[SciPy-Dev] Lomb-Scargle Periodogram: Press & Rybicki Algorithm
Fri Mar 8 19:18:56 CST 2013
We have a cython version of this Lomb-Scargle algorithm in astroML , as
well as a generalized version that does not depend on the sample mean being
a good approximation of the true mean. We've not yet implemented the FFT
trick shown in Press & Rybicki, but it's fairly fast as-is for problems of
For some examples of it in use on astronomical data, see [2-3] below (the
examples are figures from our upcoming astro/statistics textbook). This
code is BSD-licensed, so if it seems generally useful enough to include in
scipy, it would be no problem to port it.
Also, if you have implemented an FFT-based version, it would get a fair bit
of use in the astronomy community if you were willing to contribute it to
On Fri, Mar 8, 2013 at 5:26 PM, Christian Geier <email@example.com>wrote:
> Hello everyone!
> Would you in general be considering to include the Lombscargle
> Periodogram by Press & Rybicki  into scipy in addition to the already
> present one? I find the included algorithm by Townend rather slow and
> had recently some "interesting" results returned by it.
> I've recently translated the original FORTRAN code (which is actually
> the description of the algorithm ) to (pure) python  and would like
> to know what the legal situation is in this case: can I release this
> translated code under the BSD license?
> In this case I would translate the code further to cython and supply
> tests and more documentation.
> Christian Geier
>  http://adsabs.harvard.edu/full/1989ApJ...338..277P
> SciPy-Dev mailing list
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