danselem / altaipony

THIS IS WORK IN PROGRESS. An improved and lean version of Appaloosa w/o extensive I/O, but with de-trending but using K2SC and lightkurve.

AltaiPony

An improved and lean version of Appaloosa w/o extensive I/O, but with de-trending but using K2SC and lightkurve. The documenation (work in progress) are at altaipony.readthedocs.io

Minimum How-To ^^^^^^^^^^^^^ :

git clone https://github.com/ekaterinailin/AltaiPony.git
cd AltaiPony
python setup.py install

Structure

flarelc.py

A lightcurve class with its constructor that inherits from `k2sc and/or lightkurve`. If raw LC is read in - run detrend.py Convenience function: check if K2SC has de-trended LC already available.

detrend.py

Do K2SC detrending is stitched in here: use standalone.py

findflares.py

Split LC into continuous observation chunks. Apply thresholds to detect candidates.

fakeflares.py

Includes:

• semi-empirical flare model
• injection/recovery procedure for synthetic flares.

analysis.py

• calculates ED, duration, amplitude, uncertainties, observation times
• possibly other stats about the original flares
• (correlations with other astrophysical photometric varibility)
• flare energy correction factor
• flare recovery probability

altai.py

Main wrapper that

• 1a. takes a K2 (or TESS) ID or a path to a .fits or TPF.gz file
• 2a. creates a light curve using lightkurve.
• (2b. de-trends light curve using K2SC
• 3a. find flare candidates
• (3b. runs fake flare injection/recovery)
• (3c. Calculates flare parameters, corrects ED and returns recovery probability)