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Weighted Essentially Non-oscillatory (WENO) reconstructions.

Project description

PyWENO
======

PyWENO is a Python module for computing high-order Weighted
Essentially Non-oscillatory (WENO) reconstructions of cell-averaged
data arrays.

The basic interface provides a simple routine to compute 1D
reconstructions at various points within each grid cell. The points
at which the basic interface can reconstruct the original function at
include: left edge, right edge, Gauss-Legendre quadrature points,
Gauss-Lobatto quadrature points, and Guass-Radau quadrature points.

PyWENO can also be used as a code generator to build custom WENO
reconstructors in C, Fortran, and OpenCL on uniform grids.

Please see

http://readthedocs.org/docs/pyweno/en/latest/

for more information.


Important links
---------------

* Official project page: https://github.com/memmett/PyWENO
* Documentation: http://readthedocs.org/docs/pyweno/en/latest/


Prerequisites
-------------

To install PyWENO, you need:

* NumPy
* SymPy (optional if you avoid pyweno.symbolic)


Testing
-------

To build PyWENO and create symlinks to the extension modules:

$ python setup.py build
$ cd pyweno
$ for so in ../build/lib*/pyweno/*.so; do ln -s $so; done

Now, nosetests should work:

$ nosetests


License
-------

Please see LICENSE for copyright information.


Contributors
------------

* Matthew Emmett
* Michael Welter
* Ben Thompson

Project details


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