On Tue, Sep 6, 2011 at 5:12 PM, David Cottrell wrote:
> Actually this link: http://www.scipy.org/PerformanceTips seems to
> indicate that numpy.dot does use blas ...
This not true (you can check by looking into numpy/core/setup.py,
which explicitly checks for ATLAS for _dotblas). The idea is that
Actually this link: http://www.scipy.org/PerformanceTips seems to
indicate that numpy.dot does use blas ...
Is there some way of running ldd on the install to see what libraries
are being pulled in?
On Tue, Sep 6, 2011 at 4:13 PM, David Cottrell wrote:
> Thanks, I didn't realize dot was not just
Le 05/09/2011 18:41, Ralf Gommers a écrit :
> That rings a bell. I can reproduce this with 1.5.1, and it's fixed in
> master.
Thanks!
Cheers,
--
Fred
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Thanks, I didn't realize dot was not just calling dgemm or some
variant which I assume would be reasonably fast. I see dgemm appears
in the numpy code in various places such as the lapack_lite module.
I ran the svd test on the solaris setup and will check the OSX run
when back at my laptop. 8.4 se
On Tue, Sep 6, 2011 at 2:38 PM, David Cottrell wrote:
> I posted on stackoverflow but then noticed this message board:
>
> http://stackoverflow.com/questions/7311869/python-numpy-on-solaris-blas-slow-or-not-linked
>
> I'm reposting the full post below:
>
> Matrix-Matrix multiplies are very slow on
I posted on stackoverflow but then noticed this message board:
http://stackoverflow.com/questions/7311869/python-numpy-on-solaris-blas-slow-or-not-linked
I'm reposting the full post below:
Matrix-Matrix multiplies are very slow on my Solaris install (running
on a sparc server) compared to my OSX
Hi all,
I've been implementing the algorithm from this paper "Reducing
Aliasing Artifacts in Iso-Surfaces of Binary Volumes" from Ross T.
Whitaker. Because I develop a opensource software which works with
segmentation of CT and MRI medical images, and the results of
segmentation is a binary volume
On 02.09.2011, at 1:47AM, Russell E. Owen wrote:
>> I've made a pull request
>> https://github.com/numpy/numpy/pull/144
>> implementing that option as a switch 'prescan'; could you review it in
>> particular regarding the following:
>>
>> Is the option reasonably named and documented?
>>
>> In
On Tue, Sep 6, 2011 at 9:32 AM, Derek Homeier
wrote:
> On 02.09.2011, at 11:45PM, Christopher Jordan-Squire wrote:
and unfortunately it's for 1D-arrays only).
>>>
>>> That's not bad for this use -- make a row a struct dtype, and you've got
>>> a 1-d array anyway -- you can optionally con
On 02.09.2011, at 11:45PM, Christopher Jordan-Squire wrote:
>>>
>>> and unfortunately it's for 1D-arrays only).
>>
>> That's not bad for this use -- make a row a struct dtype, and you've got
>> a 1-d array anyway -- you can optionally convert to a 2-d array after
>> the fact.
>>
>> I don't know
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