Am 12.06.2013 19:27, schrieb Julian Taylor:
I'm guessing you are using openblas?
check with:
ls -l /etc/alternatives/libblas.so.3
there are known hanging problems with openblas and multiprocessing.
you can work around them by disabling threading in openblas
(OPENBLAS_NUM_THREADS=1).
On 11/06/2013 22:11, Chris Barker - NOAA Federal wrote:
On Tue, Jun 11, 2013 at 1:28 PM, Ralf Gommers ralf.gomm...@gmail.com wrote:
The binaries will still be built against python.org Python, so there
shouldn't be an issue here. Same for building from source.
My point was that it's nice to be
On Wed, Jun 12, 2013 at 2:55 PM, Eric Firing efir...@hawaii.edu wrote:
On 2013/06/12 8:13 AM, Warren Weckesser wrote:
That's why I suggested 'filledwith' (add the underscore if you like).
This also allows a corresponding masked implementation, 'ma.filledwith',
without clobbering the
Dear Numpy users,
I have a memory leak in my code. A simple way to reproduce my problem is:
import numpy
class test():
def __init__(self):
pass
def t(self):
temp = numpy.zeros([200,100,100])
A = numpy.zeros([200], dtype = numpy.float)
for i in
Hi Petro,
What version of numpy are you running?
A
On Thu, Jun 13, 2013 at 3:50 PM, Pietro Bonfa' pietro.bo...@fis.unipr.itwrote:
Dear Numpy users,
I have a memory leak in my code. A simple way to reproduce my problem is:
import numpy
class test():
def __init__(self):
The numpy version is 1.7.0
In [5]: numpy.version.full_version
Out[5]: '1.7.0b2'
Thanks,
Pietro
On 06/13/13 16:56, Aron Ahmadia wrote:
Hi Petro,
What version of numpy are you running?
A
On Thu, Jun 13, 2013 at 3:50 PM, Pietro Bonfa'
pietro.bo...@fis.unipr.it
On Thu, Jun 13, 2013 at 8:56 AM, Aron Ahmadia a...@ahmadia.net wrote:
Hi Petro,
What version of numpy are you running?
A
On Thu, Jun 13, 2013 at 3:50 PM, Pietro Bonfa'
pietro.bo...@fis.unipr.itwrote:
Dear Numpy users,
I have a memory leak in my code. A simple way to reproduce my
Upgrading numpy solved the problem!
Thanks!
On 06/13/13 17:06, Sebastian Berg wrote:
On Thu, 2013-06-13 at 16:50 +0200, Pietro Bonfa' wrote:
Dear Numpy users,
I have a memory leak in my code. A simple way to reproduce my problem is:
import numpy
class test():
def __init__(self):
On Thu, 2013-06-13 at 16:50 +0200, Pietro Bonfa' wrote:
Dear Numpy users,
I have a memory leak in my code. A simple way to reproduce my problem is:
import numpy
class test():
def __init__(self):
pass
def t(self):
temp = numpy.zeros([200,100,100])
A
hi,
I posted a pull with a minor change instructing the GCC compiler to
unroll the strided copy loops (gcc will almost never do that on its own,
not even on O3).
https://github.com/numpy/numpy/pull/3429
It improves performance of these copies by 20%-50% depending on the size
of the data copied
12.06.2013 00:29, Ralf Gommers kirjoitti:
[clip]
Sounds like a good idea. Would still make sense to move Accelerate down
in the list of preferred libs, so that one can install ATLAS, MKL or
OpenBLAS once and be done, instead of always having to remember these
envvars.
It goes like this:
On Thu, Jun 13, 2013 at 9:36 AM, Aldcroft, Thomas
aldcr...@head.cfa.harvard.edu wrote:
On Wed, Jun 12, 2013 at 2:55 PM, Eric Firing efir...@hawaii.edu wrote:
On 2013/06/12 8:13 AM, Warren Weckesser wrote:
That's why I suggested 'filledwith' (add the underscore if you like).
This also
On 2013/06/13 10:36 AM, Benjamin Root wrote:
On Thu, Jun 13, 2013 at 9:36 AM, Aldcroft, Thomas
aldcr...@head.cfa.harvard.edu mailto:aldcr...@head.cfa.harvard.edu
wrote:
On Wed, Jun 12, 2013 at 2:55 PM, Eric Firing efir...@hawaii.edu
mailto:efir...@hawaii.edu wrote:
On
On 6/13/2013 4:36 PM, Benjamin Root wrote:
np.values() might be a decent alternative.
This could then reasonably support broadcasting
from the shape of the input to the shape of
the array.
Alan Isaac
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On Thu, Jun 13, 2013 at 4:47 PM, Eric Firing efir...@hawaii.edu wrote:
On 2013/06/13 10:36 AM, Benjamin Root wrote:
On Thu, Jun 13, 2013 at 9:36 AM, Aldcroft, Thomas
aldcr...@head.cfa.harvard.edu mailto:aldcr...@head.cfa.harvard.edu
wrote:
On Wed, Jun 12, 2013 at 2:55 PM, Eric Firing
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