About this software

Clawpack stands for “Conservation Laws Package” and was initially developed for linear and nonlinear hyperbolic systems of conservation laws, with a focus on implementing high-resolution Godunov type methods using limiters in a general framework applicable to many applications. These finite volume methods require a “Riemann solver” to resolve the jump discontinuity at the interface between two grid cells into waves propagating into the neighboring cells. The formulation used in Clawpack allows easy extension to the solution of hyperbolic problems that are not in conservation form.

See Wave-propagation algorithms for a brief description of the finite volume methods used in Clawpack and Riemann solvers for a description of the subroutine(s) needed to specify the hyperbolic equation being solved.

Adaptive mesh refinement is included, see AMRClaw, and routines specialized to depth-averaged geophysical flows can be found in GeoClaw.

The Pyclaw software provides a more pythonic interface and parallelism that scales to tens of thousands of cores.

New users may wish to read Which Clawpack solver should I use? before starting.

The “wave propagation” algorithms implemented in Clawpack are discribed in detail in the book Finite Volume Methods for Hyperbolic Problems [LeVeque-FVMHP]. Virtually all of the figures in this book were generated using Clawpack (version 4.3). See Examples from the book FVMHP for a list of available examples with pointers to the codes and resulting plots.

See the Bibliography for some pointers to papers describing Clawpack and the algorithms used in more detail.

License

Clawpack is distributed under the terms of the Berkeley Software Distribution (BSD) license.

See License for details.

Authors

Many people have contributed to the development of Clawpack since its inception in 1994.

Major algorithmic and software design contributions have been made by the following individuals:

  • Randall J. LeVeque, University of Washington, @rjleveque.

  • Marsha Berger, Courant Institute, NYU, @mjberger.

  • Jan Olav Langseth, Norwegian Defence Research Establishment.

  • David George, USGS Cascades Volcano Observatory, @dlgeorge.

  • David Ketcheson, KAUST @ketch.

  • Kyle Mandli, UT-Austin, @mandli.

Other major contributors include:

Numerous students and other users have also contributed towards this software, by finding bugs, suggesting improvements, and exploring its use on new applications. Thank you!

Citing this work

If you use Clawpack in publications, please cite the software itself as well, with a citation similar to the following:

Clawpack Development Team (2019), Clawpack Version 5.6.0,
http://www.clawpack.org, doi: 10.5281/zenodo.3237295

Here’s the bibtex:

@misc{clawpack,
    title={Clawpack software},
    author={{Clawpack Development Team}},
    url={http://www.clawpack.org},
    note={Version 5.6.0},
    doi={10.5281/zenodo.3237295},
    year={2019}}

Please fill in the version number that you used, and its year, with the appropriate DOI from Zenodo, if available. See Releases of Clawpack and release notes.

Also please cite the recent article:

Mandli, K.T., Ahmadia, A.J., Berger, M.J., Calhoun, D.A., George, D.L.,
Hadjimichael, Y., Ketcheson, D.I., Lemoine, G.I., LeVeque, R.J., 2016.
Clawpack: building an open source ecosystem for solving hyperbolic PDEs.
PeerJ Computer Science. doi:10.7717/peerj-cs.68

Here’s the bibtex:

@article{mandli2016clawpack,
    title={Clawpack: building an open source ecosystem for solving hyperbolic PDEs},
    author={Mandli, Kyle T and Ahmadia, Aron J and Berger, Marsha and Calhoun, Donna
    and George, David L and Hadjimichael, Yiannis and Ketcheson, David I
    and Lemoine, Grady I and LeVeque, Randall J},
    journal={PeerJ Computer Science},
    volume={2},
    pages={e68},
    year={2016},
    publisher={PeerJ Inc.},
    doi={10.7717/peerj-cs.68} }

Please also cite at least one of the following regarding the algorithms used in Clawpack (click the links for bibtex citations):

Funding

Development of this software has been supported in part by

  • NSF Grants DMS-8657319, DMS-9204329, DMS-9303404, DMS-9505021, DMS-96226645, DMS-9803442, DMS-0106511, CMS-0245206, DMS-0609661, DMS-0914942, DMS-1216732, EAR-1331412.

  • DOE Grants DE-FG06-93ER25181, DE-FG03-96ER25292, DE-FG02-88ER25053, DE-FG02-92ER25139, DE-FG03-00ER2592, DE-FC02-01ER25474

  • AFOSR grant F49620-94-0132,

  • NIH grant 5R01AR53652-2,

  • ONR grant N00014-09-1-0649

  • The Norwegian Research Council (NFR) through the program no. 101039/420.

  • The Scientific Computing Division at the National Center for Atmospheric Research (NCAR).

  • The Boeing Professorship and the Founders Term Professorship in the Department of Applied Mathematics, University of Washington.

  • University of Washington CoMotion Fellowship.

  • Grants from King Abdullah University of Science and Technology (KAUST)

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of these agencies.