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The '''latest stable release''' is Eigen 3.1.
The '''latest stable release''' is Eigen 3.1.. Get it here:
The '''latest 3.0 series release''' is Eigen 3.0.6. Get it here:
The '''latest 3.0 seriesrelease''' is Eigen 3.0.6. Get it here:
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The '''2.0 seriesrelease''' is Eigen 2.0.17. Get it here:
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hg clone https://bitbucket.org/eigen/eigen/
hg clone https://bitbucket.org/eigen/eigen/
== License ==
== License ==
Revision as of 15:09, 22 July 2012
Eigen is a C++ template library for linear algebra: matrices, vectors, numerical solvers, and related algorithms.
Eigen 3.4.0 released! (18.08.2021)
Eigen 3.4.0 has been released on August 18, 2021.
Notice: that 3.4.x will be the last major release series of Eigen that will support c++03. The master branch will drop c++03 support after this release.
The source archive is available at: https://gitlab.com/libeigen/eigen/-/releases/3.4.0Please check the release page for a list of changes.
Eigen 3.4-rc1 released! (19.04.2021)
Eigen 3.4-rc1 has been released on April 19, 2021.
Depending on the amount of reported issues, 3.4 will be released late April or early May.
The source archive is available at: https://gitlab.com/libeigen/eigen/-/releases/3.4-rc1Please check the release page for a list of changes.
Eigen 3.3.9 released! (04.12.2020)
Eigen 3.3.9 has been released on December 4, 2020.
This is a maintenance release fixing minor bugs and compilation issues. For more details have a look at the changelog.The sources are available at https://gitlab.com/libeigen/eigen/-/releases/3.3.9.
Eigen on Discord (16.11.2020)
Join our Discord server to discuss Eigen-related topics with other users and developers.
Eigen 3.3.8 released! (05.10.2020)
Eigen 3.3.8 has been released on October 5, 2020.
This is a maintenance release fixing minor bugs and compilation issues. For more details have a look at the changelog.The sources are available at https://gitlab.com/libeigen/eigen/-/releases/3.3.8.
To check out the Eigen repository using Mercurial, also known as "hg", do:
hg clone https://bitbucket.org/eigen/eigen/
- Eigen is versatile.
- It supports all matrix sizes, from small fixed-size matrices to arbitrarily large dense matrices, and even sparse matrices.
- It supports all standard numeric types, including std::complex, integers, and is easily extensible to custom numeric types.
- It supports various matrix decompositions and geometry features.
- Its ecosystem of unsupported modules provides many specialized features such as non-linear optimization, matrix functions, a polynomial solver, FFT, and much more.
- Eigen is fast.
- Expression templates allow to intelligently remove temporaries and enable lazy evaluation, when that is appropriate.
- Explicit vectorization is performed for SSE 2/3/4, ARM NEON, and AltiVec instruction sets, with graceful fallback to non-vectorized code.
- Fixed-size matrices are fully optimized: dynamic memory allocation is avoided, and the loops are unrolled when that makes sense.
- For large matrices, special attention is paid to cache-friendliness.
- Eigen is reliable.
- Eigen is elegant.
- The API is extremely clean and expressive while feeling natural to C++ programmers, thanks to expression templates.
- Implementing an algorithm on top of Eigen feels like just copying pseudocode.
- Eigen has good compiler support as we run our test suite against many compilers to guarantee reliability and work around any compiler bugs. Eigen also is standard C++98 and maintains very reasonable compilation times.
- Eigen 3 documentation: this includes a getting started guide, a long tutorial, a quick reference, and page about porting from Eigen 2 to Eigen 3.
Eigen doesn't have any dependencies other than the C++ standard library.
We use the CMake build system, but only to build the documentation and unit-tests, and to automate installation. If you just want to use Eigen, you can use the header files right away. There is no binary library to link to, and no configured header file. Eigen is a pure template library defined in the headers.
Earlier versions were licensed under the LGPL3+.
Note that currently, a few features rely on third-party code licensed under the LGPL: SimplicialCholesky, AMD ordering, and constrained_cg. Such features can be explicitly disabled by compiling with the EIGEN_MPL2_ONLY preprocessor symbol defined.
Virtually any software may use Eigen. For example, closed-source software may use Eigen without having to disclose its own source code. Many proprietary and closed-source software projects are using Eigen right now, as well as many BSD-licensed projects.
Eigen is standard C++98 and so should theoretically be compatible with any compliant compiler. Whenever we use some non-standard feature, that is optional and can be disabled.
Eigen is being successfully used with the following compilers:
- GCC, version 4.1 and newer. Very good performance with GCC 4.2 and newer.
- MSVC (Visual Studio), 2005 and newer. Vectorization is enabled with 2008 and newer, which also gives good performance.
- Intel C++ compiler. Very good performance.
- LLVM/CLang++ (2.8 and newer).
- MinGW, recent versions. Very good performance when using GCC 4.
- QNX's QCC compiler.
Projects using Eigen
Extensions, numerical computation and bindings
- Google's Ceres solver is a portable C++ library that allows for modeling and solving large complicated nonlinear least squares problems.
- The Manifold ToolKit MTK provides easy mechanisms to enable arbitrary algorithms to operate on manifolds. It also provides a Sparse Least Squares Solver (SLoM) and an Unscented Kalman Filter (UKFoM).
- redsvd is a RandomizED Singular Value Decomposition library for sparse or very large dense matrices.
- The RcppEigen package provides bindings and more for R.
- sparray: a python binding of the Sparse module - alpha stage.
- Shogun: a large scale machine learning toolbox.
- The Space Trajectory Analysis project at the European Space Agency. They even have an announcement on using Eigen.
- Avogadro, an opensource advanced molecular editor.
- The 3D astronomical visualization application Celestia is now using Eigen for all orbital and geometric calculation.
- Yade, platform for dynamic particle models, uses Eigen for geometric computations (switched from the WildMagic package)
- SLangTNG, an application suite for numerical analysis, linear algebra, advanced statistics, FEM, structural dynamics, data visualization, etc.
- Clip, an opensource program for the orientation of Laue exposures.
- Multiprecision Computing Toolbox for MATLAB uses Eigen as core library for matrix computations.
- Pteros, a C++ library for molecular modeling.
- Cufflinks, a tool for transcript assembly, differential expression, and differential regulation for RNA-Sequences.
Robotics and engineering
- The Yujin Robot company uses Eigen for the navigation and arm control of their next gen robots. (switched from blitz, ublas and tvmet)
- The Robotic Operating System (ROS) developed by Willow Garage.
- openAHRS Open Source IMU / AHRS
- The Darmstadt Dribblers autonomous Humanoid Robot Soccer Team and Darmstadt Rescue Robot Team use Eigen for navigation and world modeling.
- The Mobile Robot Programming Toolkit (MRPT), a set of libraries for SLAM, localization and computer vision, moved to Eigen (blog announcement) (switched from home made math classes).
- RBDL: a C++ library for rigid body dynamics.
- Computational Geometry Algorithms Library (CGAL), a collaborative effort to develop a robust, easy to use, and efficient C++ software library of geometric data structures and algorithms.
- Point Cloud Library (PCL), a large scale, BSD licensed, open project for point cloud processing. Uses Eigen as their math backend.
- VcgLib, an opensource C++ template library for the manipulation and processing of triangle and tetrahedral meshes. (switched from home made math classes)
- MeshLab, an opensource software for the processing and editing of unstructured 3D triangular meshes and point cloud. (switched from vcglib's math classes)
- Expe, an experimental framework for the rapid prototyping of graphics applications. No release yet, but it uses 90% of Eigen's features. (switched from home made math classes).
- libmv, an opensource structure from motion library. (switched from FLENS)
- Google uses Eigen for machine learning, computer vision, and optimization.
- In particular, see the mention of Ceres above.
- Layar, an augmented reality appplication for IPhone and Android.
- Red Sword Studios, maker of the iPhone games Gradient, Fortress Luna, Stimulus, and Lustre, uses Eigen extensively. Why roll your own matrix/vector/transformation code when there's Eigen?
- iPerfectPutt, an iPhone game, uses Eigen for 3D geometry calculations.
KDE (our origins!)
- Step, an educational physics simulator.
- Koffice2 (KDE's office suite), in particular Krita, the painting and image editing module. Eigen is also used a bit by KSpread, the spreadsheet module, for matrix functions such as MINVERSE, MMULT, MDETERM.
- Kalzium uses Eigen indirectly through the aforementioned Avogadro library.
- the Mandelbrot wallpaper plugin, some screensavers, kgllib, solidkreator, etc.
If you are aware of some interesting projects using Eigen, please send us a message or directly edit this wiki page !
Need help using Eigen? Try this:
- The Users Forum is your best resource.
- You can always try our IRC channel.
- Want to discuss something with the developers? Use our mailing list.
- To subscribe, send a mail with subject subscribe to email@example.com
- To unsubscribe, send a mail with subject unsubscribe to firstname.lastname@example.org
The Eigen mailing list can be used for discussing general Eigen development topics. Notice that:
- End-user questions are better asked on the Users Forum.
- Development of specific features is best tracked and discussed on our Bugzilla. See this page.
This mailing list is public and has public archives.
Important: You must subscribe before you may post. Sorry, this is our only way to prevent spam.
Important: After you sent your subscription request, you will receive a confirmation e-mail. Check your spam folder, as these confirmation e-mails are often filtered as spam!
Core Team Mailing list
This private mailing list should only be used for matters that need to be discussed privately. It is read by Benoît and Gaël.
Its address is eigen-core-team at the same lists server as for the Eigen mailing list.
No need to subscribe (actually, subscription is closed).
The point of the eigen-core-team list is that sometimes, people want to write privately to a few core developers. This list provides a simple way of doing so.
Our IRC channel is #eigen on irc.freenode.net.
Everybody's welcome to discuss Eigen-related topics or just chat. Some quick Eigen development chat happens over IRC, but the main place for Eigen development discussion remains the Eigen mailing list. Some user support also happens over IRC, but the main place for Eigen user support is the Users Forum.
The Eigen project was started by Benoît Jacob (founder) and Gaël Guennebaud (guru). Many other people have since contributed their talents to help make Eigen successful. Here's an alphabetical list: (note to contributors: do add yourself!)
|Abraham Bachrach||Added functions for cwise min/max with a scalar|
|Carlos Becker||Wrote some of the pages of the tutorial|
|David Benjamin||Artwork: the owls|
|Cyrille Berger||Fix error in logic of installation script|
|Armin Berres||Lots of fixes (compilation warnings and errors)|
|Jose Luis Blanco||Build fixes for MSVC and AMD64, correction in docs|
|Mark Borgerding||FFT module|
|Romain Bossart||Updates to Sparse solvers|
|Kolja Brix||Added documentation to Householder module|
|Thomas Capricelli||Migration to mercurial, Non-linear optimization and numerical differentiation, cron-job to update the online dox|
|Andrew Coles||Fixes (including a compilation error)|
|Marton Danoczy||MSVC compilation fix, support for ARM NEON with Clang 3.0 and LLVM-GCC|
|Christian Ehrlicher||MSVC compilation fix|
|Daniel Gomez Ferro||Improvements in Sparse and in matrix product|
|Rohit Garg||Vectorized quaternion and cross products, improved integer product|
|Mathieu Gautier||QuaternionMap and related improvements|
|Anton Gladky||Visual Studio 2008 and GCC 4.6 compilation fixes|
|Stuart Glaser||Prevent allocations in LU decomposition|
|Marc Glisse||C++11 compilation issues (suffices for literals)|
|Frederic Gosselin||Improve filter for hidden files in CMake|
|Gaël Guennebaud||Core developer|
|Philippe Hamelin||Allow CMake project to be included in another project|
|Marcus D. Hanwell||CMake improvements. Marcus is a developer at Kitware!|
|Chen-Pang He||Extend matrix functions to accept more types|
|Hauke Heibel||Extended matrix functions, STL compatibility, Splines, CMake improvements, and more ...|
|Christoph Hertzberg||Quaternions (vectorized multiplication, unaligned)|
|Pavel Holoborodko||Multi-precision support with MPFR C++|
|Tim Holy||Improvements to tutorial, LDLT update and downdate|
|Intel||Back-end to Intel Math Kernel Library (MKL)|
|Trevor Irons||Square root for complex numbers, fix compile errors and mistake in docs|
|Benoît Jacob||Core developer|
|Bram de Jong||Improvement to benchmark suite|
|Kibeom Kim||Implement *= /= * / operations for VectorwiseOp|
|Claas Köhler||Improvements to FFTW CMake module|
|Igor Krivenko||Properly cast constants when using non-standard scalars|
|Marijn Kruisselbrink||CMake fixes|
|Moritz Lenz||Allow solving transposed problem with SuperLU|
|Sebastian Lipponer||MSVC compilation support|
|Daniel Lowenberg||Add SparseView class|
|David J. Luitz||Bug fix for sparse * dense matrix product|
|D J Marcin||Fix operator& precedence bug|
|Konstantinos A. Margaritis||AltiVec and ARM NEON vectorization|
|Ricard Marxer||Reverse, redux improvements, the count() method, some dox|
|Vincenzo Di Massa||CMake fix|
|Christian Mayer||Early code review and input in technical/design discussions|
|Frank Meier-Dörnberg||MSVC compatibility fixes|
|Keir Mierle||LDLT decomposition and other improvements|
|Laurent Montel||CMake improvements. Laurent is (with Alexander) one of the CMake gurus at KDE!|
|Eamon Nerbonne||Compilation fixes for win32|
|Alexander Neundorf||CMake improvements. Alexander is (with Laurent) one of the CMake gurus at KDE!|
|Jason Newton||Componentwise tangent functions|
|Jitse Niesen||Matrix functions, large improvements in the Eigenvalues module and in the docs|
|Desire Nuentsa||Many improvements to Sparse module: ILUT, PaStiX|
|Jan Oberländer||Compatibility with termios.h|
|Jos van den Oever||Compilation fix|
|Michael Olbrich||Early patches, including the initial loop meta-unroller|
|Bjorn Piltz||Visual C compilation fix|
|Zach Ploskey||Copy-editing of tutorial|
|Manoj Rajagopalan||Introduce middleRows() / middleCols(), bug fix for nonstandard numeric types|
|Stjepan Rajko||MSVC compatibility fix|
|Jure Repinc||CMake fixes|
|Kenneth Frank Riddile||Lots of Windows/MSVC compatibility fixes, handling of alignment issues|
|Adolfo Rodriguez||Prevent allocations in matrix decompositions|
|Peter Román||Support for SuperLU's ILU factorization|
|Oliver Ruepp||Bug fix in sparse matrix product with row-major matrices|
|Radu Bogdan Rusu||Fix compilation warning|
|Guillaume Saupin||Skyline matrices|
|Jakob Schwendner||Test for unaligned quaternions|
|Martin Senst||Bug fix for empty matrices|
|Benjamin Schindler||gdb pretty printers|
|Michael Schmidt||Compilation fix connected to min/max|
|Dennis Schridde||New typedefs like AlignedBox3f|
|Sameer Sheorey||Fix gdb pretty printer for variable-size matrices|
|Andy Somerville||Functions to get intersection between two ParametrizedLines|
|Alex Stapleton||Help with tough C++ questions|
|Adam Szalkowski||Bug fix in MatrixBase::makeHouseholder()|
|Adolfo Rodriguez Tsourouksdissian||Version of JacobiSVD that pre-allocates its resources|
|Piotr Trojanek||QCC compilation fixes|
|Anthony Truchet||Bugfix in QTransform and QMatrix support|
|James Richard Tyrer||CMake fix|
|Rhys Ulerich||Pkg-config support, improved GDB pretty-printer|
|Ingmar Vanhassel||CMake fix|
|Scott Wheeler||Documentation improvements|
|Urs Wolfer||Fixed a serious warning|
|Manuel Yguel||Bug fixes, work on inverse-with-check, the Polynomial module|
Eigen is also using code that we copied from other sources. They are acknowledged in our sources and in the Mercurial history, but let's also mention them here:
|Intel Corporation||SSE code for 4x4 matrix inversion taken from here.|
|Tim Davis||AMD reordering simplicial sparse Cholesky factorization adapted from SuiteSparse|
|Julien Pommier||SSE implementation of exp,log,cos,sin math functions from GMM++|
|Yousef Saad||IncompleteLUT preconditioner coming from ITSOL|
|Minpack authors||Algorithms for non linear optimization.|
Special thanks to Tuxfamily for the wonderful quality of their services, and the GCC Compile Farm Project that gives us access to many various systems including ARM NEON.
If you are looking for a BibTeX entry to use to cite Eigen in academic papers, see the BibTeX page.