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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.

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Credit: Elizaveta Ilin, 2018

AltaiPony

An improved and lean version of Appaloosa w/o extensive I/O, but with de-trending but using K2SC and lightkurve. Find the documentation at altaipony.readthedocs.io

Installation

git clone https://github.com/ekaterinailin/AltaiPony.git
cd AltaiPony
python3 setup.py install

Getting Started

See this notebook for an easy introduction.

Structure

flarelc.py

Contains the core class - FlareLightCurve. Flare finding, characterization and many utils, such as finding gaps are implemented as methods.

lcio.py and mast.py

Everything related to reading in KeplerTargetPixelFiles, KeplerLightCurveFiles, and K2SC light curves is dealt with here. All these data formats can be fetched from MAST.

altai.py

All the core flare finding functions live here.

fakeflares.py

Includes:

  • semi-empirical flare model
  • injection/recovery procedure for synthetic flares.
  • flare characterization functions that use the results from injection/recovery

utils.py

Internal helper function dump.

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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.

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  • Jupyter Notebook 66.6%
  • Python 33.4%