minieigen is small boost::python wrapper for Eigen's core classes (dense fixed and dynamic-sized vectors, matrices, aligned boxes, quaternions; with integer, floating and complex scalars) …

1990年3月4日 · They are themselves composed of user manual pages describing the different features in a comprehensive way, and reference pages that gives you access to the API …

Eigen 3.4 was released on August 18 2021. It can be downloaded from the Download section on the Main Page or from Gitlab . Notice: that 3.4.x will be the last major release series of Eigen …

The Eigen library is divided in a Core module and several additional modules. Each module has a corresponding header file which has to be included in order to use the module. The Dense and …

2022年4月21日 · This is a very short guide on how to get started with Eigen. It has a dual purpose. It serves as a minimal introduction to the Eigen library for people who want to start …

Eigen provides two implementations. The recommended one is the BDCSVD class, which scales well for large problems and automatically falls back to the JacobiSVD class for smaller …

In Eigen, all matrices and vectors are objects of the Matrix template class. Vectors are just a special case of matrices, with either 1 row or 1 column. The first three template parameters of …

1990年3月4日 · Eigen provides native CMake support which allows the library to be easily used in CMake projects. Note CMake 3.0 (or later) is required to enable this functionality. Eigen …

Executive summary: Eigen has intelligent compile-time mechanisms to enable lazy evaluation and removing temporaries where appropriate. It will handle aliasing automatically in most cases, …

Eigen has built-in support for sparse matrices and vectors. Eigen provides a lot of convenience features (see Geometry module, Array module, etc), which are also very widely used. Using …