Metadata-Version: 1.1
Name: serhiisavruk-kxQ2GLDZtw
Version: 1.3.9
Summary: A Pythonic approach to cluster expansions
Home-page: http://icet.materialsmodeling.org/
Author: icet developer group
Author-email: icet@materialsmodeling.org
License: Mozilla Public License 2.0 (MPL 2.0)
Description: icet
        ====
        
        **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
        <https://icet.materialsmodeling.org/>`_.
        
        **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:
        
        .. code-block:: python
        
           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.
        
        
        Installation
        ------------
        
        **icet** can be installed using pip as follows::
        
            pip3 install icet --user
        
        or alternatively::
        
            python3 -m pip install icet --user
        
        Installation requires a C++11 compliant compiler. Please consult the
        `installation section of the user guide
        <https://icet.materialsmodeling.org/installation.html>`_ for details.
        
        **icet** is based on Python3 and invokes functionality from other Python
        libraries including
        `ase <https://wiki.fysik.dtu.dk/ase>`_,
        `pandas <https://pandas.pydata.org/>`_,
        `numpy <http://www.numpy.org/>`_,
        `scipy <https://www.scipy.org/>`_,
        `scitkit-learn <http://scikit-learn.org/>`_, and
        `spglib <https://atztogo.github.io/spglib/>`_.
        
        
        Credits
        -------
        
        **icet** has been developed at Chalmers University of Technology in Gothenburg
        (Sweden) in the `Materials and Surface Theory division
        <http://www.materialsmodeling.org>`_ at the Department of Physics, in
        collaboration with the Data Analysis group at the `Data Management and Software
        Center of the European Spallation Source
        <https://europeanspallationsource.se/data-management-software#data-analysis-modelling>`_
        in Copenhagen (Denmark).
        
        When using **icet** in your research please cite
        
        | M. Ångqvist, W. A. Muñoz, J. M. Rahm, E. Fransson, C. Durniak, P. Rozyczko, T. H. Rod, and P. Erhart
        | *ICET – A Python Library for Constructing and Sampling Alloy Cluster Expansions*
        | Adv. Theory. Sim., 1900015 (2019)
        | `doi: 10.1002/adts.201900015 <https://doi.org/10.1002/adts.201900015>`_
        
        Also consult the `Credits <https://icet.materialsmodeling.org/credits>`_ page
        of the documentation for additional references.
        
        **icet** and its development are hosted on
        `gitlab <https://gitlab.com/materials-modeling/icet>`_.
        Bugs and feature requests are ideally submitted via the
        `gitlab issue tracker <https://gitlab.com/materials-modeling/icet/issues>`_.
        The development team can also be reached by email via
        icet@materialsmodeling.org.
        
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Mozilla Public License 2.0 (MPL 2.0)
Classifier: Topic :: Scientific/Engineering :: Physics
