matador is an aggregator, manipulator and runner of first-principles calculations, written with a bent towards battery electrode materials. The source can be found on GitHub and online documentation is hosted on ReadTheDocs.
Example Jupyter notebooks and tutorials can be found online or in the examples/ folder of the matador source code.
Written & maintained by Matthew Evans (2016-).
In the simplest case (e.g. you already have Python 3.6+ set up), pip install matador-db is sufficient to get up and running, preferably in a fresh virtual environment. More detailed instructions can be found in the Installation instructions.
Upgrading to the latest version should be as simple as pip install -U matador-db.
matador is primarily a Python library that can be used inside Python scripts/modules to create a custom workflow. There are, however, several command-line scripts bundled with matador itself. All of these scripts are listed under CLI Usage.
For basic command-line usage, please explore the help system for command. Common workflows can be found inside examples/ and in the online docs.
Please consult the full Python API documentation for programmatic usage.
The API has many features that can be explored in the examples and API documentation. As a summary, matador can be used for:
- Scraping of CASTEP (and Quantum Espresso) input/output files into flexible Python dictionaries/models.
- The creation and curation of MongoDB collections of geometry optimisation, calculations, with a powerful querying CLI/API.
- Customisable, publication-ready plots for all models, e.g. phase diagrams, PDF, PXRD, voltage profiles, electronic/vibrational bandstructures etc.
- Automated high-throughput geometry optimisations, electronic and vibrational properties using CASTEP (and Quantum Espresso) with
run3. Tested on several supercomputers. - Creation of phase diagrams and electrochemical voltage profiles from the results of DFT calculations.