Contributing¶
Contributions are welcome and can be submitted as pull requests here. Before contributing new material, please raise a new issue and tag it as enhancement. This will provide an opportunity to discuss the proposed changes with other contributors before a new feature is introduced.
Pull request checklist:
- Please ensure that your contributions follow general PEP 8 style guidelines;
- Only submit documented code;
- Make sure that all existing tests still pass or update the failing ones if they are no longer relevant;
- Include new tests if the current suite does not cover your contributions;
- Keep each pull request small and linked to a single issue.
Raising Issues¶
Raise any issues encountered on the appropriate GitHub page. Please include a MWE of the problem, a list of packages installed in your python environment, and a detailed description of the workflow which led to the error.
Citing GloMPO in Your Work¶
If you find GloMPO useful, please cite the follow article in your work:
Freitas Gustavo, M., Verstraelen, T. GloMPO (Globally Managed Parallel Optimization): a tool for expensive, black-box optimizations, application to ReaxFF reparameterizations. J Cheminform 14, 7 (2022). https://doi.org/10.1186/s13321-022-00581-z
References¶
| [a] | Gavana, A. (2013). Test Functions Index. Infinity77. http://www.infinity77.net/global_optimization/test_functions.html#test-functions-index |
| [b] | Surjanovic, S. and Bingham, Derek (2013). Optimization Test Problems. Simon Fraser University. http://www.sfu.ca/~ssurjano/optimization.html |
| [c] | Hansen, N. (2021). CMA-ES, Covariance Matrix Adaptation Evolution Strategy for non-linear numerical optimization in Python. PyPI. https://pypi.org/project/cma/ |
| [d] | Verstraelen, T. (2021). Optimization and Sampling. GitHub. https://github.com/tovrstra/optsam |