[Numpy-discussion] fixing up datetime

Mark Wiebe mwwiebe@gmail....
Tue Jun 14 15:51:15 CDT 2011


On Fri, Jun 10, 2011 at 7:04 PM, Pierre GM <pgmdevlist@gmail.com> wrote:

>
> On Jun 11, 2011, at 1:03 AM, Mark Wiebe wrote:
> >
> > I don't think you would want to extend the datetime with more metadata,
> but rather use it as a tool to create the timeseries with. You could create
> a lightweight wrapper around datetime arrays which exposed a
> timeseries-oriented interface but used the datetime functionality to do the
> computations and provide good performance with large numbers of datetimes. I
> would love it if you have the time to experiment a bit with the
> https://github.com/m-paradox/numpy branch I'm developing on, so I could
> tweak the design or add features to make this easier based on your feedback
> from using the new data type.
>
> I'll do my best, depending on my free time, alas... Did you have a chance
> to check scikits.timeseries (and its experimental branch) ? If you have any
> question about it, feel free to contact me offlist (less noise that way, we
> can always summarize the discussion).
>

I've taken a look through the documentation and some of the code, but am
finding it a bit difficult to see the motivation of all the pieces. Probably
the examples Dave Hirschfeld put in his emails are the most illuminating
thing I've seen so far, as well as some birds-eye view explanations of what
time series are within statistics.

It seems to me that what the time series analysis needs is operations for
functions sampled at particular points in time or aggregated over particular
intervals of time. With the datetime dtype in place, it should be possible
to have one code which does that for any of floats, integers, or datetimes
as the domain, and I think removing the multiplier in dtypes like 'M8[10s]'
and having that be represented as time intervals might be more flexible and
still do everything the current scikits.timeseries can do.

-Mark


> Cheers
> P.
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