A toolkit for handling bead-spring polymers and LAMMPS output in Python
Project description
pylimer-tools
Pronunciation: "pylimer” like "pü-limer”, with the "py” as in the German word "müde” (IPA: /ˈpyːlɪmɚ/).
pylimer-tools is a toolkit for simulation, analysis, and data handling of bead–spring polymer systems in Python and C++. It combines high-level Python utilities with performant C++ extensions for common tasks in computational polymer science.
Table of Contents
1. Features
A selection of features includes:
- Monte Carlo structure (network "universe”) generation
- Dissipative Particle Dynamics (DPD) simulation with slip-springs
- Maximum Entropy Homogenization Procedure (MEHP) with and without slip-links
- LAMMPS output readers: data, dump, thermodynamic outputs
- Network analysis: loops, chain reconstruction, degree statistics
- Structural metrics: radius of gyration, end-to-end distance, distributions
- Normal mode analysis for stress autocorrelation, loss and storage modulus
- Command line interfaces for batch workflows
2. Installation
Requirements
Python >= 3.9.
Stable Release
Stable release from PyPI:
pip install pylimer-tools
Build from Source
Requirements
Build requires CMake, a C++17 compiler, and (optionally) Ninja for faster builds.
Additionally, the system packages flex and bison are required (winflexbison on Windows using choco) to build the dependency igraph.
Build
To build from source (compiles C++ extension):
git clone https://github.com/GenieTim/pylimer-tools.git
cd pylimer-tools
pip install -e .
Optional: Use provided helper scripts in ./bin (e.g. ./bin/build-wheel.sh, ./bin/build-tests.sh).
3. Test Installation
import pylimer_tools
import pylimer_tools_cpp
print("Installed version: {} == {}".format(
pylimer_tools.__version__,
pylimer_tools_cpp.__version__
))
More examples: see the examples in the documentation and their code in examples/.
Additionally, the tests and the CLI Tools may serve as examples.
4. CLI Tools
Installed console scripts:
pylimer-generate-network– generate random bead-spring networks using our MC generation procedurepylimer-analyse-networks– batch analysis / statistics given LAMMPS data (structure) filespylimer-basic-lammps-stats– quick structural stats from LAMMPS data (structure) filepylimer-displace-randomly– random displacement utility
Run any with --help for usage.
5. Documentation
Full documentation (API reference, tutorials, examples): https://genietim.github.io/pylimer-tools
6. Development & Testing
Clone and install in editable mode (see Installation). Then:
./bin/run-tests.sh # full test suite (Python + C++), includes benchmarks & tests that may fail
./bin/run-tests-short.sh # quicker subset, generates coverage, is what's run in the CI
./bin/format-code.sh # apply formatting & style (run before PR)
Generate docs:
./bin/make-stubs.sh # builds the stubs for the C++ module
./bin/make-docs.sh # build Sphinx HTML docs
Adding Features
- Add tests in
tests/(unit or integration). New functionality without tests may be deferred. - Keep public APIs documented in docstrings so they surface in Sphinx.
- If a change alters behavior, update existing tests rather than deleting them. Explain rationale in the PR.
7. Citing
If you use pylimer-tools in published work, please cite it. A minimal BibTeX example:
@software{pylimer-tools,
title = {pylimer-tools},
author = {Bernhard, Tim},
url = {https://github.com/GenieTim/pylimer-tools},
year = {2025},
note = {See CITATION.cff for full metadata and related method references}
}
Also cite the specific theoretical / methodological papers corresponding to the components you use (listed in CITATION.cff).
8. Contributing
We welcome contributions on GitHub via Issues and Pull Requests.
- Discuss larger ideas in an Issue first (helps align scope).
- Fork, branch, implement, add tests & docs.
- Run formatting and tests locally.
- Submit PR referencing the Issue (if any).
See also: Code of Conduct.
9. Code of Conduct
We strive for an inclusive, respectful environment. By participating you agree to uphold the Code of Conduct. Report concerns to the maintainer email specified there.
10. Acknowledgements
The authors gratefully acknowledge financial support from the Swiss National Science Foundation (SNSF project 200021_204196).
11. License
GPL-3.0-or-later. See LICENSE.
This project includes third-party code and libraries under various compatible licenses. See THIRD_PARTY_LICENSES.md for detailed information about all third-party dependencies and their licenses.
Pronunciation Note
"pylimer” resembles "polymer”; the playful spelling emphasizes Python integration.
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