Welcome to pyREVS’s documentation!¶
pyREVS is a modular implementation of rare-event sampling algorithms in stochastic dynamical systems. Initially focused on Trajectory-adaptive Multilevel Splitting (TAMS), pyREVS is now amendable to other algorithms of the Importance Splitting (IS) family. pyREVS was developed to specifically handle (computationally) expensive stochastic models, where integrating the model can take hours to days on supercomputers and using a naive Monte-Carlo approach is impractical.
Warning
PR#173 introduced significant changes to the source code and API, as well as the scope of the package. The documentation has been mostly updated, but might still refers solely to TAMS or pyTAMS in some locations. Please report any issues to the GitHub repository
Installation:¶
To install pyREVS, simply use pip in your favorite environment manager
to get the latest stable version:
pip install pyrevs
or if you plan on modifying the code or test the shipped-in examples, install from sources:
git clone git@github.com:nlesc-eTAOC/pyREVS.git
cd pyREVS
pip install -e .
Quick start:¶
Only if you have used the second option above you can readily test pyREVS on a simple problem:
cd pyREVS/examples/DoubleWell2D
python sample_dw2dim.py
otherwise, please read through this documentation and in particular follow the tutorials Section to see how to implement your own model within pyREVS.
User guide:
Documentation¶
The documentation pages are distributed with the code in the docs
folder as “reStructuredText” files. The HTML is built automatically
whenever changes are pushed to the main branch on GitHub.
A local version can also be built as follows:
cd <pyREVS_root_folder>/docs
make html