README
The Free Energy and Advanced Sampling Simulation Toolkit (FEASST) is a free, open-source, public domain software to conduct molecular and particle-based simulations with Monte Carlo methods.
Note
Manuscript: https://doi.org/10.6028/jres.123.004
Website: https://pages.nist.gov/feasst/
Website DOI: https://doi.org/10.18434/M3S095
Code repository: https://github.com/usnistgov/feasst
Discussion list: https://groups.google.com/a/list.nist.gov/d/forum/feasst
Features
The features available in the Text Interface are summarized as follows:
Monte Carlo simulation techniques
Metropolis
Wang-Landau
Transition-matrix
Mayer-sampling
Thermodynamic ensembles
Microcanonical ensemble
Canonical ensemble
Grand-canonical ensemble
Temperature and growth expanded ensembles
Gibbs ensemble
Interaction potentials
Lennard-Jones and Mie with cut/force shift and corrections
Hard spheres and square wells
Patchy and anisotropic particles
Yukawa and charged interactions
Ewald summation and 2D slab correction
Bonds, angles and dihedrals
TraPPE small molecules and n-alkanes
Slab, cylindrical and spherical confinement
Cell list and neighbor list
Monte Carlo trials
Translation, rotation, crankshaft and pivot
Rigid cluster rotation and translation
Configurational bias transfers and partial regrowth
Dual-cut configurational bias
Aggregation volume bias
Reptation
Branches
Modern software
Interface as text input, C++ or Python module
OpenMP parallelization and prefetching
Checkpoint files to save, restart and analyze simulations
How to get started
First, compile the executables as described below. Second, find Tutorials that are closest to what you would like to accomplish. Third, reproduce the expected result of those tutorials. Fourth, use the Text Interface documentation to better understand and modify the tutorial to accomplish your goals. When you Contact us with issues, include the text input file instead of the python script that generates that text file.
How to install (i.e., compile the executables)
[apt/yum/brew] install g++ cmake git python3
git clone https://github.com/usnistgov/feasst.git
mkdir feasst/build
cd feasst/build
cmake ..
make install -j4
# optional python packages for feasst tutorials
pip install ../pyfeasst jupyter matplotlib pandas scipy
The executables fst and rst should appear in /path/to/feasst/build/bin/. Text input files are run using fst < input.txt while simulations are restarted using rst checkpoint.txt. It is important to provide pip a path to the specific pyfeasst directory in feasst to ensure the versions match (e.g., do not leave out the “../” above).
Troubleshooting install
Please Contact us if you run into an issue not listed below.
CentOS 7
CMake version is usually too old. Try the command cmake3 instead of cmake.
Rocky 8
yum install gcc-c++
Ubuntu 16
Update to CMake 3 (https://cmake.org/download/)
Ubuntu 18, 20, 22
We are not aware of any install issues with these OS.
Cray (NERSC CORI)
OpenMP functions may not work unless the cray programming environment is disabled.
macOS Mojave
for omp, try brew install libomp
Windows 10
Install Windows subsystem for Linux (Ubuntu 16)
See Ubuntu 16
Documentation for a specific version of FEASST
You can access the documentation of a specific version of FEASST as follows.
git clone https://github.com/usnistgov/feasst.git
cd feasst
git checkout nist-pages
git log
# find the commit of your version from git log
# (e.g., 0.19.0 is a50b4fe943832f012373f23658a9497990d70d21)
git checkout a50b4fe943832f012373f23658a9497990d70d21
google-chrome index.html
Contact
Project lead
Harold Wickes Hatch
Email list
Issue tracker
Bug reporting
Any and all bug reports are greatly appreciated in order to improve FEASST.
The following checklist is recommended to improve reproducibility so that I can get back to you more quickly.
Reproduce the issue with a minimal example to reduce the complexity, run time and file size.
Provide all output.
Provide the version (for a git install, bash command “git describe –abbrev=10 –dirty –always –tags” and commit from git log).
Provide the user code (e.g., input text file, C++ with int main() or .py file).
For installation errors, include the output of the “cmake ..” command on an empty build directory.
Disclaimer
Certain commercial firms and trade names are identified in this document in order to specify the installation and usage procedures adequately. Such identification is not intended to imply recommendation or endorsement by the National Institute of Standards and Technology, nor is it intended to imply that related products are necessarily the best available for the purpose.
License
This license was obtained from https://www.nist.gov/director/licensing (revised as of July 2017).
This data/software was developed by employees of the National Institute of Standards and Technology (NIST), an agency of the Federal Government. Pursuant to title 15 United States Code Section 105, works of NIST employees are not subject to copyright protection in the United States and are considered to be in the public domain.
The data/software is provided by NIST as a public service and is expressly provided “AS IS.” NIST MAKES NO WARRANTY OF ANY KIND, EXPRESS, IMPLIED OR STATUTORY, INCLUDING, WITHOUT LIMITATION, THE IMPLIED WARRANTY OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, NON-INFRINGEMENT AND DATA ACCURACY. NIST does not warrant or make any representations regarding the use of the data/software or the results thereof, including but not limited to the correctness, accuracy, reliability or usefulness of the data/software. NIST SHALL NOT BE LIABLE AND YOU HEREBY RELEASE NIST FROM LIABILITY FOR ANY INDIRECT, CONSEQUENTIAL, SPECIAL, OR INCIDENTAL DAMAGES (INCLUDING DAMAGES FOR LOSS OF BUSINESS PROFITS, BUSINESS INTERRUPTION, LOSS OF BUSINESS INFORMATION, AND THE LIKE), WHETHER ARISING IN TORT, CONTRACT, OR OTHERWISE, ARISING FROM OR RELATING TO THE DATA (OR THE USE OF OR INABILITY TO USE THIS DATA), EVEN IF NIST HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.
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