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This is a maintenance release fixing a few regressions and other issues. 3 has been released on February 21, 2017. This is a maintenance release fixing a few regressions and other issues. 2 has been released on January 18, 2017.
1 has been released on December 06, 2016. This is a maintenance release with few bug fixes and performance regressions since the first release of the 3. After more than three years of efforts, Eigen 3.
3 has been released on November 10, 2016. 3 version leverage numerous major novel features and improvements that are summarized in the dedicated 3. The latest stable release is Eigen 3.
Looking for the outdated Eigen2 version? 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. Expression templates allow to intelligently remove temporaries and enable lazy evaluation, when that is appropriate.
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. Algorithms are carefully selected for reliability. Reliability trade-offs are clearly documented and extremely safe decompositions are available.
BLAS test suite, and parts of the LAPACK test suite. 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. 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.
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.