Stephan Rave
René Fritze
Petar Mlinarić
Felix Schindler
Michael Laier
Andreas Buhr
renemilk
Michael Schaefer
Dennis Eickhorn
Julia Brunken
cabuze
2019-01-17
<p>pyMOR is a software library for building model order reduction applications with the Python programming language. Implemented algorithms include reduced basis methods for parametric linear and non-linear problems, as well as system-theoretic methods such as balanced truncation or IRKA. All algorithms in pyMOR are formulated in terms of abstract interfaces for seamless integration with external PDE solver packages. Moreover, pure Python implementations of finite element and finite volume discretizations using the NumPy/SciPy scientific computing stack are provided for getting started quickly.</p>
<p>Highlights of this release are:</p>
<ul>
<li>Support for Python 3.</li>
<li>System-theoretic reduction methods.</li>
<li>Bindings for the NGSolve finite element library.</li>
<li>New linear algebra algorithms.</li>
<li>Various VectorArray usability improvements.</li>
<li>Redesign of pyMOR's projection algorithms based on RuleTables.</li>
</ul>
<p>The full release notes can be found under the following address:
<a href="http://docs.pymor.org/en/0.5.1/release_notes.html">http://docs.pymor.org/en/0.5.1/release_notes.html</a></p>
https://doi.org/10.5281/zenodo.2542937
oai:zenodo.org:2542937
Zenodo
https://github.com/pymor/pymor/tree/0.5.1
https://doi.org/10.5281/zenodo.592992
info:eu-repo/semantics/openAccess
Other (Open)
pymor/pymor: pyMOR 0.5.1
info:eu-repo/semantics/other