lightcurves 1.1.1

A package to analyze any kind of light curve/time series, e.g. with Bayesian Blocks, flare fitting (HOP), and a stochastic processe

lightcurves

This is the lightcurves 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.

Reference

If you use this code please cite:
Wagner, S. M., Burd, P., Dorner, D., et al. 2021, PoS, ICRC2021, 868 https://ui.adsabs.harvard.edu/abs/2022icrc.confE.868W/abstract