[Numpy-discussion] [ANN] Nanny, faster NaN functions
josef.pktd@gmai...
josef.pktd@gmai...
Sun Nov 21 17:02:05 CST 2010
On Sun, Nov 21, 2010 at 5:09 PM, Keith Goodman <kwgoodman@gmail.com> wrote:
> On Sun, Nov 21, 2010 at 12:30 PM, <josef.pktd@gmail.com> wrote:
>> On Sun, Nov 21, 2010 at 2:48 PM, Keith Goodman <kwgoodman@gmail.com> wrote:
>>> On Sun, Nov 21, 2010 at 10:25 AM, Wes McKinney <wesmckinn@gmail.com> wrote:
>>>> On Sat, Nov 20, 2010 at 7:24 PM, Keith Goodman <kwgoodman@gmail.com> wrote:
>>>>> On Sat, Nov 20, 2010 at 3:54 PM, Wes McKinney <wesmckinn@gmail.com> wrote:
>>>>>
>>>>>> Keith (and others),
>>>>>>
>>>>>> What would you think about creating a library of mostly Cython-based
>>>>>> "domain specific functions"? So stuff like rolling statistical
>>>>>> moments, nan* functions like you have here, and all that-- NumPy-array
>>>>>> only functions that don't necessarily belong in NumPy or SciPy (but
>>>>>> could be included on down the road). You were already talking about
>>>>>> this on the statsmodels mailing list for larry. I spent a lot of time
>>>>>> writing a bunch of these for pandas over the last couple of years, and
>>>>>> I would have relatively few qualms about moving these outside of
>>>>>> pandas and introducing a dependency. You could do the same for larry--
>>>>>> then we'd all be relying on the same well-vetted and tested codebase.
>>>>>
>>>>> I've started working on moving window statistics cython functions. I
>>>>> plan to make it into a package called Roly (for rolling). The
>>>>> signatures are: mov_sum(arr, window, axis=-1) and mov_nansum(arr,
>>>>> window, axis=-1), etc.
>>>>>
>>>>> I think of Nanny and Roly as two separate packages. A narrow focus is
>>>>> good for a new package. But maybe each package could be a subpackage
>>>>> in a super package?
>>>>>
>>>>> Would the function signatures in Nanny (exact duplicates of the
>>>>> corresponding functions in Numpy and Scipy) work for pandas? I plan to
>>>>> use Nanny in larry. I'll try to get the structure of the Nanny package
>>>>> in place. But if it doesn't attract any interest after that then I may
>>>>> fold it into larry.
>>>>> _______________________________________________
>>>>> NumPy-Discussion mailing list
>>>>> NumPy-Discussion@scipy.org
>>>>> http://mail.scipy.org/mailman/listinfo/numpy-discussion
>>>>>
>>>>
>>>> Why make multiple packages? It seems like all these functions are
>>>> somewhat related: practical tools for real-world data analysis (where
>>>> observations are often missing). I suspect having everything under one
>>>> hood would create more interest than chopping things up-- would be
>>>> very useful to folks in many different disciplines (finance,
>>>> economics, statistics, etc.). In R, for example, NA-handling is just a
>>>> part of every day life. Of course in R there is a special NA value
>>>> which is distinct from NaN-- many folks object to the use of NaN for
>>>> missing values. The alternative is masked arrays, but in my case I
>>>> wasn't willing to sacrifice so much performance for purity's sake.
>>>>
>>>> I could certainly use the nan* functions to replace code in pandas
>>>> where I've handled things in a somewhat ad hoc way.
>>>
>>> A package focused on NaN-aware functions sounds like a good idea. I
>>> think a good plan would be to start by making faster, drop-in
>>> replacements for the NaN functions that are already in numpy and
>>> scipy. That is already a lot of work. After that, one possibility is
>>> to add stuff like nancumsum, nanprod, etc. After that moving window
>>> stuff?
>>
>> and maybe group functions after that?
>
> Yes, group functions are on my list.
>
>> If there is a lot of repetition, you could use templating. Even simple
>> string substitution, if it is only replacing the dtype, works pretty
>> well. It would at least reduce some copy-paste.
>
> Unit test coverage should be good enough to mess around with trying
> templating. What's a good way to go? Write my own script that creates
> the .pyx file and call it from the make file? Or are there packages
> for doing the templating?
Depends on the scale, I tried once with simple string templates
http://codespeak.net/pipermail/cython-dev/2009-August/006614.html
here is a pastbin of another version by ....(?),
http://pastebin.com/f1a49143d discussed on the cython-dev mailing
list.
The cython list has the discussion every once in a while but I haven't
seen any conclusion yet. For heavier duty templating a proper
templating package (Jinja?) might be better.
I'm not an expert.
Josef
>
> I added nanmean (the first scipy function to enter nanny) and nanmin.
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