pyMOR - Model Order Reduction with Python

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.

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License

Copyright 2013-2016 pyMOR developers and contributors. All rights reserved.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

The following files contain source code originating from other open source software projects:

See these files for more information.

Citing

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

Distribution Packages

Packages for Ubuntu are available via our PPA:

sudo apt-add-repository ppa:pymor/stable
sudo apt-get update
sudo apt-get install python-pymor

Daily snapshots are available via the pymor/daily PPA.

Demo applications and documentation are packaged separately:

sudo apt-get install python-pymor-demos
sudo apt-get install python-pymor-doc

The latter makes a pymor-demo script available, which can be used to run all installed demos.

Installation via pip

pyMOR can also easily be installed via the pip command:

pip install [--user] pymor

This will install the latest release of pyMOR on your system. If you pass the optional --user argument, pyMOR will only be installed for your local user, not requiring administrator privileges. To install the latest development version of pyMOR, execute

pip install [--user] git+https://github.com/pymor/pymor

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

From time to time, the master branch of pyMOR undergoes major changes and things might break (this is usually announced on our mailing list), so you might prefer to install pyMOR from the current release branch:

pip install [--user] git+https://github.com/pymor/pymor@0.4.x

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

Note that pyMOR depends on Cython, as well as the NumPy and SciPy packages. On all major Linux distributions, these packages can be easily installed via the distribution's package manager. For Debian-based systems (e.g. Ubuntu), the following command should work:

sudo apt-get install cython python-pip python-numpy python-scipy

When not available on your system, pip will automatically build and install these dependencies. This, however, will in turn require a full C/C++ compiler toolchain and header files for several libraries (BLAS, etc.).

After installation of pyMOR, further optional packages will be suggested if not already installed. Some of these (PySide, matplotlib, pyopengl, mpi4py) are again most easily installed via your package manager. For Debian-based systems, try:

sudo apt-get install python-pyside python-matplotlib python-opengl python-mpi4py

Again, all these dependencies can also be installed directly via pip.

Warning: Ubuntu 16.04 currently ships broken mpi4py packages which will cause pyMOR to fail at import time. Fixed packages can be found in the pyMOR PPA.

Documentation

Documentation is available online at Read the Docs or offline in the python-pymor-doc package.

To build the documentation yourself, execute

make doc

inside the root directory of the pyMOR source tree. 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.

A basic approach is to use the solver only to generate high-dimensional system matrices which are then read by pyMOR from disk (pymor.discretizers.disk). Another possibility is to steer the solver via an appropriate network protocol.

Whenever possible, we recommend to recompile the solver as a Python extension module which gives pyMOR direct access to the solver without any communication overhead. A basic example using pybindgen can be found in src/pymordemos/minimal_cpp_demo. A more elaborate nonlinear example using Boost.Python can be found here. Moreover, we provide bindings for the following solver libraries:

Do not hesitate to contact us if you need help with the integration of your PDE solver.

Setting up an Environment for pyMOR Development

First make sure that all dependencies are installed. This can be easily achieved by first installing pyMOR with its dependencies as described above. Then uninstall the pyMOR package itself, e.g.

sudo apt-get uninstall python-pymor

or

pip uninstall pyMOR

Then, clone the pyMOR git repository using

git clone https://github.com/pymor/pymor $PYMOR_SOURCE_DIR
cd $PYMOR_SOURCE_DIR

and, optionally, switch to the branch you are interested in, e.g.

git checkout 0.4.x

Then, add pyMOR to the search path of your Python interpreter, either by setting PYTHONPATH

export PYTHONPATH=$PYMOR_SOURCE_DIR/src:$PYTHONPATH

or by using a .pth file:

echo "$PYMOR_SOURCE_DIR/src" > $PYTHON_ROOT/lib/python2.7/site-packages/pymor.pth

Here, PYTHON_ROOT is either '/usr', '$HOME/.local' or the root of your virtual environment. Finally, build the Cython extension modules as described in the next section.

Cython extension modules

pyMOR uses Cython extension modules to speed up numerical algorithms which cannot be efficiently expressed using NumPy idioms. The source files of these modules (files with extension .pyx) have to be processed by Cython into a .c-file which then must be compiled into a shared object (.so file). The whole build process is handeled automatically by setup.py.

If you want to develop Cython extensions modules for pyMOR yourself, you should add your module to the ext_modules list defined in the _setup method of setup.py. Calling

python setup.py build_ext --inplace

will then build the extension module and place it into your pyMOR source tree.

Tests

pyMOR uses pytest for unit testing. To run the test suite, simply execute make test in the base directory of the pyMOR repository. This will also create a test coverage report which can be found in the htmlcov directory. Alternatively, you can run make full-test which will also enable pyflakes and pep8 checks.

All tests are contained within the src/pymortests directory and can be run individually by executing py.test src/pymortests/the_module.py.

Contact

Should you have any questions regarding pyMOR or wish to contribute, do not hestitate to contact us via our development mailing list:

http://listserv.uni-muenster.de/mailman/listinfo/pymor-dev