I've been playing around with some TimeSeries examples for the cookbook and I have noticed a couple of things that seem frankly annoying and I just wanted to ping the list and see if there was a reason for them.
1) If I run more than one task in a script, it has to load all of the pfs again. Is this by design?
2) Secondly, I have noticed that what gets returned in a parameter lookup or a quantities computation has one dimension more than desired. For example, getting the simulation time of each pf in the TimeSeries yields:
times = ts.params.current_time
where times is a list of lists, each sublist with one member, with
na.array(times).shape == (number of pfs, 1)
The same sort of thing happens with returning, say, the angular momentum vector, which will have a shape of (number of pfs, 1, 3).
It seems to me that what should be returned is a NumPy array with the dimensionality scaled down by one, e.g. the lists "in the middle" should be eliminated.