{"id":17493340,"url":"https://github.com/fsciortino/aurora","last_synced_at":"2025-04-05T04:08:29.904Z","repository":{"id":39486728,"uuid":"296983706","full_name":"fsciortino/Aurora","owner":"fsciortino","description":"Modern toolbox for impurity transport, neutrals and radiation modeling in magnetically-confined plasmas","archived":false,"fork":false,"pushed_at":"2025-03-26T15:02:14.000Z","size":27566,"stargazers_count":47,"open_issues_count":18,"forks_count":25,"subscribers_count":5,"default_branch":"master","last_synced_at":"2025-03-28T22:47:47.134Z","etag":null,"topics":["aurora","fusion","impurity-transport","julia","magnetic","modeling","neutrals","radiation","simulation","stellarator","tokamak"],"latest_commit_sha":null,"homepage":"https://aurora-fusion.readthedocs.io","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/fsciortino.png","metadata":{"files":{"readme":"README.rst","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2020-09-20T01:56:23.000Z","updated_at":"2025-03-18T13:47:29.000Z","dependencies_parsed_at":"2023-02-19T08:45:28.694Z","dependency_job_id":"8f93697f-ed6c-46a9-bc66-d8657eb8b605","html_url":"https://github.com/fsciortino/Aurora","commit_stats":{"total_commits":561,"total_committers":22,"mean_commits":25.5,"dds":0.1657754010695187,"last_synced_commit":"ad977d1f4e7a3714cf6f8c69622292581a8044ed"},"previous_names":[],"tags_count":51,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fsciortino%2FAurora","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fsciortino%2FAurora/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fsciortino%2FAurora/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fsciortino%2FAurora/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/fsciortino","download_url":"https://codeload.github.com/fsciortino/Aurora/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246131309,"owners_count":20728302,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["aurora","fusion","impurity-transport","julia","magnetic","modeling","neutrals","radiation","simulation","stellarator","tokamak"],"created_at":"2024-10-19T12:06:39.306Z","updated_at":"2025-03-29T03:01:58.993Z","avatar_url":"https://github.com/fsciortino.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"Aurora: a modern toolbox for impurity transport, plasma-wall interaction, neutrals and radiation modeling\n=========================================================================================================\n\n.. image:: https://badge.fury.io/py/aurorafusion.svg\n    :target: https://badge.fury.io/py/aurorafusion\n    \n.. image:: https://anaconda.org/conda-forge/aurorafusion/badges/version.svg   \n    :target: https://anaconda.org/conda-forge/aurorafusion\n\n.. image:: https://anaconda.org/conda-forge/aurorafusion/badges/latest_release_date.svg   \n    :target: https://anaconda.org/conda-forge/aurorafusion\n\n.. image:: https://anaconda.org/conda-forge/aurorafusion/badges/platforms.svg   \n    :target: https://anaconda.org/conda-forge/aurorafusion\n\n.. image:: https://anaconda.org/conda-forge/aurorafusion/badges/license.svg   \n    :target: https://anaconda.org/conda-forge/aurorafusion\n\n.. image:: https://anaconda.org/conda-forge/aurorafusion/badges/downloads.svg   \n    :target: https://anaconda.org/conda-forge/aurorafusion\n\nAurora is a package to simulate heavy-ion transport, plasma-wall interaction (PWI), neutrals and radiation in magnetically-confined plasmas. It includes a 1.5D impurity transport forward model for the plasma ions, thoroughly benchmarked with the widely-adopted STRAHL code, and a simple multi-reservoir particle balance model including neutrals recycling, pumping and interaction with the material surfaces of the simulated device. A simple interface to plot and process atomic and surface data for fusion plasmas makes it a convenient tool for spectroscopy, PWI and integrated modeling. It also offers routines to analyze neutral states of hydrogen isotopes, both from the edge of fusion plasmas and from neutral beam injection. The spectroscopic and PWI calculations can be not only applied to the output of Aurora's own forward model, but also coupled with other 1D, 2D or 3D transport codes.\n\nAurora's code is mostly written in Python 3 and Fortran 90. An experimental Julia interface has also been added. \n\nDocumentation is available at https://aurora-fusion.readthedocs.io.\n\n\nDevelopment \n-----------\n\nThe code is developed and maintained by F. Sciortino (MPI-IPP) in collaboration with T. Odstrcil (GA), A. Zito (MPI-IPP), D. Fajardo (MPI-IPP), A. Cavallaro (MIT) and R. Reksoatmodjo (W\u0026M), with support from O. Linder (MPI-IPP), C. Johnson (U. Auburn), D. Stanczak (IPPLM) and S. Smith (GA). The STRAHL documentation provided by R.Dux (MPI-IPP) was extremely helpful to guide the initial development of Aurora.\n\nNew contributors are more than welcome! Please get in touch at fsciortino-at-proximafusion.com or open a pull-request via Github. \n\nGenerally, we would appreciate if you could work with us to merge your features back into the main Aurora distribution if there is any chance that the changes that you made could be useful to others. \n\nInstallation\n------------\n\nAurora can be installed from PyPI using\n\n    pip install aurorafusion --user\n    \nYou can omit the `--user` flag if you have write-access to the default package directory on your system and wish to install there.\n\nInstalling via conda is also possible using\n\n    conda install -c conda-forge aurorafusion \n    \n    \nBoth the PyPI and conda installation are automatically updated at every package release. Note that the conda installation does not currently install dependencies on `omfit_classes`, which users may need to install via `pip` (see the `PyPI repo \u003chttps://pypi.org/project/omfit-classes/\u003e`_). \n\nTo look at the code and contribute to the Aurora repository, it is recommended to install from source, by git-cloning the  `Aurora repo \u003chttps://github.com/fsciortino/aurora\u003e`_ from Github. This will ensure that you can access the latest version of the tools. \n\nFor compilation after git-cloning, users can make use  \n\n    pip3 install . \n\n   \nNote that the makefile will not install any of the dependencies, listed in the `requirements.txt` file in the main directory. You can use this file to quickly install dependencies within a Python virtual environment, or install each dependency one at a time.\n\nThe Julia version of the code is not built by default. If you have Julia installed on your system, you can do  \n\n    make julia\n\nfrom the main package directory. This will build a Julia `sysimage` to speed up access of Julia source code from Python, but it is not strictly necessary. See the documentation to read about interfacing Python and Julia. \n\n\nAtomic data\n-----------\n\nAurora offers a simple interface to download, read, process and plot atomic data from the Atomic Data and Structure Analysis (ADAS) database, particularly through the OPEN-ADAS website: www.open-adas.ac.uk . ADAS data files can be fetched remotely and stored within the Aurora distribution directory, or users may choose to fetch ADAS files from a chosen, pre-existing directory by setting\n\n    export AURORA_ADAS_DIR=my_adas_directory\n    \nwithin their Linux environment (or analogous). If an ADAS files that is not available in AURORA_ADAS_DIR is requested by a user, Aurora attempts to download it and store it there. If you are using a public installation of Aurora and you do not have write-access to the directory where Aurora is installed, make sure to set AURORA_ADAS_DIR to a directory where you do have write-access before starting.\n\nSeveral ADAS formats can currently be managed -- please see the docs. Please contact the authors to request and/or suggest expansions of current capabilities.\n\n\nSurface data\n------------\n\nAurora also contains an interface to read and plot plasma-material interaction data, for the most fusion-relevant ion species and wall materials, namely concerning reflection, sputtering and implantation of plasma ions from/into wall materials. The data were generated with the TRIM.SP Monte Carlo program. \n\nPlease contact the authors to request and/or suggest expansions of current capabilities.\n\n\nLicense\n-------\n\nAurora is distributed under the MIT License. The package is made open-source with the hope that this will speed up research on fusion energy and make further code development easier. However, we kindly ask that all users communicate to us their purposes, difficulties and successes with Aurora, so that we may support users as much as possible and grow the code further. \n\n\nCiting Aurora\n-------------\n\nPlease see the `User Agreement \u003chttps://github.com/fsciortino/Aurora/blob/master/USER_AGREEMENT.txt\u003e`_. \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffsciortino%2Faurora","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffsciortino%2Faurora","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffsciortino%2Faurora/lists"}