A Pythonic approach to cluster expansions
icet is a the 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 in 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, list_of_training_structure) opt = Optimizer(sc.get_fit_data()) opt.train() ce = ClusterExpansion(cs, opt.parameters)
Afterwards the cluster expansion can be used in various ways, e.g., for finding ground state structures or for running Monte Carlo simulations.
icet can be installed by cloning the repository and running the setup.py script:
git clone firstname.lastname@example.org:materials-modeling/icet.git cd icet python3 setup.py install --user
icet requires Python3 and invokes functionality from several external libraries including the atomic simulation environment, pandas, scipy, and spglib. Installation also requires a C++11 compliant compiler. Please consult the installation section of the user guide for details.
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