Python package for K2 systematics correction using Gaussian processes.
git clone https://github.com/OxES/k2sc.gitcd k2scpython setup.py install --user
A MAST K2 light curve can be detrended by calling
where<filename> is either a MAST light curve filename, list of files, or a directory.
--flux-type can be eitherpdc orsap--de-max-time <ss> maximum time (in seconds) to run global GP hyperparameter optimization (differential evolution) before switching to local optimization.--de-npop <nn> size of the de population, can be set to 50 to speed up the optimization.--save-dir <path> defines where to save the detrended files--logfile <filename>
K2SC supports MPI automatically (requires MPI4Py.) Call k2sc as
where<files> is a list of files or a directory to be detrended (for example,path/to/ktwo*.fits).
- NumPy, SciPy, astropy, George, MPI4Py
If you use K2SC in your research, please cite
Aigrain, S., Parviainen, H. & Pope, B. (2016, accepted to MNRAS), arXiv:1603.09167
or use this ready-made BibTeX entry
@article{Aigrain2016, arxivId = {1603.09167}, author = {Aigrain, Suzanne and Parviainen, Hannu and Pope, Benjamin}, keywords = {data analysis,methods,photometry,planetary systems,techniques}, title = {{K2SC: Flexible systematics correction and detrending of K2 light curves using Gaussian Process regression}}, url = {http://arxiv.org/abs/1603.09167}, year = {2016}}
- Hannu Parviainen
- Suzanne Aigrain
- Benjamin Pope
