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README.rst

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+exoplanet
+=========
+
+.. raw:: html
+
+    <p>
+    <a href="https://github.com/dfm/exoplanet"><img src="https://img.shields.io/badge/GitHub-dfm%2Fexoplanet-blue.svg?style=flat"/></a>
+    <a href="https://github.com/dfm/exoplanet/blob/master/LICENSE"><img src="https://img.shields.io/badge/license-MIT-blue.svg?style=flat"/></a>
+    <a href="https://travis-ci.org/dfm/exoplanet"><img src="https://img.shields.io/travis/dfm/exoplanet/master.svg?style=flat"/></a>
+    <a href="https://travis-ci.org/dfm/exoplanet"><img src="https://img.shields.io/readthedocs/exoplanet.svg?style=flat"/></a>
+    <br>
+    <a href="https://rodluger.github.io/starry"><img src="https://img.shields.io/badge/powered_by-starry-EB5368.svg?style=flat"/></a>
+    <a href="https://celerite.readthedocs.io"><img src="https://img.shields.io/badge/powered_by-celerite-EB5368.svg?style=flat"/></a>
+    <a href="https://docs.pymc.io"><img src="https://img.shields.io/badge/powered_by-PyMC3-EB5368.svg?style=flat"/></a>
+    <a href="http://www.astropy.org"><img src="https://img.shields.io/badge/powered_by-AstroPy-EB5368.svg?style=flat"/></a>
+    </p>
+
+
+*exoplanet* is a toolkit for probabilistic modeling of transit and/or radial
+velocity observations of `exoplanets <https://en.wikipedia.org/wiki/Exoplanet>`_
+and other astronomical time series using `PyMC3 <https://docs.pymc.io>`_.
+*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:
+
+* A fast and robust solver for Kepler's equation.
+* Scalable Gaussian Processes using `celerite
+  <https://celerite.readthedocs.io>`_.
+* Fast and accurate limb darkened light curves using `starry
+  <https://rodluger.github.io/starry>`_.
+* Common reparameterizations for `limb darkening parameters
+  <https://arxiv.org/abs/1308.0009>`_, and `planet radius and impact
+  parameter <https://arxiv.org/abs/1811.04859>`_.
+* And many others!
+
+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 <https://arxiv.org/abs/1206.1901>`_,
+`No U-Turns Sampling <https://arxiv.org/abs/1111.4246>`_, and `variational
+inference <https://arxiv.org/abs/1603.00788>`_. These methods tend to be more
+robust than the methods more commonly used in astronomy (like `ensemble
+samplers <https://emcee.readthedocs.io>`_ and `nested sampling
+<https://ccpforge.cse.rl.ac.uk/gf/project/multinest/>`_) 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.
+
+*exoplanet* is being actively developed in `a public repository on GitHub
+<https://github.com/dfm/exoplanet>`_ so if you have any trouble, `open an issue
+<https://github.com/dfm/exoplanet/issues>`_ there.