TooN Class List

Here are the classes, structs, unions and interfaces with brief descriptions:
TooN::Cholesky< Size, Precision >Decomposes a positive-semidefinite symmetric matrix A (such as a covariance) into L*D*L^T, where L is lower-triangular and D is diagonal
TooN::ConjugateGradient< Size, Precision >This class provides a nonlinear conjugate-gradient optimizer
TooN::DiagonalMatrix< Size, Precision, Base >A diagonal matrix
TooN::DownhillSimplex< N >This is an implementation of the Downhill Simplex (Nelder & Mead, 1965) algorithm
TooN::ILinearA reweighting class representing no reweighting in IRLS
TooN::IRLS< Size, Reweight >Performs iterative reweighted least squares
TooN::Internal::LineSearch< Size, Precision, Func >Turn a multidimensional function in to a 1D function by specifying a point and direction
TooN::LU< Size, Precision >Performs LU decomposition and back substitutes to solve equations
TooN::Matrix< Rows, Cols >A matrix
TooN::RobustIRobust reweighting (type I) for IRLS
TooN::RobustIIRobust reweighting (type II) for IRLS
TooN::SE2< Precision >Represent a two-dimensional Euclidean transformation (a rotation and a translation)
TooN::SE3< Precision >Represent a three-dimensional Euclidean transformation (a rotation and a translation)
TooN::SL< N, Precision >Element from the group SL(n), the NxN matrices M with det(M) = 1
TooN::SO2< Precision >Class to represent a two-dimensional rotation matrix
TooN::SO3< Precision >Class to represent a three-dimensional rotation matrix
TooN::SQSVD< Size, Precision >Version of SVD forced to be square princiapally here to allow use in WLS
TooN::SVD< Rows, Cols, Precision >Performs SVD and back substitute to solve equations
TooN::SymEigen< Size, Precision >Performs eigen decomposition of a matrix
TooN::Vector< Size, Precision, Base >A vector
TooN::WLS< Size, Precision, Decomposition >Performs weighted least squares computation

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