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Using atom-centered symmetry functions to characterize local atomic\nenvironments, Fortnet provides easy access to the famous BPNN neural network\narchitecture to predict atomic or global properties of your physical system,\nfeaturing powerful but optional MPI parallelism.\n\n|logo|\n\n\nInstallation\n============\n\n|build status|\n\nBuilding from source\n--------------------\n\n**Note:** This section describes the building with default settings in a typical\nLinux environment. For more detailed information on the build customization and\nthe build process, consult the **detailed building instructions** in\n`INSTALL.rst \u003cINSTALL.rst\u003e`_.\n\nDownload the latest stable source code from `GitHub\n\u003chttps://github.com/vanderhe/fortnet/\u003e`_::\n\n  git clone https://github.com/vanderhe/fortnet.git\n\nYou need CMake (\u003e= 3.16) to build and h5py to test Fortnet. If your environment\noffers no CMake/h5py or only older versions, you can easily install the latest\nsoftware via Python's ``pip`` command::\n\n  pip install cmake h5py\n\nStart CMake by passing your compilers environment variables ``FC``, ``CC`` and\nthe location where the code should be installed and the build directory\n(``_build``) as options::\n\n  FC=mpifort CC=gcc cmake -DCMAKE_INSTALL_PREFIX=$HOME/opt/fnet -B _build .\n\nIf the configuration was successful, start the build with::\n\n  cmake --build _build -- -j\n\nAfter successful build, you should test the code by running::\n\n  pushd _build\n  ctest -j\n  popd\n\nIf the tests were successful, install the package via::\n\n  cmake --install _build\n\nFor further details see the `detailed building instructions \u003cINSTALL.rst\u003e`_.\n\n\nObtaining via Conda\n-------------------\n\nAn alternative way of obtaining Fortnet is to install it via the conda package\nmanagement framework using `Miniconda\n\u003chttps://docs.conda.io/en/latest/miniconda.html\u003e`_ or `Anaconda\n\u003chttps://www.anaconda.com/products/individual\u003e`_. Make sure to add/enable the\n``conda-forge`` channel in order to be able to access Fortnet::\n\n  conda config --add channels conda-forge\n\nWe recommend to set up a dedicated conda environment and to use the\n`mamba installer \u003chttps://mamba.readthedocs.io/\u003e`_::\n\n  conda create --name fortnet\n  conda activate fortnet\n  conda install mamba\n\nThere are several build variants available, choose the one suiting your needs.\nFor example, by issuing ::\n\n  mamba install 'fortnet=*=nompi_*'\n\nor ::\n\n  mamba install 'fortnet=*=mpi_mpich_*'\n\nor ::\n\n  mamba install 'fortnet=*=mpi_openmpi_*'\n\nto get the last stable release of Fortnet with, respectively, serial build or\nwith MPI-parallelized build using either the MPICH or the OpenMPI framework.\n\nDepending on whether you decided for a serial or parallel version, you may\nissue ::\n\n  fnet\n\nor ::\n\n  mpirun -np ${NPROCS} fnet\n\nto start Fortnet. ${NPROCS} is to be substituted by the number of MPI tasks (in\ngeneral number of CPU cores) available.\n\n\nDocumentation\n=============\n\n|docs status|\n\nConsult following resources for documentation:\n\n* `Step-by-step instructions with selected examples (Fortnet Recipes)\n  \u003chttps://fortnet.readthedocs.io/\u003e`_\n\n\nCiting\n======\n\nWhen publishing results obtained with Fortnet, please cite the following\narticle:\n\n* `Fortnet, a software package for training Behler-Parrinello neural\n  networks; Computer Physics Communications 284, 108580 (2023)\n  \u003chttps://doi.org/10.1016/j.cpc.2022.108580\u003e`_\n\n\nContributing\n============\n\nNew features, bug fixes, documentation, tutorial examples and code testing is\nwelcome during the ongoing Fortnet development!\n\nThe project is `hosted on github \u003chttps://github.com/vanderhe/fortnet/\u003e`_.\nPlease check `CONTRIBUTING.rst \u003cCONTRIBUTING.rst\u003e`_ for guide lines.\n\nI am looking forward to your pull request!\n\n\nLicense\n=======\n\nFortnet is released under the GNU Lesser General Public License. See the\nincluded `LICENSE \u003cLICENSE\u003e`_ file for the detailed licensing conditions.\n\n\n.. |logo| image:: ./utils/art/logo.svg\n    :alt: Fortnet logo\n    :width: 90\n    :target: https://github.com/vanderhe/fortnet/\n\n.. |license| image:: ./utils/art/gnu-lgplv3.svg\n    :alt: LGPL v3.0\n    :scale: 100%\n    :target: https://opensource.org/licenses/LGPL-3.0\n\n.. |latest version| image:: https://img.shields.io/github/v/release/vanderhe/fortnet\n    :target: https://github.com/vanderhe/fortnet/releases/latest\n\n.. |doi| image:: https://img.shields.io/badge/DOI-10.1016%2Fj.cpc.2022.108580-blue\n   :target: https://doi.org/10.1016/j.cpc.2022.108580\n\n.. |docs status| image:: https://readthedocs.org/projects/fortnet/badge/?version=latest\n    :alt: Documentation Status\n    :scale: 100%\n    :target: https://fortnet.readthedocs.io/en/latest/\n\n.. |issues| image:: https://img.shields.io/github/issues/vanderhe/fortnet.svg\n    :target: https://github.com/vanderhe/fortnet/issues/\n\n.. |build status| image:: https://img.shields.io/github/actions/workflow/status/vanderhe/fortnet/build.yml\n    :target: https://github.com/vanderhe/fortnet/actions/\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvanderhe%2Ffortnet","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fvanderhe%2Ffortnet","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvanderhe%2Ffortnet/lists"}