Hi Chuck,
Spider is good. If you are coming from Matlab world.
http://spyder-ide.blogspot.co.uk/
I don't think it supports C. But Maybe you are after Eclipse.
Best,
-m
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On Mon, Apr 6, 2015 at 9:22 PM, Charles R Harris charlesr.har...@gmail.com
wrote:
Hi All,
I'd like to mark current PR's for inclusion in 1.10.
Good idea. If you're going to do this, it may be helpful to create a new
1.10 milestone and keep but clean up the 1.10 blockers milestone so there
Hi All,
I'd like to mark current PR's for inclusion in 1.10. If there is something
that you want to have in the release, please mention it here by PR #.I
think new enhancement PR's should be considered for 1.11 rather than 1.10,
but bug fixes will go in. There is some flexibility, of course, as
On 07/04/15 01:49, Nathaniel Smith wrote:
Any opinions, objections?
Accelerate does not break multiprocessing, quite the opposite. The bug
is in multiprocessing and has been fixed in Python 3.4.
My vote would nevertheless be for OpenBLAS if we can use it without
producing test failures in
Hi all,
Starting with 1.9.1, the official numpy OS X wheels (the ones you get by
doing pip install numpy) have been built to use Apple's Accelerate
library for linear algebra. This is fast, but it breaks multiprocessing in
obscure ways (e.g. see this user report:
On 06/04/15 20:33, Suzen, Mehmet wrote:
Hi Chuck,
Spider is good. If you are coming from Matlab world.
http://spyder-ide.blogspot.co.uk/
I don't think it supports C. But Maybe you are after Eclipse.
Spyder supports C.
Sturla
___
On Mon, Apr 6, 2015 at 3:01 PM, Ralf Gommers ralf.gomm...@gmail.com wrote:
On Mon, Apr 6, 2015 at 9:22 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
Hi All,
I'd like to mark current PR's for inclusion in 1.10.
Good idea. If you're going to do this, it may be helpful to create
On Apr 6, 2015 2:01 PM, Ralf Gommers ralf.gomm...@gmail.com wrote:
There are too many PRs marked as 1.10 blockers, I think the only real
blockers are:
- __numpy_ufunc__ PRs (#4815, #4855)
The main blocker here is figuring out how to coordinate __numpy_ufunc__ and
__binop__ dispatch, e.g. PR
On Mon, Apr 6, 2015 at 5:59 PM, Nathaniel Smith n...@pobox.com wrote:
On Apr 6, 2015 2:01 PM, Ralf Gommers ralf.gomm...@gmail.com wrote:
There are too many PRs marked as 1.10 blockers, I think the only real
blockers are:
- __numpy_ufunc__ PRs (#4815, #4855)
The main blocker here is
On 07/04/15 02:41, Nathaniel Smith wrote:
Sure, but in some cases accelerate reduces speed by a factor of infinity
by hanging, and OpenBLAS may or may not give wrong answers (but
quickly!) since apparently they don't do regression tests, so we have to
pick our poison.
OpenBLAS is safer on
Hi,
On Mon, Apr 6, 2015 at 5:13 PM, Sturla Molden sturla.mol...@gmail.com wrote:
On 07/04/15 01:49, Nathaniel Smith wrote:
Any opinions, objections?
Accelerate does not break multiprocessing, quite the opposite. The bug
is in multiprocessing and has been fixed in Python 3.4.
My vote would
On 07/04/15 02:13, Sturla Molden wrote:
Most of the test failures with OpenBLAS and Carl Kleffner's toolchain on
Windows are due to differences between Microsoft and MinGW runtime
libraries
... and also differences in FPU precision.
Sturla
___
With the indexing example from the documentation:
y = np.arange(35).reshape(5,7)
Why does selecting an item from explicitly every row work as I’d expect:
y[np.array([0,1,2,3,4]),np.array([0,0,0,0,0])]
array([ 0, 7, 14, 21, 28])
But doing so from a full slice (which, I would naively expect to
On 07/04/15 02:19, Matthew Brett wrote:
ATLAS compiled with gcc also gives us some more license complication:
http://numpy-discussion.10968.n7.nabble.com/Copyright-status-of-NumPy-binaries-on-Windows-OS-X-tp38793p38824.html
Ok, then I have a question regarding OpenBLAS:
Do we use the f2c'd
On Apr 6, 2015 5:13 PM, Sturla Molden sturla.mol...@gmail.com wrote:
On 07/04/15 01:49, Nathaniel Smith wrote:
Any opinions, objections?
Accelerate does not break multiprocessing, quite the opposite. The bug
is in multiprocessing and has been fixed in Python 3.4.
I disagree, but it hardly
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