lsbi: Linear Simulation Based Inference

lsbi:: Linear Simulation Based Inference
Author:: Will Handley & David Yallup
Version:: 0.12.2
Homepage:: https://github.com/handley-lab/lsbi
Documentation:: http://lsbi.readthedocs.io/

A repository for linear modelling and simulation based inference

UNDER CONSTRUCTION

Features

Installation

lsbi can be installed via pip

pip install lsbi

via conda

conda install -c handley-lab lsbi

or via the github repository

git clone https://github.com/handley-lab/lsbi
cd lsbi
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 lsbi

Dependencies

Basic requirements:

Python 3.6+
anesthetic

Documentation:

Tests:

pytest

Documentation

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/ lsbi/

Citation

If you use lsbi to generate results for a publication, please cite as:

Handley et al, (2024) lsbi: Linear Simulation Based Inference.

or using the BibTeX:

@article{lsbi,
    year  = {2023},
    author = {Will Handley et al},
    title = {lsbi: Linear Simulation Based Inference},
    journal = {In preparation}
}

Contributing

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.