EigenPy is an open-source framework that allows the binding of the famous Eigen C++ library in Python via Boost.Python.

EigenPy provides:

• full memory sharing between Numpy and Eigen, avoiding memory allocation
• full support Eigen::Ref avoiding memory allocation
• full support of the Eigen::Tensor module
• exposition of the Geometry module of Eigen for easy code prototyping
• standard matrix decomposion routines of Eigen such as the Cholesky, SVD and QR decompositions
• full support of SWIG objects
• full support of runtime declaration of Numpy scalar types
• extended API to expose several STL types and some of their Boost equivalents: optional types, std::pair, maps, variants...
• full support of vectorization between C++ and Python (all the hold objects are properly aligned in memory)

• EigenPy — Versatile and efficient Python bindings between Numpy and Eigen
  • Installation
    • Conda
    • Ubuntu
      • Add robotpkg apt repository
      • Install EigenPy
    • Mac OS X
    • Docker
  • Build
  • Contribution
  • Core-dev team
  • Credits
  • Acknowledgments

The installation of EigenPy on your computer is made easy for Linux/BSD, Mac OS X, and Windows environments.

You simply need this simple line:

conda install eigenpy -c conda-forge

You can easily install EigenPy from binaries.

1. Register the authentication certificate of robotpkg:

curl http://robotpkg.openrobots.org/packages/debian/robotpkg.asc | sudo tee /etc/apt/keyrings/robotpkg.asc

2. Add robotpkg as source repository to apt:

sudo tee /etc/apt/sources.list.d/robotpkg.list <<EOF
deb [arch=amd64 signed-by=/etc/apt/keyrings/robotpkg.asc] http://robotpkg.openrobots.org/packages/debian/pub $(lsb_release -cs) robotpkg
EOF

3. You need to run at least one apt update to fetch the package descriptions:

sudo apt update

4. The installation of EigenPy and its dependencies is made through the line:

sudo apt install robotpkg-py35-eigenpy

where 35 should be replaced by the Python 3, you want to work this (e.g., robotpkg-py36-eigenpy to work with Python 3.6).

The installation of EigenPy on Mac OS X is made via HomeBrew. You just need to register the tap of the software repository.

brew tap gepetto/homebrew-gepetto

and then install EigenPy for Python 3.x with:

brew install eigenpy

docker run --rm -it ghcr.io/stack-of-tasks/eigenpy:devel

Build instruction can be found here

If you want to ask a question, report a bug, request a new feature or contributing with a pull requests please, follow the contribution guideline.

The currently active core developers of EigenPy are:

• Justin Carpentier (Inria): main developer and manager of the project
• Guilhem Saurel (LAAS-CNRS): core maintainer
• Joris Vailant (Inria): core developer and manager of the project
• Lucas Haubert (Inria): core developer
• Jeanne Matheron (Inria): core developer

In addition to the core dev team, the following people have also been involved in the development of EigenPy and are warmly thanked for their contributions:

• Nicolas Mansard (LAAS-CNRS): initial project instructor
• Wolfgang Merkt (University of Edinburgh): ROS integration and support
• Sean Yen (Microsoft): Windows integration
• Loïc Estève (Inria): Conda integration
• Wilson Jallet (Inria): core developer

The development of EigenPy is supported by the Gepetto team @LAAS-CNRS and the Willow team @INRIA.