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A dynamic nested sampling package for computing Bayesian posteriors and evidences.

Project description

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dynesty

dynesty in action

A Dynamic Nested Sampling package for computing Bayesian posteriors and evidences. Pure Python. MIT license.

Documentation

Documentation can be found here.

Installation

The most stable release of dynesty can be installed through pip via

pip install dynesty

The current (less stable) development version can be installed by running

python setup.py install

from inside the repository.

Demos

Several Jupyter notebooks that demonstrate most of the available features of the code can be found here.

Attribution

If you find the package useful in your research, please cite it together with the papers describing the methods (see the documentation)

Project details


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