On Friday 11 July 2008 14:01:39 Francesc Alted wrote: > Ah! Very smart! I wonder if we could use this to implement a special > array with a fixed timestep that could be indexed by time instead than > by index. Something like: > > t1 = datetime.datetime(1,2,3) > t2 = datetime.datetime(3,4,5)
Well, we coded something like that in our TimeSeries class: its __getitem__ is quite bloated, but you can use integers/dates/strings as indices and get your result. We implemented in Python, so that's slow, but it works great. On Friday 11 July 2008 13:54:31 Jon Wright wrote: > Hello, > > Nice idea - please can you make it work with matplotlib's time/date > stuff too? <product placement> FYI, the scikits.timeseries has a module for plotting w/ TimeSeries objects. We had fun implementing the part where the labels change depending on the level of zoom... </product placement> About the representation (datetime vs integer): I think that everything depends on what you want to do. Our DateArray class pretty-prints results in a human format while still using integers internally. For example, >>> import scikits.timeseries as ts >>> example=ts.date_array(start_date=ts.now('M'), length=6) >>> print example [Jul-2008 Aug-2008 Sep-2008 Oct-2008 Nov-2008 Dec-2008] >>> print example.tovalue() [24091 24092 24093 24094 24095 24096] >>> print example.tolist() [datetime.datetime(2008, 7, 31, 0, 0), datetime.datetime(2008, 8, 31, 0, 0), datetime.datetime(2008, 9, 30, 0, 0), datetime.datetime(2008, 10, 31, 0, 0), datetime.datetime(2008, 11, 30, 0, 0), datetime.datetime(2008, 12, 31, 0, 0)] Et voila (like we say at home) Francesc: A few weeks back, I coded some interface between TimeSeries and pytables. I haven't really cleaned it yet but will post it very soon. Roughly, a TimeSeries object is the combination of a MaskedArray and a DateArray, and it can be readily transformed into a record-array which in turns can be transformed into a table. I experimented with various levels of nesting in the definition of dtypes, and I've been amazed by how powerful tailor-made dtypes can be. I bow to Travis O. et al. for the implementation... _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion