best regards Sebastian

1 0

PyData/Sparse 0.12.0 Release Announcement
by Hameer Abbasi March 19, 2021

March 19, 2021

Apologies in advance for the cross-post! I’m happy to announce the release of PyData/Sparse 0.12.0! PyData/Sparse provides sparse arrays with a NumPy-like API for the PyData ecosystem. This is a large release with GCXS support, preliminary CSR/CSC support and extensions to DOK, as well as bugfixes. Changelog: https://sparse.pydata.org/en/stable/changelog.html Documentation: https://sparse.pydata.org/ Source: https://github.com/pydata/sparse/ Best regards, Hameer Abbasi -- Sent from Canary (https://canarymail.io)

1 0

Google Season of Docs 2021
by Melissa Mendonça March 17, 2021

March 17, 2021

Hello, folks! NumPy is hoping to participate again in Google Season of Docs this year, and we have a couple of project ideas listed here: https://github.com/numpy/numpy/wiki/Google-Season-of-Docs-2021-Project-Ideas This year, GSoD has a different structure: we must choose only one project idea (ideally, the one prospective technical writers are most interested in) and submit a sort of grant proposal (details are here: https://developers.google.com/season-of-docs/docs/admin-guide). If we are selected, we can hire up to 2 technical writers to work on our project, depending on the budget allocated to us by Google. The final proposal must be submitted by March 26 (you can find the complete timeline here https://developers.google.com/season-of-docs/docs/timeline). Feedback and input is appreciated, and please feel free to share with technical writers who may be interested. Cheers, - Melissa

1 0

NumPy Community Meeting Wednesday (no DST: for those in the US, one hour later)
by Sebastian Berg March 16, 2021

March 16, 2021

Hi all, There will be a NumPy Community meeting Wednesday March 3rd at 20:00 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: As the subject says, we will stay on UTC 20:00, so for those in the US and anyone else who had daylight saving times switches the time will have shifted.

1 0