Skip to content

v1.13.1
Compare
Choose a tag to compare
@charris charris released this 07 Jul 01:51
v1.13.1
This tag was signed with the committer’s verified signature.
charris Charles Harris
GPG key ID: 679F228377C5247B
Learn about vigilant mode.
1462df1

==========================
NumPy 1.13.1 Release Notes

This is a bugfix release for problems found in 1.13.0. The major changes are
fixes for the new memory overlap detection and temporary elision as well as
reversion of the removal of the boolean binary - operator. Users of 1.13.0
should upgrade.

Thr Python versions supported are 2.7 and 3.4 - 3.6. Note that the Python 3.6
wheels available from PIP are built against 3.6.1, hence will not work when
used with 3.6.0 due to Python bug 29943_. NumPy 1.13.2 will be released shortly
after Python 3.6.2 is out to fix that problem. If you are using 3.6.0 the
workaround is to upgrade to 3.6.1 or use an earlier Python version.

.. _#29943: https://bugs.python.org/issue29943

Pull requests merged

A total of 19 pull requests were merged for this release.

  • #9240 DOC: BLD: fix lots of Sphinx warnings/errors.
  • #9255 Revert "DEP: Raise TypeError for subtract(bool_, bool_)."
  • #9261 BUG: don't elide into readonly and updateifcopy temporaries for...
  • #9262 BUG: fix missing keyword rename for common block in numpy.f2py
  • #9263 BUG: handle resize of 0d array
  • #9267 DOC: update f2py front page and some doc build metadata.
  • #9299 BUG: Fix Intel compilation on Unix.
  • #9317 BUG: fix wrong ndim used in empty where check
  • #9319 BUG: Make extensions compilable with MinGW on Py2.7
  • #9339 BUG: Prevent crash if ufunc doc string is null
  • #9340 BUG: umath: un-break ufunc where= when no out= is given
  • #9371 DOC: Add isnat/positive ufunc to documentation
  • #9372 BUG: Fix error in fromstring function from numpy.core.records...
  • #9373 BUG: ')' is printed at the end pointer of the buffer in numpy.f2py.
  • #9374 DOC: Create NumPy 1.13.1 release notes.
  • #9376 BUG: Prevent hang traversing ufunc userloop linked list
  • #9377 DOC: Use x1 and x2 in the heaviside docstring.
  • #9378 DOC: Add $PARAMS to the isnat docstring
  • #9379 DOC: Update the 1.13.1 release notes

Contributors

A total of 12 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.

  • Andras Deak +
  • Bob Eldering +
  • Charles Harris
  • Daniel Hrisca +
  • Eric Wieser
  • Joshua Leahy +
  • Julian Taylor
  • Michael Seifert
  • Pauli Virtanen
  • Ralf Gommers
  • Roland Kaufmann
  • Warren Weckesser

Checksums

MD5

010a6325ec8e7df2f305e716c871880a  numpy-1.13.1-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
7774a1a5f93b45bfa7045b98eb102cca  numpy-1.13.1-cp27-cp27m-manylinux1_i686.whl
7906018278f3471a9a166a3975523ddd  numpy-1.13.1-cp27-cp27m-manylinux1_x86_64.whl
7ecd9304c319fc6b9ea481d6bf2e5051  numpy-1.13.1-cp27-cp27mu-manylinux1_i686.whl
de272621d41b7856e1580307be9d1fba  numpy-1.13.1-cp27-cp27mu-manylinux1_x86_64.whl
21c4dc286991347f506c0e27475f9058  numpy-1.13.1-cp27-none-win32.whl
245e3ebe32cf60d9d16e7267aa4292fc  numpy-1.13.1-cp27-none-win_amd64.whl
3eee3605dd61f02583264eb5697d8207  numpy-1.13.1-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
4a9f08ad5f3073ecaeea939158eaf955  numpy-1.13.1-cp34-cp34m-manylinux1_i686.whl
c51520d0d3836c91cba18d1fa8cf299c  numpy-1.13.1-cp34-cp34m-manylinux1_x86_64.whl
b1f13004ee992203d8c15940d60d0e7c  numpy-1.13.1-cp34-none-win32.whl
062bf4ed9e0fd5af995a17360e7bdec9  numpy-1.13.1-cp34-none-win_amd64.whl
b14a4749abbab74c21ef0743f7426245  numpy-1.13.1-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
a5b6bffc5a0e4950748ab0969457a728  numpy-1.13.1-cp35-cp35m-manylinux1_i686.whl
4558a2357849d9ef7b80260a76b7c990  numpy-1.13.1-cp35-cp35m-manylinux1_x86_64.whl
dd062ef029279bd795653a768d50180d  numpy-1.13.1-cp35-none-win32.whl
4df5bb3eb4787ff9850c1a5694922ab4  numpy-1.13.1-cp35-none-win_amd64.whl
449926c081bd27655d8bf76e03c5c75c  numpy-1.13.1-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
6ab8632d38c0313d9e063841a7e43edf  numpy-1.13.1-cp36-cp36m-manylinux1_i686.whl
a3664260fc73c6c2645a00b22109a2b8  numpy-1.13.1-cp36-cp36m-manylinux1_x86_64.whl
0a5d74ebce74e2a557d7bc0183398ac1  numpy-1.13.1-cp36-none-win32.whl
ab789d91bc6e423084df7fc73e667270  numpy-1.13.1-cp36-none-win_amd64.whl
6d459e4a24f5035f720dda3c57716a92  numpy-1.13.1.tar.gz
2c3c0f4edf720c3a7b525dacc825b9ae  numpy-1.13.1.zip

SHA256

91a4f5c6594a61b57b0ab6031a084fa3686b1e847cc2215983e444583594b529  numpy-1.13.1-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
ab6abc2083013dd86a8fcba2ba16bab00690cb81db62588781d656572809c9a9  numpy-1.13.1-cp27-cp27m-manylinux1_i686.whl
02e6279d95081086469e6ed83c708c4c48ed03a28ab87c71bea28af3b95fa56d  numpy-1.13.1-cp27-cp27m-manylinux1_x86_64.whl
05a7a81397e1391ae34cc0d14764a31ab6f73dbd0abe0952b3550d3ad4df265d  numpy-1.13.1-cp27-cp27mu-manylinux1_i686.whl
73fd54d9787f4f8747f823a7e2d0693da94c66b670ccf436e4bb488bbcd5ce8c  numpy-1.13.1-cp27-cp27mu-manylinux1_x86_64.whl
4b7da62ba159bfc5fee6f54709b0708686ee15081f16dc5f81cda7f1e0e77941  numpy-1.13.1-cp27-none-win32.whl
1980c4bc1eb495624c8414f3763da83b91d37c3c69772ab6912e9a857a143cdb  numpy-1.13.1-cp27-none-win_amd64.whl
436d47018c3cd2b9723ed3cd4ed4698ea7641449c71096781478ef6a20ae3bd0  numpy-1.13.1-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
43722270fbfb07d91558985a3da37aa92a2d4e2d271182526959a5773f9fb12a  numpy-1.13.1-cp34-cp34m-manylinux1_i686.whl
838e48df3703c8747f355cd6386e0680b906a2f7b2bbd304e8a2d531692484ce  numpy-1.13.1-cp34-cp34m-manylinux1_x86_64.whl
1400ec59c7f6c4f9390cc3bc5e56a6cbae2c30b39024eef317a0b52fe9c174c6  numpy-1.13.1-cp34-none-win32.whl
ed6a909a78e29a4056e30f918a26b231e33edc77bd785bbceb461877baf9feb5  numpy-1.13.1-cp34-none-win_amd64.whl
c1833829526ce8f5177a3e07554b6c98c194072f66f018839ecd1ef2d15e6c4a  numpy-1.13.1-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
a09a4707066fe9431c6b79a1be922bc126f4bc50502ae7e9f67d40917d0cc6d4  numpy-1.13.1-cp35-cp35m-manylinux1_i686.whl
9a8515002f143a5934f25ad2aacdfd1fcf57a7f5da6142c439eb8787ef65e8a6  numpy-1.13.1-cp35-cp35m-manylinux1_x86_64.whl
b49caeb170e54cc59863017a199667a51526bd906bcd5ee340fcf0e01bd7fa94  numpy-1.13.1-cp35-none-win32.whl
405c3dbb6a57415ec8576ff1c0248f332ac1c3be2e5eea04d498dad8431bf57b  numpy-1.13.1-cp35-none-win_amd64.whl
42b3cf886701bb16f3bdf2ae6c39af67b464cdd67d5fc86619ef2a876a23de27  numpy-1.13.1-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
94cb6ef9ffd15d7d904d0825ada642a51dc8890cdc06f1e4fb8e46cff79fe2ef  numpy-1.13.1-cp36-cp36m-manylinux1_i686.whl
d910a24f536f926bd56fb30d6f17ae8b89a1406e105087a49e014e000b00e8db  numpy-1.13.1-cp36-cp36m-manylinux1_x86_64.whl
b064211a4d86fc8009ef90c66d1443ba4a0c56d481659e085a190299569955e3  numpy-1.13.1-cp36-none-win32.whl
f4b4b2da8c1b4f7c212742d2be03aa9277d46fd7b309025d930ad554e5739932  numpy-1.13.1-cp36-none-win_amd64.whl
de020ec06f1e9ce1115a50161a38bf8d4c2525379900f9cb478cc613a1e7cd93  numpy-1.13.1.tar.gz
c9b0283776085cb2804efff73e9955ca279ba4edafd58d3ead70b61d209c4fbb  numpy-1.13.1.zip
Assets 6