Python Tools for Reproducible Research on Hyperbolic Problems
by R. J. LeVeque. Computing in Science and Engineering (CiSE) 11(2009), pp. 19-27. (Special issue on reproducible research.)

Abstract. Reproducible research in computational science is only possible if the computer codes used to generate published results are archived in a form that can later be used to regenerate the results and can be examined to determine details of the method used. Some difficulties in achieving this goal are discussed. A set of Python tools for facilitating reproducible research on finite volume methods for hyperbolic conservation laws using the Clawpack software are briefly surveyed and illustrated on a sample application.

Guest Editors' Introduction to the Special Issue: Reproducible Research, by S. Fomel and J. Claerbout.

Paper: cise09.pdf

Note that Clawpack is rapidly evolving and the tools used in the code below are being supplanted by better ones.
For more recent documentation and links on sharing Clawpack codes, see www.clawpack.org/sharing

Python and Fortran code to reproduce the results in this paper:

• README file with links to browse

• cise08levequeV3.tar.gz Self-contained tar file. Unpack using:
  

   tar -zxvf cise08levequeV3.tar.gz

  Then see the README or README.html file.

• Hints on getting python / matplotlib to work

• mathcode2html python script for literate programming.
• A modified version of this, clawcode2html.py is included in the tar file.

The two-dimensional advection equation is solved on three different types of grids both with and without limiters and the accuracy compared.

• Grid 1: Cartesian
• Grid 2: Polar
• Grid 3: Quadrilateral grid from paper with D. Calhoun and C. Helzel

• Log-log plot of errors

bibtex entry:

@article{rjl:cise09,
  author="R. J. LeVeque",
  title="Python Tools for Reproducible Research on Hyperbolic Problems",
  journal="Computing in Science and Engineering",
  volume="11",
  year="2009",
  pages="19-27"
}