FLEUR with AiiDA
Developed at Forschungszentrum Jülich GmbH
Hosted at http://aiida-fleur.readthedocs.io/en/develop/index.html. For other information checkout the AiiDA docs or http://www.flapw.de.
MIT license. See license file.
The plug-in and the workflows will only work with a Fleur version using xml files as I/O.
For example check out the Fleur version released withing MAX.
WARNING: This version runs, but is still under heavy development. Restructurings are For anything contact email@example.com and feel free to write issues and contribute.
This is the basic package (plugin plus workflows) to use the FLEUR-code with the AiiDA Framework. The FLEUR-code is an all-electron DFT code using the FLAPW method, and widely applied in the material science and physics community.
The plugin :
The Fleur plug-in consists of a datastructure called FleurinpData and two plug-ins,
one for the Fleur inputgenerator (inpgen) and one for a Fleur calculation itself.
Every plug-in has an input part (defines the calculation) and an output parser, see the AiiDA documentation for general info.
Workflows in this package:
|scf||SCF-cycle of Fleur. Converge the charge density and the Total energy with multiple FLEUR runs|
|eos||Calculate and Equation of States (Lattice constant) with FLEUR|
|dos||Calculate a Density of States (DOS) with FLEUR|
|bands||Calculate a Band structure with FLEUR|
|relax||Relaxation of a crystal structure with FLEUR|
|initial_cls||initial corelevel shifts and formation energies with FLEUR|
|corehole||Workflow for corehole calculations, calculation of Binding energies with FLEUR|
See the AiiDA documentation for general info about the AiiDA workflow system or how to write workflows.
|Structure_util.py||Constains some methods to handle AiiDA structures (some of them might now be methods of the AiiDA structureData, if so use them from there!)|
|merge_parameter.py||Methods to handle parameterData nodes, i.e merge them. Which is very useful for all-electron codes, because instead of pseudo potentialsfamilies you can create now families of parameter nodes for the periodic table.|
|xml_util.py||All xml functions that are used, by parsers and other tools are in here. Some are 'general' some a very specific to Fleur.|
|read_cif.py||This can be used as stand-alone to create StructureData nodes from .cif files from an directory tree.|
Utility and tools, which are independend of AiiDA are moved to the masci-tools (material science tools) repository, which is a dependency of aiida-fleur.
From the aiida-fleur folder use:
$ pip install . # or which is very useful to keep track of the changes (developers) $ pip install -e .
To uninstall use:
$ pip uninstall aiida-fleur
Latest package release from PyPI:
$ pip install aiida-fleur
To test wether the installation was successful use:
$ verdi calculation plugins
# example output: ## Pass as a further parameter one (or more) plugin names ## to get more details on a given plugin. ... * fleur.fleur * fleur.inpgen
You should see fleur.* in the list
Also running the test set once is recommented. Under aiida_fleur/tests/:
A short sum up of the most important classes and where to find them, how to import them.
fleurinpData : aiida_fleur.data.fleurinp.py
fleurinpModifier : aiida_fleur.data.fleurinpmodifier.py
FleurinputgenCalculation : aiida_fleur.calculation.fleurinputgen.py
FleurCalculation : aiida_fleur.calculation.fleur.py
XML Schema Files:
in fleur_schema folder
The Fleur code needs a XMLSchema file, the package comes with the usual fleur schema files. The code looks in the fleur_schema/input folder for file versions that fit to the FLEUR input. Further the plugin looks in our pythonpath if it does not find any matching schema files in this defaul location.
|Class name||file name|
Utility under '/aiida_fleur/tools/':
Requirements are listed in 'requirements.txt'.
Easy plotting and other useful routines that do not depend on aiida_core are part of the masci-tools (material science tools) repository.
Besides the Forschungszentrum Juelich, this work is supported by the MaX European Centre of Excellence funded by the Horizon 2020 EINFRA-5 program, Grant No. 676598.