grudge ====== .. image:: https://gitlab.tiker.net/inducer/grudge/badges/master/pipeline.svg :alt: Gitlab Build Status :target: https://gitlab.tiker.net/inducer/grudge/commits/master .. image:: https://github.com/inducer/grudge/workflows/CI/badge.svg?branch=master&event=push :alt: Github Build Status :target: https://github.com/inducer/grudge/actions?query=branch%3Amaster+workflow%3ACI+event%3Apush .. .. image:: https://badge.fury.io/py/grudge.png :alt: Python Package Index Release Page :target: https://pypi.org/project/grudge/ grudge helps you discretize discontinuous Galerkin operators, quickly and accurately. It relies on * `numpy <http://pypi.org/project/numpy>`_ for arrays * `modepy <http://pypi.org/project/modepy>`_ for modes and nodes on simplices * `meshmode <http://pypi.org/project/meshmode>`_ for modes and nodes on simplices * `loopy <http://pypi.org/project/loopy>`_ for fast array operations * `leap <http://pypi.org/project/leap>`_ for time integration * `dagrt <http://pypi.org/project/dagrt>`_ as an execution runtime * `pytest <http://pypi.org/project/pytest>`_ for automated testing and, indirectly, * `PyOpenCL <http://pypi.org/project/pyopencl>`_ as computational infrastructure PyOpenCL is likely the only package you'll have to install by hand, all the others will be installed automatically. .. image:: https://badge.fury.io/py/grudge.png :target: http://pypi..org/project/grudge Resources: * `documentation <http://documen.tician.de/grudge>`_ * `wiki home page <http://wiki.tiker.net/Grudge>`_ * `source code via git <http://gitlab.tiker.net/inducer/grudge>`_