[SciPy-dev] time series implementation approach

[Matt Knox]

I have just completed a fairly major rework of a lot of the guts of the timeseries module (particularly with respect to frequency conversion). Take a look at the examples script for a few ideas. But one major addition worth mentioning is that you can now do things like:

   from numpy import ma

   # assume I have defined a daily time series called myDailyData

   monthlyAverageSeries = myDailyData.convert(freq='MONTHLY', func=ma.average) 

David, you mentioned wanting to compute monthly variance... that should be fairly easy to do now, except there is no masked array version of the var function, so currently you would have to make your own version of var that works on masked arrays and then pass that in.

Also, the origin is no longer based on the year 1850, it is based on the same 0 date mx.DateTime uses (0 AD). Secondly frequency is still not supported very well, so if you need to work with intraday data, the module probably won't work very well right now.

- Matt