Le lundi 20 août 2012 à 22:04 +0200, Ralf Gommers a écrit :
https://github.com/FabricioS/scipy/commit/f867f2b8133d3f6ea47d449bd760a77a7c90394e
This is probably not worth the cost for existing users imho. It is a
backwards compatibility break that doesn't really add anything except
for some
Hi,
I'm pleased to announce the availability of the first beta release of
NumPy 1.7.0b1.
Sources and binary installers can be found at
https://sourceforge.net/projects/numpy/files/NumPy/1.7.0b1/
Please test this release and report any issues on the numpy-discussion
mailing list. The following
Announcing carray 0.5
=
What's new
--
carray 0.5 supports completely transparent storage on-disk in addition
to memory. That means that everything that can be done with an
in-memory container can be done using the disk instead.
The advantages of a disk-based
://www.lfd.uci.edu/~gohlke/pythonlibs/.
The test results are at
http://www.lfd.uci.edu/~gohlke/pythonlibs/tests/20120821-win-amd64-py2.7-numpy-MKL-1.7.0rc1.dev-28ffac7/.
For comparison, the tests against numpy-MKL-1.6.2 are at
http://www.lfd.uci.edu/~gohlke/pythonlibs/tests/20120821-win-amd64
-py2.7\msvc9\MKL build of the numpy
maintenance/1.7.x branch against a number of package binaries from
http://www.lfd.uci.edu/~gohlke/pythonlibs/.
The test results are at
http://www.lfd.uci.edu/~gohlke/pythonlibs/tests/20120821-win-amd64-py2.7-numpy-MKL-1.7.0rc1.dev-28ffac7/
.
For comparison
of the numpy
maintenance/1.7.x branch against a number of package binaries from
http://www.lfd.uci.edu/~gohlke/pythonlibs/.
The test results are at
http://www.lfd.uci.edu/~gohlke/pythonlibs/tests/20120821-win-amd64-py2.7-numpy-MKL-1.7.0rc1.dev-28ffac7/.
For comparison, the tests against numpy-MKL-1.6.2
