ILinearAlgebra (FSharp.Stats)

ILinearAlgebra Type

Namespace: FSharp.Stats.Algebra
Assembly: FSharp.Stats.dll
Base Type: obj
All Interfaces: ILinearAlgebra

This is an internal interface and not for user usage. It exposes a specialised subset of BLAS/LAPACK functionality. This functionality is used by us to build the exposed APIs. It is those exposed APIs that should be used.

Instance members

Instance member	Description
`this.dgemm_ (arg1, arg2)` Full Usage: `this.dgemm_ (arg1, arg2)` Parameters: arg0 : `Matrix<float>` arg1 : `Matrix<float>` Returns: `Matrix<float>` Modifiers: abstract	arg0 : `Matrix<float>` arg1 : `Matrix<float>` Returns: `Matrix<float>`
`this.dgesdd_ arg1` Full Usage: `this.dgesdd_ arg1` Parameters: arg0 : `Matrix<float>` Returns: `double array * Matrix<float> * Matrix<float>` Modifiers: abstract	Returns the full Singular Value Decomposition of the input MxN matrix A : A = U * SIGMA * VT in the tuple (S, U, VT), where S is an array containing the diagonal elements of SIGMA. uses the LAPACK routine dgesdd with the argument JOBZ = 'A' arg0 : `Matrix<float>` Returns: `double array * Matrix<float> * Matrix<float>`
`this.dgesdd_thin_ arg1` Full Usage: `this.dgesdd_thin_ arg1` Parameters: arg0 : `Matrix<float>` Returns: `double array * Matrix<float> * Matrix<float>` Modifiers: abstract	Returns the thin Singular Value Decomposition of the input MxN matrix A A = U * SIGMA * VT in the tuple (S, U, VT), where S is an array containing the diagonal elements of SIGMA. The first min(M,N) columns of U and the first min(M,N) rows of V*T are returned in the arrays U and VT; uses the LAPACK routine dgesdd with the argument JOBZ = 'S' arg0 : `Matrix<float>` Returns: `double array Matrix<float> * Matrix<float>`
`this.dsyevd_ arg1` Full Usage: `this.dsyevd_ arg1` Parameters: arg0 : `Matrix<float>` Returns: `Matrix<float> * Vector<float>` Modifiers: abstract	Computes for a N-by-N real symmetric matrix A, the eigenvalue decomposition of eigenvalues and right eigenvectors. The right eigenvector v(j) of A satisfies A * v(j) = lambda(j) * v(j) where lambda(j) is its eigenvalue. arg0 : `Matrix<float>` Returns: `Matrix<float> * Vector<float>`