First you’ll need a de-trended light curve (Find out how here.). If you have a raw
FlareLightCurve we can call
rawflc, for Kepler and TESS light curves use:
>>> flc = rawflc.detrend("savgol")
K2 is more difficult, and computationally intense, but doable with:
>>> flc = rawflc.detrend("k2sc")
Now you have a de-trended light curve
flc, and you can search it for flares:
>>> flc = flc.find_flares()
This will return the initial light curve with a new attribute -
flares, which is a DataFrame with the following columns:
ampl_rec- recovered amplitude measured relative to the quiescent stellar flux
ed_rec- recovered equivalent duration of the flare, that is, the are under the light curve with quiescent flux subtracted.
ed_rec_err- the minimum uncertainty on equivalent duration derived from the uncertainty on the flare flux values (see Davenport (2016) for details, Eq. (2)).
cstart, cstop, istart, istop, tstart, tstop- start and end of flare candidates in units of cadence, array index and actual time in days.