Tiny package to compute dynamics correlations
A tiny package to compute the dynamics of stochastic and molecular simulations.
|Author:||Pierre de Buyl|
- performs the computation of mean-square displacements and correlation functions.
- accepts as input NumPy arrays storing the positions and velocities of particles.
- implements the so-called Fast Correlation Algorithm proposed by Kneller and others for the nMOLDYN analysis program.
- depends only Python and NumPy.
For a quick jump into tidynamics, have a look at the examples.
Goals and plans:
- Minimal dependencies.
- Serve as a reference implementation for common algorithms that are useful for molecular and stochastic simulations.
- Provide later a bit more flexibility to handle cross correlations and many-body systems.
It is necessary to have Python and NumPy to install and use tidynamics.
tidynamics can be installed with pip:
pip install --user tidynamics
or with conda (via conda-forge):
conda install -c conda-forge tidynamics
It is also possible to download the source code and execute the setup.py file.
I ran the tests with Python 2.7, 3.5 and 3.6 and NumPy 1.11 and 1.13. If you encounter any issue, let me know (see Contact below).
When using tidynamics in a publication, please cite the following paper:
Pierre de Buyl (2018), tidynamics: A tiny package to compute the dynamics of stochastic and molecular simulations, The Journal of Open Source Software https://doi.org/10.21105/joss.00877
We use pytest for testing:
python -m pytest
Installing tidynamics does not install the tests. It is necessary to download tidynamics’ source and to install pytest to run the tests.
Contact, support, and contribution information
Bug reports are welcome. If you consider proposing a feature, please keep in mind the goals and plans exposed above.
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