ANN: SciPy 1.2.3 (LTS)

classic Classic list List threaded Threaded
1 message Options
Reply | Threaded
Open this post in threaded view
|

ANN: SciPy 1.2.3 (LTS)

Tyler Reddy
-----BEGIN PGP SIGNED MESSAGE-----
Hash: SHA256

Hi all,

On behalf of the SciPy development team I'm pleased to announce
the release of SciPy 1.2.3, which is a bug fix release. This is part
of the long-term support (LTS) branch that includes Python 2.7.

Sources and binary wheels can be found at:
https://pypi.org/project/scipy/
and at: https://github.com/scipy/scipy/releases/tag/v1.2.3

One of a few ways to install this release with pip:

pip install scipy==1.2.3

==========================
SciPy 1.2.3 Release Notes
==========================

SciPy 1.2.3 is a bug-fix release with no new features compared to 1.2.2. It is
part of the long-term support (LTS) release series for Python 2.7.

Authors
=======

* Geordie McBain
* Matt Haberland
* David Hagen
* Tyler Reddy
* Pauli Virtanen
* Eric Larson
* Yu Feng
* ananyashreyjain
* Nikolay Mayorov
* Evgeni Burovski
* Warren Weckesser

Issues closed for 1.2.3
--------------------------------
* `#4915 <https://github.com/scipy/scipy/issues/4915>`__: Bug in unique_roots in scipy.signal.signaltools.py for roots with same magnitude
* `#5546 <https://github.com/scipy/scipy/issues/5546>`__: ValueError raised if scipy.sparse.linalg.expm recieves array larger than 200x200
* `#7117 <https://github.com/scipy/scipy/issues/7117>`__: Warn users when using float32 input data to curve_fit and friends
* `#7906 <https://github.com/scipy/scipy/issues/7906>`__: Wrong result from scipy.interpolate.UnivariateSpline.integral for out-of-bounds
* `#9581 <https://github.com/scipy/scipy/issues/9581>`__: Least-squares minimization fails silently when x and y data are different types
* `#9901 <https://github.com/scipy/scipy/issues/9901>`__: lsoda fails to detect stiff problem when called from solve_ivp
* `#9988 <https://github.com/scipy/scipy/issues/9988>`__: doc build broken with Sphinx 2.0.0
* `#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
* `#10535 <https://github.com/scipy/scipy/issues/10535>`__: TST: master branch CI failures
* `#11121 <https://github.com/scipy/scipy/issues/11121>`__: Calls to `scipy.interpolate.splprep` increase RAM usage.
* `#11198 <https://github.com/scipy/scipy/issues/11198>`__: BUG: sparse eigs (arpack) shift-invert drops the smallest eigenvalue for some k
* `#11266 <https://github.com/scipy/scipy/issues/11266>`__: Sparse matrix constructor data type detection changes on Numpy 1.18.0

Pull requests for 1.2.3
--------------------------------
* `#9992 <https://github.com/scipy/scipy/pull/9992>`__: MAINT: Undo Sphinx pin
* `#10071 <https://github.com/scipy/scipy/pull/10071>`__: DOC: reconstruct SuperLU permutation matrices avoiding SparseEfficiencyWarning
* `#10076 <https://github.com/scipy/scipy/pull/10076>`__: BUG: optimize: fix curve_fit for mixed float32/float64 input
* `#10138 <https://github.com/scipy/scipy/pull/10138>`__: BUG: special: Invalid arguments to ellip_harm can crash Python.
* `#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
* `#10540 <https://github.com/scipy/scipy/pull/10540>`__: MAINT: Fix Travis and Circle
* `#10633 <https://github.com/scipy/scipy/pull/10633>`__: BUG: interpolate: integral(a, b) should be zero when both limits are outside of the interpolation range
* `#10833 <https://github.com/scipy/scipy/pull/10833>`__: BUG: Fix subspace_angles for complex values
* `#10882 <https://github.com/scipy/scipy/pull/10882>`__: BUG: sparse/arpack: fix incorrect code for complex hermitian M
* `#10906 <https://github.com/scipy/scipy/pull/10906>`__: BUG: sparse/linalg: fix expm for np.matrix inputs
* `#10961 <https://github.com/scipy/scipy/pull/10961>`__: BUG: Fix signal.unique_roots
* `#11126 <https://github.com/scipy/scipy/pull/11126>`__: BUG: interpolate/fitpack: fix memory leak in splprep
* `#11199 <https://github.com/scipy/scipy/pull/11199>`__: BUG: sparse.linalg: mistake in unsymm. real shift-invert ARPACK eigenvalue selection
* `#11269 <https://github.com/scipy/scipy/pull/11269>`__: Fix: Sparse matrix constructor data type detection changes on Numpy 1.18.0



Checksums
=========

MD5
~~~

702e7f68e024359d5cf0627337944520  scipy-1.2.3-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
53035df3bf9c688fb7803df11b74eb97  scipy-1.2.3-cp27-cp27m-manylinux1_i686.whl
6a07e4864228d4d6bc8d396b9e09f71c  scipy-1.2.3-cp27-cp27m-manylinux1_x86_64.whl
645b4211dc2f2b3bdc4e5cf85454e164  scipy-1.2.3-cp27-cp27m-win32.whl
49e6c189ca1a0d92f426e4efaa782f37  scipy-1.2.3-cp27-cp27m-win_amd64.whl
a875abf6f3f52fac916739dd556ccefb  scipy-1.2.3-cp27-cp27mu-manylinux1_i686.whl
46138092ed3b9e9f0b67afb3765ca041  scipy-1.2.3-cp27-cp27mu-manylinux1_x86_64.whl
608650168cfeda8fb9c1f44ccfb9b6a7  scipy-1.2.3-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
3acbfaf35ad246e4cffd0f7e35f88483  scipy-1.2.3-cp34-cp34m-manylinux1_i686.whl
807bca9d17cf3221a062c6b72192a1ed  scipy-1.2.3-cp34-cp34m-manylinux1_x86_64.whl
327a19bd65112ee59425f57cf65dce67  scipy-1.2.3-cp34-cp34m-win32.whl
a1b627a5b0b1adb3c5418d3c9081615b  scipy-1.2.3-cp34-cp34m-win_amd64.whl
80d65fd4266bcb29e02b03545ae80b7a  scipy-1.2.3-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
bd1e8f80f9e0427855ff10810e68118f  scipy-1.2.3-cp35-cp35m-manylinux1_i686.whl
35f03968403ad3049db956b90a346a59  scipy-1.2.3-cp35-cp35m-manylinux1_x86_64.whl
bf489f87f8bfeb6a14c5e606b539f16a  scipy-1.2.3-cp35-cp35m-win32.whl
7a618445b53f4f8671352ea52df5cc9f  scipy-1.2.3-cp35-cp35m-win_amd64.whl
7b7e8889babc121b4c1340f4b8081423  scipy-1.2.3-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
8339ebba078ee752b2bd15eb3fc64f2f  scipy-1.2.3-cp36-cp36m-manylinux1_i686.whl
4dd7be670ce0b1bd2b4c3f5038cf6fb9  scipy-1.2.3-cp36-cp36m-manylinux1_x86_64.whl
9130c940f3b811b9281ac64a3bd610a6  scipy-1.2.3-cp36-cp36m-win32.whl
adeb6e4e9c270df4a5e55d0f1a4a72f0  scipy-1.2.3-cp36-cp36m-win_amd64.whl
19f6644944227c64c50dedbb04f8d91d  scipy-1.2.3-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
f75450b9399acd7eb3c0fc1724de4be3  scipy-1.2.3-cp37-cp37m-manylinux1_i686.whl
fc1cb1164479e070af722e579604bea2  scipy-1.2.3-cp37-cp37m-manylinux1_x86_64.whl
6c2057a41b73f17daf100f3fc1252903  scipy-1.2.3-cp37-cp37m-win32.whl
27f26a031ac1884ac5cb3e35343aba7c  scipy-1.2.3-cp37-cp37m-win_amd64.whl
43b42a507472dfa1dff4c91d58a6543f  scipy-1.2.3.tar.gz
561ee26a6d0a9b31d644db5e8244bc76  scipy-1.2.3.tar.xz
5b9f47308d06b22078810fca4f97fad2  scipy-1.2.3.zip

SHA256
~~~~~~

2ff82db1393bd5d8ddeb9134e8f77a8e971e635452d7e65f7238f40c71d385a8  scipy-1.2.3-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
5d950892a6a2da6dae2b5a3021b329dbf04483a7fb0bd3011685db7f51578ae7  scipy-1.2.3-cp27-cp27m-manylinux1_i686.whl
487a61a7e477923c7a9e8fa06f27e3f2dbc7ce9450a970a2e5d902b0a305d028  scipy-1.2.3-cp27-cp27m-manylinux1_x86_64.whl
3397ce30e240e9a543d81f623a9e8e98ae39012cf72e42e95929530a03f20791  scipy-1.2.3-cp27-cp27m-win32.whl
8533e8c2e467eed913a0aa4fac09c9fb824f32d1ab1121db3a50845f9b347825  scipy-1.2.3-cp27-cp27m-win_amd64.whl
b6cbb7125b0c742e0f31fb293d19e9f1a03db58f6ddefc51a2025ee15ae607cb  scipy-1.2.3-cp27-cp27mu-manylinux1_i686.whl
e870dfd006ab657f9cc48b099646c5ceb4e812e59a7d460dc80ac9a659f089dc  scipy-1.2.3-cp27-cp27mu-manylinux1_x86_64.whl
b8b0e81a2b87d68acf4a54aea800edafbb5bc9a04f38256718826f95f625fb75  scipy-1.2.3-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
ecc27dda36d7172bb4ed7f245499e28251fa17909b314b4e8956a942f302e1a3  scipy-1.2.3-cp34-cp34m-manylinux1_i686.whl
ee213d8c8eee0540ba91efca61605dc0e2b5bd90ca35ab49c85f0ad7038df00f  scipy-1.2.3-cp34-cp34m-manylinux1_x86_64.whl
57a0ee083b94944ba6329e755d112bfd53a98bd9a6a4faf10bc7722c955a7653  scipy-1.2.3-cp34-cp34m-win32.whl
1bc0720f149fbb69d19156cf91730aa21455c58949aea56bfaa2b74c06868100  scipy-1.2.3-cp34-cp34m-win_amd64.whl
d39ae9cfd7bdea7753fd617e2edfc68b94a019a65c0153c3fced35cf657b79e7  scipy-1.2.3-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
7e6c485c3f2789c790fe4cc5c6c3b4554000d284fd05be90479b6fbd8795d064  scipy-1.2.3-cp35-cp35m-manylinux1_i686.whl
92fbdcf9acebf2007502adbed1b22e3a3e9445aceb5e7a568f9759d76461368b  scipy-1.2.3-cp35-cp35m-manylinux1_x86_64.whl
b2fad2430232f8c2faeb0abff7ed5191f0a534bd1bd482c71a9616c44e674c76  scipy-1.2.3-cp35-cp35m-win32.whl
8b3ac1e50188792fdf811e5a747df2b784c65d9a17f59609a73c8285424a48ad  scipy-1.2.3-cp35-cp35m-win_amd64.whl
b38f2e6d53f852ae1de1aacead2c26a69c91b36f833e744557ca370979b81652  scipy-1.2.3-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
39bf06b2536e69f08a257b260aaa25d088d755b73cf3751b44e5838ccb1d0a82  scipy-1.2.3-cp36-cp36m-manylinux1_i686.whl
c08013e0fe1554372da9312d5bad588402f71c0636f0f86a9b9b61d507c59bac  scipy-1.2.3-cp36-cp36m-manylinux1_x86_64.whl
cac83647970115dfb6d29dc3b4ab44b3aa11254e8aeba115f88ad0ccbb273085  scipy-1.2.3-cp36-cp36m-win32.whl
0c23e5b3a314dce4049b969c81ad801cf05e1fe699760846c7567deaa9b8c548  scipy-1.2.3-cp36-cp36m-win_amd64.whl
503e25b8da22b1be6f2f81e1dcf26f42bfb13fe89bccbf8bc48e1b6f2a4789c8  scipy-1.2.3-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
19904399501ecf56ead21b307cc52c8ff03a2103343f554f3fbc189bb2cf1609  scipy-1.2.3-cp37-cp37m-manylinux1_i686.whl
f658f90db1530f70128bbeb2c1e61006de2eb2382408080a211d885f501af3a7  scipy-1.2.3-cp37-cp37m-manylinux1_x86_64.whl
7aeb232273b38e74d89181d9165ca47314e1c4269afe7c3a1926aea3e63345a2  scipy-1.2.3-cp37-cp37m-win32.whl
53353a504ad2181eb27c9d61e91ce29324f8b7550876736a08a36e6b60c43407  scipy-1.2.3-cp37-cp37m-win_amd64.whl
ecbe6413ca90b8e19f8475bfa303ac001e81b04ec600d17fa7f816271f7cca57  scipy-1.2.3.tar.gz
94ef2ac3c9c83cbbda0a5c5552fffa22993c1c21313c0eb7a2e7102b4629bc31  scipy-1.2.3.tar.xz
a4f09f8c6f5924582fc61d3c5cd8174e8f8857a45dfa4a81c0d134b7c4af74cc  scipy-1.2.3.zip
-----BEGIN PGP SIGNATURE-----
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=E9q4
-----END PGP SIGNATURE-----

_______________________________________________
NumPy-Discussion mailing list
[hidden email]
https://mail.python.org/mailman/listinfo/numpy-discussion