A Pythonic approach to cluster expansions
icet is a tool for the construction and sampling of alloy cluster expansions. A detailed description of the functionality provided as well as an extensive tutorial can be found in the user guide.
icet is written in Python, which allows easy integration with countless first-principles codes and analysis tools accessible from Python, and allows for a simple and intuitive user interface. All computationally demanding parts are, however, written in C++ providing performance while maintaining portability. The following snippet illustrates how one can train a cluster expansion:
cs = ClusterSpace(primitive_cell, cutoffs, species) sc = StructureContainer(cs) for structure in training_structures: sc.add_structure(structure) opt = Optimizer(sc.get_fit_data()) opt.train() ce = ClusterExpansion(cs, opt.parameters)
Afterwards the cluster expansion can be used, e.g., for finding ground state structures, or sampled via Monte Carlo simulations.
icet can be installed using pip as follows:
pip3 install icet --user
python3 -m pip install icet --user
Installation requires a C++11 compliant compiler. Please consult the installation section of the user guide for details.
icet has been developed at Chalmers University of Technology in Gothenburg (Sweden) in the Materials and Surface Theory division at the Department of Physics, in collaboration with the Data Analysis group at the Data Management and Software Center of the European Spallation Source in Copenhagen (Denmark).
When using icet in your research please cite
Also consult the Credits page of the documentation for additional references.
icet and its development are hosted on gitlab. Bugs and feature requests are ideally submitted via the gitlab issue tracker. The development team can also be reached by email via firstname.lastname@example.org.
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