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2020.2.0 release 2020.2.0
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2020.2rc0 post release bump to 2020.2rc0
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2020.1.1 2020.1.1
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2020.1.0 2020.1.0
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tr-rb-26_06_2020 State before pymor bump
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2019.2.0 2019.2.0
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2019.2rc0 2019.2rc0 version bump for CI
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0.5.1 Release 0.5.1 fixes wheel deploymentRelease 0.5.1
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.
Highlights of this release are:
- Support for Python 3.
- System-theoretic reduction methods.
- Bindings for the NGSolve finite element library.
- New linear algebra algorithms.
- Various VectorArray usability improvements.
- Redesign of pyMOR's projection algorithms based on RuleTables.
The full release notes can be found under the following address: http://docs.pymor.org/en/0.5.1/release_notes.html
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0.5.0 Release 0.5.0
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0.4.1Release 0.4.1
pyMOR is a software library for building model order reduction applications with the Python programming language. Its main focus lies on the application of reduced basis methods to parameterized partial differential equations. All algorithms in pyMOR are formulated in terms of abstract interfaces for seamless integration with external high-dimensional PDE solvers. Moreover, pure Python implementations of finite element and finite volume discretizations using the NumPy/SciPy scientific computing stack are provided for getting started quickly.
Highlights of this release are:
- Support for the FEniCS and deal.II PDE solver libraries.
- Parallelization of pyMOR’s reduction algorithms.
- Support classes for MPI distributed PDE solvers.
- Adaptive greedy basis generation.
- Generic reduction error estimation for parabolic problems.
- Copy-on-write semantics for VectorArrays.
- Multiple improvements to pyMOR’s discretizaion tookit.
- Improved cache backend.
The full release notes can be found under the following address: http://docs.pymor.org/en/0.4.x/release_notes.html