| /external/eigen/doc/ |
| UsingIntelMKL.dox | 29 * Content : Documentation on the use of Intel MKL through Eigen
33 namespace Eigen {
35 /** \page TopicUsingIntelMKL Using IntelŪ Math Kernel Library from Eigen
37 \section TopicUsingIntelMKL_Intro Eigen and IntelŪ Math Kernel Library (IntelŪ MKL)
39 Since Eigen version 3.1 and later, users can benefit from built-in Intel MKL optimizations with an installed copy of Intel MKL 10.3 (or later).
40 <a href="http://eigen.tuxfamily.org/Counter/redirect_to_mkl.php"> Intel MKL </a> provides highly optimized multi-threaded mathematical routines for x86-compatible architectures.
43 \warning Be aware that IntelŪ MKL is a proprietary software. It is the responsibility of the users to buy MKL licenses for their products. Moreover, the license of the user product has to allow linking to proprietary software that excludes any unmodified versions of the GPL. As a consequence, this also means that Eigen has to be used through the LGPL3+ license.
45 Using Intel MKL through Eigen is easy:
46 -# define the \c EIGEN_USE_MKL_ALL macro before including any Eigen's header
50 When doing so, a number of Eigen's algorithms are silently substituted with calls to Intel MKL routines
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| /external/ceres-solver/internal/ceres/generated/ |
| schur_eliminator_d_d_d.cc | 45 #include "ceres/internal/eigen.h"
50 template class SchurEliminator<Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic>;
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| schur_eliminator_2_2_d.cc | 46 #include "ceres/internal/eigen.h"
51 template class SchurEliminator<2, 2, Eigen::Dynamic>;
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| schur_eliminator_2_3_d.cc | 46 #include "ceres/internal/eigen.h"
51 template class SchurEliminator<2, 3, Eigen::Dynamic>;
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| schur_eliminator_2_4_d.cc | 46 #include "ceres/internal/eigen.h"
51 template class SchurEliminator<2, 4, Eigen::Dynamic>;
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| schur_eliminator_4_4_d.cc | 46 #include "ceres/internal/eigen.h"
51 template class SchurEliminator<4, 4, Eigen::Dynamic>;
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| /external/ceres-solver/include/ceres/internal/ |
| eigen.h | 34 #include "Eigen/Core"
38 typedef Eigen::Matrix<double, Eigen::Dynamic, 1> Vector;
39 typedef Eigen::Matrix<double,
40 Eigen::Dynamic,
41 Eigen::Dynamic,
42 Eigen::RowMajor> Matrix;
43 typedef Eigen::Map<Vector> VectorRef;
44 typedef Eigen::Map<Matrix> MatrixRef;
45 typedef Eigen::Map<const Vector> ConstVectorRef
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| /external/eigen/lapack/ |
| lapack_common.h | 1 // This file is part of Eigen, a lightweight C++ template library
19 typedef Eigen::Map<Eigen::Transpositions<Eigen::Dynamic,Eigen::Dynamic,int> > PivotsType;
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| /external/eigen/demos/opengl/ |
| camera.h | 1 // This file is part of Eigen, a lightweight C++ template library
13 #include <Eigen/Geometry>
22 inline Frame(const Eigen::Vector3f& pos = Eigen::Vector3f::Zero(),
23 const Eigen::Quaternionf& o = Eigen::Quaternionf())
32 Eigen::Quaternionf orientation;
33 Eigen::Vector3f position;
60 void setPosition(const Eigen::Vector3f& pos);
61 inline const Eigen::Vector3f& position(void) const { return mFrame.position;
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| /external/eigen/doc/examples/ |
| Tutorial_ReductionsVisitorsBroadcasting_broadcast_1nn.cpp | 2 #include <Eigen/Dense>
5 using namespace Eigen;
9 Eigen::MatrixXf m(2,4);
10 Eigen::VectorXf v(2);
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| class_Block.cpp | 1 #include <Eigen/Core>
3 using namespace Eigen;
7 Eigen::Block<Derived>
10 return Eigen::Block<Derived>(m.derived(), 0, 0, rows, cols);
14 const Eigen::Block<const Derived>
17 return Eigen::Block<const Derived>(m.derived(), 0, 0, rows, cols);
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| class_FixedBlock.cpp | 1 #include <Eigen/Core>
3 using namespace Eigen;
7 Eigen::Block<Derived, 2, 2>
10 return Eigen::Block<Derived, 2, 2>(m.derived(), 0, 0);
14 const Eigen::Block<const Derived, 2, 2>
17 return Eigen::Block<const Derived, 2, 2>(m.derived(), 0, 0);
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| class_FixedVectorBlock.cpp | 1 #include <Eigen/Core>
3 using namespace Eigen;
7 Eigen::VectorBlock<Derived, 2>
10 return Eigen::VectorBlock<Derived, 2>(v.derived(), 0);
14 const Eigen::VectorBlock<const Derived, 2>
17 return Eigen::VectorBlock<const Derived, 2>(v.derived(), 0);
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| DenseBase_middleCols_int.cpp | 1 #include <Eigen/Core>
4 using namespace Eigen;
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| DenseBase_middleRows_int.cpp | 1 #include <Eigen/Core>
4 using namespace Eigen;
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| DenseBase_template_int_middleCols.cpp | 1 #include <Eigen/Core>
4 using namespace Eigen;
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| DenseBase_template_int_middleRows.cpp | 1 #include <Eigen/Core>
4 using namespace Eigen;
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| QuickStart_example.cpp | 2 #include <Eigen/Dense>
4 using Eigen::MatrixXd;
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| TutorialLinAlgInverseDeterminant.cpp | 2 #include <Eigen/Dense>
5 using namespace Eigen;
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| Tutorial_ArrayClass_mult.cpp | 1 #include <Eigen/Dense>
4 using namespace Eigen;
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| Tutorial_ReductionsVisitorsBroadcasting_colwise.cpp | 2 #include <Eigen/Dense>
7 Eigen::MatrixXf mat(2,4);
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| Tutorial_ReductionsVisitorsBroadcasting_rowwise.cpp | 2 #include <Eigen/Dense>
7 Eigen::MatrixXf mat(2,4);
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| tut_matrix_resize_fixed_size.cpp | 2 #include <Eigen/Dense>
4 using namespace Eigen;
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| /external/eigen/doc/special_examples/ |
| Tutorial_sparse_example.cpp | 1 #include <Eigen/Sparse>
4 typedef Eigen::SparseMatrix<double> SpMat; // declares a column-major sparse matrix type of double
5 typedef Eigen::Triplet<double> T;
7 void buildProblem(std::vector<T>& coefficients, Eigen::VectorXd& b, int n);
8 void saveAsBitmap(const Eigen::VectorXd& x, int n, const char* filename);
17 Eigen::VectorXd b(m); // the right hand side-vector resulting from the constraints
24 Eigen::SimplicialCholesky<SpMat> chol(A); // performs a Cholesky factorization of A
25 Eigen::VectorXd x = chol.solve(b); // use the factorization to solve for the given right hand side
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| /external/eigen/bench/ |
| bench_sum.cpp | 2 #include <Eigen/Core>
3 using namespace Eigen;
8 typedef Matrix<SCALAR,Eigen::Dynamic,1> Vec;
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