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pymor/pymor: pyMOR 2020.1.2

Stephan Rave; Petar Mlinarić; Felix Schindler; Tim Keil; Hendrik Kleikamp; Michael Laier; Andreas Buhr; Michael Schaefer; Julia Brunken; René Fritze; Luca Mechelli; cabuze

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<oai_dc:dc xmlns:dc="" xmlns:oai_dc="" xmlns:xsi="" xsi:schemaLocation="">
  <dc:creator>Stephan Rave</dc:creator>
  <dc:creator>Petar Mlinarić</dc:creator>
  <dc:creator>Felix Schindler</dc:creator>
  <dc:creator>Tim Keil</dc:creator>
  <dc:creator>Hendrik Kleikamp</dc:creator>
  <dc:creator>Michael Laier</dc:creator>
  <dc:creator>Andreas Buhr</dc:creator>
  <dc:creator>Michael Schaefer</dc:creator>
  <dc:creator>Julia Brunken</dc:creator>
  <dc:creator>René Fritze</dc:creator>
  <dc:creator>Luca Mechelli</dc:creator>
  <dc:description>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.
pyMOR 2020.1.2 is a bugfix release:

for the PyMESS bindings we now ensure solve_lyap_dense returns a NumPy array
to avoid setup problems, and following NumPy we require setuptools &lt; 49.2.0
improved consistency in Newton and line search logging output
  <dc:title>pymor/pymor: pyMOR 2020.1.2</dc:title>
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