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SVD scythe::svd ( const Matrix<> &  A, int  nu = -1, int  nv = -1  ) [inline] Calculates the singular value decomposition of a matrix, optionally computing the left and right singular vectors. This function returns the singular value decomposition (SVD) of a matrix A, optionally computing the left and right singular vectors. It returns the singular values and vectors in a SVD object. Note: This function requires BLAS/LAPACK functionality and is only available on machines that provide these libraries. Make sure you enable the SCYTHE_LAPACK preprocessor flag if you wish to use this function. Furthermore, note that this function takes and returns only column-major concrete matrices. Future versions of Scythe will provide a native C++ implementation of this function with support for general matrix templates. Parameters: A The matrix to decompose. nu The number of left singular vectors to compute and return. Values less than zero are equivalent to min( , ). nv The number of right singular vectors to compute and return. Values less than zero are equivalent to min( , ). Exceptions: scythe_null_error (Level 1) scythe_convergence_error (Level 1) scythe_lapack_internal_error (Level 1) See also: SVD eigen(const Matrix<>& A, bool vectors) References scythe::Matrix_base< ORDER, STYLE >::cols(), scythe::Matrix< T_type, ORDER, STYLE >::getArray(), scythe::Matrix_base< ORDER, STYLE >::isNull(), min(), scythe::Matrix_base< ORDER, STYLE >::rows(), and SCYTHE_CHECK_10.