index.rst

.red {color:red; font-weight:bold;} .b {color:#0000FF; background-color:white;}

zeus is a Python implementation of the Ensemble Slice Sampling method.

• Fast & Robust Bayesian Inference,
• Efficient Markov Chain Monte Carlo (MCMC),
• Black-box inference, no hand-tuning,
• Excellent performance in terms of autocorrelation time and convergence rate,
• Scale to multiple CPUs without any extra effort,
• Automated Convergence diagnostics. NEW

Basic use

For instance, if you wanted to draw samples from a 10-dimensional Normal distribution, you would do something like:

import zeus
import numpy as np

def log_prob(x, ivar):
    return - 0.5 * np.sum(ivar * x**2.0)

nsteps, nwalkers, ndim = 1000, 100, 10
ivar = 1.0 / np.random.rand(ndim)
start = np.random.randn(nwalkers, ndim)

sampler = zeus.EnsembleSampler(nwalkers, ndim, log_prob, args=[ivar])
sampler.run_mcmc(start, nsteps)
chain = sampler.get_chain(flat=True)

Installation

To install zeus using pip run:

pip install zeus-mcmc

To install zeus in a [Ana]Conda environment use:

conda install -c conda-forge zeus-mcmc

Getting Started

• See the :doc:`cookbook` page to learn how to perform Bayesian Inference using zeus.
• See the :doc:`faq` page for frequently asked questions about zeus' operation.
• See the :doc:`api` page for detailed API documentation.

Citation

Please cite the following papers if you found this code useful in your research:

@article{karamanis2021zeus,
         title={zeus: A Python implementation of Ensemble Slice Sampling for efficient Bayesian parameter inference},
         author={Karamanis, Minas and Beutler, Florian and Peacock, John A},
         journal={arXiv preprint arXiv:2105.03468},
         year={2021}
        }

@article{karamanis2020ensemble,
         title = {Ensemble slice sampling: Parallel, black-box and gradient-free inference for correlated & multimodal distributions},
         author = {Karamanis, Minas and Beutler, Florian},
         journal = {arXiv preprint arXiv: 2002.06212},
         year = {2020}
        }

Licence

Copyright 2019-2021 Minas Karamanis and contributors.

zeus is free software made available under the GPL-3.0 License.

Changelog

2.4.1 (17/11/21)

• Introduced ParallelSplitRCallback callback function for checking Gelman-Rubin statistics during MPI runs.

2.4.0 (01/11/21)

• Introduced callback interface.
• Added convergence diagnostics.
• Added H5DF support.

2.3.1 (03/08/21)

• Raise exception if model fails.

2.3.0 (25/02/21)

• Added sample method which advances the chain as a generator.
• Added light_mode. When used, light_mode can significantly reduce the number of log likelihood evaluations and increase the general efficiency of the algorithm. light_mode works by performing no expansions after the end of the tuning phase. The scale factor is set to its opttimal value. This works best for approximately Gaussian distributions.
• Added start=None support for run_mcmc. When used, the sampler proceeds from the last known position of the walkers.
• Added support for both thin and thin_by arguments.

2.2.2 (21/02/21)

• Added log_prob0 and blobs0 arguments in run.
• Added get_last_sample(), get_last_log_prob() and get_last_blobs() methods.

2.2.0 (03/11/20)

• Improved vectorization.

2.1.1 (29/10/20)

• Added blobs interface to track arbitrary metadata.
• Updated GlobalMove and multimodal example.
• Fixed minor bugs.

2.0.0 (05/10/20)

• Added new Moves interface (e.g. DifferentialMove, GlobalMove, etc).
• Plotting capabilities (i.e. cornerplot).
• Updated docs.
• Fixed minor bugs.

1.2.2 (19/09/20)

• Sampler class is deprecated. New EnsembleSampler class in now available.
• New estimator for the Integrated Autocorrelation Time. It's accurate even with short chains.
• Updated ChainManager to handle thousands of CPUs.

1.2.1 (04/08/20)

• Changed to Flat-not-nested philosophy for diagnostics and ChainManager.

1.2.0 (03/08/20)

• Extended ChainManager with gather, scatter, and bcast tools.

1.1.0 (02/08/20)

• Added ChainManager to deploy into supercomputing clusters, parallelizing both chains and walkers.
• Added Convergence diagnostic tools (Gelman-Rubin, Geweke).

1.0.7 (11/05/20)

• Improved parallel distribution of tasks

.. toctree::
    :maxdepth: 1
    :caption: Cookbook Recipes
    :hidden:

    Overview <cookbook>
    notebooks/normal_distribution.ipynb
    notebooks/datafit.ipynb
    notebooks/multiprocessing.ipynb
    notebooks/MPI.ipynb

.. toctree::
    :maxdepth: 3
    :caption: Help & Reference
    :hidden:

    faq
    api