An object oriented Python interface for atomistic simulations

• Published in: Computer physics communications Vol. 198; pp. 230 - 237
• Main Authors: Hynninen, T., Himanen, L., Parkkinen, V., Musso, T., Corander, J., Foster, A.S.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01-01-2016
• Subjects: Atomistic simulations; Classical potential; Computer simulation; FORTRAN; Mathematical models; Object oriented; Operating systems; Programming languages; Python; Summaries; UNIX (operating system); Windows (computer programs); Atomistic simulations; Classical potential; Object oriented; Python; Fortran
• ISSN: 0010-4655; 1879-2944
• DOI: 10.1016/j.cpc.2015.09.010

Programmable simulation environments allow one to monitor and control calculations efficiently and automatically before, during, and after runtime. Environments directly accessible in a programming environment can be interfaced with powerful external analysis tools and extensions to enhance the functionality of the core program, and by incorporating a flexible object based structure, the environments make building and analysing computational setups intuitive. In this work, we present a classical atomistic force field with an interface written in Python language. The program is an extension for an existing object based atomistic simulation environment.
Program title: Pysic
Catalogue identifier: AEYE_v1_0
Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEYE_v1_0.html
Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland.
Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html
No. of lines in distributed program, including test data, etc.: 74.743.
No. of bytes in distributed program, including test data, etc.: 758.903.
Distribution format: tar.gz
Programming language: Python, Fortran 90.
Computer: Program has been tested on Linux and OS X workstations, and a Cray supercomputer.
Operating system: Linux, Unix, OS X, Windows.
RAM: Depends on the size of system.
Classification: 7.7, 16.9, 4.14.
External routines: Atomic Simulation Environment, NumPy necessary. Scipy, Matplotlib, HDF5, h5py recommended. The random number generator, Mersenne Twister, is included from the source: http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/VERSIONS/FORTRAN/mt95.f90
Nature of problem: Automated simulation control, interaction tuning and an intuitive interface for running atomistic simulations.
Solution method: Object oriented interface to a flexible classical potential.
Additional comments:
User guide:http://thynnine.github.io/pysic/
Running time: Depends on the size of system.