John Hunter wrote: > On Thu, Dec 18, 2008 at 8:27 PM, Bradford Cross > <[email protected]> wrote: >> This is a new project I just released. >> >> I know it is C#, but some of the design and idioms would be nice in >> numpy/scipy for working with discrete event simulators, time series, and >> event stream processing. >> >> http://code.google.com/p/incremental-statistics/ > > I think an incremental stats module would be a boon to numpy or scipy. > Eric Firing has a nice module wrtten in C with a pyrex wrapper > (ringbuf) that does trailing incremental mean, median, std, min, max, > and percentile. It maintains a sorted queue to do the last three > efficiently, and handles NaN inputs. I would like to see this > extended to include exponential or other weightings to do things like > incremental trailing exponential moving averages and variances. I > don't know what the licensing terms are of this module, but it might
Licensing is no problem; I have never bothered with it, but I can tack on a BSD-type license if that would help. Eric > be a good starting point for an incremental numpy stats module, at > least if you were thinking about supporting a finite lookback window. > We have a copy of this in the py4science examples dir if you want to > take a look: > > svn co > https://matplotlib.svn.sourceforge.net/svnroot/matplotlib/trunk/py4science/examples/pyrex/trailstats > cd trailstats/ > make > python movavg_ringbuf.py > > Other things that would be very useful are incremental covariance and > regression. > > JDH _______________________________________________ Numpy-discussion mailing list [email protected] http://projects.scipy.org/mailman/listinfo/numpy-discussion
