lightcurves 0.0.2

A package to analyze variability in light curves/ time series

lightcurves

This is the lightcurve repository. Check it out:
See here for scientific application of this code: https://pos.sissa.it/395/868

LC.py

Initialize a LightCurve object based on time, flux and flux_error. Study its Bayesian block representation (based on Scargle et al. 2013 https://ui.adsabs.harvard.edu/abs/2013arXiv1304.2818S/abstract ).
Characterize flares (start, peak, end time) with the HOP algorithm (following Meyer et al. 2019 https://ui.adsabs.harvard.edu/abs/2019ApJ...877...39M/abstract ). There are four different methods to define flares (baseline, half, flip, sharp) as illustrated in the Jupyter Notebook.

HOP.py

Initialize a Hopject to consider parameters of an individual flare.

LC_Set

Initialize a (large) sample of light curves to study the distribution of flare parameters whithin that sample.

If you use this code please cite:
@article{Wagner:2021jn, author = "Wagner, Sarah M. and Burd, Paul and Dorner, Daniela and Mannheim, Karl and Buson, Sara and Gokus, Andrea and Madejski, Greg and Scargle, Jeffrey and Arbet-Engels, Axel and Baack, Dominik and Balbo, Matteo and Biland, Adrian and Bretz, Thomas and Buss, Jens and Elsaesser, Dominik and Eisenberger, Laura and Hildebrand, Dorothee and Iotov, Roman and Kalenski, Adelina and Neise, Dominik and Noethe, Maximilian and Paravac, Aleksander and Rhode, Wolfgang and Schleicher, Bernd and Sliusar, Vitalii and Walter, Roland", title = "{Statistical properties of flux variations in blazar light curves at GeV and TeV energies}", doi = "10.22323/1.395.0868", journal = "PoS", year = 2021, volume = "ICRC2021", pages = "868" }