A dynamic nested sampling package for computing Bayesian posteriors and evidences.
A Dynamic Nested Sampling package for computing Bayesian posteriors and evidences. Pure Python. MIT license.
Documentation can be found here.
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.
Several Jupyter notebooks that demonstrate most of the available features of the code can be found here.
If you find the package useful in your research, please see the documentation for papers you should cite.
Release history Release notifications | RSS feed
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size||File type||Python version||Upload date||Hashes|
|Filename, size dynesty-1.1-py2.py3-none-any.whl (87.6 kB)||File type Wheel||Python version py2.py3||Upload date||Hashes View|
|Filename, size dynesty-1.1.tar.gz (80.6 kB)||File type Source||Python version None||Upload date||Hashes View|
Hashes for dynesty-1.1-py2.py3-none-any.whl