Git Product home page Git Product logo

variable_stars's Introduction

RAMP starting kit on classification of variable stars from light curves

Build Status

Most stars emit light steadily in time, but a small fraction of them has a variable light curve: light emission versus time. We call them variable stars. The light curves are usually periodic and highly regular. There are essentially two reasons why light emission can vary. First, the star itself can be oscillating, so its light emission varies in time. Second, the star that seems a single point at Earth (because of our large distance) is actually a binary system: two stars that orbit around their common center of gravity. When the orbital plane is parallel to our line of view, the stars eclipse each other periodically, creating a light curve with a characteristic signature. Identifying, classifying, and analyzing variable stars are hugely important for calibrating distances, and making these analyses automatic will be crucial in the upcoming sky survey projects such as LSST.

The challenge in this RAMP is to design an algorithm to automatically classify variable stars from light curves.

Getting started

Install

To run a submission and the notebook you will need the dependencies listed in requirements.txt. You can install install the dependencies with the following command-line:

pip install -U -r requirements.txt

If you are using conda, we provide an environment.yml file for similar usage.

Challenge description

Get started on this RAMP with the dedicated notebook.

Test a submission

The submissions need to be located in the submissions folder. For instance for my_submission, it should be located in submissions/my_submission.

To run a specific submission, you can use the ramp-test command line:

ramp-test --submission my_submission

You can get more information regarding this command line:

ramp-test --help

To go further

You can find more information regarding ramp-workflow in the dedicated documentation

variable_stars's People

Contributors

agramfort avatar glemaitre avatar maikia avatar stephanebereux avatar

Stargazers

 avatar  avatar  avatar

Watchers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.