On Thu, Mar 7, 2013 at 12:26 PM, Frédéric Bastien wrote:
> Hi,
>
> It is normal that unaligned access are slower. The hardware have been
> optimized for aligned access. So this is a user choice space vs speed.
The quantitative difference is still important, so this thread is
useful for future ref
On Thu, Mar 7, 2013 at 11:47 AM, Francesc Alted wrote:
> On 3/6/13 7:42 PM, Kurt Smith wrote:
>
> Hmm, that clearly depends on the architecture. On my machine:
> ...
> That is, the unaligned column is 4x slower (!). numexpr allows somewhat
> better results:
> ...
> Yes, in this case, the unalign
On 7 Mar 2013 20:27, "Henry Gomersall" wrote:
>
> On Thu, 2013-03-07 at 13:36 -0600, Mayank Daga wrote:
> > Can someone point me to the definition of dot() in the numpy source?
> > The only instance of 'def dot()' I found was in numpy/ma/extras.py but
> > that does not seem to be the correct one.
On Thu, 2013-03-07 at 13:36 -0600, Mayank Daga wrote:
> Can someone point me to the definition of dot() in the numpy source?
> The only instance of 'def dot()' I found was in numpy/ma/extras.py but
> that does not seem to be the correct one.
It seems to be in a dynamic library.
In [9]: numpy.dot.
Hi,
Can someone point me to the definition of dot() in the numpy source? The
only instance of 'def dot()' I found was in numpy/ma/extras.py but that
does not seem to be the correct one.
~mayank
--
Mayank Daga
"Nothing Succeeds Like Success"
___
NumPy-
On Sat, Mar 2, 2013 at 5:32 PM, Scott Collis wrote:
> Good afternoon list,
> I am looking at feature tracking in a 2D numpy array, along the lines of
> Dixon and Wiener 1993 (for tracking precipitating storms)
>
> Identifying features based on threshold is quite trivial using
> ndimage.label
>
>
Hi,
It is normal that unaligned access are slower. The hardware have been
optimized for aligned access. So this is a user choice space vs speed.
We can't go around that. We can only minimize the cost of unaligned
access in some cases, but not all and those optimization depend of the
CPU. But newer
On 3/7/13 6:47 PM, Francesc Alted wrote:
> On 3/6/13 7:42 PM, Kurt Smith wrote:
>> And regarding performance, doing simple timings shows a 30%-ish
>> slowdown for unaligned operations:
>>
>> In [36]: %timeit packed_arr['b']**2
>> 100 loops, best of 3: 2.48 ms per loop
>>
>> In [37]: %timeit aligned
On 3/6/13 7:42 PM, Kurt Smith wrote:
> And regarding performance, doing simple timings shows a 30%-ish
> slowdown for unaligned operations:
>
> In [36]: %timeit packed_arr['b']**2
> 100 loops, best of 3: 2.48 ms per loop
>
> In [37]: %timeit aligned_arr['b']**2
> 1000 loops, best of 3: 1.9 ms per l
On Thu, Mar 7, 2013 at 9:22 AM, eat wrote:
> Hi,
>
> On Thu, Mar 7, 2013 at 1:52 AM, Jaime Fernández del Río <
> jaime.f...@gmail.com> wrote:
>
>> On Tue, Mar 5, 2013 at 5:23 AM, Charles R Harris <
>> charlesr.har...@gmail.com> wrote:
>>
>>>
>>>
>>> On Tue, Mar 5, 2013 at 12:41 AM, Jaime Fernánde
Under what conditions should I expect fminbound
to call the supplied function with argument values
substantially outside the user-provided bounds?
Thanks,
Alan Isaac
___
NumPy-Discussion mailing list
NumPy-Discussion@scipy.org
http://mail.scipy.org/mailm
11 matches
Mail list logo
