J/A+A/573/A101Generalised 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.101MADC_Keywords: ModelsKeywords: methods: data analysis - methods: statisticalAbstract: 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

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