[SciPy-dev] Timeseries Unusual Behaviour

[Dave]

Firstly, thanks for a great package I find it very useful for my timeseries 
analysis at work. I have however just stumbled upon some unusual behaviour...

It appears that the `date_array` function sorts the dates when constructing a 
DateArray instance. This bit me when I tried to compare the timestamps against 
another `values` array so perhaps this behaviour should be mentioned in the 
docstring if it is indeed desirable.

The `time_series` function magically appears to be able to handle the sorted 
`DateArray` when first called, but when called again with the same arguments it 
gets the order wrong. Is this reproducible? Is it a bug? Or am I just doing 
something stupid?!

Thanks,
Dave


Python 2.5.2 (r252:60911, Feb 21 2008, 13:11:45) [MSC v.1310 32 bit (Intel)]
IPython 0.9.1 -- An enhanced Interactive Python.

In [2]: import datetime

In [3]: import scikits.timeseries as ts

In [4]: ts.__version__
Out[4]: '0.67.dev'

In [5]: numpy.__version__
Out[5]: '1.3.0.dev5859'

In [6]: dates = (datetime.datetime(2011, 5, 1, 0, 0),
   ...: datetime.datetime(2011, 8, 1, 0, 0),
   ...: datetime.datetime(2011, 6, 1, 0, 0),
   ...: datetime.datetime(2011, 9, 1, 0, 0),
   ...: datetime.datetime(2011, 7, 1, 0, 0))

In [7]: values = rand(len(dates))

In [8]: zip(dates,values)
Out[8]:
[(datetime.datetime(2011, 5, 1, 0, 0), 0.68325143668413102),
 (datetime.datetime(2011, 8, 1, 0, 0), 0.5341201248082369),
 (datetime.datetime(2011, 6, 1, 0, 0), 0.419866941013046),
 (datetime.datetime(2011, 9, 1, 0, 0), 0.73489099683479775),
 (datetime.datetime(2011, 7, 1, 0, 0), 0.7040093508897648)]

In [9]: date_array = ts.date_array(dlist=dates)

In [10]: # INCORRECT !

In [11]: zip(date_array,values)
Out[11]:
[(<U : 01-May-2011>, 0.68325143668413102),
 (<U : 01-Jun-2011>, 0.5341201248082369),
 (<U : 01-Jul-2011>, 0.419866941013046),
 (<U : 01-Aug-2011>, 0.73489099683479775),
 (<U : 01-Sep-2011>, 0.7040093508897648)]

In [12]: # CORRECT

In [13]: timeseries = ts.time_series(values,dates=date_array)

In [14]: zip(timeseries.dates,timeseries.data)
Out[14]:
[(<U : 01-May-2011>, 0.68325143668413102),
 (<U : 01-Jun-2011>, 0.419866941013046),
 (<U : 01-Jul-2011>, 0.7040093508897648),
 (<U : 01-Aug-2011>, 0.5341201248082369),
 (<U : 01-Sep-2011>, 0.73489099683479775)]

In [15]: # INCORRECT !?!

In [16]: timeseries = ts.time_series(values,dates=date_array)

In [17]: zip(timeseries.dates,timeseries.data)
Out[17]:
[(<U : 01-May-2011>, 0.68325143668413102),
 (<U : 01-Jun-2011>, 0.5341201248082369),
 (<U : 01-Jul-2011>, 0.419866941013046),
 (<U : 01-Aug-2011>, 0.73489099683479775),
 (<U : 01-Sep-2011>, 0.7040093508897648)]

In [18]