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pyMOR - Model Order Reduction with Python

pyMOR is a software library for building model order reduction applications with the Python programming language. All algorithms in pyMOR are formulated in terms of abstract interfaces, allowing generic implementations to work with different backends, from NumPy/SciPy to external partial differential equation solver packages.



pyMOR is licensed under BSD-2-clause. See LICENSE.txt.


If you use pyMOR for academic work, please consider citing our publication:

R. Milk, S. Rave, F. Schindler
pyMOR - Generic Algorithms and Interfaces for Model Order Reduction
SIAM J. Sci. Comput., 38(5), pp. S194--S216, 2016

Installation via pip

We recommend installation of pyMOR in a virtual environment.

pyMOR can easily be installed with the pip command. Please note that pip versions prior to 21.1 might have problems resolving all dependencies, so running the following first is recommended:

pip install --upgrade pip

If you are not operating in a virtual environment, you can pass the optional --user argument to pip. pyMOR will then only be installed for your local user, not requiring administrator privileges.

Latest Release (without Optional Dependencies)

For an installation with minimal dependencies, run

pip install pymor

Note that most included demo scripts additionally require Qt bindings such as pyside2 to function. Therefore we recommend install pyMOR with the gui extra:

pip install pymor[gui]  # 2023.1 and later

Latest Release (with all Optional Dependencies)

The following installs the latest release of pyMOR on your system with most optional dependencies:

pip install pymor[full]

There are some optional packages not included with pymor[full] because they need additional setup on your system:

Latest Development Version

To install the latest development version of pyMOR, execute

pip install 'pymor[full] @ git+'

which requires that the git version control system is installed on your system.

Current Release Branch Version

From time to time, the main branch of pyMOR undergoes major changes and things might break (this is usually announced in our discussion forum), so you might prefer to install pyMOR from the current release branch:

pip install 'pymor[full] @ git+'

Release branches will always stay stable and will only receive bugfix commits after the corresponding release has been made.

Installation via conda

We recommend installation of pyMOR in a conda environment.

pyMOR can be installed using conda by running

conda install -c conda-forge pymor


Documentation is available online. We recommend starting with getting started, tutorials, and technical overview.

To build the documentation locally, run the following from inside the root directory of the pyMOR source tree:

make docs

This will generate HTML documentation in docs/_build/html.

External PDE Solvers

pyMOR has been designed with easy integration of external PDE solvers in mind.

We provide bindings for the following solver libraries:

A simple example for direct integration of pyMOR with a a custom solver can be found in pymordemos.minimal_cpp_demo.

An alternative approach is to import system matrices from file and use scipy.sparse-based solvers.

Environments for pyMOR Development and Tests

Please see the Developer Documentation.


Should you have any questions regarding pyMOR or wish to contribute, do not hesitate to send us an email at