Examples

This software was written in 2016/17 by Michael P. Allen [email protected]/[email protected] and Dominic J. Tildesley [email protected] ("the authors"), to accompany the book Computer Simulation of Liquids, second edition, 2017 ("the text"), published by Oxford University Press ("the publishers").

Licence

Creative Commons CC0 Public Domain Dedication. To the extent possible under law, the authors have dedicated all copyright and related and neighboring rights to this software to the PUBLIC domain worldwide. This software is distributed without any warranty. You should have received a copy of the CC0 Public Domain Dedication along with this software. If not, see http://creativecommons.org/publicdomain/zero/1.0/.

Disclaimer

The authors and publishers make no warranties about the software, and disclaim liability for all uses of the software, to the fullest extent permitted by applicable law. The authors and publishers do not recommend use of this software for any purpose. It is made freely available, solely to clarify points made in the text. When using or citing the software, you should not imply endorsement by the authors or publishers.

Language

The programs contain some explanatory comments, and are written, in the main, in Fortran 2003/2008. This has some advantages: a built-in syntax for array operations, a straightforward approach to modular programming, and a basic simplicity. It is also a compiled language, which means that it is quite efficient, and widely used, so it is easy to find compilers which are optimized for different machine architectures. The common tools for parallelizing scientific codes (OpenMP and MPI) are compatible with Fortran. The User Guide contains some notes to assist in running the programs, and some typical results.

We hope that those who are used to other program languages will find little difficulty in converting these examples; also we point out the provisions, in current Fortran standards, for interoperability with C codes.

The python-examples subdirectory contains Python versions of several of these same examples, also with an accompanying User Guide.

Building the codes

On some computing platforms, the supplied SConstruct and SConscript files will build all the working examples, using SCons, an Open Source software construction tool based on Python. The homepage for SCons is at http://www.scons.org/. The SConstruct file may need to be edited (for example, to point to the correct location of libraries such as fftw3 and lapack on your system). Then, simply type scons to build each full example program in its own directory. A few examples consist of individual routines or modules, rather than working programs, so there is no need to build them.

The build process for the Fortran examples has been tested using SCons v4.6.0 (and some earlier versions back to v2.5.1 with minor changes to the SConstruct file).

If you don't like using SCons, or can't get it to work, it is not difficult to compile the programs using other methods. Bear in mind that, with Fortran, it is usually essential to compile any modules that are used by the main program, before compiling the main program itself. Take a look at the SConstruct file in any case, as it shows the file dependencies for each example. Also bear in mind that several alternative module files (e.g. md_lj_module.f90, md_lj_ll_module.f90, md_lj_omp_module.f90) contain modules with the same name (md_module in this case), since they act as drop-in replacements for each other. To avoid confusion during compilation due to intermediate files with the same name (e.g. md_module.mod) it is advisable to compile each example in its own build directory (which is what the SConstruct file is configured to do) or to delete all intermediate files before each individual compilation.

We have used gfortran v13.2.0 (and earlier versions back to v6.3) for testing, but have attempted to stick to code which conforms to the Fortran 2008 standard. Note that, by default, we do not select any optimization options in compilation. If you are using a different compiler, then the compiler and linker options in the SConstruct file will most likely need changing.

The above, general, advice should help you to build the codes on your system. Unfortunately, due to the enormous variety of computing platforms and compilers, we cannot offer more specific advice on the build process.

The Python versions do not require building, they are simply run through the Python interpreter. They have been tested with Python 3.12.2 and NumPy 1.26.4 (and previously, Python versions back to 3.6.0).

Random number generators

The Fortran examples use, for simplicity, the built-in intrinsic subroutines random_seed and random_number respectively to initialize and generate sequences of random numbers. From gfortran v7 onwards, calling random_seed() generates different, non-reproducible, sequences each time, and the examples assume this behaviour. Prior to gfortran v7, it was necessary to do something more complicated to generate different sequences each time, as exemplified by the routine init_random_seed contained in the file gnu_v6_init_random_seed.f90; but this file is now retained only for historical reference and is not included in the build process.

The Python examples use, for simplicity, NumPy convenience routines such as random.seed() and random.rand() for the same purpose. Since NumPy v1.17.0, this random number generator is classified as "legacy": a different, and more flexible, approach is now provided and recommended in the NumPy documentation. Nonetheless, the legacy generator continues to be supported within NumPy, for backwards compatibility, and so we continue to use it in these examples.

We do not recommend the above choices (using built-in and/or legacy random number generators) for production work. In any case, quite generally, you should check the behaviour of the random number generator on your own system.

Reporting errors

If you spot an error in these program files, or the accompanying documentation, please check the CONTRIBUTING guidelines first, and then raise an "issue" using the Issues tab. (You will need to be logged in to GitHub to do this).