aurorafusion 0.3.7

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Aurora is a package to simulate heavy-ion transportm neutrals and radiation in magnetically-confined plasmas. It includes a 1.5D impurity transport forward model, thoroughly benchmarked with the widely-adopted STRAHL code. It also offers routines to analyze neutral states of hydrogen isotopes, both from the edge of fusion plasmas and from neutral beam injection. A simple interface to atomic data for fusion plasmas makes it a convenient tool for spectroscopy and integrated modeling. Aurora’s code is mostly written in Python 3 and Fortran 90. An experimental Julia interface has also been added.

Documentation is available at https://aurora-fusion.readthedocs.io.

Development

The code is developed and maintained by F. Sciortino (MIT-PSFC) in collaboration with T. Odstrcil (GA), A. Cavallaro (MIT) and R. Reksoatmodjo (W&M), 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.

New contributors are more than welcome! Please get in touch at sciortino-at-psfc.mit.edu or open a pull-request via Github.

Generally, 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.

Installation

Aurora can be installed from PyPI using

pip install aurorafusion –user

You can omit the –user flag if you have write-access to the default package directory on your system and wish to install there.

Installing via conda is also possible using

conda install -c conda-forge aurorafusion

Both 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).

To look at the code and contribute to the Aurora repository, it is recommended to install from source, by git-cloning the Aurora repo from Github. This will ensure that you can access the latest version of the tools.

For compilation after git-cloning, users can make use of the setup.py file, e.g. using

python setup.py -e .

or use the makefile in the package directory to build the Fortran code using

make clean; make

Note 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.

The Julia version of the code is not built by default. If you have Julia installed on your system, you can do

make julia

from 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.

Atomic data

Aurora 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

export AURORA_ADAS_DIR=my_adas_directory

within 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.

Several ADAS formats can currently be managed – please see the docs. Please contact the authors to request and/or suggest expansions of current capabilities.

License

Aurora 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.

Citing Aurora

Please see the User Agreement. Home-page: https://github.com/fsciortino/Aurora Author: F. Sciortino Author-email: [e-mail] License: UNKNOWN Description: UNKNOWN Keywords: particle and impurity transport,neutrals,radiation,magnetic confinement fusion Platform: UNKNOWN Classifier: Programming Language :: Python :: 3 Classifier: Operating System :: OS Independent Description-Content-Type: text/markdown