Mailman 3 August 2019 - SciPy-Dev

Matrix identification methods
by Joseph Gama Aug. 15, 2019

Aug. 15, 2019

Hi, Just submitted a PR with these methods:is_matrix_hermitianis_matrix_symmetricis_matrix_skew_symmetric is_matrix_nonsingularis_matrix_singularis_matrix_idempotentis_matrix_positive_definiteis_matrix_positive_semidefiniteis_matrix_negative_definiteis_matrix_negative_semidefiniteis_matrix_indefinite Feedback is welcome. :) https://github.com/tuxcell/scipy/tree/helperfuncs

2 2

triage team
by Ralf Gommers Aug. 15, 2019

Aug. 15, 2019

Hi all, Now that GitHub has introduced triage permissions [1] and we've got Season of Docs starting, I have create a triage team [2] for the SciPy org. This allows labelling closing/reopening/assigning issues and PRs. I've invited a few people already, if anyone else would like an invite please let me know. Cheers, Ralf [1] https://github.blog/changelog/2019-05-23-triage-and-maintain-roles-beta/ [2] https://github.com/orgs/scipy/teams/triage

2 2

NaN insensitive circular statistics
by Burrell, Angeline Aug. 14, 2019

Aug. 14, 2019

Second attempt for a response for a new feature to scipy.stats, since I was alerted that my first email was going into spam folders. I do hope to hear back (positively or negatively) from the community. I have NaN insensitive versions of the SciPy circular mean and standard deviation routines that I would like to contribute to the scipy.stats subpackage. Since the hacking guidelines recommend discussing new contributions on this mailing list, I'd like to get the communal go-ahead before proceeding to integrate the routines and unit tests into scipy. For consistency, I would also add a NaN insensitive version of the circular variance routine. Cheers, Angeline ----------------------------------------------------- Dr. Angeline G. Burrell [she/her/hers] Research Physicist, Bldg. 209 Naval Research Laboratory (NRL) 4555 Overlook Ave SW Washington, DC 20375 (P) 202-404-4065 -----------------------------------------------------

1 0

Using OpenMP in SciPy
by Peter Bell Aug. 9, 2019

Aug. 9, 2019

Hello all, I'd like to revisit a discussion started a while ago in gh-10239<https://github.com/scipy/scipy/issues/10239>: Can we build and use OpenMP in a portable way? andyfaff<https://github.com/scipy/scipy/issues/10239>'s comment on the issue pointed out a number of portability issues that he's experienced that put him off of OpenMP. Summarising: 1. macOS's apple clang doesn't support openmp and supporting OpenMP requires distributing a runtime with your library. 2. On macOS, the openmp version crashes if mkl numpy is installed. This is a general problem because several different OpenMP runtimes exist. 3. openmp doesn't play nicely with multiprocessing.Pool To expand on that 3rd point, some openmp runtimes aren't fork-safe. Most notably, this includes gcc's libgomp. Upon entering the first openmp parallel region, the runtime initializes a thread pool which won't be rebuilt in the child after fork. This means that any parallel regions in the child will deadlock. Single threaded openmp loops seem to be safe though. Eric Larson has also recently had a chat with an sklearn maintainer which has been using OpenMP in the wild for ~6 months. A few of the key take-aways from his discussion were: * Packaging OpenMP code has many pitfalls but they think they've found a solution that works for them. * They use joblib with the "loky" backend to avoid multiprocessing and the associated forking issues. * They had issues related to incompatibility with macOS Accelerate for BLAS/LAPACK but SciPy has already dropped support for accelerate<https://github.com/scipy/scipy/wiki/Dropping-support-for-Accelerate>. * Some macOS users still needed the option to compile the library without OpenMP. Although, this might have also been Accelerate related. So, given these issues, are we willing to use OpenMP in SciPy? Peter

4 7

ANN: SciPy 1.3.1
by Tyler Reddy Aug. 9, 2019

Aug. 9, 2019

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA256 Hi all, On behalf of the SciPy development team I'm pleased to announce the release of SciPy 1.3.1, 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/v1.3.1 One of a few ways to install this release with pip: pip install scipy==1.3.1 ========================== SciPy 1.3.1 Release Notes ========================== SciPy 1.3.1 is a bug-fix release with no new features compared to 1.3.0. Authors ======= * Matt Haberland * Geordie McBain * Yu Feng * Evgeni Burovski * Sturla Molden * Tapasweni Pathak * Eric Larson * Peter Bell * Carlos Ramos Carreño + * Ralf Gommers * David Hagen * Antony Lee * Ayappan P * Tyler Reddy * Pauli Virtanen A total of 15 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 1.3.1 ------------------------------- * `#5040 <https://github.com/scipy/scipy/issues/5040>`__: BUG: Empty data handling of (c)KDTrees * `#9901 <https://github.com/scipy/scipy/issues/9901>`__: lsoda fails to detect stiff problem when called from solve_ivp * `#10206 <https://github.com/scipy/scipy/issues/10206>`__: sparse matrices indexing with scipy 1.3 * `#10232 <https://github.com/scipy/scipy/issues/10232>`__: Exception in loadarff with quoted nominal attributes in scipy... * `#10292 <https://github.com/scipy/scipy/issues/10292>`__: DOC/REL: Some sections of the release notes are not nested correctly. * `#10303 <https://github.com/scipy/scipy/issues/10303>`__: BUG: optimize: `linprog` failing TestLinprogSimplexBland::test_unbounded_below_no_presolve_corrected * `#10376 <https://github.com/scipy/scipy/issues/10376>`__: TST: Travis CI fails (with pytest 5.0 ?) * `#10384 <https://github.com/scipy/scipy/issues/10384>`__: CircleCI doc build failing on new warnings * `#10398 <https://github.com/scipy/scipy/issues/10398>`__: Scipy 1.3.0 build broken in AIX * `#10501 <https://github.com/scipy/scipy/issues/10501>`__: BUG: scipy.spatial.HalfspaceIntersection works incorrectly * `#10514 <https://github.com/scipy/scipy/issues/10514>`__: BUG: cKDTree GIL handling is incorrect * `#10535 <https://github.com/scipy/scipy/issues/10535>`__: TST: master branch CI failures * `#10572 <https://github.com/scipy/scipy/issues/10572>`__: BUG: ckdtree query_ball_point errors on discontiguous input * `#10597 <https://github.com/scipy/scipy/issues/10597>`__: BUG: No warning on PchipInterpolator changing from bernstein base to local power base Pull requests for 1.3.1 ------------------------------ * `#10071 <https://github.com/scipy/scipy/pull/10071>`__: DOC: reconstruct SuperLU permutation matrices avoiding SparseEfficiencyWarning * `#10196 <https://github.com/scipy/scipy/pull/10196>`__: Fewer checks on xdata for curve_fit. * `#10207 <https://github.com/scipy/scipy/pull/10207>`__: BUG: Compressed matrix indexing should return a scalar * `#10233 <https://github.com/scipy/scipy/pull/10233>`__: Fix for ARFF reader regression (#10232) * `#10306 <https://github.com/scipy/scipy/pull/10306>`__: BUG: optimize: Fix for 10303 * `#10309 <https://github.com/scipy/scipy/pull/10309>`__: BUG: Pass jac=None directly to lsoda * `#10377 <https://github.com/scipy/scipy/pull/10377>`__: TST, MAINT: adjustments for pytest 5.0 * `#10379 <https://github.com/scipy/scipy/pull/10379>`__: BUG: sparse: set writeability to be forward-compatible with numpy>=1.17 * `#10426 <https://github.com/scipy/scipy/pull/10426>`__: MAINT: Fix doc build bugs * `#10431 <https://github.com/scipy/scipy/pull/10431>`__: Update numpy version for AIX * `#10457 <https://github.com/scipy/scipy/pull/10457>`__: BUG: Allow ckdtree to accept empty data input * `#10503 <https://github.com/scipy/scipy/pull/10503>`__: BUG: spatial/qhull: get HalfspaceIntersection.dual_points from the correct array * `#10516 <https://github.com/scipy/scipy/pull/10516>`__: BUG: Use nogil contexts in cKDTree * `#10520 <https://github.com/scipy/scipy/pull/10520>`__: DOC: Proper .rst formatting for deprecated features and Backwards incompatible changes * `#10540 <https://github.com/scipy/scipy/pull/10540>`__: MAINT: Fix Travis and Circle * `#10573 <https://github.com/scipy/scipy/pull/10573>`__: BUG: Fix query_ball_point with discontiguous input * `#10600 <https://github.com/scipy/scipy/pull/10600>`__: BUG: interpolate: fix broken conversions between PPoly/BPoly objects Checksums ========= MD5 ~~~ 818dc6325a4511d656582ff2946eed80 scipy-1.3.1-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 83a11b3127b19e71353ee2a04c4be20c scipy-1.3.1-cp35-cp35m-manylinux1_i686.whl 49c52e00706b47b7311171fe37b9efac scipy-1.3.1-cp35-cp35m-manylinux1_x86_64.whl 015b3d443e2a9e4e664a50af64a7f5b6 scipy-1.3.1-cp35-cp35m-win32.whl 43cf62be72bf7b8e42a1a0fad6570e22 scipy-1.3.1-cp35-cp35m-win_amd64.whl 08d697cdeeb2a4121bbeca8d8d756da9 scipy-1.3.1-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 25f6364aa052213d4f504bc96031e431 scipy-1.3.1-cp36-cp36m-manylinux1_i686.whl 2fb8c8c5c17dd7d811165b59d070ef4a scipy-1.3.1-cp36-cp36m-manylinux1_x86_64.whl 6559f4a0438d849cac85ea57f1baa3ba scipy-1.3.1-cp36-cp36m-win32.whl 8164a4832b3b5e948135b92f91d6e8fa scipy-1.3.1-cp36-cp36m-win_amd64.whl 1054925a3d2130f803b27a30e8779282 scipy-1.3.1-cp37-cp37m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl cf90a33975bfcd08f7275bbc885785cf scipy-1.3.1-cp37-cp37m-manylinux1_i686.whl a9f6dbda23d81ff544d5e0debcc78320 scipy-1.3.1-cp37-cp37m-manylinux1_x86_64.whl 701657c017eb5164582035232bde5769 scipy-1.3.1-cp37-cp37m-win32.whl f7d8824ff9193c34b10017a1d67ce9fe scipy-1.3.1-cp37-cp37m-win_amd64.whl 69db58ceb4b4c3ff3f3ea816e4e426b9 scipy-1.3.1.tar.gz 66e95ade5399a9a336c1b2b78edb2d3a scipy-1.3.1.tar.xz 62ebcbc144342800c5e6b1c3ba86ba0d scipy-1.3.1.zip SHA256 ~~~~~~ 3ae3692616975d3c10aca6d574d6b4ff95568768d4525f76222fb60f142075b9 scipy-1.3.1-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 7ccfa44a08226825126c4ef0027aa46a38c928a10f0a8a8483c80dd9f9a0ad44 scipy-1.3.1-cp35-cp35m-manylinux1_i686.whl cbc0611699e420774e945f6a4e2830f7ca2b3ee3483fca1aa659100049487dd5 scipy-1.3.1-cp35-cp35m-manylinux1_x86_64.whl 435d19f80b4dcf67dc090cc04fde2c5c8a70b3372e64f6a9c58c5b806abfa5a8 scipy-1.3.1-cp35-cp35m-win32.whl 243b04730d7223d2b844bda9500310eecc9eda0cba9ceaf0cde1839f8287dfa8 scipy-1.3.1-cp35-cp35m-win_amd64.whl 46a5e55850cfe02332998b3aef481d33f1efee1960fe6cfee0202c7dd6fc21ab scipy-1.3.1-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl dd3b52e00f93fd1c86f2d78243dfb0d02743c94dd1d34ffea10055438e63b99d scipy-1.3.1-cp36-cp36m-manylinux1_i686.whl 75b513c462e58eeca82b22fc00f0d1875a37b12913eee9d979233349fce5c8b2 scipy-1.3.1-cp36-cp36m-manylinux1_x86_64.whl 396eb4cdad421f846a1498299474f0a3752921229388f91f60dc3eda55a00488 scipy-1.3.1-cp36-cp36m-win32.whl a81da2fe32f4eab8b60d56ad43e44d93d392da228a77e229e59b51508a00299c scipy-1.3.1-cp36-cp36m-win_amd64.whl 0baa64bf42592032f6f6445a07144e355ca876b177f47ad8d0612901c9375bef scipy-1.3.1-cp37-cp37m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl d02d813ec9958ed63b390ded463163685af6025cb2e9a226ec2c477df90c6957 scipy-1.3.1-cp37-cp37m-manylinux1_i686.whl 89dd6a6d329e3f693d1204d5562dd63af0fd7a17854ced17f9cbc37d5b853c8d scipy-1.3.1-cp37-cp37m-manylinux1_x86_64.whl ac37eb652248e2d7cbbfd89619dce5ecfd27d657e714ed049d82f19b162e8d45 scipy-1.3.1-cp37-cp37m-win32.whl a9d606d11eb2eec7ef893eb825017fbb6eef1e1d0b98a5b7fc11446ebeb2b9b1 scipy-1.3.1-cp37-cp37m-win_amd64.whl 2643cfb46d97b7797d1dbdb6f3c23fe3402904e3c90e6facfe6a9b98d808c1b5 scipy-1.3.1.tar.gz 326ffdad79f113659ed0bca80f5d0ed5e28b2e967b438bb1f647d0738073a92e scipy-1.3.1.tar.xz 47dd0ff4a9f17d97e9b68b363c54111f11b73a388cac55069d6e88a602d20552 scipy-1.3.1.zip -----BEGIN PGP SIGNATURE----- Version: GnuPG v2 iQIcBAEBCAAGBQJdTOWrAAoJELD/41ZX0J71Y1UP/ivoDqq6BDDdIB45Oo+XIH6h oZ3c5np+ui/jo/SIF82vM7W/7ZfTEf/BZEKM/ypqO8vk/EltF6jJb8pwyte8Mdic 5hlAQEbLLez2hipGvIIe3K2kS7OFWWorrZWcd+xuZxn9xV3BK4wDXNndpUW61xBF ElKI+HqfwZ6BLSOpDE9UuMWfIQ9wVACr+TtZSmJsQ1A55o9pcMR5HC0HrTBT40Sj SPQM1ECOJw2yNzijaYhEUvPIZsFIHjLqtAVkk+4HG675TtLw0NyqZIw9jhUax6vj rdkj1tSChtSEXE7D2AfZ446bHT+KsxHW6gMXhI96SFi0w698+h2UErZ7uqbnBkQO OAyzewcUp9yqgSf9pciR6WNiRKvPW8yW+l4XJGqERZDePQ1U4d1Ou9yx1efAkb6t j4SxpziM4n3ib3TKzRwQ574EJKKOK5TNYHAwH0BIqN4Ace3aN3D/XNojmelUh8gH d1TklvMGj54pwZjHnqeJMQG+vXbJdI2TXN5qUjFUcsghGvhKPWhl+Un9qoi0+/ZX nBOEXylKF1MkdV1vd4xLS5gFuyCf7EPnJl9vKMHnrkoUuCoxLM2YtAzjgiUiTjK2 lJAxppWZuNMgTcBsDgg6rtHiLcgl44YehPquV1pvs5DrxQzdq5kVwGu7yU2XRSbf QIsVcdAujT8MNGOvoJae =G7vC -----END PGP SIGNATURE-----

1 0

Proposed new feature: nan insensitive circular statistics
by Burrell, Angeline Aug. 7, 2019

Aug. 7, 2019

I have NaN insensitive versions of the SciPy circular mean and standard deviation routines that I would like to contribute to the scipy.stats subpackage. Since the hacking guidelines recommend discussing new contributions on this mailing list, I'd like to get the communal go-ahead before proceeding to integrate the routines and unit tests into scipy. For consistency, I would also add a NaN insensitive version of the circular variance routine. Cheers, Angeline ----------------------------------------------------- Dr. Angeline G. Burrell [she/her/hers] Research Physicist, Bldg. 209 Naval Research Laboratory (NRL) 4555 Overlook Ave SW Washington, DC 20375 (P) 202-404-4065 -----------------------------------------------------

1 0

Issues backlog
by Joshua Wilson Aug. 6, 2019

Aug. 6, 2019

Hey all, The SciPy repo currently has 1,242 open issues. The oldest open issue is from April 25th, 2013. There is definitely some signal in those old issues, but, as the project has evolved quite a bit from then, also quite a bit of noise (e.g. feature requests that one person cared about many years ago). We could spend a lot of time going through the old issues and closing the ones that are no longer relevant, but that's going to take a lot of time and I do not believe it is a high-leverage way to spend our limited developer time. Instead I propose that we simply close issues over a certain cutoff date. More concretely, we: - Determine a cutoff date beyond which we will close issues - Announce a date when we will close the old issues - During that time, if anyone wants to preserve an old issue they can open a new, updated issue, or perhaps adjust the SciPy roadmap if something is particularly important. Anyway, I am sure this will be controversial, so looking forward to hearing everyone's thoughts! - Josh

10 13

tools/win32 and tools/scipy-macosx-installer
by Andrew Nelson Aug. 6, 2019

Aug. 6, 2019

Is there any remaining need for these directories? Do we still make windows and OSX installer packages? -- _____________________________________ Dr. Andrew Nelson _____________________________________

2 1