Recent Releases of pymor
pymor - pyMOR 2025.1.1
We are proud to announce the release of pyMOR 2025.1!
This release introduces a major breaking change in pyMOR's VectorArray API, along with a few new features. By popular demand, VectorArrays can be now interpreted as matrices of column vectors instead of row vectors. Although, formally, VectorArrays are just sequences of abstract vectors, interface methods like lincomb, dofs or to_numpy work with 2D NumPy arrays. These arrays are now transposed such that array axis 1 (instead of axis 0) corresponds to the vector index. This change makes working with VectorArrays much more natural when translating typical matrix expressions from model order reduction or numerical linear algebra to pyMOR.
pyMOR 2025.1 contains contributions by @TiPlath. See here for more details.
- Python
Published by pmli 10 months ago
pymor - pyMOR 2024.2.0
We are proud to announce the release of pyMOR 2024.2!
The main new features are:
Randomized leave-one-out error estimator
Recalculated shifted Cholesky QR algorithm
Improved handling of time-dependent parameter values
The full release notes are available here.
pyMOR 2024.2 contains contributions by @maxbindhak, @dmitry-kabanov and @artpelling. See here for more details.
- Python
Published by HenKlei over 1 year ago
pymor - pymor 2024.1.1
This is a minor bugfix release.
What's Changed
- Backport "Fix pymor-vis call on windows #2316" by @sdrave in https://github.com/pymor/pymor/pull/2318
Full Changelog: https://github.com/pymor/pymor/compare/2024.1.0...2024.1.1
- Python
Published by sdrave almost 2 years ago
pymor - pyMOR 2024.1.0
We are proud to announce the release of pyMOR 2024.1!
The main new features are:
- vector fitting
- successive constraints method
- shifted Cholesky QR algorithm
- improved randomized range finder
- additional tutorials and MOR methods overview
The full release notes are available here.
pyMOR 2024.1 contains contributions by @maxbindhak and @artpelling. See here for more details.
- Python
Published by sdrave almost 2 years ago
pymor - pyMOR 2023.2
pyMOR 2023.2 (December 7, 2023)
We are proud to announce the release of pyMOR 2023.2! This release features new and improved tutorials and new Operators which enable fast computation for certain structured problems.
Over 375 single commits have entered this release. For a full list of changes see here.
- Python
Published by lbalicki over 2 years ago
pymor - pyMOR 2023.1
pyMOR 2023.1 (July 6, 2023)
We are proud to announce the release of pyMOR 2023.1! pyMOR now comes with three new MOR methods for port-Hamiltonian systems, a new data-driven MOR method, optimization methods for parametric problems, and an improved experience for Jupyter users.
Over 880 single commits have entered this release. For a full list of changes see here.
pyMOR 2023.1 contains contributions by @TiKeil, @steff-mueller, @MohamedAdelNaguib, @Jonas-Nicodemus, and @peoe. See here for more details.
- Python
Published by pmli almost 3 years ago
pymor - pyMOR 2022.2.1
This is a bugfix release. It includes a fix related to time-stepping of reduced-order LTIModels, a visualization fix concerning ipywidgets, and an updated "Building a Reduced Basis" tutorial due to the new RNG.
- Python
Published by pmli about 3 years ago
pymor - pyMOR 2022.2
pyMOR 2022.2 (December 30, 2022)
We are proud to announce the release of pyMOR 2022.2! pyMOR now comes with three new data-driven MOR methods and time domain analysis for linear time-invariant systems.
Over 500 single commits have entered this release. For a full list of changes see here.
pyMOR 2022.2 contains contributions by @TiKeil, @HenKlei, @peoe and @artpelling. We are also happy to welcome Hendrik as a new main developer! See here for more details.
- Python
Published by HenKlei over 3 years ago
pymor - pyMOR 2022.1.1 (Bugfix-only)
This is a bugfix-only release. Since the release of 2022.2.0 version 8 of ipywidgets was released, which is incompatible with our current Jupyter notebook visualizations. As a stop-gap measure we've pinned ipywidgets<8 in our packaging.
Additionally this bugfix release removes spurious import warnings in our documentation and tutorials.
- Python
Published by renefritze almost 4 years ago
pymor - pyMOR 2022.1
pyMOR 2022.1 (July 21, 2022)
We are proud to announce the release of pyMOR 2022.1! pyMOR now comes with support for discrete-time systems and structure-preserving MOR for symplectic systems. The neural network based reductors gained many new features, while the VectorArray implementation got simplified. We have added an experimental FEniCS discretizer and extended functionality for randomized linear algebra.
Over 760 single commits have entered this release. For a full list of changes see here.
pyMOR 2022.1 contains contributions by @pbuchfink, @mdessole, @HenKlei, @peoe, @artpelling and @ullmannsven. See here for more details.
- Python
Published by renefritze almost 4 years ago
pymor - pyMOR 2021.2.1
This is a bugfix release. The only change compared to 2021.2.0 is preventing users to face https://github.com/pymor/pymor/issues/1533 due to an upstream bug in qtpy
The full release notes for 2021.2 can be found here.
- Python
Published by renefritze over 4 years ago
pymor - pyMOR 2021.2.0
pyMOR 2021.2 (December 22, 2021)
We are proud to announce the release of pyMOR 2021.2! New features in this release are the addition of Dynamic Mode Decomposition for data-driven model order reduction and the formalization of model inputs. Further, general output error bounds for Reduced Basis reductors and experimental scikit-fem support as an alternative to the builtin discretizers were added. Wachspress' shifts accelerate the solution of Lyapunov equations for symmetric system matrices.
Over 300 single commits have entered this release. For a full list of changes see here.
pyMOR 2021.2 contains contributions by Tim Keil, Jonas Nicodemus and Henrike von Hülsen. See here for more details.
- Python
Published by renefritze over 4 years ago
pymor - pyMOR 2021.1.0
We are proud to announce the release of pyMOR 2021.1.0! This release includes several new reductors for LTI systems. In particular, methods for reducing and analyzing unstable systems have been added. ANNs can now be used in order to directly approximate output quantities. Furthermore, it is now possible to work with time-dependent parameters in pyMOR.
Over 700 single commits have entered this release. For a full list of changes see here.
pyMOR 2021.1 contains contributions by Tim Keil, Hendrik Kleikamp, Josefine Zeller and Meret Behrens.
Read the release notes for more details.
- Python
Published by renefritze over 4 years ago
pymor - pyMOR 2020.2.0
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: - Parameter derivatives of solutions and outputs - Neural network reductor for non-stationary problems - New tutorials
You can read the full release notes at https://docs.pymor.org/2020.2.0/release_notes/all.html
- Python
Published by renefritze over 5 years ago
pymor - pyMOR 2020.1.2
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 solvelyapdense returns a NumPy array
- to avoid setup problems, and following NumPy we require setuptools < 49.2.0
- improved consistency in Newton and line search logging output
- Python
Published by renefritze almost 6 years ago
pymor - pyMOR 2020.1.1
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: - Non-intrusive model order reduction using artificial neural networks. - The subspace accelerated dominant pole algorithm (SAMDP). - The implicitly restarted Arnoldi method for eigenvalue computation. - Parameter handling in pyMOR has been simplified. - A new series of hands-on tutorials.
You can read the full release notes at https://docs.pymor.org/2020.1.1/release_notes.html
- Python
Published by renefritze almost 6 years ago
pymor - pyMOR 2019.2.0
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:
- Improved model and reductor design makes pyMOR easier to extend.
- Extended VectorArray interface with generic complex number support.
- Improved and extended system-theoretic MOR methods.
- Builtin support for model outputs and parameter sensitivities.
- Python
Published by renefritze over 6 years ago
pymor - pyMOR 0.5.2
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 0.5.2 is a bugfix release:
- Fixes algorithms/arnoldi for the E != I case
- Fixes Thermalblock Demo GUI not launching correctly
- Removes broken LinearDelaySystem, LinearStochasticSystem, BilinearSystem
- Python
Published by renefritze almost 7 years ago
pymor - pyMOR 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
- Python
Published by sdrave over 7 years ago
pymor - pyMOR 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
- Python
Published by sdrave over 9 years ago
pymor - first submission of MRS2015
This release accompanies the first submission of the Milk, Rave, Schindler (2015) publication.
- Python
Published by ftalbrecht about 11 years ago
pymor - pyMOR 0.3.0
pyMOR is a modern, object-oriented software library for building advanced model order reduction applications with the Python programming language. The main goal of pyMOR is to ease the integration of model order reduction algorithms with external high-dimensional solvers by expressing each such algorithm via operations on simple, application agnostic interface classes.
Highlights of this release are: - The introduction of the vector space concept for even simpler integration with external solvers. - Addition of a generic Newton algorithm. - Support for Jacobian evaluation of empirically interpolated operators. - Greatly improved performance of the EI-Greedy algorithm. Addition of the DEIM algorithm. - A new algorithm for residual operator projection and a new, numerically stable a posteriori error estimator for stationary coercive problems based on this algorithm. (Cf. A. Buhr, C. Engwer, M. Ohlberger, S. Rave, 'A numerically stable a posteriori error estimator for reduced basis approximations of elliptic equations', proceedings of WCCM 2014, Barcelona, 2014.) - A new, easy to use mechanism for setting and accessing default values. - Serialization via the pickle module is now possible for each class in pyMOR. (See the new 'analyze_pickle' demo.) - Addition of generic iterative linear solvers which can be used in conjunction with any operator satisfying pyMOR's operator interface. Support for least squares solvers and PyAMG. - An improved SQLite-based cache backend. - Improvements to the built-in discretizations: support for bilinear finite elements and addition of a finite volume diffusion operator. - Test coverage has been raised from 46% to 75%.
Over 500 single commits have entered this new release. A full list of all changes can be obtained here.
Distribution packages for Ubuntu Linux can be obtained from our pyMOR PPA. pyMOR is also available at the Python Package Index an can be installed via pip. Further information can be found in the project's README file.
- Python
Published by sdrave over 11 years ago