Matrix.h File Reference

typedef and functions to augment Eigen's MatrixXd More...

Go to the source code of this file.

Classes
struct	gtsam::MultiplyWithInverse< N >
	Functor that implements multiplication of a vector b with the inverse of a matrix A. More...
struct	gtsam::MultiplyWithInverseFunction< T, N >
	Functor that implements multiplication with the inverse of a matrix, itself the result of a function f. More...

Namespaces
namespace	gtsam
	Global functions in a separate testing namespace.

Macros
#define	GTSAM_MAKE_MATRIX_DEFS(N)

Typedefs
typedef Eigen::MatrixXd	gtsam::Matrix
typedef Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor >	gtsam::MatrixRowMajor
using	gtsam::ConstMatrixView
	Dynamic-stride const Matrix view for accepting NumPy arrays without copies.
typedef Eigen::Block< Matrix >	gtsam::SubMatrix
typedef Eigen::Block< const Matrix >	gtsam::ConstSubMatrix

Functions
const Eigen::IOFormat &	gtsam::matlabFormat ()
template<class MATRIX>
bool	gtsam::equal_with_abs_tol (const Eigen::DenseBase< MATRIX > &A, const Eigen::DenseBase< MATRIX > &B, double tol=1e-9)
	equals with a tolerance
bool	gtsam::operator== (const Matrix &A, const Matrix &B)
	equality is just equal_with_abs_tol 1e-9
bool	gtsam::operator!= (const Matrix &A, const Matrix &B)
	inequality
bool	gtsam::assert_equal (const Matrix &A, const Matrix &B, double tol=1e-9)
	equals with an tolerance, prints out message if unequal
bool	gtsam::assert_inequal (const Matrix &A, const Matrix &B, double tol=1e-9)
	inequals with an tolerance, prints out message if within tolerance
bool	gtsam::assert_equal (const std::list< Matrix > &As, const std::list< Matrix > &Bs, double tol=1e-9)
	equals with an tolerance, prints out message if unequal
bool	gtsam::linear_independent (const Matrix &A, const Matrix &B, double tol=1e-9)
	check whether the rows of two matrices are linear independent
bool	gtsam::linear_dependent (const Matrix &A, const Matrix &B, double tol=1e-9)
	check whether the rows of two matrices are linear dependent
void	gtsam::print (const Matrix &A, const std::string &s, std::ostream &stream)
	print without optional string, must specify cout yourself
void	gtsam::print (const Matrix &A, const std::string &s="")
	print with optional string to cout
void	gtsam::save (const Matrix &A, const std::string &s, const std::string &filename)
	save a matrix to file, which can be loaded by matlab
istream &	gtsam::operator>> (std::istream &inputStream, Matrix &destinationMatrix)
	Read a matrix from an input stream, such as a file.
Matrix	gtsam::diag (const std::vector< Matrix > &Hs)
	Create a matrix with submatrices along its diagonal.
pair< Matrix, Matrix >	gtsam::qr (const Matrix &A)
	Householder QR factorization, Golub & Van Loan p 224, explicit version.
void	gtsam::inplace_QR (Matrix &A)
	QR factorization using Eigen's internal block QR algorithm.
list< std::tuple< Vector, double, double > >	gtsam::weighted_eliminate (Matrix &A, Vector &b, const Vector &sigmas)
	Imperative algorithm for in-place full elimination with weights and constraint handling.
void	gtsam::householder_ (Matrix &A, size_t k, bool copy_vectors)
	Imperative version of Householder QR factorization, Golub & Van Loan p 224 version with Householder vectors below diagonal, as in GVL.
void	gtsam::householder (Matrix &A, size_t k)
	Householder tranformation, zeros below diagonal.
template<class RDerived, class SDerived, class DDerived, class ParentsDerived>
void	gtsam::internal::solveUpperConditional (const Eigen::MatrixBase< RDerived > &R, const Eigen::MatrixBase< SDerived > &S, const Eigen::MatrixBase< DDerived > &d, const Eigen::MatrixBase< ParentsDerived > &parents, Vector *result)
	Solve the block upper-triangular system R*x = d - S*parents.
Matrix	gtsam::stack (const std::vector< Matrix > &blocks)
Matrix	gtsam::collect (const std::vector< const Matrix * > &matrices, size_t m=0, size_t n=0)
	create a matrix by concatenating Given a set of matrices: A1, A2, A3... If all matrices have the same size, specifying single matrix dimensions will avoid the lookup of dimensions
Matrix3	gtsam::skewSymmetric (double wx, double wy, double wz)
	skew symmetric matrix returns this: 0 -wz wy wz 0 -wx -wy wx 0
template<class Derived>
Matrix3	gtsam::skewSymmetric (const Eigen::MatrixBase< Derived > &w)
Matrix	gtsam::inverse_square_root (const Matrix &A)
	Use Cholesky to calculate inverse square root of a matrix.
void	gtsam::svd (const Matrix &A, Matrix &U, Vector &S, Matrix &V)
	SVD computes economy SVD A=U*S*V'.
std::tuple< int, double, Vector >	gtsam::DLT (const Matrix &A, double rank_tol=1e-9)
	Direct linear transform algorithm that calls svd to find a vector v that minimizes the algebraic error A*v.
Matrix	gtsam::expm (const Matrix &A, size_t K=7)
	Numerical exponential map, naive approach, not industrial strength !
std::string	gtsam::formatMatrixIndented (const std::string &label, const Matrix &matrix, bool makeVectorHorizontal)

Detailed Description

typedef and functions to augment Eigen's MatrixXd

Author

Christian Potthast

Kai Ni

Frank Dellaert

Alex Cunningham

Alex Hagiopol

Varun Agrawal

Macro Definition Documentation

GTSAM_MAKE_MATRIX_DEFS

#define GTSAM_MAKE_MATRIX_DEFS

(

N

)

Value:

using Matrix##N = Eigen::Matrix<double, N, N>;  \
using Matrix1##N = Eigen::Matrix<double, 1, N>;  \
using Matrix2##N = Eigen::Matrix<double, 2, N>;  \
using Matrix3##N = Eigen::Matrix<double, 3, N>;  \
using Matrix4##N = Eigen::Matrix<double, 4, N>;  \
using Matrix5##N = Eigen::Matrix<double, 5, N>;  \
using Matrix6##N = Eigen::Matrix<double, 6, N>;  \
using Matrix7##N = Eigen::Matrix<double, 7, N>;  \
using Matrix8##N = Eigen::Matrix<double, 8, N>;  \
using Matrix9##N = Eigen::Matrix<double, 9, N>;  \