On Wed, Apr 15, 2015 at 6:40 PM, Nathaniel Smith wrote:
> On Wed, Apr 15, 2015 at 6:08 PM, wrote:
>> On Wed, Apr 15, 2015 at 5:31 PM, Neil Girdhar wrote:
>>> Does it work for you to set
>>>
>>> outer = np.multiply.outer
>>>
>>> ?
>>>
>>> It's actually faster on my machine.
>>
>> I assume it doe
Cool, thanks for looking at this. P2 might still be better even if the
whole dataset is in memory because of cache misses. Partition, which I
guess is based on quickselect, is going to run over all of the data as many
times as there are bins roughly, whereas p2 only runs over it once. From a
cac
On Wed, Apr 15, 2015 at 6:08 PM, wrote:
> On Wed, Apr 15, 2015 at 5:31 PM, Neil Girdhar wrote:
>> Does it work for you to set
>>
>> outer = np.multiply.outer
>>
>> ?
>>
>> It's actually faster on my machine.
>
> I assume it does because np.corrcoeff uses it, and it's the same type
> of use cases
I don't understand. Are you at pycon by any chance?
On Wed, Apr 15, 2015 at 6:12 PM, wrote:
> On Wed, Apr 15, 2015 at 6:08 PM, wrote:
> > On Wed, Apr 15, 2015 at 5:31 PM, Neil Girdhar
> wrote:
> >> Does it work for you to set
> >>
> >> outer = np.multiply.outer
> >>
> >> ?
> >>
> >> It's act
On Wed, Apr 15, 2015 at 6:08 PM, wrote:
> On Wed, Apr 15, 2015 at 5:31 PM, Neil Girdhar wrote:
>> Does it work for you to set
>>
>> outer = np.multiply.outer
>>
>> ?
>>
>> It's actually faster on my machine.
>
> I assume it does because np.corrcoeff uses it, and it's the same type
> of use cases
On Wed, Apr 15, 2015 at 5:31 PM, Neil Girdhar wrote:
> Does it work for you to set
>
> outer = np.multiply.outer
>
> ?
>
> It's actually faster on my machine.
I assume it does because np.corrcoeff uses it, and it's the same type
of use cases.
However, I'm not using it very often (I prefer broadca
Does it work for you to set
outer = np.multiply.outer
?
It's actually faster on my machine.
On Wed, Apr 15, 2015 at 5:29 PM, wrote:
> On Wed, Apr 15, 2015 at 7:35 AM, Neil Girdhar
> wrote:
> > Yes, I totally agree. If I get started on the PR to deprecate np.outer,
> > maybe I can do it as p
On Wed, Apr 15, 2015 at 7:35 AM, Neil Girdhar wrote:
> Yes, I totally agree. If I get started on the PR to deprecate np.outer,
> maybe I can do it as part of the same PR?
>
> On Wed, Apr 15, 2015 at 4:32 AM, Sebastian Berg
> wrote:
>>
>> Just a general thing, if someone has a few minutes, I thin
Le 08/04/2015 21:19, Yuxiang Wang a écrit :
> I think spyder supports code highlighting in C and that's all...
> There's no way to compile in Spyder, is there?
>
Well, you could write a compilation script using Scons and run it from
spyder ! :)
But no, spyder is very python-oriented and there is
=
Announcing python-blosc 1.2.5
=
What is new?
This release contains support for Blosc v1.5.4 including changes to how
the GIL is kept. This was required because Blosc was refactored in the
v1.5.x line to remove global variables
On Wed, Apr 15, 2015 at 9:14 AM, Eric Moore wrote:
> This blog post, and the links within also seem relevant. Appears to have
> python code available to try things out as well.
>
>
> https://dataorigami.net/blogs/napkin-folding/19055451-percentile-and-quantile-estimation-of-big-data-the-t-digest
On Wed, Apr 15, 2015 at 8:06 AM, Neil Girdhar wrote:
> You got it. I remember this from when I worked at Google and we would
> process (many many) logs. With enough bins, the approximation is still
> really close. It's great if you want to make an automatic plot of data.
> Calling numpy.partit
This blog post, and the links within also seem relevant. Appears to have
python code available to try things out as well.
https://dataorigami.net/blogs/napkin-folding/19055451-percentile-and-quantile-estimation-of-big-data-the-t-digest
-Eric
On Wed, Apr 15, 2015 at 11:24 AM, Benjamin Root wrot
"Then you can set about convincing matplotlib and friends to
use it by default"
Just to note, this proposal was originally made over in the matplotlib
project. We sent it over here where its benefits would have wider reach.
Matplotlib's plan is not to change the defaults, but to offload as much as
You got it. I remember this from when I worked at Google and we would
process (many many) logs. With enough bins, the approximation is still
really close. It's great if you want to make an automatic plot of data.
Calling numpy.partition a hundred times is probably slower than calling P^2
with n=
On Wed, Apr 15, 2015 at 4:36 AM, Neil Girdhar wrote:
> Yeah, I'm not arguing, I'm just curious about your reasoning. That
> explains why not C++. Why would you want to do this in C and not Python?
>
Well, the algorithm has to iterate over all the inputs, updating the
estimated percentile posit
Yeah, I'm not arguing, I'm just curious about your reasoning. That
explains why not C++. Why would you want to do this in C and not Python?
On Wed, Apr 15, 2015 at 1:48 AM, Jaime Fernández del Río <
jaime.f...@gmail.com> wrote:
> On Tue, Apr 14, 2015 at 6:16 PM, Neil Girdhar
> wrote:
>
>> If y
Yes, I totally agree. If I get started on the PR to deprecate np.outer,
maybe I can do it as part of the same PR?
On Wed, Apr 15, 2015 at 4:32 AM, Sebastian Berg
wrote:
> Just a general thing, if someone has a few minutes, I think it would
> make sense to add the ufunc.reduce thing to all of th
Just a general thing, if someone has a few minutes, I think it would
make sense to add the ufunc.reduce thing to all of these functions at
least in the "See Also" or "Notes" section in the documentation.
These special attributes are not that well known, and I think that might
be a nice way to make
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