[SciPy-dev] time series implementation approach

Pierre GM pgmdevlist at gmail.com
Wed Dec 13 10:21:19 CST 2006

On Wednesday 13 December 2006 10:31, Matt Knox wrote:
> Hi David,

We're working on the same kind of data. I already have routines for my 
TimeSeries to group daily data to season (a season being defined as a group 
of months such as DJF, MAM...), and compute whatever stats on those groups. 
The bottleneck is the grouping of the data, done  entirely in Python as I 
speak no C whatsoever. It works pretty fine, but it's slow. And that's 
somehow an easy case. Matt gave me some far more gruesome examples of 

> Computing monthly variance can not be done easily at the moment. The
> frequency conversion code is implemented in C and the method of conversion
> is applied at the same time in one step (averaged in this example).  Pierre
> made a good suggestion that I am going to look at doing shortly, which is
> to just group the data in C and return a 2 dimensional array to python,

Well, ultimately the idea would to group a 2D array (where each column 
represents a 1D series) in C, and get a 3D array. 

> I'm still wavering on the ShiftingArray vs sub-classing MaskedArray
> approach as the backbone of the TimeSeries object. At this moment I think I
> am leaning more towards sub-classing MaskedArray (bet you didn't expect
> that, Pierre!), but who knows what I will feel like this afternoon.

Oh, you'll probably still be leaning towards MA (I'll make sure of that). And 
we can still have the ShiftingTimeSeries approach in parallel

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