Python Package code is moved to light-curve-python

light-curve

Irregular time series analysis toolbox for Rust and Python

The project is aimed to build high-performance tools for light curve analysis suitable to process alert and archival data of current ZTF and future Vera Rubin Observatory LSST photometric surveys.

The most of the code base is written on Rust and split into several crates. This repository contains light-curve crate only, which will be an umbrella for all other Rust crates. Please refer to a specific repository in this organisation to find a code you need:

• light-curve this repo containing a light-curve crate which is WIP
• light-curve-common (Currently in this repo) Common tools for other crates
• light-curve-dmdt dm-dt mapper crate and executable
• light-curve-feature A collection of feature extractors for light curves
• light-curve-interpolWIP (currently in this repo) Light curve interpolation tools. Currently it includes linear interpolation only
• light-curve-python Python light-curve and light-curve-python packages, a Python interface to light-curve-feature and light-curve-dmdt Cargo crates. It also contains few features implemented in pure Python
• base-docker-images Custom Docker images. Currently used for internal CI needs only
• test-data Light-curve data required for testing, benchmarking and development of the new features

Versioning

All package versions are unlinked, for example light-curve-python v0.a.b can depend on light-curve-dmdt v0.d.e and light-curve-feature v0.f.g. We use semver, so release 0.3.0 can be backward incompatible with 0.2.5 version of the same crate. Please refer to CHAMGELOG.md files for the changes between versions.

Citation

If you found this project useful for your research please cite Malanchev et al., 2021

@ARTICLE{2021MNRAS.502.5147M,
       author = {{Malanchev}, K.~L. and {Pruzhinskaya}, M.~V. and {Korolev}, V.~S. and {Aleo}, P.~D. and {Kornilov}, M.~V. and {Ishida}, E.~E.~O. and {Krushinsky}, V.~V. and {Mondon}, F. and {Sreejith}, S. and {Volnova}, A.~A. and {Belinski}, A.~A. and {Dodin}, A.~V. and {Tatarnikov}, A.~M. and {Zheltoukhov}, S.~G. and {(The SNAD Team)}},
        title = "{Anomaly detection in the Zwicky Transient Facility DR3}",
      journal = {\mnras},
     keywords = {methods: data analysis, astronomical data bases: miscellaneous, stars: variables: general, Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Solar and Stellar Astrophysics},
         year = 2021,
        month = apr,
       volume = {502},
       number = {4},
        pages = {5147-5175},
          doi = {10.1093/mnras/stab316},
archivePrefix = {arXiv},
       eprint = {2012.01419},
 primaryClass = {astro-ph.IM},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2021MNRAS.502.5147M},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}