rhaschke / eigenpy

Bindings between Numpy and Eigen using Boost.Python

EigenPy

EigenPy is an open source framework which allows to bind the famous Eigen in Python as NumPy object (as matrix or array). EigenPy also exposes the Geometry module of Eigen for easy code prototyping. EigenPy also supports the basic matrix decomposion routines of Eigen such as the Cholesky decomposition, SVD decomposition, QR decomposition, and etc.

Setup

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

Ubuntu

You can easily install EigenPy from binairies.

Add robotpkg apt repository

1. Check your distribution codename in a terminal with the following command:

$ lsb_release -c
Codename:       xenial

2. Add robotpkg as source repository to apt:

sudo sh -c "echo 'deb [arch=amd64] http://robotpkg.openrobots.org/packages/debian/pub xenial robotpkg' >> /etc/apt/sources.list.d/robotpkg.list"

3. Register the authentication certificate of robotpkg:

curl http://robotpkg.openrobots.org/packages/debian/robotpkg.key | sudo apt-key add -

4. You need to run at least once apt update to fetch the package descriptions:

sudo apt-get update

Install EigenPy

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

For Python 2.7

sudo apt install robotpkg-py27-eigenpy

or for Python 3.{5,6,7}

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).

Mac OS X

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

brew tap gepetto/homebrew-gepetto

and then install EigenPy with:

brew install eigenpy

for Python 2.7 or:

brew install eigenpy-python3

for Python 3 support.

Credits

The following people have been involved in the development of EigenPy:

• Justin Carpentier (INRIA): main developer and manager of the project
• 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

If you have taken part to the development of EigenPy, feel free to add your name and contribution here.

Acknowledgments

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