I agree w/ the original poster that it would help to have a MEP to clearly define what the goals of the overhaul are
Something else to keep in mind: we at least don’t normally plot dates in “earth” based time systems. ~10 years ago we contracted with John Hunter to add the arbitrary unit system to MPL. This allows users to plot in their own data types and define a converter
to handle the conversion to MPL types and labeling. We have our own “date time” like class which handles relativistic time scales (TDB, TT, TAI, GPS, Mars time, etc) at extremely high precision. We register a unit converter w/ MPL which allows our users
to plot these types natively and use the xunits keyword (or yunits) to control how the plot looks. So we can do this:
plot( x, y, xunits=“GPS”, yunits=“km/s” )
plot( x, y, xunits=“PST”, yunits=“mph” )
It would also be pretty easy to add a time zone aware unit converter with the existing MPL code which would allow you to do things w/ datetime like this:
plot( x, y, xunits=“UTC+8” )
plot( x, y, xunits=“EST” )
I guess the point of this is to remind folks that not everyone plots dates in time zone based systems…
On Thu, Jan 8, 2015 at 7:04 AM, Skip Montanaro
I’m real naive about this stuff, but I have always wondered why
matplotlib didn’t just use datetime objects, or at least use
timezone-aware datetime objects as an “interchange” format to get the
timezone stuff right.
Time zone handling is a pain in the %}€*
And the definitions keep changing.
So you need a complex DB and library that needs frequent updating.
This is why neither the standard library nor numpy support time zone handling out of the box.
But the datetime object does support a hook to add timezone info.
The numpy datetime64 may implementation may provide a similar hook in the future.
There is the pytz package, which MPL could choose to depend on.
But even that is a bit ugly–e.g. from the pytz docs:
“”“Unfortunately using the tzinfo argument of the standard datetime constructors ‘’does not work’’ with pytz for many timezones.”""
So my suggestion is that MPL punts, and stick with leaving time zone handling up to the user, I.e only use datetimes that are timezone “naive”. What this means is that MPL would always a assume all datetimes interacting with
each other are in the same time zone (including same DST status).
Anyway, I’m being a bit lazy here, so I may be wrong, but I think the issue at hand is that MPL currently uses a float array to store and manipulate datetimes, and the thought is that it may be better to use
numpy datetime64 arrays – that would give us more consistent precision, and less code to convert to/from various datetime formats.
I’m a bit on the fence about whether it’s time to do it, as datetime64 does have issues with the locale timezone, but as any implementation would want to work with not-just-the-latest numpy anyway, it may make sense to start now.
Christopher Barker, Ph.D.
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