![]() ![]() Shyue Ping Ong, William Davidson Richards, Anubhav Jain, Geoffroy If you use pymatgen in your research, please consider citing the following work: Please refer to the official pymatgen docs for tutorials and examples. Please check GitHub releases and commit history for the latest changes. Some extra functionality (e.g., generation of POTCARs) does require additional setup (see the pymatgen docs). If you'd like to use the latest unreleased changes on the main branch, you can install directly from GitHub: pip install -U git+ The version at the Python Package Index PyPI is always the latest stable release that is relatively bug-free and can be installed via pip: pip install pymatgen Check out the contributing page and add-ons page for details and examples. We also now have an architecture to support add-ons that expand pymatgen's functionality even further. Pymatgen has contributions from materials scientists all over the world. ![]() A growing ecosystem of developers and add-ons.It is also actively being developed and maintained by the Materials Virtual Lab, the ABINIT group and many other research groups. It is used in the well-established Materials Project. Pymatgen also comes with a complete system for handling periodic boundary conditions. This means that coordinate manipulations are fast. Many of the core numerical methods in pymatgen have been optimized by vectorizing in numpy/ scipy. Contributing to pymatgen means your research becomes more visible, which translates to greater impact. We will attribute any code you contribute to any publication you specify. It also means that pymatgen is continuously being improved. You are free to use and contribute to pymatgen. A fairly comprehensive documentation has been written to help you get to grips with it quickly. Pymatgen also uses Github Actions for continuous integration, which ensures that every new code passes a comprehensive suite of unit tests. Bugs tend to be found and corrected quickly. ![]() The analysis it produces survives rigorous scrutiny every single day. Pymatgen is used by thousands of researchers and is the analysis code powering the Materials Project. matgenb provides some example Jupyter notebooks that demonstrate how to use pymatgen functionality.For questions that are not bugs or feature requests, please use the pymatgen MatSci forum or open a GitHub discussion.Code contributions via pull request are welcome.Bug reports or feature requests: Please submit a GitHub issue.The following are resources for pymatgen: These contributions can be in the form of additional tools or modules you develop, or feature requests and bug reports. However, we also welcome your help to improve this library by making your contributions. Integration with the Materials Project REST API.Electronic structure analyses, such as density of states and band structure.Powerful analysis tools, including generation of phase diagrams, Pourbaix diagrams, diffusion analyses, reactions, etc.Extensive input/output support, including support for VASP, ABINIT, CIF, Gaussian, XYZ, and many other file formats.Highly flexible classes for the representation of Element, Site, Molecule and Structure objects.Pymatgen (Python Materials Genomics) is a robust, open-source Python ![]()
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