nsbi: | Simulation Based Inference with Nested Sampling |
---|---|
Author: | Will Handley |
Version: | 0.0.0 |
Homepage: | https://github.com/handley-lab/nsbi |
Documentation: | http://nsbi.readthedocs.io/ |
A repository for linear modelling and simulation based inference
UNDER CONSTRUCTION
nsbi
can be installed via pip
pip install nsbi
via conda
conda install -c handley-lab nsbi
or via the github repository
git clone https://github.com/handley-lab/nsbi
cd nsbi
python -m pip install .
You can check that things are working by running the test suite:
python -m pytest
black .
isort --profile black .
pydocstyle --convention=numpy nsbi
Basic requirements:
- Python 3.6+
- anesthetic
Documentation:
Tests:
Full Documentation is hosted at ReadTheDocs. To build your own local copy of the documentation you'll need to install sphinx. You can then run:
python -m pip install ".[all,docs]"
cd docs
make html
and view the documentation by opening docs/build/html/index.html
in a browser. To regenerate the automatic RST files run:
sphinx-apidoc -fM -t docs/templates/ -o docs/source/ nsbi/
If you use nsbi
to generate results for a publication, please cite
as:
Handley et al, (2024) nsbi: Simulation Based Inference with Nested Sampling
or using the BibTeX:
@article{nsbi,
year = {2023},
author = {Will Handley et al},
title = {nsbi: Simulation Based Inference with Nested Sampling},
journal = {In preparation}
}
There are many ways you can contribute via the GitHub repository.
- You can open an issue to report bugs or to propose new features.
- Pull requests are very welcome. Note that if you are going to propose major changes, be sure to open an issue for discussion first, to make sure that your PR will be accepted before you spend effort coding it.
- Adding models and data to the grid. Contact Will Handley to request models or ask for your own to be uploaded.