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eigen    音标拼音: ['ɑɪgən]
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  • Eigen: Getting started
    The Eigen header files define many types, but for simple applications it may be enough to use only the MatrixXd type This represents a matrix of arbitrary size (hence the X in MatrixXd), in which every entry is a double (hence the d in MatrixXd) See the quick reference guide for an overview of the different types you can use to represent a
  • Eigen: Eigen::Quaternion lt; Scalar_, Options_ gt; Class Template Reference
    template<typename Scalar_, int Options_> class Eigen::Quaternion< Scalar_, Options_ > The quaternion class used to represent 3D orientations and rotations
  • Eigen: Matrix-free solvers
    Iterative solvers such as ConjugateGradient and BiCGSTAB can be used in a matrix free context To this end, user must provide a wrapper class inheriting EigenBase<> and implementing the following methods: Indexrows () and Indexcols (): returns number of rows and columns respectively operator* with your type and an Eigen dense column vector (its actual implementation goes in a specialization of
  • Eigen: Assertions
    The macro eigen_assert is defined to be eigen_plain_assert by default We use eigen_plain_assert instead of assert to work around a known bug for GCC <= 4 3 Basically, eigen_plain_assert isassert
  • Eigen: Eigen::SimplicialLDLT lt; MatrixType_, UpLo_, Ordering_ gt; Class . . .
    This class provides a LDL^T Cholesky factorizations without square root of sparse matrices that are selfadjoint and positive definite The factorization allows for solving A X = B where X and B can be either dense or sparse
  • Eigen
    Eigen is a C++ template library for linear algebra: matrices, vectors, numerical solvers, and related algorithms
  • Eigen: Core module
    This is the main module of Eigen providing dense matrix and vector support (both fixed and dynamic size) with all the features corresponding to a BLAS library and much more
  • Eigen::PardisoLLT lt; MatrixType, _UpLo gt; Class Template Reference
    class Eigen::PardisoLLT< MatrixType, _UpLo > A sparse direct Cholesky (LLT) factorization and solver based on the PARDISO library This class allows to solve for A X = B sparse linear problems via a LL^T Cholesky factorization using the Intel MKL PARDISO library The sparse matrix A must be selfajoint and positive definite
  • Eigen: Member List
    This is the complete list of members for Eigen::FullPivLU< MatrixType_ >, including all inherited members
  • Eigen: Translation lt; _Scalar, _Dim gt; Class Template Reference
    This class is not aimed to be used to store a translation transformation, but rather to make easier the constructions and updates of Transform objects





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