pxmcmc 1.0.1

Proximal Markov Chain Monte Carlo

Python ProxMCMC

Installation

Available on pypi

pip install pxmcmc

If installing from source it recommended to use poetry

git clone https://github.com/auggiemarignier/pxmcmc
cd pxmcmc
poetry install
source <ENVIRONMENT_LOCATION>/bin/activate
pytest

Documentation

Full documentation available on readthedocs.

Examples

Examples of how to use this code with sample data are found in the experiments directory. Please start with the earthtopography example, which will quickly run something to get you going!

cd experiments/earthtopography
python main.py --infile ETOPO1_Ice_hpx_256.fits
python plot.py myula_synthesis_<timestamp>.hdf5 .

The phasevel and weaklensing examples replicate the work shown in this paper.

Contributing

Contributions to the package are encouraged! If you wish to contribute, are experiencing problems with the code or need further support, please open an issue to start a discussion. Changes will be integrated via pull requests.

CITATION

If you use this package in your work please cite the following papers

Marignier (2023) PxMCMC: A Python package for proximal Markov Chain Monte Carlo, Journal of Open Source Software, 0(0), 5582. https://doi.org/10.xxxxxx

Marignier et al., Posterior sampling for inverse imaging problems on the sphere in seismology and cosmology, RAS Techniques and Instruments, Volume 2, Issue 1, January 2023, Pages 20–32, https://doi.org/10.1093/rasti/rzac010