[pkgsrc/trunk]: pkgsrc/math/py-numpy py-numpy: updated to 1.15.2

[adam <adam%pkgsrc.org@localhost>]

details:   https://anonhg.NetBSD.org/pkgsrc/rev/f48beabf5e3c
branches:  trunk
changeset: 385640:f48beabf5e3c
user:      adam <adam%pkgsrc.org@localhost>
date:      Mon Sep 24 09:01:20 2018 +0000

description:
py-numpy: updated to 1.15.2

NumPy 1.15.2:

This is a bugfix release for bugs and regressions reported following the 1.15.1
release.

* The matrix PendingDeprecationWarning is now suppressed in pytest 3.8.
* The new cached allocations machinery has been fixed to be thread safe.
* The boolean indexing of subclasses now works correctly.
* A small memory leak in PyArray_AdaptFlexibleDType has been fixed.

The Python versions supported by this release are 2.7, 3.4-3.7. The wheels are
linked with OpenBLAS v0.3.0, which should fix some of the linalg problems
reported for NumPy 1.14.

diffstat:

 math/py-numpy/Makefile |   4 ++--
 math/py-numpy/distinfo |  10 +++++-----
 2 files changed, 7 insertions(+), 7 deletions(-)

diffs (30 lines):

diff -r a48f96368426 -r f48beabf5e3c math/py-numpy/Makefile
--- a/math/py-numpy/Makefile    Mon Sep 24 09:00:06 2018 +0000
+++ b/math/py-numpy/Makefile    Mon Sep 24 09:01:20 2018 +0000
@@ -1,6 +1,6 @@
-# $NetBSD: Makefile,v 1.53 2018/08/27 06:04:35 adam Exp $
+# $NetBSD: Makefile,v 1.54 2018/09/24 09:01:20 adam Exp $
 
-DISTNAME=      numpy-1.15.1
+DISTNAME=      numpy-1.15.2
 PKGNAME=       ${PYPKGPREFIX}-${DISTNAME}
 CATEGORIES=    math python
 MASTER_SITES=  ${MASTER_SITE_PYPI:=n/numpy/}
diff -r a48f96368426 -r f48beabf5e3c math/py-numpy/distinfo
--- a/math/py-numpy/distinfo    Mon Sep 24 09:00:06 2018 +0000
+++ b/math/py-numpy/distinfo    Mon Sep 24 09:01:20 2018 +0000
@@ -1,9 +1,9 @@
-$NetBSD: distinfo,v 1.35 2018/08/27 06:04:35 adam Exp $
+$NetBSD: distinfo,v 1.36 2018/09/24 09:01:20 adam Exp $
 
-SHA1 (numpy-1.15.1.zip) = 2e7548d4972e5366dd8b30ca3639e243dae96af9
-RMD160 (numpy-1.15.1.zip) = 1eade7058bc7739f2994946e55390587680e3ef2
-SHA512 (numpy-1.15.1.zip) = 9f674fd5944f6a60a41f60c5cd79cc172c621fcf41fe5064f292bee94b16f28de339005d1f1535586d5d3caa6c0d3eb9bb78221d80327e4edec84936f857c59f
-Size (numpy-1.15.1.zip) = 4482769 bytes
+SHA1 (numpy-1.15.2.zip) = 71404df59f7a07d34274d95febc7bbc0101685bb
+RMD160 (numpy-1.15.2.zip) = 22075d72e14f98cd8b25d1c2fa57d62a861741bd
+SHA512 (numpy-1.15.2.zip) = 6a2c9c5e67963558749e6468d79c7dc55f13749400640dbb7dea8c87a30c9cadb04df6b3cf3f92ac7d720486ef3f3c248ab4680b954e7adeb44edf2f2a072250
+Size (numpy-1.15.2.zip) = 4484511 bytes
 SHA1 (patch-aa) = c964fa13fb120b1b0f9d0bf5bc713507cd60b945
 SHA1 (patch-ab) = b421455fdbb666c8075d8bffbeb59533434d23e6
 SHA1 (patch-numpy_distutils_fcompiler_g95.py) = be73b64a3e551df998b6a904d6db762bf28a98ed