General Toolkit for Modeling Radial Velocities.
Written by BJ Fulton, Erik Petigura, Sarah Blunt, and Evan Sinukoff. Fulton et al. (2018)
Please cite the original publication and the following DOI if you make use of this software in your research.
Documentation is available here
With RadVel you can
- Optimize
- leverages the suite of minimizers in scipy.optimize
- Run MCMC
- leverages the emcee package for MCMC exploration of the posterior probability distribution
- Visualize
- creates quicklook summary plots and statistics
RadVel is
- Flexible
- fix/float parameters that are indexed as strings (emulates lmfit API)
- convert between different parameterizations e.g.
e omega <-> sqrtecosw sqrtesinw
- incorporate RVs from multiple telescopes
- Extensible
- Object-oriented programing makes adding new likelihoods, priors, etc. easy
- Scriptable
- Code can be run through a convenient Command-line Interface (CLI)
- Fast
- Kepler's equation solved in C (slower Python solver also included)
- MCMC is multi-threaded
Follow examples in
radvel/docs/tutorials/SyntheticData.ipynb
radvel/docs/tutorials/K2-24_Fitting+MCMC.ipynb
radvel/docs/tutorials/164922_Fitting+MCMC.ipynb
radvel/docs/tutorials/GaussianProcess-tutorial.ipynb