[Numpy-discussion] fixing up datetime

[Mark Wiebe]

On Thu, Jun 9, 2011 at 1:44 AM, Pierre GM <pgmdevlist at gmail.com> wrote:

> >
> > The fact that it's a NumPy dtype probably is the biggest limiting factor
> preventing parameters like 'start' and 'end' during conversion. Having a
> datetime represent an instant in time neatly removes any ambiguity, so
> converting between days and seconds as a unit is analogous to converting
> between int32 and float32.
>
> Back to Dave's example, '2011' is not necessarily the same instant in time
> as '2011-01'. The conversion from low to high frequencies requires some
> reference. In scikits.timeseries terms, we could assume that 'START' is the
> reference. No problem with that, if we can have a way to extend that (eg,
> through some metadata). I tried something like that in the experimental
> version of scikits.timeseries I was babbling about earlier...
>

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.

Cheers,
Mark


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