aim2dat 0.4.0

Automated Ab-Initio Materials Modeling and Data Analysis Toolkit: Python library for pre-, post-processing and data management of ab-initio high-throughput workflows for computational materials science.

aim2dat

aim2dat (Automated Ab-Initio Materials Modeling and Data Analysis Toolkit) is a library for pre-, post-processing and data management of ab-initio high-throughput workflows for computational materials science. For further details and documentation, please visit https://aim2dat.github.io.

Feature List

• Managing and analysing sets of crystals and molecules.
• Ab-initio high-throughput calculations based on AiiDA.
• Plotting material's properties such as electronic band structures, projected density of states or phase diagrams.
• Interface to machine learning routines via sci-kit learn.
• Function analysis: discretizing and comparing 2-dimensional functions.
• Parsers for the DFT codes CP2K, FHI-Aims and QuantumESPRESSO as well as phonopy and critic2.

Installation

pip install aim2dat

More detailed instructions are given in the documentation (https://aim2dat.github.io/installation.html).

Contributing

Contributions are very welcome and are directly handled via the code's github repository. Bug reports, feature requests or general discussions can be accomplished by filing an issue. Extensions or changes to the code can also be directly suggested by opening a pull request. Some guidelines for code contributions are given in the documentation (https://aim2dat.github.io/#contributing).