A dynamic nested sampling package for computing Bayesian posteriors and evidences.
Project description
A dynamic nested sampling package for computing Bayesian posteriors and evidences. Pure Python. MIT license. Beta release.
### Documentation Documentation can be found [here](https://dynesty.readthedocs.io).
### Installation dynesty can be installed through [pip](https://pip.pypa.io/en/stable) via ` pip install dynesty ` It can also 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](https://github.com/joshspeagle/dynesty/tree/master/demos).
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
File details
Details for the file dynesty-0.8.4.tar.gz.
File metadata
- Download URL: dynesty-0.8.4.tar.gz
- Upload date:
- Size: 67.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
d6cd76ebc1d28c7e1540235f3ab229bfca96d14ff6e60329743dc98c56abdafa
|
|
| MD5 |
a52a02f8597847b46d4ca9c270abb275
|
|
| BLAKE2b-256 |
d0ae2b1a7b29ee66f3655b97cdf033a8e53b5ce0a6003159920d094454677829
|
