Skip to main content

Automated Classification of Periodic Variable Stars Using Machine Learning

Project description

UPSILoN (AUtomated Classification of Periodic Variable Stars using MachIne LearNing) aims to classify periodic variable stars such as Delta Scuti stars, RR Lyraes, Cepheids, Type II Cepheids, eclipsing binaries, and long-period variables (i.e. superclasses), and their subclasses (e.g. RR Lyrae ab, c, d, and e types) using well-sampled light curves from any astronomical time-series surveys in optical bands regardless of their survey-specific characteristics such as color, magnitude, sampling rate, etc (Kim & Bailer-Jones 2015, A&A accepted, http://arxiv.org/abs/1512.01611).

Visit https://github.com/dwkim78/upsilon for details.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for upsilon, version 1.2.8
Filename, size File type Python version Upload date Hashes
Filename, size upsilon-1.2.8.tar.gz (43.7 MB) File type Source Python version None Upload date Hashes View

Supported by

Pingdom Pingdom Monitoring Google Google Object Storage and Download Analytics Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page