exoplanet is a toolkit for probabilistic modeling of transit and/or radial velocity observations of exoplanets and other astronomical time series using PyMC3. PyMC3 is a flexible and high-performance model building language and inference engine that scales well to problems with a large number of parameters. exoplanet extends PyMC3’s language to support many of the custom functions and distributions required when fitting exoplanet datasets. These features include:
All of these functions and distributions include methods for efficiently calculating their gradients so that they can be used with gradient-based inference methods like Hamiltonian Monte Carlo, No U-Turns Sampling, and variational inference. These methods tend to be more robust than the methods more commonly used in astronomy (like ensemble samplers and nested sampling) especially when the model has more than a few parameters. For many exoplanet applications, exoplanet (the code) can improve the typical performance by orders of magnitude.
Copyright 2018, 2019 Daniel Foreman-Mackey.
The source code is made available under the terms of the MIT license.
If you make use of this code, please cite this package and its dependencies. You can find more information about how and what to cite in the Citing exoplanet & its dependencies documentation.
DotLOpfor scalable conditional mean calculation and prior sampling with celerite
TTVOrbitmodels with large TTVs
starryto get much better performance for high order spherical harmonics
Angledistribution when the value of the angle is well constrained
optimizefunction since the
find_MAPmethod in PyMC3 is deprecated