Installation

fdfault requires a C++ compiler and an MPI library, though you can run the code on a single processor if you want. The code has mostly been tested with the GNU compiler and Open MPI. Parallelization is achieved through domain decomposition, with interprocessor communication occuring after each Runge-Kutta stage to populate ghost cells with the appropriate values. Python with Numpy is required if you want to use the Python module for setting up problems and generating the input files, with support for either Python 2 or 3. The code also includes Python (requires Numpy) and MATLAB scripts for loading simulation data.

Building the Main Executable

If installing from a downloaded zip archive, enter

unzip fdfault-1.0.zip

Depending on which version you downloaded, the filename for the zipped archive might be different. Or clone the git repository using

git clone https://github.com/egdaub/fdfault.git

For most users, building the source code should simply require

cd fdfault/src
make

assuming you have Make and an appropriate C++ compiler with an MPI Library. You may need to change some of the compiler flags – I have mostly tested the code using the GNU Compilers and OpenMPI on both Linux and Mac OS X. This will create the fdfault executable in the main fdfault directory.

Installing the Python Module

You will also need to configure the python module. There are several ways to do this:

  1. Install the Python module system-wide. To make the Python tools available system-wide, change to the python directory and run setup.py (you must have setuptools installed):

    cd fdfault/python
python setup.py install

    You may also use Python 3 without any modifications. Depending on your setup, you might need administrative privileges to do the installation step. If you obtained the code by cloning the Git repository, installation in this manner will not update automatically if any of the source code files are updated. If you want to keep up to date without having to reinstall, install a development version:

    cd fdfault/python
python setup.py develop

This will simply place a link to the fdfault python directory in the system Python libraries, so any updates will automatically be available.

  1. If you would like the Python module available in any directory without installing for other users, you can simply modify your PYTHONPATH environment variable to include the full path to fdfault/python. This will only effect the current user.

  2. Some users prefer to only have the Python tools available in certain directories. The tools for setting up problems are most often used in the problems directory, and the analysis tools are most often used in the data directory.

    To make these tools available in these directories only, make a symbolic link to the python/fdfault directory in the problems directory:

    cd fdfault/problems
ln -s ../python/fdfault/ fdfault

    This will allow you to simply type import fdfault in python from within the problems directory. Similarly, to make the analysis features available in the data directory:

    cd fdfault/data
ln -s ../python/fdfault/analysis fdfault

    This allows you to type “import fdfault” from within the data directory and have the analysis tools at your disposal.

Building the Documentation

Finally you will need to build the User’s Guide (requires Sphinx, with MathJax required for the HTML verions and a LaTeX distribution for the PDF version).

cd fdfault/docs/
make html && make latexpdf

This should build the notes in the fdfault/docs/_build/html or fdfault/docs/_build/latex directories. If you wish to build only the html or pdf version, use the appropriate command. If you do not have Sphinx or LaTeX on your machine, both versions of the documentation are available on the web:

http://www.ceri.memphis.edu/people/egdaub/fdfault/_build/html/index.html (html)

http://www.ceri.memphis.edu/people/egdaub/fdfault/_build/latex/fdfault_docs.pdf (pdf)