J/A+A/573/A101 Generalised Lomb-Scargle periodogram code (Mortier+, 2015)
BGLS: A Bayesian formalism for the generalised Lomb-Scargle periodogram.
Mortier A., Faria J.P., Correia C.M., Santerne A., Santos N.C.
<Astron. Astrophys. 573, A101 (2015)>
=2015A&A...573A.101M 2015A&A...573A.101M
ADC_Keywords: Models
Keywords: methods: data analysis - methods: statistical
Abstract:
Frequency analyses are very important in astronomy today, not least in
the ever-growing field of exoplanets, where short-period signals in
stellar radial velocity data are investigated. Periodograms are the
main (and powerful) tools for this purpose. However, recovering the
correct frequencies and assessing the probability of each frequency is
not straightforward.
We provide a formalism that is easy to implement in a code, to
describe a Bayesian periodogram that includes weights and a constant
offset in the data. The relative probability between peaks can be
easily calculated with this formalism. We discuss the differences and
agreements between the various periodogram formalisms with simulated
examples.
We used the Bayesian probability theory to describe the probability
that a full sine function (including weights derived from the errors
on the data values and a constant offset) with a specific frequency is
present in the data.
From the expression for our Baysian generalised Lomb-Scargle
periodogram (BGLS), we can easily recover the expression for the
non-Bayesian version. In the simulated examples we show that this new
formalism recovers the underlying periods better than previous
versions. A Python-based code is available for the community.
Description:
The BGLS tool calculates the Bayesian Generalized Lomb-Scargle
periodogram as described in the paper. It is written in Python (tested
on Python 2.7).
The code contains the definition of the algorithm, takes as input
arrays with a time series, a dataset and errors on those data, and
returns arrays with sampled periods and the periodogram values at
those periods.
In order to run, it requires the following python packages:
* numpy (http://www.numpy.org/)
* mpmath (http://mpmath.org/)
File Summary:
--------------------------------------------------------------------------------
FileName Lrecl Records Explanations
--------------------------------------------------------------------------------
ReadMe 80 . This file
bgls.py 81 99 BGLS code (in python)
license.txt 78 21 License
--------------------------------------------------------------------------------
Acknowledgements:
Annelies Mortier, am352(at)st-andrews.ac.uk
(End) Patricia Vannier [CDS] 01-Dec-2014