A Python implementation of the Ensemble Slice Sampling method
zeus
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.
Example
For instance, if you wanted to draw samples from a 10-dimensional Gaussian, 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)
Documentation
Read the docs at zeus-mcmc.readthedocs.io
Installation
To install zeus using pip run:
pip