- Tool name , objectives, feature:
ECLAIR: Ensemble of Codes for Likelihood Analysis, Inference, and Reporting.
The ECLAIR suite of codes is meant to be used as a general inference tool, allowing to sample via MCMC techniques the posterior distribution of a set of parameters corresponding to a particular physical model, under the constraint of a number of datasets/likelihoods. It also contains a robust maximizer aimed at finding the point in parameter space corresponding to the best likelihood of any considered model.The suite also include a plotting script allowing to conveniently diagnose and check the convergence of a chain, as well as produce summary statistics on the parameters of interest.
- contact: Stéphane Ilić
- author(s):
Stéphane Ilić
with feedback and suggestions from: Michael Kopp, Louis Perenon, Daniel B. Thomas, Constantinos Skordis, Tom G. Złośnik, Nadia Bolis
- publication(s), refs: Please refer to : https://github.com/s-ilic/ECLAIR#code-of-conduct
- main url: https://github.com/s-ilic/ECLAIR
- documentation: https://github.com/s-ilic/ECLAIR/wiki
- type: (library/app?) : Python scripts + modules
- language: Python
- parallelism: OpenMP (for CLASS), Multithreading and MPI (for the sampler)
- resources required: none specifically, although the bigger the machine the better
- availability: (is it already installed somewhere?): public code on github, not installed anywhere particular